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.
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.
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.
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:
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.
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.
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.
