5 uses of AI for product managers

Wish you were a master in data analysis, making confident decisions with ease? AI for product managers is breaking down barriers, helping you work smarter and stay ahead.

By automating time-consuming tasks and uncovering actionable insights from vast datasets, AI empowers product managers to focus on what truly matters.

It helps you make faster, smarter decisions, driving better outcomes for your product and your users.

By analyzing how users interact with a product, AI can help product managers uncover trends, behaviors, and pain points.

Tools like Mixpanel or Amplitude use AI for:

• Page and feature tracking.

• Highlighting friction points in workflows.

• Generating actionable insights.

For example, AI can quickly identify where users drop off in a conversion funnel and suggest improvements.

Product managers use customer feedback to prioritize improvements. However, sorting through qualitative data can be overwhelming.

AI tools for product managers like Qualtrics and Medallia use natural language processing (NLP) to analyze open-text responses in surveys or app reviews.

By extracting recurring themes and sentiments:

• AI highlights which problems are most common or pressing.

• This clarity helps prioritize fixes or improvements effectively.

Planning roadmaps is one of the most critical tasks for product managers. The challenge lies in making future decisions based on past data, with limited insight into how user needs or market trends might shift.

AI can help product managers plan and prioritize the features that will have the most significant impact by:

• Analyzing historical data to predict the effect of features on retention, satisfaction, or revenue.

• Prioritizing features with the highest potential for success, based on data-driven insights.

For example, tools like Productboard analyze historical data to forecast how features will influence key metrics like retention, satisfaction, or revenue.

User stories and personas improve internal communication by creating a shared understanding of users and their needs, helping align teams around a product vision.

Instead of manually sifting through survey data, AI for product managers can:

• Analyze data from product usage, surveys, and market research.

• Generate user personas and stories based on the analysis.

Tools like Sprig or UserTesting use AI to process large datasets and create profiles that help teams understand customer needs.

Generative AI for product managers can improve in-app experiences by crafting copy, guides, and onboarding flows. For instance:

• ChatGPT or Jasper can generate user-friendly text for tooltips, modals, or FAQs.

• Tools like WalkMe use AI to create automated step-by-step guides for onboarding users.

Photo by bruce mars on Unsplash

AI for product managers can automate tasks and suggest recommendations, but it has limitations and shouldn’t make decisions for you. To use AI effectively:

• Question AI-driven insights — don’t accept them without verification.

• Trust your intuition and product expertise to make the best calls.

• Make sure your team reviews AI recommendations to ensure they align with your goals and user needs.

In what ways does the use of AI for product managers streamline workflows and improve efficiency? Choose all that apply:

A. By quickly synthesizing data from multiple sources to uncover actionable insights, so product managers can make faster, data-driven decisions.

B. By generating optimal in-app copy, eliminating the need for usability testing.

C. By processing large amounts of feedback, allowing product managers to avoid manually reading and analyzing any responses.

D. By improving predictions and recommendations for roadmap planning based on historical and market data, helping product managers prioritize features more effectively.

When starting to utilize AI for product managers, remember that you don’t have to do everything at once. Here’s how to get started: