How Rule-Based Chatbots Compete Against AI in Business

Chatbots used to be seen as a novelty before rule-based bots entered the scene. Now they're gaining business' attention and helping with online support.

These chatbots, which work on a decision tree “if/then” logic, perform basic tasks and can hold a conversation with customers — but within limits. That’s why some businesses consider advanced AI options that understand context and intents to emulate their agents to a T.

Each has their own strengths, which I’ll cover in the next section, but a rule-based chatbot is sometimes a better fit for some businesses. Keep reading to learn why.

  1. Rule-based vs. contextual chatbots
  2. How to use rule-based chatbots in business
  3. How to get started with a rule-based chatbot
  4. Create a rule-based chatbot with Userlike

Rule-based vs. contextual chatbots

When my mom bought a Camaro, my siblings and I were confused. Why was our mom, a nervous driver who only needed five minutes to get to work, buying a fast sports car? It sat low to the ground, created major blind spots and was so long it was difficult to park.

But it looked cool.

The thing is, the Camaro just wasn’t a good fit. The allure of owning it soon wore off and its impracticality started to show. This is what happens when you go big instead of being realistic.

That’s why it’s important to look past the “cool” factor of chatbots, and instead focus on its specs and what’s under the hood.

Rule-based chatbots use a series of defined rules to answer questions it identifies. Conversations are mapped out like a flowchart, which allows for few topic deviations but quicker resolutions. They’re often used as FAQ or knowledge base chatbots.

Contextual chatbots, meanwhile, can have free-flowing conversations and often learn from them, which later improves the quality of their replies. They can also follow mapped conversation flows, but they are often looser and allow for topic deviation.

Elisa displaying button options
Lufthansa created “Elisa” using Cognigy to assist customers with flight cancellations, refunds and answering FAQs.

For a business, both options sound attractive. Rule-based solutions are quick to build, easy to maintain and capable of assisting customers. Contextual chatbots are great for recreating the feel of speaking to an agent and learning from and dissecting customer information into actionable insights.

Choosing a contextual chatbot option might be the Camaro of choices when it comes to your business. If you list the most common reasons why you may need a chatbot, such as to answer common questions, promote your products and help with lead generation, then rule-based chatbots may be the better choice.

If you just need a chatbot to take care of simple tasks, such as collecting the customer’s info before forwarding them to an agent, then it’s not worth using a contextual bot.

A chatbot is a tool first and foremost, so if your use cases are general, then spending time and money on an advanced chatbot could be a big unnecessary investment.

This kind of chatbot is more often used in energy, healthcare, automotive, insurance and banking. These industries often process large amounts of sensitive and/or complex data, and customers have high expectations for the type of service they receive from these types of businesses considering their serious nature.

Of course, a rule-based chatbot may still be ideal if your business is a pharmacy, car dealer or bank.

Chatbot Ebbie on ebase's website
Ebase, a European B2B Bank for Financial Services, uses a rule-based Userlike chatbot on its website to assist customers with FAQs.

It all depends on the extent of the service you wish to offer, plus your budget, team size and more.

How to use rule-based chatbots in business

Provide 24/7 assistance

Chatbots provide instant, real-time assistance 24/7. If your customers are active after business hours, chatbots can help by answering simple questions, creating tickets and forwarding the chat for agent follow-up.

Perform simple tasks

A rule-based chatbot is a great assistant for taking over all those boring and time-consuming (but important) tasks. Besides answering common questions, it can schedule calls, redirect users to relevant pages on your website and update contact information, just to name a few.

Answer frequently asked questions

Customers value speed, and the fast nature of the internet amplifies this expectation for instant answers.

To take the pressure off your agents, you can use a rule-based FAQ chatbot to answer your customers’ most common questions. It can also help you track popular search terms so you’re aware of what troubles customers are often facing. This may benefit your marketing efforts and help with growing and revising your FAQ pages and internal knowledge base.

Collect customer data

Rule-based chatbots may not learn from their conversations, but they can help you grow your customer knowledge base. They can ask for the site visitor’s name and contact information at the beginning of the chat to begin building a profile in your customer messaging software and/or CRM.

Product image of stored contacts in Userlike

If the chat is forwarded to an agent, or if the customer contacts your business again, a profile helps you quickly familiarize yourself with the lead.

Generate and filter leads

You only have a few seconds to keep a site visitor’s attention. You can use a proactive lead generation chatbot to capture customer interest and keep them from leaving your site.

A rule-based chatbot can use a series of qualifying questions to determine if the visitor is a good candidate for agent follow-up. If the site visitor is still on the fence, your chatbot can lead them through your sales funnel by linking relevant articles, product pages and lead magnets.

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How to get started with a rule-based chatbot

If you just need a chatbot to perform a few simple tasks, then a rule-based chatbot is a good fit for your business. There’s no need to put effort into a full-fledged digital assistant if you just need it to collect email addresses and give shipment updates.

Creating a rule-based chatbot can be broken down into these few steps:

  • Collect data. If you’ve determined your chatbot’s duties, gather all the data it needs to start mapping its conversation structure. This includes information from your knowledge base, past customer conversations and relevant business intelligence.
  • Create conversation flows. Diagram conversation paths for the topics your chatbot will cover. You can break this down into various elements, such as greetings and apologies, which I covered in detail in my post, “6 steps for creating a smooth chatbot conversation flow.”
  • Screenshot of an example flow in figma
    Try creating a conversation map in Figma to visualize your bot.
  • Convert flows into the bot’s language. Depending on the chatbot provider you choose, you may either need to convert your chatbot into html, use a drag and drop interface or create intents. Rule-based chatbot providers often offer no-code solutions, and most providers are generally user–friendly.
  • Upload or embed your chatbot into your preferred channels. Once you’ve built your chatbot, we recommend pairing it with customer messaging software, like Userlike. That way you can deploy it on your website and multiple messaging channels, such as WhatsApp. This helps you monitor your chatbot’s performance and allows you to keep your agents as a fallback.
  • Test, and test again. Before your customers meet your chatbot, test it among your team. If possible, ask a select number of “outsiders” like existing customers, friends or even family to chat with your bot and give their honest thoughts. Working on something so closely can cloud your perspective, so outside opinions will help you see anomalies you may have missed.
  • Deploy. Once you’re happy with your chatbot’s flows and look and have tested all integrations and functionalities, it’s go time. Consider using proactive chat to make your chatbot visible to site visitors, and promote it on your social channels.

Create a chatbot with Userlike

At Userlike, we make it easy to have a rule-based chatbot connected to your customer messaging software without having to build it elsewhere.

Our Logic Bot functions as an active member of your team: it can greet customers, answer questions using simple syntax and navigate visitors through your sales funnel.

KTR System's chatbot, Buddy
KTR Systems use Userlike’s Logic Bot to deploy “Buddy,” which automatically redirects users to the pages they’re looking for using button options.

But if a contextual chatbot sounds more your speed, we have you covered. We have an AI Automation Hub built into our software, which includes a self-learning AI chatbot, Smart FAQ and Contact Form Suggestions. It’s a blend of intelligent automation features that will make your website an attractive self-service station.

AI chatbot speaking to customers on WhatsApp, Messenger and in live chat
Use your AI chatbot on all your customers’ favorite channels.

The Smart FAQ is a responsive self-service portal that helps customers resolve their issues quickly. You can pin popular topics to the top and ensure that customers receive consistent answers with every search.

Responsive FAQ page predicts customer question and answers immediately

Contact Form Suggestions attempts to answer the customer’s question before they write to your team. This reduces tickets and redundant inquiries, freeing up your agents’ time.

Both features use auto-completion to answer customer questions as they’re typing them, saving time and effort.

And the best part - the AI Automation Hub doesn’t require a developer or IT experience to set it up.

You can have all the benefits of an AI chatbot and customer service tools that are easy to set up and deploy without having to turn to big expensive names like IBM.

Sign up for our free 14-day trial to get an impression of Userlike’s AI Automation Hub. If you like what you see, reach out to us in the chat on our website or reach out to our team at so we can discuss your chatbot needs.