Chatbots for Customer Engagement: Benefits, Setup and Software Options
A useful chatbot gives customers a quicker route to an answer. A poorly configured chatbot adds another obstacle between a customer and your support team.
The difference starts with the job you give the chatbot. Answering delivery questions, explaining a service and collecting booking details are separate tasks. Each requires accurate information, clear limits and a sensible next step when automated help falls short.
For your business, the decision begins with the questions customers already ask. From there, choose suitable software, prepare the answers and test the experience before opening the conversation to everyone.
How Chatbots Support Customer Engagement
Customer engagement includes the conversations people have with your business before, during and after a purchase. A chatbot provides another way to ask questions, find information or request help.
Useful conversations have a clear purpose. A visitor comparing services needs help choosing. An existing customer with a missing delivery needs an update or someone responsible for resolving the problem. Treat these as different situations when designing your chatbot.
What Are Chatbots?
Chatbots are software applications which communicate through text or voice. Businesses use them on websites, messaging apps and customer service portals.
Some follow predefined rules and scripted answers. Others use AI to interpret questions and generate responses. A simple menu offering delivery, returns and contact options works differently from an AI assistant answering open-ended questions.
Choose the approach around the task. A short, predictable process often needs only a few clear options. More varied questions require broader language support, reliable knowledge sources and closer review.
Where Automated Support Fits
Start with requests your team handles repeatedly. Examples include opening hours, service areas, published policies and instructions for common tasks.
Keep a distinction between providing information and taking action. Explaining how to cancel an order requires access to your cancellation policy. Cancelling a particular order requires access to the order system, appropriate permissions and confirmation of the result.
Write down these requirements before comparing platforms. Otherwise, a chatbot might explain a process without completing the task your customer expected.
Benefits of Chatbots for Customers and Support Teams
The useful benefits depend on your setup and the questions customers bring. Faster replies matter when the answers are accurate and help someone move forward.
Answers Outside Working Hours
Automated answers give visitors access to published information when staff are unavailable. A customer checking delivery areas late at night should receive the same current policy available during office hours.
Set clear expectations for anything requiring staff involvement. Explain your support hours and provide a contact form or ticket option. Avoid messages suggesting a person is reviewing a request when nobody is available.
Separate response time from resolution time. An immediate greeting offers little value if the customer still has no answer or route to help.
More Relevant Customer Interactions
A relevant answer uses information appropriate to the question. For someone comparing two services, this might mean explaining the differences and asking about their requirements.
For an existing customer, relevant help might involve an order status or account record. Access to those details depends on the platform, your integrations and the customer’s identity checks.
Use personal information only where needed. Asking for an email address before answering a question about opening hours adds friction without improving the answer.
Less Repetition for Support Staff
Routine questions are sensible candidates for automation. If your team repeatedly explains the same return steps, a chatbot offers another way to deliver those instructions.
Review the remaining work too. Staff still need to maintain answers, inspect failed conversations and handle transfers. Assess the time saved alongside the time spent running the system.
Keep exceptions visible. A standard return instruction is different from a dispute about a damaged item or a request outside your published policy.
A Clearer View of Missing Information
Reviewing conversations helps identify gaps in your website and support content. Repeated questions about delivery charges, booking changes or service eligibility deserve attention.
Sometimes the best fix belongs on the page customers were already reading. Add missing delivery information beside the ordering process or explain booking rules before checkout.
Use these patterns to improve both the chatbot and the wider customer journey. Avoid collecting extra personal details solely to produce more detailed reports.
Implementing a Chatbot in Your Business
Begin with a limited set of tasks. A focused first version gives you a manageable way to check answer quality, staff workload and customer feedback.
Choose a Platform Around Your Requirements
List the tasks your chatbot must perform, then assess platforms against the same requirements.
- Knowledge sources: How do you add, update and remove information?
- Integrations: Does the platform connect to your support inbox, booking system or order records?
- Human support: How does a conversation reach the appropriate person?
- Channels: Which website, app or messaging channels need support?
- Languages: Which languages require testing and ongoing maintenance?
- Reporting: Are conversation history, unanswered questions and transfers available for review?
- Costs: What counts as billable usage and what happens after reaching a limit?
Use your own sample questions during demonstrations. Ask the provider to show a failed answer and a transfer to staff, alongside the successful examples.
Prepare Your Knowledge Sources
Review the information customers already receive. Correct conflicting policies, expired offers and unclear instructions before loading content into the chatbot.
Write answers around specific questions. A customer asking about a late delivery needs the next step, the details to provide and the right contact route.
Assign an owner to each source of information. Include chatbot content in your normal process for changing prices, opening hours and service terms.
Design Conversations Around the Next Step
Keep the opening message short. Explain the chatbot’s role and offer a few useful starting points where appropriate.
Ask one necessary question at a time. If someone wants to book a consultation, establish the service they need before requesting contact details.
Avoid long answers when a short explanation and a relevant link would serve the customer better. Use follow-up questions to resolve ambiguity, with a clear exit when the conversation stops progressing.
Connect Automated and Human Support
Decide which requests should reach staff immediately. Examples include unresolved complaints, payment disputes and questions outside the chatbot’s approved scope.
Check whether staff receive the conversation history and details already supplied. Customers should not need to repeat their full explanation after a transfer.
Test the process outside working hours too. The chatbot should explain whether the next step is an email reply, a support ticket or contact during office hours.
Test Before Launch
Build a test set from real support questions, with personal details removed. Include spelling mistakes, brief messages and follow-up questions.
Test an unknown answer, a changed policy and a direct request to speak to someone. Check whether the chatbot acknowledges missing information and provides a useful next step.
Run the same questions again after changing knowledge sources or settings. Keep a record of failed examples so future updates receive consistent checks.
Best Practices for Everyday Use
Running a chatbot requires ongoing decisions about content, customer access and data. Include those responsibilities in your support process from the start.
Keep Access to a Person Visible
Provide a clear option for human assistance. Do not require customers to complete an unrelated sequence of questions before requesting help.
Explain what happens next. A queue, a ticket and an immediate live transfer create different expectations.
Give staff a way to report poor automated answers. Use those reports to improve the source content or remove unsuitable tasks from automation.
Review Answers After Business Changes
Update the chatbot when your business changes a policy, product or process. Check whether the platform refreshes connected sources automatically or requires a manual update.
Pay particular attention to temporary information such as holiday hours and promotional terms. Assign a review date when adding this content.
Inspect unanswered questions regularly. Where several customers ask the same question, decide whether to add an answer, improve an existing page or provide a clearer contact route.
Respect Customer Privacy
Collect only the personal information needed for the task. A general service question rarely needs the same details as an account-specific request.
Under the GDPR, organisations must identify an appropriate lawful basis before processing personal data. Consent is one of six legal bases. The appropriate basis depends on the purpose and circumstances.
Explain how conversation data is used, limit access and set a retention period. Review the provider’s storage arrangements and deletion options before launch.
Avoid treating a security feature or consent checkbox as proof of overall compliance. Assess the full process, including the information collected and the people or systems receiving access.
Common Challenges and How to Handle Them
A chatbot needs a useful response when a conversation goes beyond the happy path. Plan for incomplete questions, missing information and requests requiring judgement.
Language Differences
Test every language you intend to support. Include local terms, product names and phrases customers use in real messages.
Check the meaning of policy answers as carefully as grammar. A fluent response still needs to match your delivery terms, eligibility rules or booking process.
Provide an alternative contact route when reliable support in a particular language is unavailable.
Misunderstood Questions
Customers often describe symptoms rather than name a process. Someone saying an order has disappeared might mean a missing confirmation email, a failed payment or a late parcel.
Use a short clarifying question to separate those possibilities. Avoid repeating the same answer after the customer has already rejected the suggestion.
Review these conversations to improve prompts, menu choices and knowledge sources. Do not assume the chatbot learns the correct answer automatically from every exchange.
Incorrect or Invented Answers
Generative AI sometimes produces plausible answers containing incorrect or invented details. This problem is often called hallucination.
For customer support, an invented delivery promise or refund exception creates an avoidable problem. Limit answers to approved information and test questions with no answer in your source material.
Configure a fallback rather than encouraging a guess. If a task repeatedly produces incorrect answers, pause automation for the task while you investigate.
Complex or Sensitive Requests
Send requests requiring judgement to an appropriate person. A customer describing financial difficulty or a serious complaint needs more than a sympathetic phrase.
Do not rely on automated mood detection as the only trigger for escalation. Include explicit requests for help, repeated failures and topic-based rules in your review.
Give staff the relevant context and make responsibility for the next step clear.
AI Chatbot Software and Related Tools
The following tools serve different purposes. Some provide customer-facing chat and support workflows. Others help staff write content, research questions or work with business records. Developer tools support building a custom system.
Choose according to the job you need completed. A general assistant used by staff requires a different evaluation from a chatbot handling conversations on your website.
ChatGPT
ChatGPT is a general AI assistant for tasks including research, analysis and content creation. For a support team, example uses include drafting help articles, rewriting explanations and preparing response templates for review.
Using ChatGPT internally and deploying automated support on your website are separate projects. For customer-facing use, assess the complete system for business knowledge, conversation management and access to staff. The original description tying ChatGPT to GPT-3 is outdated.
Google Gemini, Formerly Bard
Google renamed Bard to Gemini in February 2024. Gemini is a general AI assistant, with uses extending beyond poetry and creative writing.
For customer engagement work, consider internal tasks such as developing help content or exploring different explanations of a service. A separate assessment is needed for a customer-facing implementation with business-specific information and support workflows.
Jasper
Jasper focuses on marketing content and workflows. Its platform includes tools for working with brand information and producing content across marketing activities.
Consider Jasper when your main requirement is consistent marketing material, such as campaign content and product explanations. Assess a separate support platform if your priority is managing live customer conversations and resolving service requests.
Microsoft Copilot Chat, Formerly Bing Chat Enterprise
The business chat offering previously known as Bing Chat Enterprise now sits within Microsoft’s Copilot products. Microsoft’s current documentation uses the name Microsoft Copilot Chat.
This is a workplace assistant rather than a ready-made website support inbox. Features and protections depend on the account and organisational setup. Microsoft’s guidance distinguishes work or school accounts from personal accounts, so check which experience staff are using before introducing business information.
Chatsonic
Writesonic positions Chatsonic as an AI marketing agent. Its examples include researching headlines, writing product comparisons and producing marketing content.
For customer engagement, this places Chatsonic closer to preparing information and campaigns than running a support queue. If your goal is automated conversations with website visitors, check the exact product and deployment features rather than relying on the chatbot label.
OpenAI Playground
OpenAI Playground is part of the developer platform. OpenAI’s documentation describes tools for generating and improving prompts, functions and schemas.
This is relevant when developing a custom AI application. Treat prompt experiments as one part of the build. Your customer-facing system also needs the website interface, access controls, business integrations and support handoff process.
Perplexity AI
Perplexity provides an answer engine with source-linked responses and research tools. The original description as a chatbot framework was misleading.
For a customer support or marketing team, a practical use is researching a topic and following the linked sources before preparing an answer. Verify the source material, particularly for changing product details or policies.
YouChat and You.com
The original description of YouChat as software designed specifically for e-commerce order support was inaccurate. You.com’s current website focuses on search and inference services for AI, including search and research APIs.
Keep this entry on your list when assessing research tools or components for a custom AI application. For order assistance, separately establish how your proposed system accesses customer records and manages support conversations.
HuggingChat
HuggingChat is a chat application powered by open source AI models. Users have access to available models through a conversational interface.
Use the application to explore model responses and compare behaviour on sample tasks. Assess the wider requirements separately before choosing models or infrastructure for a production customer support system.
Tidio
Tidio combines customer communication tools with its Lyro AI agent. Lyro accepts website information and supplied question-and-answer material as knowledge sources.
Its setup includes response testing and handoff rules for unanswered questions, requests for a person and staff availability. During a trial, test the knowledge sources you intend to use and check the experience when no staff member is online.
ChatSpot and HubSpot Breeze Assistant
The former ChatSpot address now leads to HubSpot’s Breeze Assistant. Breeze Assistant works inside HubSpot, with uses including drafting content, summarising records and preparing for customer meetings.
Distinguish this staff assistant from HubSpot’s customer-facing support products. If your requirement is a website chatbot, assess the relevant customer agent and chat features alongside your existing HubSpot setup.
Drift and Salesloft Chat Agents
The former Drift conversational AI page now leads to Salesloft’s Chat Agents offering. The current product page focuses on engaging website visitors and connecting buyer signals to sales workflows.
Consider this category when the main goal is helping prospective customers and supporting sales follow-up. Test how conversations reach your sales team and whether the workflow fits your CRM and lead handling process.
Kommunicate
Kommunicate focuses on customer support automation with AI agents and human handoff. Its documentation describes assigning conversations to an automated agent and transferring requests when human help is needed.
A direct option to speak to a person is also documented. Test both automatic escalation and customer-requested transfers, including the context received by staff.
Freshchat
Freshchat provides customer messaging, live chat and chatbot tools within Freshworks. Freshworks also offers Freddy AI Agent for automated support.
Assess the distinction between Freshchat and the wider Freshdesk Omni offering when comparing requirements. Check which product and plan includes the ticketing, knowledge sources, channels and AI features your team needs.
Check Whether the Chatbot Is Helping
Agree on success measures before launch. A high message count or a fast first reply says little about whether customers solved their problems.
Review a sample of conversations alongside the platform’s reports. Use consistent definitions for the outcomes you measure.
- Answer accuracy: Does the response match your current information?
- Task completion: Did the customer receive the answer or complete the intended action?
- Repeat contact: Did the same problem return through email, phone or another channel?
- Human handoff: Did the request reach the right person with enough context?
- Customer feedback: Was the answer useful and the next step clear?
- Operating cost: How much time and money went into software, content maintenance and follow-up support?
Distinguish a confirmed resolution from a conversation ending without another message. Silence alone does not explain whether the answer helped.
Keep a record of recurring failures and assign an owner to each fix. Update the relevant information, repeat the failed test and check related questions before expanding the chatbot’s responsibilities.
