FAQ chatbots might have been deemed a fad when they swiftly populated websites and messengers in the mid-2010s. But thanks to further advancements in AI, they were here to stay and evolve. Gartner predicts that about will use chatbots as the primary means of communication in customer service by 2027.
Let's explore why implementing FAQ chatbots now, in 2024, is a farsighted move. And which type suits your use cases and business goals more: simple or complex, scripted or AI-powered, web- or messenger-based, off-the-shelf or custom-made?
Table of Content
1. FAQ Chatbot Types
Actually, there are many , from the simplest ones to book appointments on Facebook Messenger to full-fledged virtual assistants integrated into devices (like Siri or Alexa). Here, we'll focus on FAQ chatbots, perhaps the most widespread ones for now. As the name suggests, they're designed to address frequently asked questions in a more convenient and fast way for customers and automate inquiry handling as much as possible.
However, they're not just mere substitutes for FAQ pages. Depending on the complexity level, FAQ bots can also take and track orders, offer personalized products or services, and help onboarding employees. Let's see which types of FAQ chatbots now dominate the market.
1.1 Rule-based Chatbots
Forerunners of the modern AI chatbots, they use a fairly simple machine-learning model called a decision tree. They have a flowchart structure predefining the bot's behavior and answers as the dialog progresses. Oftentimes such a chatbot has a menu with questions or topics to choose from. Basically, when a customer taps on the menu button, a relevant predetermined response will be triggered. That's why these bots are sometimes called scripted.
These are the simplest FAQ chatbots out there implementation-wise and the cheapest option on our list. While rule-based FAQ chatbots are formally AI-based, they're usually devoid of flexibility and human-like conversational capabilities. Therefore, they're suitable for a limited number of tasks, primarily basic and straightforward queries (literally FAQs).
1.2 Keyword-based Chatbots
These bots follow a different logic, detecting specific keywords in free-form user queries and picking answers accordingly without strictly predefined scripts. So, the overall interaction with such chatbots is more informal and conversational.
Although generally considered more flexible and versatile than rule-based FAQ chatbots, keyword-based ones still aren't well-adapted to more complex queries, don't get the context, and are prone to redundant responses to similar questions. For instance, when a person asks about shipping options and then shipping time, the chatbot may end up giving the same answer, which is quite bewildering and frustrating.
1.3 Conversational AI & Gen AI Chatbots
This category of FAQ chatbots (sometimes also called NLP chatbots) reflects a huge leap in machine learning (ML), deep learning (DL), natural language processing (NLP), and other AI subsets. In practice, these chatbots excel at contextual understanding, processing, and generating meaningful answers to customer questions. They get users' intents, mimic human conversation, and don't need strict algorithms to fulfill tasks.
The tasks are also getting more diverse, like producing personalized recommendations and communicating in many languages. The apex of this AI chatbot evolution is generative AI chatbots reaching new heights in the content generation part (read more in our article on ). The more sophisticated models power the chatbot, the more tasks it can cover and the more expensive it gets.
1.4 Hybrid Chatbots
This group of FAQ chatbots leverages both rule-based and conversational/generative AI logic to handle different user requests optimally. In practice, it can mention some common queries with predefined answers at the start of the convo and search for the most appropriate answers to more complex questions users ask themselves.
2. FAQ Chatbot Benefits and Use Cases
Surely, even the most advanced FAQ chatbots are far from being omnipotent and replacing human agents. The thing is in selecting an optimal solution to smartly augment your customer service and other teams.
2.1 Five FAQ Chatbot Advantages for Businesses
Each FAQ chatbot type has its benefits as well as drawbacks and limits. In general, deploying FAQ bots (particularly NLP chatbots) typically brings these positive changes:
- Process streamlining
Be it dealing with customer queries or employee onboarding, handing over a chunk of work to bots accelerates workflows and allows managers to focus on more tricky tasks. - Cost optimization
With a modern and reliable AI-based chatbot as an auxiliary customer support agent, there's less need to expand your customer service team. - Ceaseless customer support
Chatbots cover customer service operations after employees knock off, guaranteeing prospects and clients across all time zones find their answers right away or at least leave messages for human agents to resolve later. - Better customer experience
The possibility of getting help instantly and communicating with a brand via various convenient channels (chatbots on websites or messaging apps) boosts customer satisfaction. - More leads and sales
Chatbots are a great source of visitors' contact and case info. Even if the bot itself turns out to be of little help, managers can later seize the opportunity to reach out to prospects again. Plus, smarter FAQ chatbots aim to suggest relevant products and services, among other features. - Multi-language service
Advances FAQ chatbots support many languages, a must-have for international companies. Bots can tackle more diverse customer queries without hiring translators or native-speaking customer support team members.
2.2 FAQ Bots Use Cases for Your Customers
A modern FAQ chatbot will definitely optimize company workflows. There are two major clusters of FAQ chatbot business applications: for your prospective/existing clientele and the staff members. Let's see what use cases it can cover when it comes to customer interactions.
Product/service info
A FAQ chatbot can introduce the brand's key offerings to visitors, helping them navigate the site/app and find suitable solutions.
Order updates
A FAQ bot easily resolves typical customer inquiries about order status, shipping progress, and delivery date.
Billing queries
Chatbots can handle various payment-related issues, including guiding less tech-savvy users on how to make transactions.
Ordering/booking
For many businesses, from restaurants and fast food chains to medical facilities and spas, chatbots are a must-have for taking orders and making appointment reservations.
Promotion
Chatbots can proactively showcase hot deals and personalized offers, encourage people to subscribe to a newsletter or join a loyalty program as well as take part in webinars, prize draws, or other events.
Lead generation
Chatbots collect visitor's emails, which, alongside the dialog's content, can be further leveraged by sales or customer service teams.
Personalized recommendations
Chatbots suggest relevant products or services based on the history of interactions with a particular customer/prospect and their browsing insights.
Loyalty program assistance
Leads and customers can get exhaustive info on loyalty programs and manage their membership, e.g., tracking loyalty points and starting/canceling subscriptions.
Issue tackling
Chatbots are also a good self-service solution in case of problems occurring as customers proceed towards closing the deal.
2.3 FAQ Bots Use Cases for Your Employees
Since at the core of FAQ chatbots is their ability to quickly answer common user questions, bots are perfectly applicable to many internal processes.
Employee onboarding
A FAQ chatbot can get newcomers acquainted with the company policies, benefit system, business processes, corporate culture, and so on.
Staff training
Chatbots can serve as self-service educational tools for employees, from simple knowledge bases to full-fledged training and testing systems.
Resource navigation
Each organization has a wealth of internal documentation, and chatbots can help users find the needed resources or concrete information.
3. Choosing the Right FAQ Chatbot for Your Business
For some orgs, it's just enough to deploy rule-based chatbots, pulling accurate responses to reach higher employee/customer satisfaction, while others need to invest in more powerful AI chatbots based on ML and NLP or more advanced AI technologies.
In this chapter, we'll consider criteria you should bear in mind and specific features to seek when selecting a FAQ chatbot suitinig your company best.
3.1 What Are Your Objectives?
When opting for or building an FAQ chatbot, you don't want to overshoot the budget and, at the same time, find a solution meeting all your staff's and customers' needs. To this end, start by gathering information across departments, from customer service and HR to marketing and sales.
Interviewing end users will help list concrete requirements for a future FAQ chatbot and assess optimization possibilities. After mapping business goals and available funds onto these insights, you'll know exactly what tool to search for.
3.2 What Industry Do You Represent?
The sector you operate in is another crucial factor influencing your choice of a FAQ chatbot. It should match industry-specific requirements and take into account customer preferences as well as customer engagement peculiarities and what a typical customer query looks like.
Many chatbot providers have solutions designed for particular industries like eCommerce, SaaS, or healthcare. Plus, more modern chatbots are trained on data relevant to particular market segments and use cases so as to recognize user intent, give accurate answers, and ensure a positive customer service experience even straight out of the box.
3.3 What Features Are Indispensable?
At this point, you can move on to researching what chatbot platforms and custom chatbot development agencies have to offer. You might watch dozens of demos and complete several trials before finding the right chatbot provider. Here are a few must-have and nice-to-have features we'd single out.
- Messenger integrations
A 2018 survey by Meta across four markets (the UK, US, Brazil, and India) revealed that find messaging the easiest and most convenient way to contact a business. Hence, if your organization communicates (or wants to down the road) with people on messaging platforms and social media platforms (WhatsApp, Facebook Messenger, Instagram, etc.) make sure your chatbot for FAQ can be deployed there. - Conversational AI/Gen AI capabilities
Determine whether you really need natural language processing (NLP), natural language understanding (NLU), and natural language generation (NLG) for your use cases. Most of the time, the answer will be "Definitely" since cutting-edge ML/DL models can resolve more tasks more efficiently, do so in a human-like fashion, and be context-aware during user interactions. However, a bot based on predefined rules is still helpful if it's, e.g., a replacement for a FAQ page. - Escalating the chat to a human agent
The live chat feature is crucial for any customer-facing chatbot, even the most potent AI-powered virtual assistant. As chatbots may not understand user inputs or hallucinate, a timely human intervention helps surmount chatbots' limitations and resolve cases without hurting customer experience. - Multiple languages
Generative AI chatbots have a minimal language barrier, supporting over 100 languages and popular dialects. With simpler conversational AI/rule-based/keyword-based chatbots, you need to check whether the model supports or can be customized to serve in the needed languages. - Scalability
Experience high seasons or peak times with a teeming site/app/socials? Or the company ushers in a period of growth? Then, pay attention to the scalability factor: find out how many interactions the bot can handle simultaneously and how the number of started conversations may affect both the website and the chatbot's performance.
3.4 How Much Customization Is Enough?
If you go with an off-the-shelf option, you still have room to tinker with the bot's user interface design, training data, feature set, and tone of voice. Customizability may vary from vendor to vendor. Basically, the more you can gear the chatbot to your customers, tasks, and branding, the better.
Nevertheless, many companies don't really need extensive customization options since their use cases are pretty straightforward, or there aren't experts on board, or they simply don't see the need to spend much time and money on customization efforts. After all, you can start with a basic version, try and test it in the field, analyze employee and user feedback, and then decide on further enhancements.
3.5 What About Chatbot Maintenance?
Being inherently complex and data-hungry, fancier artificial intelligence chatbots are quite needy, following the "collect data, train, fine-tune, repeat" pattern. That's why tweaking such a bot will definitely be more costly and labor-intensive than a traditional FAQ chatbot. Here, you need to check how these processes are organized and what's guaranteed in the case of SaaS platforms and custom-made tools.
3.6 Why Integrations Matter?
Third-party integrations with communication channels and internal systems make the chatbot platform an integral part of day-to-day business operations. The number of possible integrations is crucial to ensure synchronizing data across the org, omnichannel customer service, and seamless workflows.
Therefore, seek products promising to integrate the bot with your existing systems: messengers, other communication channels, project management tools, CMS and CRM systems, and so forth.
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4. How to Build a FAQ Chatbot
Now that we've explored types of FAQ chatbots, understood what you want a bot to do, and listed obligatory criteria, let's discuss ways to implement the chatbot. Most businesses follow one of two paths: selecting a ready-made chatbot or developing a сustom solution. Below, we'll describe a general step-by-step creation and deployment process, specifying nuances for different Q&A chatbot types.
4.1 Choose Between Per-built & Custom-made
Regarding simpler rule-based chatbots, the choice is pretty straightforward: find a reliable vendor focusing on such ready-to-use tools. As a rule, they're user-friendly, easily customizable, and inegrateable, not requiring technical knowledge to set them up. Simply put, they're templates you need to populate with actual questions and corresponding answers.
If you need an AI-based chatbot to answer FAQs and process a wider range of customer interactions, you have more room for maneuver: there are many vendors touting their pre-built options, as well as agencies developing custom conversational AI/gen AI chatbots. Visit our page for more.
4.2 Prepare FAQs & a Knowledge Base
Creating effective FAQ automation chatbots is impossible without carefully gathering, analyzing, and structuring questions, complaints, and feedback customers leave all over your touchpoints. Let each team glean the info from their channels: socials, company inbox, CRM, and third-party sites (catalogs, online store review sections, and so on).
Besides, compile or update your knowledge base to make sure your future AI chatbot to answer FAQs (and do other tasks) has quality data to form and send relevant answers.
4.3 Design Conversations
Different chatbots demand different approaches to ensure response accuracy. With rule-based bots, you have to preprogram the conversational flow to the maximum by adding the possible questions and linking proper answers.
With conversational AI chatbots, you need to define popular user intents with so-called training phrases embodying such intents so that the model recognizes them. Plus, you may add exemplary answers to help the bot deliver better outputs.
Generative AI-based chatbots don't need these kinds of manual inputs as they're pre-trained on massive amounts of data. However, to tailor the chatbot more to the specifics of your sector and company, developers fine-tune the base AI model on additional datasets.
4.4 Test, Deploy, Analyze, & Refine
Run multiple test sessions before the chatbot goes live and serves real customers. During these simulated interactions, you'll see where more tweaks are required. Then, finish and check integration with the business environment (in the case of custom development, these tasks are on the dev team).
After deploying FAQ chatbots, we recommend closely monitoring their performance. Among key metrics to keep tabs on are classic ones like engagement, conversion, and user satisfaction rates, plus more specific like query resolution speed and error rate. And don't forget about timely updates and fine-tuning.
5. Examples of FAQ Chatbots
What do SaaS companies, eCommerce brands, universities, financial institutions, medical centers, and barbershops have in common? Right, all of them make use of FAQ chatbots. We've picked a few fine FAQ chatbot examples from several industries operating on different channels to demonstrate how helpful and versatile these chatbots can be.
5.1 HubBot by Hubspot
Offering AI-powered chatbots among its software solutions, HubSpot uses one on its website. It features buttons with quick topic selection, an option to skip chatbot communication and contact the sales team, and a field to ask free-form questions. It fully comprehends the inputs and gives relevant, informative, conversational, and consistent responses, suggesting escalating the dialogue to a live agent if something goes beyond its capabilities. Plus, it operates in multiple languages.
5.2 Uber Bot on WhatsApp
In a couple of Indian cities, people can order an Uber right from their WhatsApp. An Uber bot in this popular messenger fully replaces the mobile app, simplifying ride booking and saving space on clients' phones. The bot supports English and Hindi, giving detailed instructions on requesting a ride and showing available deals.
5.3 Princeton University on Socials
The university partly automates communication with prospective students through FAQ chatbots on Instagram and Facebook. In the university's DMs, we see some of the most sought-after questions or topics. Bots instantly share links to relevant information, reducing the workload on the admissions office.