Many SaaS companies germany whatsapp number data
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.
How AI Chatbots Gamify the User Journey
AI chatbots can guide enhancing digital marketing strategies
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.”
How AI Analyzes User Behavior to Recommend Underutilized Features
In the SaaS industry, fax list
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.