AI Agent vs. Traditional Chatbot: Maximize Revenue and Customer Experience

Should you upgrade to an AI agent, or keep using a traditional chatbot? Assuming that everything else in your store is optimized and in tip-top shape, an AI agent can have a greater impact on your revenue potential and overall customer experience.

AI agents provide new opportunities for automation in ecommerce. They expand the abilities of traditional chatbots, enabling brands to boost sales and improve customer satisfaction at the same time:

Beerwulf’s AI agent generated 2x the ROI of their previous chatbot and increased their CSAT score to 85%
Calendars.com was able to reduce chat response wait times by 81%
True Classic generated $3 million in support-driven revenue, reduced support costs by 38% lower, and achieved a 98% CSAT score

So, should you drop every other priority and immediately upgrade to an AI agent? Before you do that, there are a few things to consider.

Checklist – should you upgrade from classic chatbot to AI Aagent?

When you’re considering if your store needs an AI agent, answering the questions below will help you make a decision.

1. How many customer queries do you get, and how complex are they?

For some sellers, a chatbot is just an interactive way for a customer to leave their contact data so that a human support agent can reach out to them. Your scale might be too small, or your buying process too complex to merit automation with an AI agent.

An AI agent will provide the most benefits if your human service agents are regularly overwhelmed with basic customer inquiries. Even more so if you get spikes in sales due to special events, holidays, or seasonal changes.

2. How much time and resources are you spending on maintaining and updating your chatbot's scripts and decision trees?

Traditional chatbots are only as good as you program them to be. You need to predict the questions that your customer might have, and provide predefined answers that are as universal as possible.

An AI agent, on the other hand, doesn’t have to be programmed like that. It learns from your knowledge base, your SOPs (Standard Operating Procedures), workflows, templates, FAQs, brand guidelines, and any other resources. Plus, it keeps learning and improving with every customer interaction that it resolves.

3. Are you losing potential sales due to the limitations of your current chatbot?

Being proactive is not something that classic chatbots are good at. They can’t really upsell or recommend products in a natural way.

An AI agent excels in this area. It contributes to sales growth thanks to its ability to understand what the customers need, what mood the customers are in, and which products will meet their needs best – or perfectly complement whatever’s already in their cart.

4. How important is personalization in your customer experience strategy, and can your current solution deliver it effectively?

If predefined responses with basic personalization (like using the customer’s first name) are all you need, a standard chatbot will do fine.

But if you want to provide a higher level or personalization, and you want automated support to behave more like a human agent, and show a greater level of understanding the customer’s preferences – an AI agent will do the trick.

5. Do you have the necessary data to teach an AI agent?

If your customer experience strategy is not documented, you don’t have FAQs or a knowledge base, your whole CX department is in its early stages, you might not benefit much from an AI agent yet. A traditional chatbot could theoretically be better, because it will force you to build a foundation of CX procedures that can be used to train an agent in the future.

6. What languages do you need to support?

The more languages you want to provide support in, the more sense it makes to use an AI agent. It can offer human-like support in over 170 languages out-of-the-box.

7. Are you looking for cost savings, increased efficiency, improved customer satisfaction, and revenue growth?

A traditional chatbot is a basic form of customer experience automation, boosting efficiency but not much else. An AI agent can provide all four of the above benefits.

8. Do you need a solution that can flexibly scale as your support inquiries fluctuate?

Seasonal changes, promotional events that drive more purchases, holiday sales boosts, random spikes in customer inquiries – these are all challenging to deal with when you’re using a traditional chatbot.

If flexibility is what you need, then an AI agent will meet your needs best. It scales up when there are more support tickets, it scales down when interest declines, and you pay only for the cases that it resolves.

Detailed comparison of AI agents and traditional chatbots

For a quick overview of the main differences between AI agents and classic chatbots, here’s all you need to know:

Feature	Chatbots	AI Agent
Natural Language Understanding	Limited, often based on keyword matching	Advanced, can understand context, nuances, and complex queries
Contextual Awareness	Minimal, often loses context between messages	High, maintains context throughout the conversation
Learning and Adaptation	Static, requires manual updates	Dynamic, learns from interactions and improves over time
Handling Complex Queries	Limited to simple, predefined scenarios	Can handle intricate issues and multi-step processes
Personalization	Basic, often based on predefined user segments	Highly personalized, adapts to individual user needs and preferences

Proactive Sales Capabilities	Limited, usually restricted to basic product recommendations	Advanced, can analyze user behavior, make tailored recommendations, and upsell naturally
Integration with Existing Knowledge Bases	Often requires manual input of information	Can be easily trained on existing databases, FAQs, and support materials
Multilingual Support	Typically requires separate setups for each language	Can provide support in multiple languages with a single setup
Scalability	Limited, performance may degrade with high volumes	Highly scalable, can handle large volumes of queries simultaneously

Conversation Flow	Rigid, follows predefined paths	Flexible, can handle unexpected turns in conversation
Response Generation	Pulls from a database of pre-written responses	Generates unique, contextually appropriate responses in real-time
Handover to Human Agents	Often abrupt and lacking context	Smooth transition with full context provided to the human agent
Continuous Improvement	Requires manual analysis and updates	Automatically identifies areas for improvement based on interactions
Integration with Other Systems	Often limited to basic API connections	Can integrate deeply with CRM, inventory, and other business systems
User Experience	Can feel robotic and impersonal	Provides a more natural, human-like conversation experience

Handling of Ambiguity	Struggles with unclear or ambiguous queries	Can ask clarifying questions and interpret ambiguous inputs
Analytics and Insights	Basic reporting on usage and common queries	Provides deep insights into customer behavior, preferences, and pain points
Maintenance Requirements	Requires regular manual updates and tweaks	Self-improving with minimal manual intervention required
Cost Efficiency	Lower initial cost, but limited capabilities	Higher initial investment, but greater long-term value and efficiency
Sentiment Analysis	Basic or non-existent	Advanced, can detect and respond to user emotions and tone, and direct an irritated customer to a human agent if necessary

How are AI agents better for ecommerce compared to traditional chatbots?

The single greatest thing about AI agents is their anthropomorphism – talking to them feels like you’re talking to a human. Compared to traditional, rule-based chatbots, AI agents are:

More intelligent
Easier to use
Able to solve more problems

This, along with other abilities of AI agents, can greatly benefit the ecommerce customer experience:

Greater satisfaction – thanks to natural, human-like interactions and the ability to resolve more issues without delegating to a human agent. Plus, AI agents recognize issues with the store and product catalog as they arise and notify you of them, helping you boost satisfaction by fixing them ASAP.
Increased efficiency – they simply get more stuff done without human involvement, which is particularly useful during sales spike events like holidays. Resolving at least 50% of issues automatically, AI agents help humans focus on the most demanding tickets.
Proactive sales – AI agents don’t just resolve issues better, but they proactively increase revenue. Ecommerce brand Burju shoes saw 50% revenue growth thanks to implementing an AI agent, along with a return rate that’s 30% below industry average.
Seamless integration – you don’t really program an AI agent, you simply teach them all of the information they need to help your customers, along with guidelines to speak in your brand voice.
Multilingual support – easily automate support in different locations thanks to the AI agents’ ability to speak any language, like ecommerce brand Answear whose AI agent achieved a 90% CSAT score across 8 different languages.
24/7 availability – this has always been a key selling point for chatbots, however AI agents finally make it feel like you’re talking to a human, so customers always get a satisfying, personalized experience rather than a cold, rigid interaction with a traditional chatbot.

Benefits of standard, rule-based chatbots

Traditional chatbots, the precursors to today's AI agents, are good at handling simple, repetitive tasks in customer service. They can automate the simplest customer service tasks, reduce wait times for simple queries, and provide 24/7 availability for basic support.

They are rule-based systems that provide predefined options and answers to common questions and even guide users through basic troubleshooting steps or a simple buying process.

When the needs of your customers are basic, it might be enough to program a classic chatbot to handle them or direct users to self-service resources like FAQs.

The ability of classic chatbots to handle nuance or complexity is very limited. You basically need to predict every question a customer might ask, and program a scenario of how the chatbot should address it.

Compared to an AI agent, classic chatbots are limited in many ways:

Lack of flexibility – rule-based chatbots struggle to understand user inputs outside their predefined rules and parameters. If a customer asks a question in an unexpected way, the chatbot might fail to provide a relevant response, leading to a poor user experience.
No personalization – chatbots don’t offer highly personalized, user-specific interactions. They mostly provide generic responses based on predefined rules, resulting in conversations that feel impersonal and robotic.
Couldn’t navigate complex issues – rule-based chatbots can’t handle intricate or multi-layered conversations. When faced with complex questions, they can give irrelevant or incomplete answers, frustrating users.
No learning capability – rule-based chatbots can’t learn from experience. They require manual updates and maintenance, which is time-consuming and resource-intensive.
Limited conversational flow – conversations with rule-based chatbots follow a fixed, linear dialogue based on decision trees. This rigid structure makes interactions feel unnatural and boring.

How AI agents influence ecommerce operations, customer satisfaction, and brand perception

AI agents are an evolved tool for the ecommerce brands that want to lead their market in customer experience. They have a greater impact on brand perception and customer satisfaction than classic chatbots, and they add a boost in revenue potential to the mix thanks to their abilities:

Enabling natural, context-aware interactions
Adapting to customer needs in real-time
Becoming smarter with every customer interaction
Learning your service workflows, standard operating procedures, FAQs, knowledge bases, brand guidelines, and any other resources you feed them

This all translates into clear business outcomes. AI agents can handle more queries that previously required human intervention, reducing wait times and increasing first-contact resolution rates. For example, AirHelp aimed to automate 25% of incoming chats but found their AI agent could actually resolve 48%.

The personalized, round-the-clock service that AI agents provide enhances brand perception. It demonstrates a commitment to innovative, responsive support. They free up human agents to focus on complex issues, resulting in a higher level of service across all customer touchpoints. By maintaining context throughout conversations and offering more relevant responses, they foster engaging and satisfying interactions, boosting customer loyalty and improving brand perceptions.

The next step in customer experience automation

Traditional chatbots have served businesses well, offering basic automation for simple customer inquiries. For some stores with straightforward needs, they might still do a decent job. But customer expectations evolve and ecommerce complexities grow, so most stores will find themselves needing a more sophisticated solution.

If you're aiming to enhance customer satisfaction, drive revenue growth, and future-proof your business, it may be time to upgrade from a chatbot to an AI agent – we’re here to help you.

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