AI tools for Product Managers [The Ultimate Guide]

If you are a product manager who is not leveraging AI tools, you are clearly missing out on significant opportunities to enhance their productivity and build better products.

Here are the notes from our masterclass on AI for Product Managers, where you will learn how AI can revolutionize various aspects of product management, from market research and user feedback analysis to stakeholder communication and analytics.

Table of Contents

1. The Current Product Management Workflow
2. Challenges in the Current Workflow
3. AI-Powered Tools for Product Managers
   • Chat GPT and Claude
   • Notebook LM
   • Atlassian Intelligence
   • Mixpanel Spark AI
   • Kraftful
   • Chatbase
   • MoEngage
   • Text-to-SQL Tools
4. The Future of Product Management with AI
5. Improving Communication with AI
6. Next Steps for Product Managers
7. Conclusion & Resources

2. The Current Product Management Workflow

The traditional product management workflow involves several key stages:

1. Idea Collection: Gathering input from users, business teams, stakeholders, partners, and market research.
2. Validation and Brainstorming: Evaluating ideas and aligning them with business goals and user needs.
3. Product Roadmap Creation: Developing a high-level strategic document outlining future plans.
4. Product Backlog: Breaking down the roadmap into smaller, actionable tasks.
5. Sprint Execution: Implementing features in short, iterative cycles.
6. Go-to-Market: Collaborating with sales and marketing for product launch.
7. User Feedback: Collecting and analyzing user responses post-launch.

This workflow can be categorized into three main phases: product discovery, product delivery, and product distribution.

3. Challenges in the Current Workflow

Despite best practices, product managers often face several challenges:

1. Time-consuming Research: Thorough research requires significant mind space and time, which PMs often lack.
2. Limited Brainstorming: Team members may not have the same level of user empathy or expertise.
3. Underutilized Best Practices: Known frameworks and methodologies often remain unused due to time constraints.
4. Communication Barriers: Articulating ideas with the right words and tone can be challenging.
5. Operational Overload: PMs often become bogged down in operational tasks rather than focusing on strategy.

4. AI-Powered Tools for Product Managers

ChatGPT and Claude

These conversational AI tools can assist with various tasks:

• Market research: Generating questions and insights for product development.
• Competitive analysis: Providing overviews of competitors and their value propositions.
• User persona creation: Developing detailed user profiles based on input data.
• Feature ideation: Brainstorming potential features and improvements.

Learn how to use chatGPT as a PM in our detailed guide.

Related tools: Perplexity, Llama.

Notebook LM

Google’s Notebook LM offers enhanced capabilities:

• Larger context window for processing more extensive data.
• Ability to upload and analyze multiple resources (documents, videos, websites).
• Generation of insights and summaries from uploaded content.
• Creation of audio content from text-based information.

Atlassian Intelligence

Integrated with tools like Jira and Confluence, Atlassian Intelligence streamlines project management:

• Natural language querying for finding relevant tickets and information.
• Automated story and task creation.
• Improved communication with stakeholders through AI-assisted writing.
• Automated follow-ups and ticket processing.

Related tools: Asana, Clickup, Zoho.

Mixpanel Spark AI

This AI-powered analytics tool enhances data analysis:

• Natural language queries for creating funnels and graphs.
• Automated insights generation from existing data.
• Suggestion of follow-up questions for deeper analysis.

Related tools: Amplitude, Mode, Text2SQL.

Kraftful

Kraftful helps collect and analyze customer insights:

• Aggregation of feedback from multiple sources (app stores, customer support, surveys).
• AI-powered analysis of customer sentiment and feature requests.
• Conversion of insights into actionable product backlog items.

Related tools: Zeda.io, Canny.io

Chatbase

This tool automates customer support:

• Creation of AI-powered chatbots based on existing data and FAQs.
• Integration with various platforms (website, Shopify, Facebook Messenger, WhatsApp).
• Reduction of manual customer support workload.

Related tools: Zendesk, Intercom.

MoEngage

MoEngage assists with customer communication and engagement:

• AI-driven segmentation of users for targeted messaging.
• Automated copywriting for various communication channels.
• Optimization of customer journeys based on user behavior.

Related tools: Clevertap, WebEngage.

Text-to-SQL Tools

These tools help product managers with data querying:

• Conversion of natural language queries into SQL code.
• Integration with existing database schemas for accurate results.
• Empowerment of non-technical PMs to perform data analysis.

5. The Future of Product Management with AI

As AI tools become more sophisticated, the role of product managers will evolve:

• Focus on Strategy: AI will handle more operational tasks, allowing PMs to concentrate on high-level strategy.
• Enhanced Creativity: AI can serve as a thinking partner, helping PMs generate more innovative solutions.
• Efficient Teamwork: Smaller, more efficient teams will leverage AI for faster experimentation and product iteration.

6. Improving Communication with AI

Effective communication is crucial for product managers. AI can help in two key areas:

1. Content Clarity: AI can help refine ideas and ensure that the core message is clear and concise.
2. Word Choice: AI tools can suggest better phrasing, adjust tone, and improve overall articulation of ideas.

By leveraging AI for communication, product managers can enhance their stakeholder management skills and drive better team collaboration.

7. Next Steps for Product Managers

To effectively integrate AI into your product management workflow:

1. Pause and Reflect: Before starting any task, consider if AI can assist.
2. Explore Tools: Familiarize yourself with various AI tools and their capabilities.
3. Fine-tune Prompts: Experiment with different prompts to get the best results from AI tools.
4. Create an AI Knowledge Base: Document useful prompts, tools, and workflows for future reference.
5. Regular Audits: Review and optimize your AI processes weekly or bi-weekly.
6. Focus on Discovery: Use the time saved by AI to enhance product discovery and user research.
7. Empower Your Team: Encourage developers, designers, and other team members to leverage AI tools in their work.

8. Conclusion

AI tools are revolutionizing product management, opportunities like never before for increased productivity and innovation.

By embracing these technologies and integrating them thoughtfully into their workflows, product managers can focus more on strategic thinking, user empathy, and creative problem-solving.

The key to success lies in continuous learning, experimentation, and a willingness to adapt to this AI-driven future of product management.

As the field evolves, staying updated with the latest AI advancements and continuously refining your AI skills will be crucial.

Remember, AI is a powerful tool, but it’s the product manager’s insight, creativity, and strategic thinking that will ultimately drive the creation of successful products. Embrace AI as your collaborative partner in building better products and delivering exceptional user experiences.