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FAQ Chatbot: Types, Use Cases & Best Practices in 2024

Updated on May 9
5 min read
Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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A consumer survey about chatbots and virtual assistants revealed that as long as the answers are correct, most have no qualms about speaking with chatbots. Some even prefer them to live agents.

FAQ bots are specific types of chatbots that help direct customers to designated pages or products, as well as provide answers about a business’s products and services, allowing customer reps to address complex customer needs. 

In this article we explore: 

  • What FAQ chatbots are
  • How they succeed
  • The different types of FAQ chatbots
  • How to choose an FAQ chatbot
  • And their use cases.

What are FAQ chatbots?

Businesses publish FAQ sections on their website to answer frequent user questions. However, users may have a hard time getting their questions answered because:

  • If they are navigating the questions by the “search functions,” not using the exact words the company has also used might leave them empty-handed. 
  • Their question might be complicated and involve a combination of questions, for which there might not be a specific answer for.
  • The FAQ section may not be mobile friendly.
  • They may just not like the traditional layout of using FAQ sections, and would prefer to receive an instant answer from a chatbot.


Salesforce is the CRM market leader and Salesforce Contact Genie enables multi-channel live chat supported by AI-driven assistants. Salesforce Contact Center enables workflow automation for many branches of the CRM and especially for the customer service operations by leveraging chatbot and conversational AI technologies for a personalized customer experience.

How to create an FAQ chatbot?

FAQ chatbots aim to resolve these problems by using NLP capabilities and providing answers in an intuitive chat interface. To build FAQ chatbots, chatbot vendors:

  • Crawl the company’s website for information,
  • Use the crawled data to build an initial bot,
  • Enable users to automatically make changes to the built-bot via a user interface.

How do FAQ chatbots succeed?

User conversations with chatbots are simple and direct. However, to get past the stigma of “lacking a personal touch”, research articles suggests that FAQ chatbot developers need to focus on:

  1. Making it human-friendly: Although chatbots should be designed to converse in a professional manner, they should also speak in a natural-sounding language.
  2. Giving it a personality: The type and style of dialog of a chatbot should reflect the attitude of the business. For example, a healthcare facility chatbot should not have the same style of conversation as a customer service chatbot in retail.
  3. Keeping the conversation simple and direct: A chatbot conversation should focus more on engaging the potential customer than on offering multiple solutions and services at the same time. The first aim of a chatbot is to get user contact info and general queries in order to provide relevant information and potentially generate a lead.
  4. Less typing, more clicking: The more a user needs to type, the more developed the intent recognition feature in the chatbot should be. However, interactive questions with multiple options enable:
    1. An easier way for the chatbot to provide the correct answer.
    2. Introducing business products or services the customer doesn’t know about.

To learn more about developing better chatbots, feel free to read our article about chatbot development best practices.

What are the use cases of FAQ chatbots?

As the name implies, FAQ chatbots aim to answer users’ common and frequently asked questions. Different businesses can integrate FAQ chatbots in various ways for both employees and customers, for example:

For customers

FAQ chatbots are excellent candidates for helping customers and improving their experience. Their use cases include:

Help pages

Sponsored: Zoho SalesIQ’s Answer Bot can respond to FAQs in related queries. Additionally, you can link FAQs to relevant articles to display alongside the response (Figure 1).

Figure 1. Zoho SalesIQ FAQ bot.

Capturing leads

FAQ chatbots are a great candidate to understand customer needs by identifying their queries and behavior. Throughout the conversation, the sales chatbot can ask users for their contact information and redirect this information to the marketing department for more personalized contact.

Cross selling

Although the goal of FAQ chatbots is to answer user’s questions, AI-enabled FAQ chatbots can further lead the conversation according to users’ previous inquiries, and provide them with info and promotions about products or services.

In general, integrating FAQ chatbots can facilitate business workflows and provide insights about users for product management, customer success and marketing departments. For example, the increase in frequency of a question can indicate that users are having a hard time accessing a new feature after a UX change.

For more chatbot use cases, feel free to read top 9 Customer Service Chatbot Use cases/ Applications.

For employees

FAQ chatbots can benefit employees by:

Facilitate employee self-service

Depending on the department, new employees can reach information about holidays, working hours, weekly, monthly, and annual meeting times. Additionally, FAQ chatbots can provide information about company software downloads and updates, as well as answer questions about common IT issues.

Reduce the load on customer service employee

By implementing FAQ chatbots on business websites, customers can find responses to most of their questions without needing to contact a live agent. By doing so you can augment your workforce since they do not need to focus on time consuming tasks.

What are the types of FAQ chatbots?

According to business needs, developers can choose from the 3 types of FAQ chatbots:

  • Rule-based
  • AI/NLP
  • Hybrids

In FAQ chatbot solutions, they have the following pros and cons:


Easy and fast training
Easy integration with available legacy systems
Dependable and do not go off the rails

Not flexible
Limited conversation flow
Limited personalization

Ability to learn from new data
Understand patterns and customer behavior
Support different language depending on the user

Longer training time
Require larger data volumes to avoid underfitting
Data bias

Leverage NLP technology
Ability to predict conversation flow
Easier to tweek database than rule-based chatbots

Have a restricted conversation compared to AI chatbots
Difficult to program the conversation flip from rule-based to AI

Pros and cons of FAQ chatbot types

To learn more about chatbot types, feel free to read our comprehensive article Conversational AI/ Chatbot Types.

How to choose an FAQ chatbot?

Choosing the type of chatbot to integrate to the business depends on 3 factors:

  • Business aim of integrating a chatbot: For example,
    • A retail company may integrate an FAQ chatbot as a marketing tool. Such a bot would need to be good at understanding different forms of customer questions and be able to match customers to products that are a good fit to their challenges. This scope can require understanding pricing, discounts as well as competitors’ solutions or substitutes
    • A contact center that primarily supports existing users, may aim to decrease the live agent call volume. In this case, especially if customer queries are focused on a few topics, even a rule-based bot can provide customers with responses from FAQ and help pages. This can significantly reduce agent call volume.
  • FAQ database: The volume and complexity of the database impact the level of intelligence the chatbot needs to have. Typically AI chatbots require a larger volume of training data for better performance whereas rule-based are better if the complexity and volume are low.
  • Integration channels:
    • Companies managing multiple channels may want to use the same technology to serve customers since it makes maintenance easier, provides a consistent user experience and enables users to move between channels without the system losing context of their request.
    • However, companies that will just be focusing on a single channel could have a wider range of companies to choose from when choosing their chatbot provider. However, as customers demand customer service in the channels that they use, we expect companies to prefer chatbots that serve clients across multiple channels.

For more on chatbots

If you are interested in learning about conversational AI and chatbot use cases, feel free to read our articles:

If you feel like you are ready to purchase an off-the-shelf chatbot solution, make sure to check out our data-driven lists of chatbot platform vendors and voice bot platform vendors.

And we can guide you in selecting a vendor:

Find the Right Vendors

This article was drafted by former AIMultiple industry analyst Alamira Jouman Hajjar.

Cem Dilmegani
Principal Analyst

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

Sources: Traffic Analytics, Ranking & Audience, Similarweb.
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Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
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Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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