Beyond Support: Using Conversational AI to Drive Product Adoption and Feature Utilization in SaaS

Many SaaS companies already use conversational AI for customer support. It's a great way to provide fast, personalized help to customers around the clock. However, only some businesses use it to its full potential to get customers to adopt and use their product features.

The rise of generative artificial intelligence is changing the game. By 2026, over 80% of businesses will have used generative artificial intelligence APIs or models or have GenAI applications working in real-world settings, up from under 5% in 2023. 

By moving beyond traditional support and embracing AI as a tool for product adoption, SaaS companies can unlock new levels of customer success and drive long-term growth. In this article, we'll explore how conversational AI can be leveraged to guide users through your product, highlight key features, and provide contextual assistance that encourages deeper engagement.

How AI Chatbots Gamify the User Journey

AI chatbots can guide users through key features, making the onboarding process engaging and personalized. This approach is similar to regular, gamified onboarding processes, where users are motivated to complete tasks and achieve milestones.

Instead of static guides, conversational AI can provide:

• Welcome series: They can send welcome messages introducing users to key features and guiding them through a customized onboarding process. For instance, a project management tool might say, "Hey! Let's get started. Create your first board and invite team members." This conversational marketing approach ensures that users feel engaged and supported immediately.

• Interactive tours: A chatbot can provide interactive tours, allowing users to explore features and complete tasks hands-only. For example, a marketing automation platform might integrate a no-code chatbot saying, "Let's set up your first campaign together. Create a new email template."

• Contextual help: Stuck on a specific task? No need to dig through help docs. An AI chatbot within a social media management platform can answer real-time questions. For example, a user struggling to schedule a post can simply ask the chatbot, "How do I schedule a post for next week?" and receive instant instructions.

• Progress tracking and rewards: Chatbots can gamify the user journey by tracking progress and offering rewards for completing specific tasks or reaching milestones. For example, a project management tool could say, "Congratulations on completing your first project! You've unlocked a new set of templates. Would you like to explore them now?" Chatbots can keep users motivated and engaged by celebrating user achievements and unlocking new features.

• Task-oriented prompts: A chatbot provides task-oriented prompts, encouraging users to complete specific tasks and achieve milestones. For instance, a communication platform might prompt, "You're almost there! Complete your profile by adding a profile picture and bio."

How AI Analyzes User Behavior to Recommend Underutilized Features

In the SaaS industry, users often overlook valuable features that can improve their experience. AI-powered feature adoption solutions can help bridge this gap by analyzing user behavior and recommending underutilized features. This approach can improve:

•  Feature adoption rates;
•  User satisfaction;
•  Revenue growth.

AI can analyze user behavior in various ways to recommend underutilized features, including:

• Usage patterns: AI examines how users interact with the product, identifying areas where they may struggle or overlook valuable features. For example, a project management tool might notice that a user frequently creates new boards but does not use the "Power-Ups" feature. A chatbot can be implemented to recommend Power-Ups with a personalized prompt.

• Clickstream data: AI examines the sequence of clicks and user actions to understand their workflow. For instance, a marketing automation platform might analyze clickstream data to see that users often navigate to the "Contacts" page but do not use the "Sequence" feature. Based on this insight, the chatbot can recommend 'Sequences' through a tooltip.

• Feature adoption rates: By leveraging AI, platforms can compare feature adoption across various user segments. For instance, it might reveal that a specific group of users is not using the "Integrations" feature on a communication platform. This insight will allow AI-driven campaigns to promote integrations to the targeted user segment.

AI-Driven Feature Adoption Success Stories: Case Studies of Targeted Recommendations

Let's explore two compelling real-world examples of targeted AI-driven recommendations that boost feature adoption.

1. Plum

Plum, an employee benefits platform in India, transformed its claims process using Landbot's WhatsApp chatbot. Initially, the claims process was very slow, relying mostly on emails. Recognizing WhatsApp’s popularity in India, Plum shifted their claims process to this platform. By integrating Landbot, they created a user-friendly and automated claims filing system.

This shift led to impressive results: 

• 80% of their claims are processed via WhatsApp, improving user experience and operational efficiency. The intuitive chatbot solution informs users about their claim status.
• This resulted in an 85% opt-in rate for future communications. This strategic move streamlines the claims process and increases feature adoption by making it easier and faster for users to file and track their claims.

2. Bank of America

Bank of America's virtual assistant, Erica, is a great example of how AI can boost feature use.

Erica was introduced to provide personalized financial guidance and assist customers with various banking tasks through Bank of America's mobile app.

Erica utilizes predictive analytics and machine learning algorithms to analyze customer spending patterns, savings habits, and financial goals. Based on this analysis, Erica provides tailored recommendations to customers, such as optimizing savings, learning how to manage debt, or suggesting appropriate financial products.

This AI-driven approach has significantly enhanced user engagement and adoption of Bank of America's digital banking features. Customers appreciate Erica's proactive notifications and personalized financial insights, which ultimately encourage them to explore more features within the mobile banking app.

3. Asana

Asana, a leading work management platform, recently introduced AI Teammates, which is designed to increase productivity by advising on priorities and workflows. 

Built on Asana’s Work Graph, these AI teammates provide the ideal structure, visibility, and context for scaling AI within organizations. The Work Graph links work and workflows to higher-level company objectives, ensuring that AI recommendations are contextually relevant and actionable.

For example, a creative production team at an outdoor advertising company uses Asana’s AI teammates to streamline their request process. The AI helps by triaging incoming requests, gathering missing information, assigning tasks based on context, and improving reporting quality with consistent data. This targeted recommendation system ensures that users know and use all the available tools for a better workflow, leading to increased feature adoption.

Creating Compelling AI-Driven Feature Demos with Landbot: A Step-by-Step Guide

Whether you're showcasing new functionalities or demonstrating key features, leveraging AI can increase engagement and streamline user interactions.

In this section, we will walk you through the process of creating an AI-driven feature demo using Landbot.

1. Choose chatbot type: Determine the type of bot you will launch:

2. Select Launch Platform: Decide where to deploy your AI assistant on the web or WhatsApp.

3. Pick a Lead Generation Template: After choosing "Lead Gen," you will be presented with several pre-built settings examples to get started quickly. These examples are ideal if you don't have specific ideas or want to accelerate the setup process. Each one focuses on a different aspect of lead generation.

• Capture contact details: This option allows you to create a bot that asks leads for their name, email, phone number, and location. It's ideal for gathering essential contact information to follow up later.‍
• BANT: This example helps you qualify leads by asking questions about Budget, Authority, Need, and Timing. It's designed to identify high-quality leads based on these crucial criteria.‍
• Ask for a meeting based on qualification criteria: This option is helpful for scheduling meetings with leads who meet specific qualifications. The bot will ask questions to determine if the lead matches the criteria and then offer to set up a meeting.‍
• Pre-meeting discovery chat: This option prepares leads for a meeting by asking preliminary questions to gather necessary information. It helps ensure that the meeting is productive and that both parties are well-prepared.

4. Customize Your Lead Gen Bot

If you would rather not utilize a pre-built template and prefer to create your own customized bot, proceed with the following:

• Customize your welcome message: Set how your assistant will greet your customers. For example, "How can I help you?"‍
• Define your smart questions: Gather specific information you need from the lead. ‍
• Define your assistant's settings: Summarize your company's offering in one sentence, such as "Driving digital transformation with cutting-edge tech."‍
• Provide information to answer lead's questions: Offer details such as price options, FAQs, and unique features.‍
• Goodbye message: Set how your assistant will end the conversation. For example, "Thank you for your time! If you need any further assistance, don't hesitate to reach out. We're here to help!"‍
• Company's name: Enter the name of your company.‍
• Assistant’s name: Choose a name for your assistant.‍
• Personalize your conversation: Provide extra directions, rules, or prompts for assistance. 

Building AI Chatbots That Offer Real-Time Support

Let's explore some actionable ways to build chatbots that offer immediate, relevant assistance within the flow of your service.

• Focus on accessibility: Integrate chatbots directly into your product landing page for instant and contextual help. Don't force users to hunt for help documentation or leave their workflow. A chatbot that's always available provides a seamless and efficient support experience.
• Provide guided tutorials: Use your chatbot to offer step-by-step tutorials when users interact with complex features. For example, when a user starts creating a report, the chatbot can guide them through each step, ensuring they utilize all available tools.
• Read between the lines: Use sentiment analysis to understand customer satisfaction levels. This goes beyond simple feedback and reveals how users really feel about your features. Are they frustrated? Delighted? Sentiment analysis provides crucial context for product development decisions.‍
• Ask for feedback: After a user interacts with a feature, trigger the chatbot to gather specific feedback. For example, after a user saves a new project, the chatbot can pop up and ask, "How easy was it to save your project?" Timely prompts increase the likelihood of receiving valuable feedback.‍
• Provide personalized recommendations: Use AI to analyze user behavior and offer personalized tips or shortcuts. For instance, if a user frequently performs tasks in your software, the chatbot can suggest a more efficient workflow or introduce them to a feature that automates part of the process.‍
• Close the feedback loop: Integrate your chatbot with tools like Slack or Jira. This ensures product teams receive real-time user feedback and insights, allowing quicker responses and updates. Create a dedicated Slack channel for feature feedback or automatically generate Jira tickets from user conversations.

Conclusion

Conversational AI is a game-changer for SaaS companies. It’s not just about offering support anymore; it’s about ensuring users fully understand and use your product. AI-powered chatbots can guide users through onboarding, highlight key features, and provide real-time help, making the whole experience smoother and more enjoyable.

If you’re looking to take your user engagement to the next level, Landbot’s tools are a great place to start. They make it easy to build advanced AI-driven strategies that keep users informed and engaged. By leveraging these tools, you can ensure your SaaS platform is not just meeting user needs but exceeding them, driving long-term success for your business.