Chatbots are most useful when they take on a defined step in a customer workflow: answering a routine support question, qualifying a sales inquiry, helping a shopper find a product, or retrieving an order update. They are not one uniform technology, and automation works best when the bot has reliable information, a clear limit, and a way to hand a conversation to a person when needed.
What chatbots can do across the customer journey
A chatbot is a conversational interface that can respond to questions or guide a user through tasks. Depending on how it is built and connected, it may rely on scripted choices, retrieve approved information, or use AI to interpret a request and generate a response. Not every chatbot uses generative AI, and a bot’s ability to answer a question depends on its available information and configured workflow.
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In customer-facing work, the same business may use chat for several different jobs: support after a purchase, sales assistance before a purchase, and product or order help during ecommerce. These functions overlap, but each requires different information and success criteria. IBM describes ecommerce chatbot uses that include FAQs, product recommendations, order status, lead qualification, and routing (IBM).
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Common chatbot workflows at a glance
| Workflow | Customer need | What the bot may do | Information or connection it depends on | Useful next step |
|---|---|---|---|---|
| Customer support | A quick answer or help with an existing issue | Answer routine questions, share order-status information, collect issue details, or route a case | Approved policy and product information; order details when order lookup is offered | Transfer the conversation or create a service case when the request needs human attention |
| Sales qualification | Help deciding whether a product or service fits | Ask qualifying questions, capture structured details, answer product questions, and route the inquiry | Current product information and a defined sales-routing process | Send qualified inquiries to the appropriate sales representative or follow-up workflow |
| Ecommerce discovery | Find a relevant product or understand its options | Respond to natural-language questions, make recommendations, and direct a shopper to a product or purchase path | Reliable catalog and product information | Link the shopper to a supported product page or checkout path |
| Messaging-based commerce | Ask a question or take a purchase-related action in a messaging conversation | Provide product or service information and, where supported, connect a conversation to a transaction or payment link | A channel and implementation that support the intended commerce action | Continue in the messaging channel or move the customer to another supported purchase path |
The capabilities in the table describe workflow patterns, not features guaranteed by every chatbot. Microsoft’s commerce chat overview distinguishes virtual-agent and live-agent capabilities and documents chat, voice, and SMS channels; the channels and functions available depend on the particular platform and deployment (Microsoft Learn).
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Customer support use cases
Answer routine questions from approved information
A support bot can handle questions with stable, documented answers—for example, basic shipping, product, or policy information. Give it a controlled source of current answers rather than assuming it can safely respond to any question. Define what it should do when it cannot find a reliable answer: ask a clarifying question, say it does not know, or route the customer to a person.
Keep the boundary clear. A policy question may be suitable for an automated answer; a disputed charge, unusual exception, or sensitive complaint may need an employee. The bot should not make a confident guess simply to keep the conversation automated.
Provide order updates and collect context
Order-status requests are a practical support task when a system can retrieve the relevant order information. IBM lists order-status assistance as an ecommerce chatbot use case (IBM). If the bot cannot access a customer’s order data, it should not imply that it has checked the order. It can instead direct the customer to the appropriate tracking or service path.
Before handing off a more complex issue, the chatbot can collect a concise description and relevant details. Salesforce’s Agentforce use-case index includes knowledge retrieval and customer-service case creation among agent actions (Salesforce). A useful handoff carries the conversation context forward so the customer does not have to repeat information already provided.
Route requests to the right service path
Routing is valuable even when the bot cannot resolve the issue itself. It can identify the broad request—such as an order question or product problem—and direct the customer to the relevant team or workflow. Decide which conditions require escalation, what details should be captured, and whether the handoff is to a live agent, a case, or another service channel.
How chatbots can help sales
Qualify an inquiry without turning the conversation into a form
A sales chatbot can ask a small number of relevant questions and capture structured details such as the customer’s need, intended use, or budget range. IBM identifies lead qualification and routing as chatbot use cases (IBM). The questions should help determine the right next step, not burden every visitor with a long intake sequence.
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When the inquiry meets the business’s criteria, the bot can route it to the appropriate representative or follow-up workflow. Make clear what information is being collected and avoid asking for details that are not needed for the next step.
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A chatbot can help a prospect compare relevant product information or surface a recommendation when the system has dependable, up-to-date details. Salesforce describes conversational commerce as including product discovery and personalized service (Salesforce). A recommendation is only as useful as the catalog data and rules behind it: outdated availability, incomplete specifications, or unclear eligibility can mislead a buyer.
Think of sales assistance as helping someone make progress—finding the right information, clarifying a need, or reaching a specialist. It is not evidence that a bot can replace consultative selling in every situation or close every sale.
Ecommerce chatbot use cases
Product discovery and recommendations
A shopper may describe a need in their own words rather than know the category or product name. A chatbot can ask a follow-up question, narrow the choices, and point to relevant products when it can access reliable catalog information. Salesforce and IBM both describe product discovery or recommendation among conversational-commerce and ecommerce chatbot uses (Salesforce; IBM).
Recommendations should have a usable destination: a product page, a supported purchase flow, or a human-assisted path. If a customer asks about a specification, the bot should use the product’s stated information rather than infer an answer from a vague description.
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A bot can answer catalog questions and help a shopper move from a question to a product page or another supported purchase path. In messaging channels, a commerce implementation may connect conversation to a transaction or payment link; that depends on the channel and implementation, not on the word “chatbot” alone. Salesforce describes messaging conversations that can support transactions and payment links, with the available actions dependent on the implementation (Salesforce).
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Post-purchase questions
After checkout, shoppers may want an order update or basic help. A bot can direct them to status information or the right service workflow if it has the relevant access. For requests involving exceptions, account changes, or a problem that needs judgment, make a human route available rather than forcing the customer through a loop of automated answers.
Choose the channel to match the workflow
Website chat is only one option. Salesforce describes conversational commerce across messaging apps, chatbots, and voice assistants; Microsoft’s commerce documentation covers chat, voice, and SMS in its platform context (Salesforce; Microsoft Learn). A business should select channels based on where its customers need help and what its actual implementation supports.
- Website chat: Useful when customers are already browsing a site or need support there. Confirm what information the bot can access during that interaction.
- Messaging apps: Can keep a service or purchase conversation in a messaging channel. Confirm channel availability and which actions—such as sending a link or supporting a transaction—are enabled for the implementation.
- Voice or SMS: May suit service workflows that use those channels, but each requires platform support and a suitable design for that medium.
Do not assume that a bot deployed on one channel can automatically be moved to another with the same functions, context, or regional availability. Check the capabilities of the platform and deployment you intend to use.
Design a chatbot workflow that can be trusted
- Choose one defined job. Name the customer task in plain terms, such as answering a particular set of policy questions, providing order updates, qualifying sales inquiries, or helping shoppers find products. Avoid starting with the vague goal of “automating support.”
- Map the successful path and the exceptions. Write down what the customer asks, what information the bot needs, what answer or action counts as completion, and what happens when information is missing or the request falls outside scope.
- Connect only the information required. Identify whether the workflow needs approved knowledge, catalog data, order information, or customer details. Keep answers aligned with current source information, and do not claim a specific integration unless it is confirmed for the chosen service.
- Set escalation rules before launch. Decide when the bot should offer a person or create a service case, which team receives the handoff, and what conversation context goes with it. Microsoft documents virtual-agent and live-agent capabilities in its commerce chat context (Microsoft Learn).
- Select the channel and supported action. Match the workflow to a channel customers can use, then confirm that the platform supports the required interaction there—such as a live-agent handoff, order lookup, or purchase link.
- Test realistic and difficult cases. Include ambiguous questions, unavailable information, incorrect assumptions, and requests that need a human. Check whether the bot admits uncertainty, routes correctly, and preserves context.
- Measure task quality, not just automation volume. Track whether the customer’s intended task was completed, whether the response was accurate, whether escalation worked, and whether the customer had to restart or repeat the issue. Containment or conversation count alone does not establish that a problem was resolved.
How to compare chatbot approaches
Before comparing vendors or implementations, compare the job each approach is meant to do. A simple FAQ workflow, an order lookup, a lead-qualification conversation, and a messaging-based transaction have different data, channel, and escalation needs. The table below compares those workflow choices; it does not imply that any particular product includes them.
| Approach | Best fit | Key dependency | Escalation consideration | Evidence in cited sources |
|---|---|---|---|---|
| FAQ and routine support | Repeat questions with stable answers | Approved, maintained product or policy information | Provide an exit when the answer is unavailable or the issue is exceptional | IBM describes FAQ and support functions (IBM) |
| Order assistance | Order-status questions and basic post-purchase help | Order information or a clear route to its source | Route exceptions and unresolved problems to service staff | IBM describes order-status use; Microsoft documents virtual-agent and live-agent capabilities (IBM; Microsoft Learn) |
| Sales qualification | Capturing an inquiry’s needs and routing suitable prospects | Relevant qualification questions and a defined follow-up process | Route qualified or complex inquiries to the appropriate sales representative | IBM describes lead qualification and routing (IBM) |
| Product discovery | Helping shoppers find or understand products | Reliable product and catalog information | Offer a person or another path when recommendations do not answer the question | Salesforce and IBM describe discovery or recommendations (Salesforce; IBM) |
| Messaging commerce | Purchase-related help within a messaging conversation | A supported channel and an implementation that enables the intended transaction action | Provide a clear alternative if the transaction cannot be completed in-channel | Salesforce describes messaging transactions and payment links; availability depends on implementation (Salesforce) |
What the published adoption figures do—and do not—show
Salesforce reports that 36% of shoppers made a purchase through a messaging app in 2023 and describes that as a 227% increase since 2021. These are Salesforce-published figures, not an independent universal estimate of messaging commerce (Salesforce).
On the same conversational-commerce page, Salesforce says 55% of shoppers had used AI-powered chatbots to resolve self-service issues and 61% said they prefer autonomy for issues that can be quickly resolved. The surfaced page does not state a year for those two figures, so they should not be read as current, year-specific measures (Salesforce).
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Salesforce’s Agentic Enterprise Index reports 119% growth in agents created and deployed in the first half of 2025, and 70% average monthly growth in daily customer-service conversations led by an agent during that period. Those are Salesforce platform activity figures for the stated period; they are not sector-wide adoption rates or proof that a chatbot will produce a particular result for another business (Salesforce).
Frequently Asked Questions
Frequently Asked Questions
Are chatbots always powered by generative AI?
No. A chatbot may use scripted choices, retrieve approved information, or use AI to interpret and generate responses. The term describes a conversational interface, not one specific underlying technology.
Can a chatbot complete a purchase inside a messaging app?
Sometimes. Salesforce describes messaging conversations that can connect to transactions and payment links, but the action depends on the channel and implementation. A chatbot does not guarantee in-app checkout.
Does automating more conversations prove that customer service improved?
No. A high number of automated or contained conversations does not show by itself that customers got accurate answers or resolved their issues. Measure task completion and quality as well as automation volume.
Can a chatbot replace customer support or sales staff?
The cited use cases support handling defined tasks and routing conversations; they do not establish that bots can replace staff across all support or sales situations. Keep a human path for requests that require judgment, exceptions, or consultative help.
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