Providing Customer Support at Scale with Ecommerce Chatbots

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Chatbots have exploded in popularity following recent advancements in generative artificial intelligence (AI). 

While some people use OpenAI’s ChatGPT to help on homework assignments and generate pickup lines for dating apps, ecommerce businesses are using chatbots to provide high-quality customer service in real time.

Given their cost-effectiveness and ability to “drive positive customer emotion,” Gartner predicts that chatbots will become a primary customer service channel by 2027.

However, chatbot deployments aren’t perfect. Some bots might have limited conversational abilities and can’t handle complex queries. They may also lack contextual understanding, even if they are programmed to pull data from a CRM system that provides insight into the customer’s purchase history and previous interactions with the bot.

Finally, bots lack a human touch. One study found that 95% of online shoppers who interacted with a chatbot said their presale experience would have been better with human help. 

That being said, there are many things chatbots can do well, including basic customer support, product recommendations, and cart abandonment.

Types of ecommerce chatbots

Ecommerce chatbots come in three types with varying AI capabilities. Machine learning algorithms enable chatbots to learn from interactions, while others are manually programmed with rule-based responses. 

AI-driven chatbots.

AI-driven algorithms can analyze the content, intent and sentiment of customer queries, and provide contextually relevant responses using natural language processing (NLP). These chatbots deliver personalized experiences through user segmentation. 

Conversational AI can generate human-like responses rather than using canned phrases, which provides a more positive experience. Machine learning algorithms continuously learn from interactions, increasing the accuracy of their output over time. 

Rules-based bots.

A rules-based bot operates on a set of predefined rules and conditions. These rules are typically based on “if…then” statements or decision trees. 

For example, if a user asks about order tracking, the bot will formulate a response by following a predefined path. Its answers usually follow a specific template with placeholders for customer-specific data: “Hello [first name], We are processing your order. Your estimated delivery time is [insert date].” 

The responses are static and do not adapt based on user responses or feedback.

Rules-based bots rely on keyword matching or pattern recognition to interpret user inputs, so their capabilities are limited.

Hybrid chatbots.

Hybrid chatbots combine the capabilities of AI-powered bots and rules-based algorithms to provide a more versatile conversational experience. 

A hybrid chatbot offers the benefits of rule-based systems, such as control and predictability, along with the flexibility and contextual understanding of AI-driven systems.

This approach enables the bot to handle structured queries (i.e.: informing a user of the store’s return policy) while fielding complex requests, such as technical troubleshooting.

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How enterprise chatbots uplevel online businesses

Enterprise chatbots enable online stores to provide 24/7 support cost-effectively. Here are some other advantages of using a chatbot:

Smart handling of a user’s request.

CRM systems build a user profile for each customer based on their chatbot interactions, purchase history, and browsing habits. Enterprise chatbots integrate with the CRM to gain insight into the user’s context and personalize its responses. This enables the bot to provide superior product suggestions and anticipate user needs. 

Integrates with more complex enterprise platforms and systems.

API integrations enable messenger bots to exchange data with other enterprise platforms, such as inventory management software, payment gateways, and product catalogs. These integrations empower chatbots to handle end-to-end transactions for online shopping. 

For example, when a customer asks for a product recommendation, the bot can pull listings from the ecommerce platform, accept payment, and fulfill the order. 

Allows for seamless takeover by a live customer service agent.

Nothing frustrates customers more than being prevented from reaching a live agent if a bot can’t handle their request. Program the chatbot to identify escalation triggers, such as specific keywords or phrases, or the customer’s explicit request to speak with a live agent. 

If the customer has a complex inquiry, the chatbot should gather context (What is the problem? When did this problem begin?) and transfer this context to a live agent.

Automates parts of the sales process.

Chatbots assist with lead generation by initiating conversations with website visitors, inquiring about their needs (i.e.: product preferences and budget), and gathering contact information. 

The best ecommerce chatbots can help guide customers through order placement, upsell or cross-sell items to boost sales, and send post-purchase feedback requests. 

Programmatically onboard and educate new users.

Think of a chatbot as an always-on concierge for an ecommerce store. When customers first visit the ecommerce website, the chatbot can introduce product features and benefits and assist with sign-up. 

The bot can then guide users through the initial setup or account creation process by offering clickable prompts or a virtual guided tour of the interface. 

Offer interactive demos, tutorials, and FAQs to help new users orient themselves. Automated onboarding is especially useful for software companies that offer free trials or a freemium version, enabling them to scale cost-effectively.

Offer post-sale support.

Customers may have questions about order status, referrals, and returns after a purchase. Chatbots can retrieve this information from the organization’s CRM system and knowledge base. 

They can provide step-by-step written instructions or a video tutorial on how to return an item or change the shipping address — which can be much more effective than relaying these instructions by phone. 

Finally, chatbots can gather feedback on the purchase experience through surveys and polls.

Customizing an enterprise chatbot

A chatbot is not an out-of-the-box solution. They must be programmed to handle interactions specific to the business. Chatbots can also be customized to reflect the brand’s identity. 

Stick to easy-to-answer questions.

Don’t delegate too much responsibility to a chatbot. Chatbots rely on predefined responses and knowledge bases to answer queries. 

By sticking to easy-to-answer questions and establishing escalation triggers for everything else, organizations can ensure their chatbots provide information that is accurate, up-to-date, and doesn’t frustrate customers. 

Consider the customer journey.

Map out the customer journey to identify key touchpoints where the chatbot can add value. 

For example, most insurance providers offer relatively similar plans that are difficult to compare. The chatbot can be triggered to initiate a chat to help customers select the best one based on their circumstances. 

Other key touchpoints include initial engagement, product exploration, and post-purchase support. Set objectives for each touchpoint (i.e.: educate customers about self-service options) and design conversations that meet these objectives. 

Track chatbot performance and continually refine their operation.

Chatbots require regular training and maintenance. Integrating analytics tools with a chatbot enables businesses to measure metrics such as user engagement, goal completion rate, escalation rate, and conversion rate. 

In addition to monitoring performance metrics, companies can use machine learning algorithms to analyze the content, intent, and sentiment of customer service interactions using natural language processing. 

Apply company branding and communication styles.

Create a personality for the chatbot that aligns with the brand. Is the brand formal, friendly, professional, or playful? Adapt the bot’s conversational style to match. 

Use the same language, vocabulary, and tone of voice in the chatbot’s responses as in all other brand communications. You can also design the chatbot interface with the brand’s color palette, logo, and visual elements. 

Internal uses for chatbots in ecommerce businesses

Chatbots are not just a customer-facing tool. Ecommerce companies can use them internally to assist employees with finding information. 


Chatbots can guide applicants through the hiring process by answering questions about company culture, benefits, and career opportunities. They can also administer pre-employment assessments (i.e.: a personality or aptitude test) and schedule interviews by prompting applicants to select their preferred timeslot. 


Payroll inquiries tend to be rote, repetitive, and easily handled by chatbots. Take the burden off the finance team by programming a chatbot to handle employee inquiries related to paycheck status, tax deductions, leave balances, or expense reimbursements. 

Chatbots can also facilitate self-service options such as updating personal information or direct deposit preferences.

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The final word

Chatbots have a variety of use cases, from customer support and technical troubleshooting to automating the sales cycle. However, chatbots are not a plug-and-play solution. 

Enterprises must design a logical conversation flow, understand user intent, and provide escalation triggers that enable customers to opt out and contact a live agent instead. 

By monitoring analytics and following a continuous improvement process, businesses can optimize their messenger chatbots, adding value to the customer journey while meeting business needs. 

FAQs about ecommerce chatbots

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