We’ve all experienced single AI models working independently, whether it's a bot answering questions or an algorithm making recommendations. But what happens when a single AI system isn't enough for a business?

When your call center deals with complex, multi-step customer queries, or you need a broader perspective on stock marketing trading and risk management, single AI agents can fall short. It’s no surprise that AI agent applications in customer service and virtual assistants are expected to account for approximately 78.65% of the market share by 2035.

If you’re considering multi-agent AI systems for your business, it’s only natural to wonder: what is a multi-agent system? What are some multi-agent system examples, and applications? We’ll cover all this and more in this blog post.

Let’s get started.

What is a multi-agent system?

A multi-agent system (MAS) is a network of single AI agents that work together to achieve business goals.

For instance, if your online store deploys a single AI chatbot, it can handle answering FAQs, giving order status updates, etc. But if a customer raises multiple queries to track an order and request a refund, a single AI agent struggles to juggle both.

In this case, introducing multiple AI agents to assist customers with refund requests, return policies, sentiment analysis, and more, reduces response time and increases customer satisfaction. In fact, 57.7% of AI-driven customer support agents now operate using a MAS to handle complex interactions. 

It operates on three core principles:

1. Autonomy

Each agent in a MAS operates independently, without waiting for a response or instruction from a central system. For instance, in an AI-driven customer support system, a refund policy handling agent retrieves the policies without waiting for instructions from another agent.

2. Collaboration

While agents in an MAS work independently, all these distributed AI systems communicate and coordinate to solve problems. For queries like, "Where's my order, I want to cancel it." The ‘order tracking’ agent and the ‘cancel orders’ agent collaborate to provide a response that addresses both queries.

3. Distributed control

Multi-AI agents distribute tasks that self-organize based on real-time inputs. For example, Google Maps doesn’t have a central system dictating traffic patterns, road closures, and delays.

Now that we’ve covered what MAS is, let’s break down how it operates in real-world scenarios.

How multi-agent systems work

Multi-agent systems work as a well-coordinated team, where each agent has a role, and follows certain rules. Here's a quick breakdown of the key components:

• Agents: These are independent decision-makers. In customer support, one might handle FAQs, another may tackle refund requests, and so on.
• Environment: This is a space where agents operate, like a website, within transaction data, or customer interactions.
• Perception and data collection: This is when agents sense surroundings (customer tone, transaction data).
• Communication protocols: Agents need structured ways to talk to each other. For example, how drivers (agents) communicate in ride-sharing apps or when riders request a ride.
• Decision-making mechanisms: Each agent must then decide how to act based on the situation. For instance, sending a cancellation confirmation or rerouting calls.
• Coordination strategies: Agents must collaborate efficiently, just as robots coordinate to pick and ship items without colliding.
• Learning and adaptation: Smart agents learn from experience. If multiple customers have order or refund-related inquiries, AI-driven agent-based modeling analyzes these patterns to help you make informed decisions.

Control architecture: Multi-agent systems can be centralized, where a single entity directs all agents (like an air traffic control tower managing flights), or decentralized, where agents operate independently while coordinating with each other (like multiple drones adjusting their paths in real-time).

Real-world applications of multi-agent systems

Multi-agent systems are working behind the scenes in many industries. They help manage traffic, improve customer support, and even assist in public health efforts.

Here’s how they make a difference in the real world.

Manage transportation systems

Traffic congestion during peak hours or roadblocks during accidents can bring an entire city to a standstill. Multi-AI agents tackle this with real-time voice updates and intelligent coordination.

In Pittsburgh, the deployment of the Scalable Urban Traffic Control (SURTRAC) system led to a 25% reduction in travel times and a 40% decrease in vehicle wait times at intersections. They used multi-AI agents that communicate to adapt traffic signals based on real-time conditions, effectively easing congestion and improving traffic flow.

So if a major highway causes a traffic jam, one AI agent can instantly analyze traffic while another delivers voice updates via navigation apps, guiding routers to take alternative routes.

Prediction and prevention in healthcare and public health

Missed appointments and no-shows in the U.S. healthcare system are leading causes of healthcare inefficiency. Even charging full fees for no-shows or missed appointments will cost you patient frustration and retention issues.

MAS bridges this gap by improving patient engagement and ensuring timely care.

For instance, Plivo's smart healthcare interactive voice response (IVR) system helps providers automate patient communication and optimize call handling.

When a patient calls a clinic, Plivo’s smart IVR can screen symptoms using AI-driven voice interactions and direct them to the appropriate specialist based on urgency. Instead of long wait times or misrouted calls, the system efficiently prioritizes critical cases while handling routine inquiries without human intervention.

Automate customer support

93% of customers are more likely to stay loyal to businesses with great service but achieving that at scale can be a challenge. In fact, long wait times and misrouted calls frustrate customers and overwhelm support teams.

AI-powered multi-voice agents improve customer service efficiency since businesses automate routine queries, ensuring customers get instant responses without waiting on hold. Smart call routing directs calls to the right department, reducing frustration, while speech recognition and customer relationship management (CRM) integration can send personalized follow-ups — whether it’s confirming appointments or providing order updates.

Streamline routine financial tasks

Managing routine financial tasks shouldn't feel like a constant back-and-forth. Multi-AI systems work together to streamline everything from payment confirmations to loan processing.

For instance, if you use one of Plivo's AI-powered voice agents to automate reminders, others can take care of fraud alerts, and give account updates in real-time. Depending on your customer base and their queries, you can customize these AI agents to provide contextual responses.

Connect components of supply chain management

Supply chain inefficiencies cost businesses an average of $1.3 trillion annually, representing nearly 10% of the global gross domestic product (GDP).

The power of MAS is that it makes every part of the supply chain, from warehouses to delivery trucks, streamlined. You can use one agent for supply management, another for inventory management, and one for demand forecasting.

It’s also convenient to send voice notifications for order confirmation, delays, and even emergency alerts in case of weather delays, stock shortages, etc.

Benefits of multi-agent systems

Multi-agent systems bring a lot to the table, making complex processes more efficient and intelligent. Let’s take a look at what makes them so useful.

Flexible

AI is already making 81% of companies respond faster to market shifts. MAS adds to this benefit as it adapts to changing business needs and automates processes like logistics, customer support, and compliance.

Scalable

Multi-agent systems are inherently scalable. As the complexity or scope of a problem increases, additional agents can be introduced to handle new tasks or responsibilities. This scalability makes these systems suitable for an array of applications, and dynamic environments.

Businesses can handle fluctuating demand without adding human resources, which reduces operational costs.

Robust

Multi-agent systems improve fault tolerance so if one AI component fails, another takes over. This ensures continuity, especially critical for industries like healthcare and finance.

Efficient

One of the primary benefits of multi-agent systems is the separate modeling-based AI agents. As each agent focuses on a singular task, agents can perform more efficiently and reduce manual errors.

Make multi-agent systems smarter with Plivo’s AI-powered voice agents

Autonomous AI agents often hit a dead-end as businesses scale, frustrating customers with repetitive, or worse, generic responses. Plivo's AI-powered voice agents understand your existing business gaps and fill those with adaptable solutions across industries.

These agents assess customer intent in real time so that callers don't waste time navigating endless IVR menus. Moreover, they sense customer sentiment, redirect them to the right department, and help gauge honest feedback to make informed decisions across tech support, appointment scheduling, or billing.

Plivo also offers data-driven analytics, where you can gain business insights and optimize customer interactions. Whether you're in healthcare, finance, or retail, Plivo's AI-powered voice agents ensure every conversation is efficient, personalized, and frustration-free.

You can use AI agents to speak your brand's language, and personality, get a 360-degree customer snapshot to make context-aware conversations, or resolve queries by utilizing internal business documents like FAQs, SOPs, and blog posts.

Contact us to deploy AI voice agents using Plivo, convert leads, resolve queries instantly, and send timely promotions in over 220 countries and territories.

A customer calls with a question. Before they even finish asking, one artificial intelligence (AI) agent is already listening, another is digging through past chats, and a third is crafting the perfect response.

It’s similar to having a team of experts working behind the scenes — fast, efficient, and always on point.

That’s the power of multi-agent artificial intelligence.

In 2025, AI isn’t a lone worker anymore. Companies like Google DeepMind are pushing it further with projects like Scalable Instructable Multiworld Agent (SIMA), where AI agents team up to follow human instructions in 3D virtual worlds. They’re training these agents to explore, build, and solve problems in video games, adapting to new tasks as a group.

When these AI agents work together, they handle challenges faster and better than a single agent could. Curious how this is changing things? Keep reading to find out!

How AI agents team up

While a single AI agent can be helpful, the real power of AI emerges when multiple agents work together. These systems bring specialized agents with unique skills to tackle complex or large-scale tasks that would be difficult for one agent to handle alone. This teamwork makes it easier for organizations to automate and improve their processes.

Here’s how multi-agent AI systems work:

• Understanding requests: One or more agents process the input, breaking it down to determine intent and key details.
• Planning workflows: Another set of agents maps out the necessary steps, assigning tasks to the right agents.
• Coordinating the team: A dedicated agent ensures that all AI agents communicate and work in sync.
• Executing tasks: Specialized agents handle their assigned steps, whether retrieving data, generating responses, or performing calculations.
• Collaborating with humans: If human input is needed, an agent flags the task and integrates their feedback.
• Validating outputs: Before delivering a final response, agents check for accuracy, consistency, and relevance.

These systems often combine standard agents like those handling user requests or managing data with specialized agents that have unique tools or skills, such as pulling data or interpreting images. Together, they work toward a goal you set.

At the heart of every agent is a large language model (LLM). This helps them understand what you’re saying and the situation around it.

Depending on the task, all agents might use the same model, or each could use a different one. This setup lets some agents share what they know while others double-check the work, making everything more reliable and consistent.

The system gets even better with shared memory. It stores information for the short- and long-term. This cuts down on how often humans need to step in during planning, checking, or refining a project.

Here’s the process in action:

• The system takes a complicated task and breaks it into smaller, more manageable parts.
• It assigns each task to the agent best equipped to handle it.
• Agents and humans collaborate seamlessly throughout the process.

Where you’ll see AI agents in action

AI agents use machine learning (ML) and advanced algorithms to make decisions, interact with diverse environments, and adapt to changing conditions. These systems are changing industries by making work faster, more accurate, and tailored to people’s needs.

Here’s how AI agents are helping out in different areas, with real examples of them in action.

Customer service

Businesses often deal with lots of customer questions and need to help people who speak different languages. This can get tough and expensive if not handled well. AI voice agents step in to make things easier by taking care of basic conversations in a way that feels natural.

Plivo’s AI voice agent, for example, can talk to customers in real time, picking up on their accents and feelings.

It works in 27 languages, which is great for companies with global customers. The voice agent also cuts costs by up to 40% and offers an uptime of 99.99%, so businesses can use it for everyday questions while human agents handle the harder ones.

Healthcare

Doctors and nurses have a lot to do, like seeing patients, filling out forms, and checking on health changes. This can eat up time they’d rather spend with people. AI agents lighten the load by handling some of these responsibilities.

Picture a doctor’s office where the physician is swamped with patient visits and notes to write up.

Oracle Health’s Clinical AI Agent fits right into this scene.

It listens to what patients say during appointments, writes up the records automatically, and even responds to voice commands. This cuts down on paperwork time, letting the doctor spend more timewith patients.

Logistics

Delivering packages sounds simple. Just take them from one place to another. But traffic jams, bad weather, or last-minute changes can make it difficult.

Companies need to figure out the fastest, cheapest way to get orders to customers on time. AI agents help by looking at all these factors and picking the best plan for deliveries, whether it’s by truck or drone.

Think about how Amazon handles millions of online orders every day. Their AI steps in to optimize delivery routes, checking traffic updates in real time to dodge delays and save gas.

Another company, Dista, uses an AI agent to watch traffic and weather, helping drivers make deliveries on the first try.

Supply chain precision

Running a supply chain means figuring out what customers will buy, ordering just enough stock, and making sure shipments go smoothly. If you get it wrong, you might run out of stock or have too much sitting around.

AI agents team up to solve this by guessing what customers will buy, ordering the right amount, and fixing shipping hiccups.

Take Walmart’s inventory system as an example. Shelves need to stay stocked with everything from cereal to socks. The AI looks at old sales and trends to predict what people will want.

Then, another AI agent tweaks orders to match those guesses, while a third keeps an eye on shipments, rerouting them if there’s a delay.

This agent shares info instantly, so suppliers and stores stay in sync. Companies using AI like this have seen 15% savings in logistics, 35% less extra stock and 65% increase in service levels.

Employee support

HR teams spend a lot of time onboarding new hires, answering questions, and setting up training. It’s a lot to juggle, and it can slow things down. AI agents step in to handle these routine tasks, making life easier for employees and giving HR more time to focus on people management.

Companies like IBM and Microsoft are leading the way with AI-driven HR tools.

IBM’s Watson, for example, automates administrative tasks and personalizes onboarding, helping new employees feel supported and engaged from day one.

Challenges that AI agents will bring

AI agents are incredible tools, but they come with challenges like energy consumption, privacy and ethics, and the costs and complexity of building them.

Here’s a detailed examination of each.

Energy consumption

Generative AI models, which power many AI agents, use a massive amount of energy. When training massive models like GPT-3, they churn out greenhouse gases equivalent to what several cars would produce over many lifetimes.

Even a single chat with one of these models can use up to 10 times more electricity than a quick Google search.

Looking ahead, experts predict that AI could be using as much power as a small country like Ireland. That’s a lot to wrap your head around!

For businesses relying on AI agents, say, for writing customer replies or generating healthcare reports, this ramps up both their energy bills and their environmental footprint.

To tackle this, opt for smarter solutions like designing energy-efficient algorithms, using specialized AI chips, and switching data centers to renewable power sources.

Privacy and ethics

AI agents use huge amounts of data to do their jobs. But here’s where it gets tricky: when that data gets shared, privacy and ethical questions pop up fast.

Picture a customer service bot passing along your chat details or a healthcare agent dealing with your personal health stats. If that info isn’t handled carefully, it could end up in the wrong hands or be misused.

AI often makes decisions without explaining how it reached them. This lack of transparency can hide biases and lead to unfair outcomes.

Research from the Information Systems Audit and Control Association (ISACA), highlights how this lack of openness is a real problem.

So, who’s keeping an eye on these systems? That’s the big question.

The solution is strong oversight, clear regulations like the General Data Protection Regulation (EU), and greater transparency in AI. People have a right to know how their data is used, and AI systems should be able to explain their decisions.

That’s the key to keeping things fair and safe.

Costs and complexity

Building an AI agent takes careful planning, design, coding, testing, and finally, deployment. Each step requires skilled experts and a well-planned budget to bring it to life.

Scaling them comes with issues such as inconsistent data quality and rising costs, as McKinsey highlights.

The complexity comes from needing top-notch experts, massive computing power, and constant training. For example, Meta’s LLaMA 2 took millions of GPU hours to train, racking up millions in hardware costs alone.

But there’s hope: businesses can cut corners (in a good way!) by using pre-trained models, tapping into cloud services, or grabbing open-source tools. These tricks bring the price down and make the process less of a headache.

And as more companies bring in generative AI agents, costs will likely reduce. This could open the door to new customer experience (CX) options, like offering human support as a premium service for those who want a more personal touch.

Trends to watch

As we look ahead, AI agents are gearing up to play an even bigger role in our lives. These smart systems are evolving fast, and a few exciting trends are starting to take shape.

Here’s what’s next for AI agents and why it’s worth paying attention.

AI agents will be everywhere

AI agents are popping up everywhere, handling everything from customer service chats to complex business operations. Companies are using them to schedule meetings, analyze data, and even assist in decision-making, while everyday users rely on them for things like smart home control and personal assistance.

As AI keeps improving, these agents will become even smarter, more independent, and a natural part of how we work and live.

The AI agents market is expected to grow from $5.1 billion in 2024 to $47.1 billion by 2030. That indicates an annual growth rate of 44.8%.

AI is already changing industries:

• Cineplex slashed customer service time from 15 minutes to 30 seconds per request. It processed over 5,000 refunds in five months.
• Fujitsu raised productivity by 67% with AI-made sales proposals.

Enterprises should catch up by 2025. Looking forward, AI agents will do more:

• By 2028, 33% of enterprise software might include AI agents. That’s up from less than 1% now. They’ll handle 15% of daily work decisions like approving loans or writing code docs.
• Beyond work, they could power self-driving cars to reduce accidents or act as personal tutors to improve learning.

Some believe AI agents could develop emotional intelligence, sensing moods and responding with empathy. It’s an exciting idea, but getting there isn’t easy.

Integrating AI agents into businesses comes with challenges. Companies often struggle to fit them into existing workflows, which means training employees and adjusting business models. As AlphaNeural points out, adoption focuses on the tech and making it work in the real world.

Despite these hurdles, AI agents will reshape work, learning, and connections. Their rise demands careful handling to benefit users while honoring values. With the right steps, they’ll be partners not just tools in a future we can embrace.

Problems will be spotted before they happen

What if problems could be fixed before they even happen? Machines could get tuned up before breaking down, and customers could receive help before they have to ask.

Thanks to AI agents, smart systems that predict and prevent issues using data, businesses are adopting them fast: 42% of enterprises used AI in 2023, and over 80% might by 2026. Why? It saves time, cuts costs, and keeps them ahead.

Companies succeed by identifying key challenges, selecting the right technology, training their teams, and starting small before scaling up.

And it’s paying well off across industries:

• In hospitals, AI catches deadly sepsis before it’s too late. It scans health records and vital signs, predicting trouble hours ahead. A study showed it cut deaths by 39.5% and shortened stays by 32.3%.
• Meanwhile, in finance, AI fights fraud as check scams soar 385% since the pandemic. The U.S. Treasury’s AI recovered $375 million in 2023, then $4 billion in 2024.
• AI keeps factories running in manufacturing. It uses sensor data to predict machine failures. General Motors, with IBM Watson, cut downtime by 15% and saved $20 million yearly. Plus. it could beat traditional fixes by 8-12%, or even 40% for reactive plants.

There are hurdles, though. Data must be clean, or predictions fail. Ethics matter — who’s to blame if AI messes up? Security’s critical too, with all that data flowing. Still, the wins are big: early fixes save cash, and experts say AI could boost profits by $4.4 trillion yearly.

Looking forward, AI agents might run supply chains or make tough financial calls, but we’ll need rules for fairness and accountability.

Experiences will be tailored like never before

AI agents predict issues before they arise, making experiences smoother and more personalized. From shopping to healthcare, they’re already shaping how we interact with services.

For example, streaming services like Netflix and Amazon use AI to figure out what we might like based on what we’ve browsed or watched before. It makes suggestions that keep us hooked.

Health apps like Fitbit tap into data from wearables to give us custom health tips, while smart home systems like Google Nest tweak our lights and thermostats based on whether we’re home and what we prefer.

Looking forward, AI agents are set to get even sharper. They could soon pull together all kinds of data like how we’re feeling or where we are to guess what we’ll need next.  Imagine an AI noticing you’re stressed and offering a calming playlist. Or one that knows you’re near a store and pings you with a deal on something you’ve been eyeing. 

Some might even predict you’ll need hiking boots for that trip you’ve got planned, urging you to grab them early.

Building AI agents will be made easy

Thanks to advancements like deep learning and natural language processing (NLP), AI agents are getting sharper. But it’s not just for tech experts anymore.

Tools like LangChain and AutoGen provide easy-to-use interfaces, while no-code platforms like Bizway and Lyzr let anyone craft AI agents without coding.

Cloud computing also helps by offering accessible power and data. Surprisingly, this shift is empowering solo entrepreneurs and small businesses to spark fresh ideas in unexpected areas.

Start your AI-powered future with Plivo

In 2025, AI agents are transforming how businesses handle tasks, especially in customer support. With growing demand for quick, reliable assistance, teams can easily feel overwhelmed.

Plivo AI steps in as a smart solution, designed to ease the burden while keeping everything running smoothly and efficiently. It aligns perfectly with the future of AI — smarter, scalable, and built to adapt.

Here’s how Plivo AI empowers your support team:

• Always available: Provides 24/7 support to deliver fast answers to customers when needed.
• Scales effortlessly: Manages peak demand without missing a beat.
• Personalized touch: Draws on past interactions to craft responses tailored to each individual.
• Streamlines processes: Walks users through complex steps, reducing frustration.

Letting Plivo tackle the routine tasks helps your team zero in on what really counts. Even better? It’s cost-effective, with a free trial to get you started.

But don’t take our word for it! Here’s what one of our users has to say:

Think of Plivo AI as a dependable partner, ready to support you today and into the future. Contact us today to see it in action.

Passwords have been the default security tool for years. But here’s the problem: they’re not enough anymore.

In 2021, 85% of data breaches happened because of phishing or stolen passwords.

The lesson? If you’re only using passwords, you’re leaving the door wide open for attackers.

That’s why two-factor authentication (2FA) and multi-factor authentication (MFA) exist. These tools add extra layers of security. In fact, studies show 2FA stops 96% of bulk phishing attacks, whereas MFA is capable of blocking 99.9% of automated account breaches.

But not every business needs the same level of protection. A small online store won’t need the same setup as a hospital handling patient records.

This article breaks down how 2FA and MFA work, where they fit in 2025, and how to choose the right approach for your needs.

What are 2FA and MFA?

You’ve probably come across 2FA and MFA when setting up security for your accounts. They both add extra protection, but what exactly do they mean? Let’s break them down and see how they work.

2FA: Two steps, stronger security

2FA does exactly what the name says: it adds two steps to verify your identity. Here’s how it works:

1. Step 1: You enter your password (something you know).
2. Step 2: You provide a second proof, like a one-time code sent via SMS or email (something you have).

For example, when you log into your bank account, you might type your password and then get a text message with a 6-digit code. Without that code, hackers can’t access your account — even if they steal your password.

2FA isn’t bulletproof, but it’s a massive upgrade over passwords alone. It’s like adding a deadbolt to a door: not impossible to break, but way harder for intruders.

MFA: More layers, more security

MFA takes the idea further. Instead of just two steps, it uses two or more different types of verification. These fall into three categories:

• Something you know (password, PIN).
• Something you have (phone, hardware token).
• Something you are (fingerprint, face scan).

For instance, logging into a corporate system might require:

1. A password (something you know),
2. A fingerprint scan (something you are),
3. And a code from a physical security key (something you have).

MFA’s flexibility makes it ideal for high-risk scenarios. Banks, healthcare systems, and government agencies use it because it’s tough for attackers to bypass multiple layers.

2FA vs. MFA: Which one do you need?

Understanding when 2FA and MFA work best and where they might fall short sets the stage for understanding which method fits into your security plan.

Let's see how these authentication methods shine in various scenarios.

When 2FA shines

2FA isn’t a one-size-fits-all solution, but in the right situations, it’s a game-changer. Let’s break down where it adds the most value:

Low-risk applications

For platforms that don’t handle highly sensitive data (think streaming services, newsletters, or forums), 2FA strikes a perfect balance.

It adds an important layer of security without overwhelming users. For example, a fitness app storing workout logs might use 2FA to protect user accounts but skip more complex MFA setups.

Customer-facing workflows

E-commerce sites, travel booking platforms, and subscription services benefit from 2FA because it secures transactions without disrupting the user experience.

Imagine a customer checking out on an online store: a quick SMS code or email OTP keeps their payment details safe without adding friction.

Challenges with 2FA

While 2FA is effective, it’s not flawless. Here are the hurdles businesses often face:

Implementation costs

Smaller businesses might struggle with the upfront costs of SMS gateways, authenticator apps, or API integrations. Maintenance also adds up — monitoring delivery rates, handling failed OTPs, and updating systems as threats evolve.

User resistance

Even a few extra seconds during login can frustrate users.

For example, if a verification code takes too long to arrive, customers might abandon a signup flow. Worse, some users may disable 2FA altogether if the process feels overly difficult.

Device dependency risks

If a user loses their phone or can’t access their email, account recovery becomes a headache. 

Support teams often field urgent requests like, “I changed my number, how do I log in now?” Without backup options (like backup codes or alternate verification methods), businesses risk locking out legitimate users.

Security gaps in SMS-based 2FA

SMS codes, while convenient, are vulnerable to SIM-swapping attacks or phishing. If a hacker hijacks a user’s phone number, they can intercept OTPs and bypass 2FA.

This is why industries like banking are moving toward app-based authenticators or hardware keys.

Accessibility issues

Not all users have smartphones or reliable internet. Relying solely on SMS or authenticator apps can exclude people in areas with poor connectivity or those using older devices.

Best practices for effective 2FA

To overcome these challenges, businesses need a strategic approach. Here’s how to make 2FA work for you, not against you:

Prioritize user education

Explain why 2FA matters. A short tutorial during signup (“This keeps your account safe from hackers”) or a friendly email reminder (“Your OTP is on the way!”) can reduce resistance. 

Transparency builds trust — users are more likely to comply if they understand the benefits.

Simplify the login experience

Simplifying the login process starts with small changes that make a big difference.

For example, let users sign in with their email address instead of forcing them to remember a complicated username. Since everyone already knows their email, this cuts down on forgotten login details.

Next, avoid overwhelming users with strict password rules. Yes, strong passwords matter, but forcing a reset every 30 days? That’s a recipe for frustration.

Pair 2FA with simple password guidelines (like a minimum length) to keep accounts secure without annoying users.

Offer multiple verification options

Not everyone wants SMS. Provide alternatives like:

• Email OTPs (for users without smartphones).
• Authenticator apps (like Google Authenticator for tech-savvy users).
• Backup codes (for emergencies when devices are lost).

Plan for account recovery

Don’t wait for lockout panics. Offer:

• Backup codes: Let users download or print them during setup.
• Alternate contact methods: Allow users to add a backup email or security questions.
• 24/7 support: Ensure users can quickly reach help if they’re stuck.

Balance security and convenience

For low-risk apps, allow users to “trust this device” for 30 days. This way, they only need to complete 2FA once per month on their personal devices.

How Plivo simplifies secure 2FA

Plivo helps businesses stop hackers in their tracks without adding friction for users. It combines strong security with seamless logins because staying protected shouldn’t be a hassle.

Here’s how.

Boost conversions with reliable OTP delivery

2FA only works if users actually get their codes. Plivo sends SMS and voice OTPs in under three seconds, so customers aren’t left waiting.

Here’s how it keeps things fast and secure:

• Automatically flags invalid or fake phone numbers.
• Routes messages through the fastest carrier to avoid delays.
• Sends millions of codes without slowdowns.

The result? Fewer abandoned carts, smoother sign-ups, and happier users.

Cut errors and fraud with phone number lookup

Plivo’s Lookup API does the detective work for you. It checks any phone number worldwide to spot:

• Fake numbers: Block accounts using disposable or invalid numbers.
• High-risk countries: Flag numbers from regions prone to fraud.
• Carrier details: Avoid sending codes to landlines (which can’t get SMS).

And the best part? It works in the background — no extra forms or user input needed.

Pricing starts at $0.004 per check, with bulk discounts for heavy users.

Save money with fewer failed messages

Plivo sends texts and calls directly to users — no detours, no middlemen. This “one-hop” system means:

• No extra fees: You’re not paying for undelivered messages.
• No delays: Codes arrive fast, every time.
• No surprises: Predictable pricing, even at high volumes.

For businesses, that means lower costs and fewer support tickets about “missing codes.”

Fraud protection built right in

Plivo also helps by:

• Blocking risky countries: Turn off SMS/calls to regions you don’t serve.
• Stopping premium number scams: Block calls to high-cost numbers hackers use to steal money.
• Giving pattern-based alerts: Get alerts if delivery rates suddenly drop (a sign of fake numbers).

When to consider MFA

Some logins are routine, while others protect something far more valuable. MFA isn’t always necessary, but in certain situations, it can be a smart safeguard. Here’s when it makes sense to use it.

Regulated industries

Financial institutions, healthcare providers, and government agencies often need to comply with strict requirements, mandating advanced security measures.

Critical systems

MFA is essential when securing servers, databases, admin panels, or tools that store intellectual property, customer data, or financial records. A breach in these systems can lead to significant financial and reputational harm.

Challenges with MFA

Implementing MFA comes with hurdles that require proactive management:

Device limitations

Older smartphones, legacy systems, or devices without biometric sensors (e.g., fingerprint scanners) may not support modern MFA methods like app-based authenticators or hardware tokens. Employees using unsupported devices risk being locked out.

Complex setup processes

Users often struggle with configuring MFA tools, especially without clear, role-specific guides. For example, setting up a YubiKey on a macOS device requires different steps than on Windows, and unclear instructions may lead to errors or abandonment.

Low user adoption

Without training, employees may view MFA as an inconvenience. Remote workers, in particular, might avoid using unfamiliar tools like biometrics or security keys if they lack guidance.

Security workarounds

Frustrated users may share passwords, reuse weak credentials, or disable MFA entirely to speed up logins — defeating the purpose of enhanced security.

Inconsistent user experience

Poorly integrated MFA solutions can disrupt workflows.

For example, requiring a hardware token, password, and SMS code for routine tasks slows productivity and fuels resentment.

Best practices for effective MFA

To tackle these challenges, businesses need a clear strategy. Here’s how to make MFA work in your favor:

Provide multiple authentication options

It’s important to offer a variety of authentication methods because not everyone uses the same devices or has the same tech skills.

Support diverse user needs and devices by offering:

• SMS/email OTPs: For employees with basic mobile phones or limited tech access.
• Authenticator apps: For users comfortable with smartphones.
• Biometrics: Fingerprint or facial recognition for modern devices.
• Hardware tokens: Physical keys for high-risk roles like system admins.

Implement role-based training programs

Training isn’t one-size-fits-all. Different teams have different needs, so your training should reflect that.

IT teams, for example, need detailed guides for setting up hardware tokens on different operating systems, like “How to Configure YubiKey on Windows 11.” Field employees, who might not have time for lengthy tutorials, benefit from short video demos showing how to approve logins via SMS or authenticator apps.

Executives, who often switch devices or travel, need personalized 1:1 sessions to make MFA setup hassle-free.

Enforce organization-wide MFA policies

If MFA is optional, attackers will target the weakest link. That’s why it should be enforced for everyone — employees, contractors, freelancers, and even legacy systems. Granting temporary access to third parties? They should use MFA too.

Outdated tools that don’t support MFA? Update or replace them. Regular audits help ensure no one is bypassing the rules.

Deploy adaptive MFA

Not every login needs the same level of security. Adaptive MFA adjusts based on the risk level of the situation.

For routine tasks, like checking email from a trusted device, a password and SMS code are enough. But for high-risk scenarios like logging in from a new country or accessing financial systems, additional checks, such as biometrics or hardware tokens, kick in.

Integrate MFA with single sign-on

Integrating MFA with single sign-on (SSO) enhances security without adding extra steps for users.

With SSO, they authenticate once using MFA and gain access to multiple systems without needing to log in repeatedly. This not only strengthens protection but also improves the user experience by reducing login fatigue.

Trends shaping authentication in 2025

As we move further into the digital world, the way we verify our identities is changing quickly. By 2025, new trends will change how people and companies confirm who they are and keep their information secure.

Here’s a look at the most important trends in authentication for 2025:

Passwordless authentication is on rise

Passwordless methods, like scanning your fingerprint, are faster and easier. Imagine logging into your account with a quick face scan instead of typing out a long password.

It’s not just convenient — it’s what people want. In fact, 52% of consumers prefer biometrics over traditional authentication methods. It’s no surprise this trend is picking up speed.

Businesses have also realized they need something better.

Already, 33% of IT departments globally are using passwordless authentication, and over one-third of companies are planning to adopt it in the near future. That’s a clear sign that companies see this as the future of security.

Plus, enterprises are already leading the way. For example, Microsoft reported 2 million monthly passwordless sign-ins through Windows Hello in early 2023. When tech giants like Microsoft push passwordless options, it’s a signal to everyone else: this is the direction we’re heading.

AI threats demand smarter defenses

AI-generated deepfakes are already posing serious security risks, and the problem is only growing.

By 2026, experts predict that 30% of businesses will no longer trust traditional identity verification methods due to the rise of AI-driven fraud. This is especially concerning for systems that rely on facial recognition or voice authentication, as deepfakes allow attackers to impersonate individuals and bypass security measures.

Financial institutions are particularly vulnerable — fraudulent identities can erode trust and compromise sensitive transactions. To counter this, businesses must adopt AI-powered tools capable of detecting deepfakes in real-time before they cause damage.

Beyond security, deepfakes also raise legal and ethical concerns.

As AI-generated content becomes more sophisticated, the reliability of biometric data declines, prompting discussions about data collection, storage, and privacy. Regulations similar to the General Data Protection Regulation (EU) (GDPR) may emerge to address these risks, ensuring stricter safeguards for personal information and reducing the potential for misuse.

Behavioural biometrics

What if your identity wasn’t based on a password you could forget or a fingerprint that could be faked, but on something uniquely yours — your online behavior?

That’s what behavioral biometrics is all about. It tracks how fast you type, the way you move your mouse, or even how you swipe on your phone to figure out if it’s really you.

This trend is picking up steam because it’s tough for hackers to mimic these unique habits, making it a powerful way to keep your digital life secure. Why is this so important?

Well, businesses and banks are jumping on board to protect millions of users. Take the Royal Bank of Scotland, for example. They’re using it to safeguard 18.7 million accounts by analyzing how people type and swipe.

It’s not just banks either; schools are using it to stop cheating in online exams by watching how students interact with their devices. The numbers back this up too — the market for this tech is projected to climb to $9.92 billion by 2030.

Decentralized identity

Picture this: instead of tech giants or governments holding all your personal info, you keep it in a secure digital wallet on your phone. That's a decentralized identity in a nutshell. So, why is this trend blowing up, and why should you care?

The rise is driven by a few key shifts. For one, cyberattacks are out of control. This makes those old-school, centralized databases look like easy targets.

People are also fed up with having no say over their data; they want to decide who sees what. Plus, new tech like blockchain is making this whole idea work better than ever. It’s no wonder the decentralized identity market is expected to jump from $156.8 million in 2021 to a massive $77.8 billion by 2031 — that’s serious growth.

With decentralized identity, you only share what’s needed, keeping your information safer. It also saves time (faster logins or ID checks) and works everywhere, from banks to online services.

Take the European Union’s EUDI Wallet: it’s already helping people access their data across borders without the hassle.

Future-proof your security strategy with Plivo

Whether you're protecting internal systems or customer data, understanding MFA vs. 2FA is important for your business. 2FA requires users to prove their identity in two simple ways. MFA takes it a step further by adding extra layers of verification for even stronger protection.

Using 2FA along with additional security checks gives you the best of both worlds: ease of use and solid security. Providers like Plivo simplify the process of setting up and integrating these tools, so you can protect your data without making things complicated for your users.

Contact us today to learn how our solutions can help secure your business.

McKinsey research shows that customer care leaders are shifting their focus across new themes.

They're moving beyond just customer experience to balance it with revenue targets and tech upgrades. At the same time, many are building future-proof, AI-enabled operational frameworks. Alongside these shifts, they’re investing in employee upskilling and deeper outsourcing collaborations.

This three-dimensional approach — customer satisfaction, profit contribution, and technological advancement — defines modern call center optimization.

That second one — AI-enabled operations is especially telling. It reflects a shift from reactive support to proactive, tech-driven efficiency.

This blog post outlines effective call center efficiency strategies, AI-aligned ideas, and key metrics to track, maximizing benefits from these advancements.

What is call center optimization beyond all the buzzwords?

Call center optimization is the strategic process of improving operational efficiency, agent productivity, and customer experience. It focuses on workflow refinement while reducing costs and enhancing service quality across all customer touchpoints.

While tracking metrics is a standard practice, effective optimization uses these metrics to boost profit margins, creating sustainable solutions rather than quick fixes.

Here are the four critical areas that call center optimization targets to deliver long-term business impact:

1. Agent performance: When you monitor and optimize agent performance, you’ll know which agents need product knowledge, soft skills development, or better tools to succeed.
2. Technology integrations: Proper tool integrations prevent data siloes, reduce repetitive tasks, and ensure your agents have complete information.
3. Customer satisfaction: Optimization ensures proper routing, agent training, and process simplification — the three key support aspects that enhance the customer experience.
4. Workforce management: Smart call centers use real-time data to match staffing with demand, improving coverage and efficiency.

The relation between call center optimization and your customer experience

Your key market differentiator is a top-notch customer experience, but the catch is to offer that without burning out your agents. Call center optimization creates a win-win by acing both. Let’s see how.

Streamlined call routing

Customers value speed above almost all other service factors. Each transfer or minute on hold ruins their perception of your brand.

AI-powered call routing optimization, like ticket classification and automatic routing, immediately connects callers to the right agent, saving agents up to 1.2 hours per day. This improves first call resolution rates and reduces abandonment.

Tailored customer service

Customers want personalized support, and 76% become frustrated when they don’t receive it. AI-powered call center solutions put customer data at agents' fingertips.

The solutions give your customer service representatives access to information like customer history, purchase patterns, and preferences on a single screen. This makes personalization possible even during high-volume periods.

Consistent service quality (across all channels)

Your customers switch between voice calls, email, chat, and social media to resolve the same issue; in fact, 37% use more than two channels. When you optimize for omnichannel support, customers receive the same accurate information, regardless of how or where they contact you.

Trained agents for proactive care

A survey found that 83% of consumers want companies to self-diagnose issues and contact them proactively before they have to reach out. 

With call center analytics and optimization insights, your agents can anticipate customer needs (say, customers at risk of churn), like sending reminders or addressing common issues via self-service.

First, assess your call center’s current state

Before you can improve your call center, you need a clear picture of your operation’s pulse. Tracking these metrics reveals strengths, exposes weaknesses, and sets a baseline for progress.

First call resolution (FCR) rate

How often do your agents solve issues on the first try? FCR matters because customers hate repeating themselves. A strong FCR rate (70-80%) cuts follow-ups, saves time, and keeps customers happy.

Check this by tracking resolved calls against the total first contacts over a week. Low numbers mean your agents might need better tools or training.

Average handling time (AHT)

This is the clock on each call — start to finish, including hold time and wrap-up. AHT averages 6 minutes and 10 seconds industry-wide, but shorter isn’t always better.

For example, a low AHT might indicate quick resolutions, but if paired with a low CSAT, it could suggest rushed interactions. Measure it daily to spot patterns (say, longer calls during peak hours) and adjust staffing or scripts accordingly.

Customer satisfaction score (CSAT)

CSAT, gathered from post-call surveys (typically on a 1-5 scale), tells you if your customers are walking away pleased. If your scores dip, learn why.

Generic post-call surveys (How satisfied are you?) often miss the point. Ask specific questions: Did the agent resolve your issue? Or were you transferred unnecessarily?

Schedule adherence

It’s the percentage of time call center agents are available to handle calls compared to their scheduled work time, accounting for breaks and other non-call activities. Low adherence means missed calls and frustrated customers.

So, track it weekly to catch chronic no-shows or overstaffing.

Call abandonment rate

This is the percentage of callers who hang up before speaking to an agent. A high rate can signal long waits or routing problems, which explains why they leave. Implement callbacks or improved interactive voice response (IVR) systems to reduce call center wait times and retain customers.

Net promoter score (NPS)

NPS measures customer loyalty by asking how likely customers are to recommend the company to others, typically on a 0-10 scale, with promoters (9-10), passives (7-8), and detractors (0-6). It’s a strong indicator of overall satisfaction and can predict business growth through word-of-mouth.

Start here. Measure these metrics now, and you’ll know exactly where to push harder.

Now, let’s begin optimizing your call center

You’ve assessed your call center’s current performance, and it’s time to improve it. Optimizing customer support centers is about smart, practical moves that deliver results.

Here’s how to get it done, step by step.

Step #1: Evaluate and establish technology integrations

To optimize your call center, start by equipping agents with tools that make their jobs easier.

Customer relationship management (CRM) software, smart call routing, and a unified desktop put everything agents need in one spot. Also, 81% of customers prefer self-service options for simple queries.

These tools can slash manual work and let your agents focus on what matters: solving problems. AI-driven customer service solutions help do that through specific functions, such as:

• Behavioral routing connects customers with agents who match both personality and skill requirements.
• Speech analytics shows agents real-time customer emotions, improving response appropriateness.
• Chatbots handle routine questions while collecting valuable CRM data (80% of consumers report positive or neutral chatbot experiences).

Plivo reduces live agent needs by 50% with Chatbots powered by OpenAI. The AI Self-Service Chatbot resolves queries instantly and handles tasks like exchanges and order tracking 24/7.

Integrated with your CRM system and knowledge base, it ensures brand-aligned responses. Escalate complex issues to agents via a unified desktop managing LiveChat, SMS, WhatsApp, and more for efficient, omnichannel support.

Step #2: Implement predictive analytics for proactive care

Predictive analytics help you stay ahead of the curve through smarter planning. It lets you dig into past data like call volumes, busy hours, and even seasonal spikes to present forecasts that let you staff right.

No more overworked agents or idle hands — analytics also guide staff schedules, meaning you’re ready for that holiday rush or surprise campaign surge.

You can also spot customer patterns, such as who’s likely to call about billing, prep agents with answers, and cut handle times.

Plivo’s Proactive Service anticipates customer needs, slashing inbound support with automated workflows triggered via API. Deliver answers before questions arise through SMS (98% open rate) and seamless live-agent handoffs, creating loyal customers.

Step #3: Use metrics and reporting to make decisions

Metrics and real-time reports show you what’s working and what’s not. Tracking key stats like average handle time, FCR, and customer satisfaction in real time helps you spot issues quickly.

With these insights, you can create targeted knowledge base articles and training for those issues.

But reporting has evolved. Traditional reporting looks backward at problems that have already affected customers. Today’s AI-powered monitoring catches issues as they form. Your agents fix these issues before most customers experience them, with 92% of CRM leaders saying their customer response times have improved.

Plivo’s Metrics & Reporting supercharges your call center decisions. Monitor queues, operations, and agent performance with real-time dashboards. Dive into historical reports for deep insights to improve your agent coaching.

Step #4: Train your agents with updated information

Agents aren’t mind readers. When they lack the tools and training they need, they struggle to perform their daily chores, leading to burnout.

Turnover is brutal, too: It takes three to four times an employee’s salary to replace them. So invest in their upskilling and see consistent results.

Hit them with fresh product details and customer insights (think role-plays on new features or breakdowns of common complaints). Equip them with cheat sheets updated monthly, not yearly. Skilled agents mean faster fixes and happier callers every time.

Apart from offering live metrics and historical insights, Plivo lets you access tools like call recording, barge, whisper, and CSAT collection to support targeted training and boost loyalty and call center performance. Your agents can also have a custom knowledge base that is fully integrated with the business systems.

Step #5: Create feedback loops (from agents and customers)

Who better than your agents to know what's broken in your call center before your metrics show it? They hear customer frustrations directly, experience system limitations daily, and develop workarounds for inefficient processes.

Your agent feedback loops require:

• Weekly team huddles where agents share recurring customer pain points.
• Anonymous suggestion systems for process improvements.
• Post-call surveys asking specific questions about tool effectiveness.

Customer feedback needs similar attention. In fact, 31% of customer service leaders analyze customer feedback as their strategy for providing excellent experiences.

An effective customer feedback loop should include:

• Targeted post-call surveys: Ask specific questions to understand the customer’s experience, not just general satisfaction.
• Call transcript analysis: Identify patterns, recurring complaints, and common friction points.
• Thematic tagging: Organize feedback into themes to highlight the most critical issues.
• Prioritized action: Focus on changes that address high-impact problems or recurring concerns.
• Transparent follow-up: Let customers know what was improved based on their feedback to build trust and show accountability.
• Continuous refinement: Keep the loop active by regularly reviewing feedback and adjusting processes or tools accordingly.

The power of AI in successful call center optimization

AI is changing how call centers operate, making them faster and more responsive. The global call center AI market hit $2 billion in 2024 and is set to grow at 23.8% yearly through 2030.

Experts at Gartner forecast that by 2025, 80% of customer service teams will use generative AI to boost agent efficiency and improve customer experiences.

Lately, industry buzz has highlighted AI’s growing role in streamlining operations. Many are eyeing automated solutions to handle routine tasks while keeping skilled agents for tough challenges.

Here’s how AI delivers value:

• Faster call wrap-ups: AI handles the grunt work of summarizing calls. It pulls key details (like complaints or follow-ups) from recordings and turns those talks into text transcripts. This cuts agent wrap-up time, with summaries and transcripts auto-added to customer records, saving effort.
• Smarter live chat: AI agents now handle chats with ease, tackling both simple and complex queries. Unlike basic bots, these agents act autonomously, offering 24/7 support, answering questions, and even scheduling meetings without human intervention.
• Better quality checks: AI-powered quality assurance tracks every interaction, spotting issues fast. It helps call center managers update processes and improve service without manual reviews, ensuring consistent quality.
• Conversational IVR: Forget rigid phone menus. AI-driven IVR uses natural language processing (NLP) to let callers explain issues in their own words. It routes calls or solves problems directly, making the experience smoother.

Implement your AI-powered contact center with Plivo

Plivo CX offers a full-featured, omnichannel solution with top-notch security to move your call center operations to the cloud.

The service packs everything you need: a single dashboard for managing omnichannel tasks, OpenAI-built self-service chatbots, a no-code workflow builder, and real-time reporting.

Plivo CX brings:

• A Unified Agent Desktop to manage calls, chats, and emails, cutting the hassle of switching channels.
• Chatbots are trained on your data to handle simple issues, leaving agents for tough cases.
• Analytics to read customer emotions in real time, helping agents respond better.
• Integration with your CRM, enterprise resource planning (ERP), or helpdesk software for a complete customer view.
• A drag-and-drop workflow builder to craft custom communication flows across channels.
• Smart routing to send queries to the right call center team, speeding up resolutions.

Plus, you can train the chatbots with your own data for spot-on answers. Contact us to book a demo today.

But don’t just take our word for it.

Businesses across industries are seeing improvements after implementing Plivo's solutions. Here’s what Scott Rosen, President and CEO of MDabroad, has to say about us:

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Are you an e-commerce business owner watching your support team drown in repetitive questions? Frustrated by customers abandoning carts because they couldn't get help fast enough? 

These pain points aren't just annoying—they're costing you revenue and growth opportunities every day.

However, custom AI agents are the breakthrough solution you've been searching for.

They constantly learn from your data, adjust to your tone, and respond like someone who knows your brand inside out. This makes every interaction feel personal, fast, and relevant. 

In this blog, we introduce you to custom AI agents, their benefits, types, and how they operate. We’ll also discuss how e-commerce businesses use custom AI agents for support with real-life AI agent use cases, recommendations, and engagement, and how you can do the same.

What are custom AI agents?

Custom AI agents are independent AI systems that utilize machine learning and natural language processing to interact with customers, process critical information, and perform specific tasks. 

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Typically, they are more effective than pre-built solutions as they can adapt to a business’s unique needs, offering more personalized and efficient support.

Benefits of custom AI agents in customer service 

As more e-commerce businesses look to personalize and scale their customer experience, custom AI agents are proving to be a smart investment. Here are some interesting findings:

• According to Gartner, by 2025, AI and automated systems are expected to handle 75% of all customer service interactions.
• It also predicts that by 2027, chatbots will become the primary customer service channel for approximately 25% of companies.
• At the same time, in McKinsey’s March 2025 Global AI Survey, 78% of respondents report using AI in at least one business function—up from 55% a year earlier. 

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Let’s go over some of the benefits of custom AI agents for your business:

Hyper-personalization at scale

Comvia’s research states that 56% of companies struggle to deliver real-time personalization, often due to disconnected systems and limited staff capacity. 

Custom AI agents can solve this problem by accessing customer data instantly, including purchase history, preferences, and behavior, and using it to tailor conversations in real time. 

These agents can deliver the personalization your team may not have time for at scale.

Cost and time savings

Salesforce data shows that 95% of decision-makers at companies using AI report reduced costs and time savings, and 92% say generative AI improves customer service.

Custom AI agents can take over high-volume, low-value tasks like answering FAQs, tracking orders, and routing queries. That means fewer support tickets for your human team and faster customer resolution.

Increased customer retention and loyalty

AI-powered systems have driven a 31.5% increase in customer satisfaction scores and a 24.8% boost in retention rates. AI agents make customers feel heard and valued by remembering past interactions, resolving issues quickly, and offering relevant suggestions. 

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And when customers get the support they need without repeating themselves or waiting in long queues, they’re more likely to stick around. This means higher loyalty, fewer churned customers, and more repeat purchases without adding pressure to your support team.

Enhanced data insights and feedback loops

AI agents can track customer behavior, identify recurring issues, and automatically flag gaps in service. That means fewer blind spots and faster responses to changing customer needs. 

These continuous feedback loops translate to smarter product decisions, more effective campaigns, and higher customer satisfaction, all without adding complexity or headcount.

Scalability for growing businesses

Custom AI agents enable e-commerce businesses to scale customer support efficiently without proportionally increasing staff. 

As a case in point, Swedish fintech company  Klarna’s AI chatbot manages two-thirds of its customer service inquiries, effectively performing the work equivalent of 700 full-time agents. This implementation has led to a projected $40 million profit improvement in a single year.

Types of custom AI Agents

Custom AI agents come in different forms, each built for a specific function, industry, or customer need. Here’s a quick breakdown of the most common types :

Conversational agents

These AI-driven tools engage users through natural language processing to carry out conversations. They’re widely used in virtual assistants, chatbots, and customer support to deliver human-like interactions.

Recommendation engines

These agents suggest products, services, or content based on user behavior and preferences. They help personalize experiences and are widely used across e-commerce sites, streaming platforms, and social media.

Predictive analytics agents

Used in industries such as finance, healthcare, and marketing, these agents analyze historical data using machine learning to forecast trends and inform strategic decisions.

RPA (Robotic Process Automation) agents

These agents are designed to automate routine tasks such as data entry and transaction processing, help organizations reduce manual effort, improve accuracy, and boost productivity.

Personalized learning agents

These AI agents are focused on education, adapting to individual learning needs, tracking progress, and enhancing online learning platforms to improve educational outcomes.

How AI agents work

To understand what makes custom AI agents effective for customer engagement, it’s helpful to look at how they operate behind the scenes. Here’s how it works:

Perception

AI agents collect input from various sources, such as text messages, voice commands, clicks, or behavioral patterns. With technologies like natural language processing (NLP) and computer vision, they interpret this data to understand what the user is saying or doing.

Reasoning

Once the data is processed, the agent evaluates the context and intent. It draws from its training data, business rules, or decision trees to determine the most appropriate response or action. This is where logic and analysis come into play.

Action

Based on its reasoning, the agent carries out an action. This might be replying to a customer, triggering a workflow, offering a recommendation, or escalating the issue to a human agent. The goal is to resolve the task efficiently and accurately.

Learning

After each interaction, the agent stores new data and feedback. Over time, it utilizes this information to refine its responses, enhance accuracy, and adjust to evolving customer behavior. 

This continuous learning loop makes AI agents increasingly useful the longer they are in use.

Key use cases of custom AI agents in E-commerce

From supporting customers around the clock to sending personalized product suggestions, custom AI agents can adapt to your workflows and goals. Here are some of the most effective ways e-commerce businesses are putting them to use:

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AI-driven customer support

• 24/7 availability
  Custom AI agents can handle customer queries at any time of day without human intervention. For example, footwear and apparel company Allbirds uses AI-powered chat support to assist customers with order tracking and FAQs around the clock.

• Context-aware query resolution
  These agents remember previous interactions and use that data to personalize responses. A user asking about a return status today will get an informed response based on their chat from last week.
  Zappos, for instance, has integrated AI into its support system to handle returns by recognizing purchase history and context automatically.

• Multilingual and omnichannel capabilities
  
  Custom AI agents can engage with customers in multiple languages across platforms like websites, mobile apps, and social media. A great example is H&M, whose AI chatbot supports users in different languages and on platforms like WhatsApp and Facebook Messenger, ensuring consistent global support.

Personalized product or content recommendations

Based on user behavior, purchase history, preferences
AI agents can analyze browsing patterns, past purchases, and user preferences to recommend real-time products and services. Amazon’s AI recommendation engine accounts for 35% of total revenue by suggesting products tailored to each user.

• Dynamic adaptability and learning
  
  Custom agents continuously learn and update recommendations based on user behavior. Stitch Fix employs AI to analyze customer preferences, sizes, and feedback. This enables the platform to deliver personalized clothing recommendations, enhancing customer satisfaction and engagement. 

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Automated engagement strategies

• Targeted messages based on the customer journey stage
  
  Custom AI agents can send different messages depending on where a customer is in the funnel, such as welcome emails for new users, product demos for engaged users, or discount codes for those at risk of churning.
  
  Sephora uses AI to send personalized birthday rewards and product suggestions based on purchase history and browsing behavior.

• Proactive outreach (cart reminders, renewal alerts, etc.)
  
  AI agents take the initiative instead of waiting for the customer to act. If someone abandons a cart, the agent can automatically send a reminder with an incentive.
  Bonobos uses AI-powered reminders to prompt repeat purchases and send personalized alerts about upcoming deliveries or product renewals.

AI-Powered chatbots with custom personas

• Tailored tone, voice, and personality
  
  Custom AI agents can be trained to reflect your brand’s tone, whether friendly, formal, or quirky.
  For instance, Casper introduced an AI chatbot named Luna 2.0. This chatbot uses a friendly and conversational tone to assist customers with their purchases, making the interaction feel more human and aligned with the brand’s approachable identity. 

• Cross-platform engagement (web, app, messaging platforms)
  
  These agents can live across multiple channels and maintain the same tone and context everywhere.
  Walmart has developed an AI-powered voice shopping assistant that integrates with Google Assistant, Siri, and Google Home devices. This allows customers to interact with Walmart’s services using natural language across various channels, ensuring a unified and personalized shopping experience.  

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Best practices to implement custom AI for businesses

With AI adoption on the rise, many businesses are still figuring out how to get it right.

A recent IBM survey shows that 35% of enterprise IT professionals use AI specifically to improve customer service agent productivity. In contrast, many others rely on it to enhance overall customer and employee experiences.

To make the most of your investment in custom AI agents, here are some practical best practices to follow:

Follow AI ethical principles

Building trust with your customers begins with the responsible use of AI. 84% of IT professionals agree that consumers are more likely to choose services from companies with transparent and ethical AI practices. 

This means being transparent about your AI agents’ decisions, avoiding biased responses, and protecting customer data. 

Promote human-AI collaboration

A recent study by the National Bureau of Economic Research found that customer support agents using a generative AI assistant increased their productivity by 14% on average. 

Notably, less experienced and lower-skilled workers saw the most significant improvements, highlighting the importance of human-AI collaboration.  Businesses can enhance performance by designing AI systems that complement human skills while ensuring quality and accountability. 

Prepare internal data

A survey by Hitachi Vantara revealed that 37% of U.S. IT leaders identify data quality as a major barrier to AI success. Yet, many organizations are not adequately enhancing their data management practices. 

To maximize the potential of custom AI agents, invest in robust data infrastructure, ensure consistent data tagging, and regularly review datasets for accuracy and completeness.  

Support ongoing training

AI agents improve over time, but only if you actively manage them. Regularly updating training data, monitoring performance, and incorporating customer feedback are essential to fine-tune their responses. 

According to an IBM study, 40% of employees will need to retrain due to AI implementations, highlighting the importance of continuous learning and human oversight in AI deployment.  

This will ensure better accuracy, relevant interactions, and customer satisfaction.

Measure and evaluate

According to PwC’s Future of Customer Experience report, 73% of consumers consider the experience an important factor in their purchasing decisions, and 65% of U.S. customers find a positive experience with a brand to be more influential than great advertising.  

By consistently monitoring and refining key metrics like resolution time, deflection rate, and customer satisfaction (CSAT), businesses can ensure their AI agents contribute to improved customer satisfaction and loyalty.

Use Plivo’s custom AI agents to engage customers before they ask 

Custom AI agents are a smart investment for brands looking to grow without compromising customer experience. If you’re ready to put AI to work for your business, Plivo can help. The platform’s custom AI agents are built to fit your workflows, learn from your data, and engage your customers the way you do. 

Here’s also what you get with Plivo to build a solid customer experience:

• Unified agent desktop: A single platform for managing all channels, enabling agents to respond swiftly and accurately while having the full context of each interaction
• AI voice agents: Human-like interactions with advanced speech recognition and contextual awareness
• Seamless integration: Works seamlessly with your CRM, billing, ticketing tools, and knowledge bases to ensure consistent, informed responses
• 24/7 self-service chatbot: Powered by OpenAI, the chatbot addresses up to 70% of common queries, allowing agents to focus on more complex cases
• Automated workflows: Handles follow-ups, routes tickets, and provides updates automatically to keep customers informed
• Intelligent handovers: When AI fails to respond to complex cases, it escalates the query to a human agent with complete context, speeding up resolution
• Top-tier security: Adheres to SOC 2 and GDPR standards to ensure secure customer communications

Want to boost your revenue with custom AI agents? Book a demo now.

Needless to say, ​customer support is a vital organ for business success, directly affecting customer satisfaction, loyalty, and revenue. In fact, a study notes that in 2024, poor customer experiences cost organizations worldwide an estimated $3.7 trillion, marking a 19% increase from the previous year.

Customers often switch companies if they don't receive good customer service, regardless of product satisfaction. Conversely, they are often willing to go out of their way to do business with a company that offers better service. 

Support agents are at the forefront of delivering these sensitive experiences, making their role crucial in fostering customer relationships and driving business growth.​

In this article, we’ll explain who they are, what they do, the essential skills needed to become one, and some steps to build your support team with the best support agents.

Who are support agents (and who are they not)?

A support agent is a trained representative of your company primarily tasked with resolving customers' complaints, answering inquiries, and providing usage guidance on your company’s products and services.

Beyond handling tickets, they also provide emotional support by ensuring customers feel heard, valued, and reassured throughout the interaction. This, in turn, strengthens customer trust and loyalty.

Support agents play a vital role in enhancing customer satisfaction—which indirectly drives ROI through repeat purchases—but they are not sales representatives or marketers. Marketers and sales reps acquire customers and sell. 

On the other hand, support agents retain these customers and boost repeat purchases through efficient assistance.

4 primary responsibilities of a support agent

A support agent's primary responsibilities include serving as the first point of contact, handling queries, providing proactive support, and gathering essential feedback.

1. Serving as a brand's first-line contact

When things go wrong, customers become frustrated and demand to speak with anyone—even the CEO. Your support agents step in to act as the first line of defense, de-escalate situations, and provide solutions professionally. 

They also represent your brand through every empathic response, ensuring customers leave with a positive experience and a lasting impression of excellent service.

2. Handling customer inquiries

Customer support agents handle all customer inquiries. Depending on the technicality of the query, they might sometimes involve a specialist or higher executive. 

For instance, if a customer has a dispute over billing that involves policy exceptions, your agent might need to coordinate with or escalate to a higher executive for approval.

3. Providing proactive support

Support agents detect customer needs ahead of time and promptly contact them even before they log a complaint. This helps reduce inbound tickets and boosts customer satisfaction. 

As an omnichannel customer support platform, Plivo CX’s proactive service enables your support team to provide a more refined and automated proactive support.

4. Gathering feedback to optimize product offerings and marketing

Your support agents are the most valuable source of feedback since they interact with customers daily. They can help you gather recurring concerns, pain points, and suggestions that drive meaningful product improvements. 

Plivo CX’s metrics tool automates this feedback collection process and ensures your agents focus on core tasks instead.

Essential soft skills of a good support agent

Being a support agent involves not only resolving queries but also understanding and communicating with customers on a personal level. This is why certain soft skills, beyond technical competency, are essential when recruiting one.

Active listening and empathy

Active listening involves paying close attention to every word and emotion communicated rather than focusing solely on the problem. 

Unsurprisingly, active listeners excel at expressing empathy since they’re more likely to understand how customers feel better. This deeper connection allows them to communicate effectively, provide reassurance, and de-escalate tense situations.

Good communication skills

A good support agent must convey their points concisely while considering the appropriate tone. 

They know when to avoid passive-aggressive words such as “actually, ought to,” colloquialisms, and slang to maintain clarity.

Adaptability

Different customers present with different complaints, personalities, and communication styles. Some are patient and easy to communicate with, whereas some are aggressive and impatient. 

So, a one-size-fits-all approach won’t work, and that’s why an ideal support agent must be able to adapt to each high and low while maintaining efficient support delivery.

Problem-solving skills

Customer support playbooks are valuable, but not every customer complaint will fit neatly into predefined solutions. Situations like this require your support agent to think outside the box while staying within your company’s guardrails. 

A good support agent must be able to devise quick solutions to new problems and escalate as soon as possible when necessary.

6 steps to hire the right support agent and build a functional support team

Your support team can either make or mar your business. Hiring the right agent and building a functional team is, therefore, essential. Let’s see how to do that.

1. Define your staffing needs and ideal agent

You can figure out how many support agents to hire based on your historical ticket volume, scale of business expansion, and anticipated growth in the next quarters. This ensures you don’t over-hire and bloat your expenses or under-hire and cripple your support delivery. 

Plivo CX’s reporting and metrics tool provides a comprehensive ticket summary, which helps you determine your historical ticket volume.

Simultaneously, you need to define who your ideal agent is—that is, the skills they should preferably possess, availability, technical proficiency, lingual capacities, and experience. You can diversify your recruitment process if you’re catering to multilingual audiences.

Once you’ve identified your staffing needs and ideal candidate profile, you can post your job listing on your company’s career page and on popular job boards like LinkedIn to attract qualified applicants.

2. Prioritize agents with empathy and problem-solving skills

You need a team of agents who can dialogue with different kinds of customers, resonate with them emotionally, and make them feel heard while providing adequate support. That’s why you should prioritize agents with empathy.

Also, look for agents with strong problem-solving skills—someone who can think quickly on their feet and provide solutions to out-of-the-script problems.

Tools like TestGorilla and Testify help you assess your applicant’s skills and ability to address different scenarios. For a more tailored assessment, present candidates with real scenarios or past customer complaints from your database and ask them to resolve the issue.

3. Test for relevant technical competency

Technical competency is your support agent’s ability to resolve customers’ technical queries. This could include troubleshooting software issues and providing answers to product-specific technical queries.

Usually, your agents don’t need to be tech geeks or specialists for L1 tickets. An entry-level customer support agent with the necessary soft skills can do a great job here.

However, it’s a different ball game for agents managing L2 and L3 tickets. They should have the necessary expertise to manage complex and product-related technical issues like specialists. 

This primarily hinges on their hard skills portfolio, which you need to consider when hiring. Provide real-world scenarios to assess these skills and ensure they genuinely have what it takes to be your ideal agents.

4. Provide comprehensive agent training

From the onboarding stage, you need to identify the gaps in your hires’ competencies and design individualized or group training to boost their efficiency. Training can include soft skills, lingual capacity, and upskilling hard skills for more proficiency.

Agent training is not a one-time process. Plivo CX’s coaching tools help your agents leverage past interactions with customers to continuously refine their delivery—how to respond or handle similar situations when they arise again.

5. Equip your support agents with AI-powered tools

Gartner notes that more than 80% are either using or planning to integrate AI-powered chatbots in 2025. Advanced chatbots are essential because they can handle the majority of L1 tickets, thus freeing up your agents to do other complex tasks.

An example is Plivo CX’s openAI-powered AI chatbot, which can leverage your database in real time to make decisions, autonomously handle refund requests, modify orders, and make personalized recommendations.

Your team also needs an omnichannel platform that centralizes all communication channels into a single dashboard. This allows agents to access everything they need without constantly switching tabs, ultimately improving response time and efficiency.

An example is Plivo CX’s unified agent desktop designed to eliminate data silos, unify all incoming customer requests, and integrate with homegrown systems, CRM, ERP, helpdesk, and more.

6. Establish KPIs and reasonable expectations

Establish KPIs, such as first response time, average resolution time, and first contact resolution, to assess the efficiency and effectiveness of your support agents. 

Customer Satisfaction Scores (CSATs) will help determine whether customers are getting the help they need and how they need it.

Plivo CX’s agent metrics and reporting tool enables you to monitor and measure your support agent’s performance while exposing gaps that need filling.

You also need to set individualized, SMART expectations and goals for your support agents. Ensure each agent does not handle more tickets—whether in quantity or complexity—than they can. This will reduce the incidence of customer service burnout and enhance the quality of your support delivery.

Scale your customer support operations with Plivo CX

Hiring the right support agent is just one part of building a functional customer support team. You also need to provide them with the right tools to enhance their efficiency and effectiveness.

That’s where Plivo CX comes in. 

As an omnichannel platform designed to streamline support delivery, Plivo CX offers a unified agent desktop to centralize your support channels, multilingual AI-powered voice support, and OpenAI-powered chatbots to slash your ticket queue.

We also offer: 

• Seamless integrations: Connect Plivo CX with your existing tools, including CRM, ERP, helpdesk, and more.
• Data-driven optimization: Track real-time analytics and generate custom reports to gain insights into customer interactions and agent performance.
• AI-enhanced efficiency: Prioritize urgent tickets, ensure brand consistency, and adapt quickly to changes with AI-powered support.
• Rich communication: Enhance interactions with multimedia support, including images, videos, and documents.
• Increased productivity: Streamline workflows with message templates, internal notes, and skills-based routing.
• Comprehensive features: Leverage call recording, IVR, multi-language support, and robust security features for a complete solution.

‍Book a demo today and start building a world-class support team with Plivo CX.

It’s ten minutes past 2 pm. A new high-value customer submits a technical complaint—but, in Spanish. The problem? None of your service reps speak Spanish. 

Now, you have only two options.

First, you say, “Thank you for reaching out. We currently accept queries only in English. Please resend your message in English so we can assist you. Thank you for your understanding!" 

Or, you scramble from Google’s translator to other free versions of online interpreters, which might give you an inaccurate response. 

Whichever you choose, your customer will likely not find it encouraging. Your inability to efficiently serve customers in their native language passes a message; that they’re not a valued part of your brand. 

According to Hyken’s report, 65% of consumers want to be treated valuably. Failure to deliver this expectation results in a poor support experience, increased churn rates, and a negative brand reputation.

To avoid such outcomes, you need to implement multilingual customer support, and this article will show you how to do that.

What is multilingual customer support?

Multilingual customer support is the ability to provide consistent, high-quality assistance in multiple languages to your customers while accounting for geographical, cultural, and contextual differences that influence communication.

As your business scales, there is also an increasing need to serve a diverse market audience. This mandates your support team to be capable of sustaining interactions with individuals of different languages outside your native business borders.

Even within your business borders, you’re bound to interact with customers of different linguistic needs. According to the United States Census record, the number of residents who utilize other languages besides English has nearly tripled in the last decade. 

So, you must be ready to cater to this diversity once necessary.

Benefits of multilingual customer support

Multilingual support increases customer satisfaction, boosts retention, and ensures you can tap into diverse markets for more opportunities. Here’s how it does that:

Improved customer satisfaction

According to Unbabel’s 2021 multilingual CX report, one in three global consumers cite a lack of multilingual support as their top concern in localized customer experience. 

Uni- or bilingual provisions lead to frustration since your customers can’t express themselves the way they want, and this culminates in a bad customer experience. 

On the other hand, providing multilingual support can enhance customer satisfaction and boost your customers’ LTV. This explains why 64% say they will pay more for a service or product if the brand offers a multilingual support service.

Higher customer retention

57% of global consumers see it as a bias when a brand fails to offer multilingual support. Two in three will also switch to another brand if their current brand does not offer broader language support.

But what happens if you fill up this communication gap? 73% of respondents in Unbabel’s survey say they will remain loyal. 

This means multilingual provisions can help you retain your existing customers and also gain an edge over your competitors in attracting new ones. 

Interestingly, 40% of consumers will likely overlook poor customer service many times if it is offered in their native language. This gives you enough time to address issues plaguing your support delivery before customers bounce.

Broader reach and competitive advantage

Scaling your business often requires crossing borders and serving new audiences. Multilingual support ensures you can easily resolve the issues coming up in these regions, eliminate communication barriers, and rapidly build a robust brand reputation.

Also, multilingual support can serve as the spearhead of your competitive advantage in new markets. That’s because your potential customers will likely choose you over competitors who do not offer multilingual support, all things being equal. So, you can make it a focus of your marketing strategy.

7 must-know strategies to implement multilingual support

One in four consumers say they will not spend more than $500 on brands offering limited language support. You can avoid this by implementing a sturdy multilingual support system. 

Let’s go through how you can do that. 

1. Be upfront about your available language options

First, inform your customers and audience about your current capacity. Include the languages you support on your website, applications, social media profiles, and customer support pages. 

This helps to manage customer expectations and reduce frustrations pending the time you make provisions for multiple languages.

2. Embrace diversity in recruitment

The most direct approach to creating a multilingual support system is to recruit multilingual customer service reps. These reps are especially crucial for managing L2 and L3 tiers of requests that AI might not be able to handle.

Ensure you have at least one native or non-native representative for each region you serve. You can also organize language training for your existing service reps instead of overhauling the entire team. 

This reduces your employee acquisition cost and helps you work with people already in tandem with your support operations.

3. Use AI chatbots to provide multilingual support

Advanced AI chatbots use ML and NLP to analyze user inputs such as complaints and provide appropriate responses while leveraging customer data. This is like having an inbuilt translation system, making them a good fit for handling multilingual L1 requests regardless of the language.

As an omnichannel platform designed to scale your support team, Plivo CX offers an OpenAI-powered chatbot capable of handling multilingual tickets and addressing your customers in the language they choose.

4. Integrate multilingual voice support 

According to a 2024 report from Statista, 54% of customers prefer to resolve issues via phone calls over other digital channels and email. To cater to this group, you need to integrate multilingual voice support technology.

An example is Plivo CX’s voice software, which prompts your customers to choose their preferred language from over 27 supported languages right on the call.

With an integrated programmable IVR, your callers can self-select options for quicker routing, shorter wait times, and faster resolution.

5. Offer language preferences in self-service options

Self-service options include FAQs, knowledge bases, chatbots, AI-powered virtual assistants, and community forums. Your customers must be able to choose their preferred language of interaction on all of these platforms in order to cater to their needs.

Additionally, ensure that automated responses, IVR systems, and in-app customer support are available in multiple languages.

6. Train support agents in cultural sensitivity

Multilingual support should cater to lingua-cultural nuances that affect communication. Otherwise, you risk irking your customers. 

For instance, there are certain words or expressions that might be normal in American English but seen as aggressive in British English.

One example is the word “sure.” To an American, it’s simply a means of acknowledgment. But it could come off as passive-aggressive to a non-American. 

Train your support reps to understand these nuances and avoid them when speaking with individuals of different cultural backgrounds.

7. Localize knowledge base and FAQs  

Language location refers to adapting your website content to a visitor’s regional language based on factors like their browser settings, IP address, or geographical location. 

o do this, you first need to translate your knowledge base and FAQs into the different languages you support. You can do this manually or with AI. Then let your web development team handle the transitioning.

This method spares customers the hassle of manually selecting their preferred language. However, you should still offer a visible option on your support pages for them to adjust language preferences if needed.

Deliver modern multilingual support with Plivo CX

Language differences stifle quality support delivery and effective communication. 

To help you, Plivo CX offers a multilingual omnichannel support system through its Unified Agent Desktop, OpenAI-powered agentic chatbot, and inclusive voice support to help you overcome these challenges.

We also offer: 

• Seamless integrations: Connect Plivo CX with your existing tools, including CRM, ERP, helpdesk, and more.
• Data-driven optimization: Track real-time analytics and generate custom reports to gain insights into customer interactions and agent performance.
• AI-enhanced efficiency: Prioritize urgent tickets, ensure brand consistency, and adapt quickly to changes with AI-powered support.
• Rich communication: Enhance interactions with multimedia support, including images, videos, and documents.
• Increased productivity: Streamline workflows with message templates, internal notes, and skills-based routing.
• Comprehensive features: Leverage call recording, IVR, multi-language support, and robust security features for a complete solution.

Book a demo now!

Let’s be real—getting leads isn’t the problem. Getting them to engage? That’s the real challenge. You can have the best offer, but if your message is not seen, it won’t get results.

The good news is that SMS is breaking through the noise. In fact, 76.2% of consumers say SMS is more effective at generating actions that lead to a purchase than email.

Why? Because texts land directly in your customer’s hands—no spam filters, no distractions, just instant, personal communication.

SMS lead generation is quickly becoming a cornerstone of modern marketing. In this article, we’ll dive into why SMS lead generation is rapidly becoming a must-have for businesses looking to engage, convert, and grow their customer base.

Why SMS is an effective lead generation tool

SMS marketing is a powerful tool for lead generation. It helps businesses build and nurture a qualified audience directly through SMS. Here are some key advantages that make SMS so effective for lead generation: 

High open rates & immediate attention

Text messages are almost always read – often within minutes. Studies confirm SMS open rates around 98%, higher than email​. The immediate visibility means your lead-gen offers (coupons, event invites, etc.) get seen right away, capturing customer attention in real time.

💡 Pro tip: Time your SMS campaigns strategically—sending messages when customers are most active can increase engagement and conversions.

Direct & personal communication

SMS creates a direct and personal connection between brands and potential customers. With the ability to personalize messages based on customer preferences, past interactions, or purchase history, SMS helps brands build stronger relationships and trust. 

Example: "Hi [Name], your favorite moisturizer is back in stock! Shop now before it’s gone: [link]."

💡Pro tip: Use first names, purchase history, or location-based offers to make SMS messages feel even more relevant and personal. 

Real-time engagement 

SMS enables businesses to engage with customers instantly. This makes SMS a preferred medium for promotions, updates, and limited-time offers. It allows for two-way conversations, where businesses can answer questions and send timely reminders when a lead is most interested. 

💡 Pro tip: Use SMS for flash sales or time-sensitive deals—customers are more likely to act quickly when they receive an offer with a clear deadline.

Cost-effective marketing

SMS campaigns are a cost-effective way to engage potential customers and increase sales. With message costs ranging from $0.015 to $0.050 per SMS, businesses can reach large audiences without significant money spent. 

Despite the low cost, SMS generates high response rates and a strong return on investment, making it an excellent text message lead generation tool for lead nurturing, promotions, and customer retention. For budget-conscious marketers, SMS offers maximum impact with minimal expense.

Example 1: A boutique clothing store replaces printed discount flyers with SMS promo codes, saving on printing costs while directly reaching active shoppers.

Example 2: Instead of investing in costly retargeting ads, a home décor brand uses SMS flash sale alerts to attract customers for exclusive discounts and limited-time offers

Automation & scalability 

With SMS automation, businesses can send messages to thousands of customers efficiently. Automated workflows allow brands to set up welcome messages, abandoned cart reminders, or follow-ups without manual effort. 

Whether you’re targeting a small segment or a nationwide audience, SMS can scale to meet your needs​

💡 Pro tip: Set up an automated drip campaign to send SMS messages over time. This helps to guide potential customers toward a purchase.

Together, these advantages explain why more businesses are leveraging SMS for lead generation. 

Proven SMS techniques for lead generation

You know SMS works—but how do you use it to drive more leads? Here are some tested strategies that top brands rely on to turn texts into conversions.

Offer exclusive content or discounts

People love getting something extra, especially when it feels exclusive. By offering discounts, special deals, or early access to new products via SMS, you create an immediate incentive for customers to respond.

Make sure your offer is time-sensitive to create urgency, which further motivates recipients to act quickly. Phrases like “For you only,” or “Exclusive offer just for our subscribers” can make recipients feel valued and increase the chances of conversion.

Create compelling CTAs for immediate action 

Create your SMS messages with a clear, strong call-to-action (CTA) that urges instant response. Since texts are typically read quickly and have a character limit, use that brief moment to spark action.

Pro tip: Use action-oriented language like “Claim your offer now,” “Get started today,” or “Shop while stocks last” to prompt immediate responses.

Lead generation through SMS thrives when your CTA is clear, direct, and compels the recipient to act fast.

Use opt-in keywords and shortcodes 

Simplify the process of joining your SMS list through keywords and shortcodes. For instance, you might advert JOIN to 12345 for updates.” This text-to-subscribe approach makes opt-ins instant. A customer sends a one-word text and is automatically added to your campaign. 

Example:

A fitness apparel brand wants to grow its SMS list. They advertise:
“Text FIT to 56789 for 15% off your first order and exclusive updates!”

By texting “FIT” to 56789, customers are instantly added to the SMS list. This quick, frictionless opt-in process allows leads to sign up easily with just one text.

Pro tip: Make sure to choose an easy-to-remember keyword related to your campaign (e.g., text SALE, VIP, DEMO, etc.).

Segment your audience for targeted campaigns

One-size-fits-all messaging yields mediocre results. Instead, segment your SMS leads based on factors like demographics, purchasing behavior, and engagement history.

Example:

An online clothing store wants to send targeted offers. They segment their audience into two groups: frequent shoppers and seasonal browsers.

• Frequent shoppers: Receive exclusive offers like “Thanks for being a loyal customer! Enjoy 25% off your next order.”
• Seasonal browsers: Receive a message like “Welcome back! Get 15% off your next purchase, just for you.”

Businesses that segment their SMS campaigns see higher conversion because the messaging is more personalized and on-point​. 

Utilize SMS automation for timely follow-ups 

Don’t rely on manual texting, set up automated SMS workflows that send follow-up messages, reminders, or abandoned cart notifications. These automated texts can remind customers about products they’ve left behind, share additional offers, or provide updates on the status of their orders. 

SMS automation ensures no customer is left unattended and helps move prospects down the funnel with well-timed nudges.

Example:

An online home goods store uses SMS automation to follow up with leads.

• Welcome message: As soon as a customer subscribes, they receive an immediate “Welcome! Get 10% off your first order. Shop now!”
• Follow-up offer: If the customer hasn’t made a purchase within two days, they receive a reminder: “Still thinking it over? Here’s 15% off your first order!”

By implementing these techniques, you can steadily grow your list of SMS leads and keep them actively engaged. 

Best practices for SMS lead generation

While SMS is powerful, success largely depends on how you use it. Here are some best practices to ensure your SMS lead generation campaigns are effective and well-received:

Personalize and be relevant 

Treat SMS leads like individuals, not numbers on a list. Use personalization wherever possible—greet recipients by name and tailor messages to their interests or past interactions. 

For example, if you know a customer’s preferred product category, mention it. Personalization shows that your texts are for them, which improves response rates. 

In this SMS (image below), they address the customer by name (Elizabeth) and highlight their status as a “Platinum Comfort Crew member.” Personal touches like this make the recipient feel special and valued.

Optimal timing and frequency 

A staggering 90% of consumers respond to a text within 30 minutes, which underscores the importance of reaching your audience at the right moment. 

To maximize engagement, aim to send texts between 10 AM and 8 PM, avoiding early mornings before 8 AM, late evenings after 9 PM, Mondays, and rush hours. Mid-afternoon often works best. 

When it comes to frequency, it’s all about balance. Nearly 60% of smartphone users opt out of a brand’s messages when they feel overwhelmed by too many updates. 

Pro tip: Space out your messages and keep them meaningful—aim for one or two valuable texts per week to avoid overwhelming your audience and maintain engagement.

Keep messages concise and clear 

SMS has a character limit, which means you must communicate your message clearly and concisely. Your text should get to the point quickly, without any unnecessary fluff. 

Focus on one core message in each SMS, whether it's an offer, update, or reminder. Use short, direct language, and avoid long sentences or paragraphs.

For example, instead of saying, “We have a new collection of products that we think you might like, and it’s available on our website,” say, “New collection just dropped! Shop now and get 10% off!”

If more detail is needed, include a link to a mobile-friendly landing page for the lead to learn more. 

Track and analyze performance 

Treat SMS campaigns like any other marketing effort – track the results and adjust the strategy accordingly. Monitor key metrics such as open rate, click-through rate, response rate, and conversion rate. 

Also, pay attention to unsubscribe rates after each SMS campaign. Analyzing these data points will tell you what’s working and what isn’t. You can experiment with A/B testing for different CTAs, message lengths, or timing to see what drives the best results

For instance, you may find that messages sent on Friday evenings receive higher engagement or that one offer generates more conversions than another. Use this insight to refine your approach, perhaps adjusting send times, wording, or segment targeting. 

The role of SMS marketing automation in lead generation

Automation simplifies lead generation by handling manual tasks, ensuring no lead slips through the cracks. With SMS marketing automation, businesses can send the right message to the right lead at the right time—without manual effort for each interaction. This makes capturing and nurturing leads easier, faster, and more efficient.

Here’s why SMS automation is so important and how it works:

Key benefits of SMS marketing automation

✅ Instant follow-ups: Automatically send a welcome message as soon as a lead opts in, keeping them engaged from the start.

✅ Personalized offers: Use customer data to send relevant offers, product recommendations, and reminders tailored to their interests.

✅ Higher conversion rates: Schedule automated follow-ups to nurture leads, recover abandoned carts, or re-engage inactive customers.

✅ Timely touchpoints: Ensure leads receive timely updates, promotions, and reminders without manual effort.

✅Scalable communication: With the right SMS lead generation tool, you can manage high volumes of leads with automated workflows. This frees up your team while maintaining consistent outreach.

As a robust omnichannel customer engagement tool, Plivo CX checks all the boxes for a reliable and efficient SMS lead generation platform. 

With its user-friendly interface and powerful analytics tools, Plivo CX optimizes your SMS marketing for maximum impact and streamlines your lead generation and conversion process with automation.

As a testament to its efficiency, Deckers Brands found Plivo's queuing system to be a game-changer. Jacob Martine, project manager at Deckers Brands, states, 

"With fewer worries about rate limits and batch sizes, our developers face less burden. If we need to send 50,000 messages, we simply send them all—Plivo handles the rest, delivering without us worrying about the process."

Drive more leads with SMS marketing powered by Plivo CX

E-commerce managers face a tough challenge—reaching customers at the right time is harder than ever. Manual campaign management takes too long, and generic messages don’t drive conversions. Without automation and personalization, it’s easy to miss opportunities to connect with potential buyers

Plivo CX is an all-in-one customer engagement platform designed to maximize SMS lead generation results. It brings together real-time delivery, intelligent automation, and data-driven insights so businesses can capture and convert more leads via SMS. 

Here’s how Plivo CX can get more leads by elevating your SMS marketing:

• Powerful audience targeting: Build highly focused campaigns by syncing your e-commerce platform data or importing contacts. With the Audiences feature, segment audiences based on purchase behavior, engagement data, and demographics to send highly personalized SMS campaigns.

• Multi-channel engagement:  Connect with your customers on their preferred channels—whether it's SMS, MMS, or Email. This increases the chances of meaningful interactions and conversions.

• AI-powered SMS personalization: Use the Copywriter AI to generate compelling, data-driven SMS messages instantly. Fine-tune your messages to resonate with your audience instantly.

• Send messages at the ideal time: Automate and schedule messages to align with optimal timings across different time zones, ensuring they reach customers when they are most likely to engage, maximizing impact.

• E-commerce integrations: Effortlessly connect with e-commerce platforms like Shopify, WooCommerce, BigCommerce, and Magento to personalize and send SMS directly from your e-commerce platforms.
• Track conversions & optimize ROI: Gain valuable insights into what resonates with your audience and continuously optimize your campaigns for maximum ROI. 

With Plivo CX’s robust global messaging network covering 220+ countries, businesses can scale their SMS marketing effortlessly, reducing costs by up to 70% while tripling ROI.

Plivo CX users generate an average of $71 for every $1 spent, making it a must-have for data-driven, high-impact SMS campaigns.

Don’t let missed opportunities hold your business back—start driving more leads and conversions today with Plivo CX. 

Schedule a free demo now!

56% of customers abandon purchases because businesses take too long to respond. That’s more than half of your potential sales lost.

That’s why 69% of users prefer brands that offer WhatsApp as a support option. It’s fast, familiar, and available right where your customers already chat. 

In fact, brands like Amazon and Zappos use WhatsApp for fast, hassle-free support. No long wait times, no back-and-forth emails, just quick answers when customers need them.

This guide will show you how to set up WhatsApp for customer service, automate responses, and improve customer satisfaction without increasing costs.

What is WhatsApp Business? 

WhatsApp Business is a free and specialized messaging tool that helps SMBs and companies connect with their customers on WhatsApp. It allows businesses to answer questions, send updates, and provide real-time customer support with tools such as quick replies and automated messages.

To understand why WhatsApp Business has become essential for modern customer service, let's examine its key features and how they benefit your business operations.

Features & benefits of WhatsApp for customer service

Now that you understand the powerful features WhatsApp Business offers, let's walk through how to set it up and optimize it for your customer service needs.

How to set up WhatsApp for customer service 

Whether you’re a small business just starting out or an established brand, follow these steps to set up your WhatsApp business account and start assisting customers in real time:

1. Create a WhatsApp for business

Start by downloading the WhatsApp Business app from the Play Store or App Store, depending on your device type. Once you’ve done this, sign in with your phone and create your business profile.

The app will guide you through the basic setup where you have you mention your registered business name, its description, contact information, and working hours.  

Review the terms of service that includes allowing access to contacts and photos, and fill out the relevant fields.

2. Link your online store and product catalog

After you are done setting up your account, it’s time for customization. This includes the following:

• Profile photo: Use your business’s logo for clarity
• Cover photo: Upload product pictures or customers with your products
• Business description: Briefly describe what your business offers and what sets it apart
• Business category: Select up to three categories to help customers understand your services
• Address: Add your location if you have a storefront
• Email contact: Provide an email option for customers who prefer it
• Website link: Direct customers to your website for more information
• Phone support: Include a contact number if you offer voice support
• Verification badge: Apply for WhatsApp verification to earn the green checkmark
• Product catalog: Display your top products with high-quality images and descriptions
• Collections: Group products into categories for easy browsing
• Business hours: Specify when a live agent is available to respond. Set up automated away messages to inform customers of response times outside these hours

3. Integrate with your existing business framework

Connect WhatsApp with existing business frameworks to track and manage all interactions from a single, centralized system. 

For example, when you use an omnichannel customer service platform like Plivo CX, you can seamlessly switch between voice, chat, SMS, and WhatsApp. What’s more, it allows you to integrate custom knowledge bases, including business documents like SOPs, FAQs, and blog posts, enabling your support team to automatically and accurately respond to customer queries.

4. Use automation to handle common questions

You can use AI chatbots from third-party providers or opt for Meta’s Business AI to interact with customers. 

However, it’s important to note that WhatsApp’s built-in Business AI is limited. It’s only available in select countries, supports just two languages (English and Spanish), and is restricted to certain businesses. That means many brands can’t entirely rely on it for automated customer support.

Instead, integrating AI chatbots from specialized platforms like Plivo CX offers greater flexibility, broader language support, and advanced automation. With the OpenAI-powered AI agents, you can:

• Converse with a natural human-like tone
• Answer common questions instantly to reduce wait times
• Guide customers to self-service resources like FAQs and order tracking
• Schedule appointments and process simple transactions without human intervention
• Scale support across multiple languages to serve a global audience

5. Send proactive notifications with WhatsApp templates

Using customer service templates saves time and ensures consistent and compliant responses. With WhatsApp, you can create Message Templates to reach out to customers proactively. 

However, WhatsApp has strict rules. You must submit templates for approval, and they’re limited to specific topics like account updates, shipping notifications, and issue resolutions. Marketing messages aren’t allowed.

If you use Plivo CX, you can submit templates for approval and send proactive messages directly through WhatsApp.

6. Gather insights through customer feedback

The last and most important step is to track key metrics to measure performance. This helps you identify strengths and spot areas for improvement to refine your customer support.

Most support tools provide detailed reports with visual insights, but if you’re focusing on just a few key metrics, start with:

• Response time: Monitor how quickly your team replies to prevent long wait times
• Resolution time: Track how long it takes to resolve customer issues fully
• Customer satisfaction (CSAT): Gather CSAT scores to understand if customers are happy with your support
• Customer feedback: Actively collect and document feedback to refine your service and better meet customer needs

Best practices of using WhatsApp for customer service 

Follow these best practices to ensure quick responses and personalized interactions and get the most from WhatsApp:

Respond quickly

Needless to say, customers expect fast replies. Chatbots provide instant support 24/7, handling common questions and freeing up agents for complex issues. AI-powered assistants can resolve service requests without preprogrammed responses.

To speed up replies, use quick replies or message templates. Always personalize messages and double-check for accuracy before sending.

Use images and videos for clarity

Visuals improve customer support. Share screenshots, product images, or tutorial videos to make solutions clearer. Adding emojis can also make messages more engaging.

Personalize your responses

You can link WhatsApp to your CRM to access customer history and tailor responses. Customers expect agents to have their past interactions on hand, as 70% say they want consistent service across all agents. Avoid frustrating them by ensuring they never have to repeat themselves.

With its unified agent desktop, Plivo CX lets your agents have a complete understanding and context of the problems customers could be experiencing.

Let customers know you’re on WhatsApp

Customers may not reach out if they don’t know you’re available on WhatsApp. Make it easy by:

• Adding a WhatsApp chat button on your website
• Including WhatsApp on your Contact Us page
• Promoting it through newsletters, marketing emails, and social media

Keep customers updated on their orders

Send a confirmation message on WhatsApp as soon as a customer places an order. Include the order number, item details, and estimated processing time.

Share timely updates as the order moves through different shipping stages, such as processing, shipping, or being out for delivery. Provide tracking details and estimated delivery times to keep customers informed.

Gather customer feedback

Encourage customers to share their thoughts on their purchase by sending a quick message on WhatsApp. You can collect feedback in several ways:

• Send a short survey with multiple-choice or rating options
• Ask open-ended questions for detailed responses
• Use quick-reply buttons to make it easier for customers to respond

Offer 24/7 WhatsApp support with Plivo CX

Plivo CX simplifies WhatsApp customer support by offering a feature-rich platform designed for automation, scalability, and ease of use. Whether you’re handling peak volumes, sending order updates, or automating responses, Plivo’s AI agents ensure a smooth experience for both your team and your customers.

Why choose Plivo CX for WhatsApp support?

• Engaging Conversations: Share images, videos, and documents to provide clear and helpful responses
• Scalability: Handle thousands of chats at once, even during high-traffic periods
• Real-time tracking: Get instant delivery reports to monitor message performance
• Faster troubleshooting: Use detailed logs to quickly identify and fix issues
• Multilingual support: Automatically detect and reply in 28 languages
• Efficient messaging: Broadcast updates to multiple customers at once
• Interactive responses: Add quick reply buttons to streamline interactions
• Consistent communication: Use pre-approved message templates for faster responses

Book a demo now to learn more.