The U.S.I.D.O. Framework for AI Product Managers
By: Curtis Savage Source: Medium — AI for Product People Type: article
Summary
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Notes
Part of a multi-article series. Each subsequent article dives deep into one step with companion Custom GPTs. The series includes: App Store Review Analyzer (Understand) and Product Manager in a Box (full lifecycle). This overview article is the entry point.
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Curtis Savage · March 2, 2024 · 9 min read · AI for PRODUCT PEOPLE (Medium)
TLDR: AI can make you a better Product Manager by helping you Understand, Strategize, Ideate, Define and Optimize your product (I call this the U.S.I.D.O. Framework for AI Product Managers).
Introduction
There are four questions every Product Manager should ask to build great AI Products:
- How can AI make me better in my role?
- What are the core use cases for my product?
- What are the best practices for working with teams to build AI features?
- How can AI accelerate value for my users and growth for my company?
In this blog series, we will exploring the first question: How can AI make me better in my role?
AI won’t be replacing Product Managers now or in the future. Being customer-centric, having keen business sense, translating user needs into compelling features, collaborating with teams and managing stakeholders remain dynamic, indispensable skills. AI, in this context, is not a replacement but a powerful ally that can amplify your efforts. Think of AI as that super-smart intern who underpromises and overdelivers.
But you still need to put in the work. AI is a tool you need to learn to help you augment, automate and speed up certain tasks. In this way it can help you build better digital experiences.
The U.S.I.D.O. Framework
To structure our approach, it’s helpful to think about how to leverage AI across 5 key steps of the product lifecycle which I call the U.S.I.D.O Framework for AI Product Managers.
AI can make you a better Product Manager by helping you Understand, Strategize, Ideate, Define and Optimize your product.
Step 1: UNDERSTAND
AI’s ability to recognize patterns and trends in data sets is a game-changer. It can sift through troves of both structured data (think product analytics) and unstructured data (think user reviews). It can spot trends and themes around customer pain points that may have taken you hours or days. And perhaps, even more importantly, it can spot patterns and generate insights that may have gone uncovered without it.
Rather than dedicating hours to combing through vast datasets, product managers can utilize AI to sift through and condense this information, allowing them to go deeper on specific themes that warrant closer inspection.
This can then power decision making and become a very powerful tool for things like product discovery, roadmap planning, and growth strategies.
Action Item #1: Use a Custom GPT like App Store Review Analyzer to analyze user reviews and understand what users love, hate, and wish for in your app.
Step 2: STRATEGIZE
The next area where AI can help Product People is at the strategy stage. This can be for a new or existing product or feature. It can help you understand the market and competition.
As an example, you can feed the LLM information about your company/product/users so it has context. With this context, it can help you identify your strengths, weaknesses, opportunities and threats (SWOT) and generate a detailed SWOT analysis to guide additional decisions across the product lifecycle like where to play, how to position yourself against competitors, and what opportunities to follow.
AI can help you perform market/competitor analysis and generate strategic artefacts and insights to then guide product development efforts in addition to things like positioning, differentiation, and go-to-market strategies.
The key takeaway is to use AI to help you generate strategic insights to then guide product development — saving you hours or even days of work. This gives you faster initial confidence that the ship is pointed in the right direction.
Action Item #2: Use a custom GPT like AI Product Manager in a Box to perform market/competitor research, generate a SWOT analysis, and output a product strategy based on its findings.
Step 3: IDEATE
This may be my favourite step because we transition from understanding and analyzing to creating.
If you’ve followed the Action Items above, then you’ve trained chatGPT on your users, competitors, and market. It understands your user’s biggest pain points by analyzing your App Store reviews and it understands your biggest opportunities by performing a SWOT analysis against your competitors in the market. With this understanding it’s well-primed for some good ol’ LLM magic.
Template: “chatGPT, based on {insert analysis}, what product features should I improve or build to {insert goal} with {insert user-type}”
Action Item #3: Using a custom GPT like AI Product Manager in a Box, ask it: “Based on {the top five pain points you identified from user reviews and the top five opportunities from SWOT analysis}, what product features should I improve or build to {drive retention} with {new users}.”
You can insert any goal/user-type and customize the prompt to focus on Adoption, Activation, Engagement, Retention, Revenue, etc.
Step 4: DEFINE
With a list of product features and enhancements that focus on your biggest pain points and opportunities you can now start prioritizing and defining a roadmap.
Roadmap: AI can help you prioritize which features to build based on their potential impact on product success. It can help you define your product roadmap by analyzing historical data and predicting the impact of specific features on strategic areas and KPIs like retention, user satisfaction and revenue.
Action Item #4: Prompt it to generate a roadmap using all of the output we generated from the previous action items as context: “Based on all of the information provided and generated from previous steps: What are the immediate features/enhancements I should focus on? Can you organize the list of features above into a one year roadmap divided into quarters of the year?”
Personas, User Stories, and Release Notes: With its ability to analyze large amounts of data from multiple data sources, there is a world where AI can generate user stories and personas based on things like product usage, user surveys and more.
Action Item #5: Prompt it to generate user stories based on all context: “Can you generate user stories in the Gherkin format for the next feature to be launched in roadmap?”
All of these steps require an AI-augmented approach. Meaning there needs to be a human in the loop (that’s you!). The outputs won’t be perfect. You will need to edit, refine, re-prompt, iterate and guide the LLM.
Step 5: OPTIMIZE
Now that you’ve used AI to understand, strategize, ideate, and define your product, it’s time to focus on optimizing. The optimization phase is about ensuring your product’s ongoing success by refining your go-to-market (GTM) strategy, identifying key metrics for success, and continuously running experiments to maximize impact.
1. Optimizing Your Go-to-Market Strategy: A successful product launch is only as strong as its go-to-market strategy. This is where you position your product to reach the right audience, using the right channels, with the right messaging. The GPT can be your secret weapon here, helping you analyze market conditions and generate a comprehensive, data-backed GTM plan.
2. Identifying Success Metrics and KPIs: With your GTM strategy in place, the next step is defining success. Which metrics will tell you whether your product is truly making an impact? Whether it’s user retention, activation, or revenue growth, selecting the right KPIs is essential for measuring performance. GPT can help you identify and prioritize KPIs that align with your specific goals.
3. A/B Testing and Experimentation: Optimization doesn’t end with tracking KPIs. To unlock your product’s full potential, you need to experiment. A/B testing allows you to test different versions of features, user flows, or messaging to understand what works best. GPT can generate A/B test ideas in seconds, allowing you to move quickly from hypothesis to action.
Summary
Product Managers aren’t going away. Our roles are more crucial than ever. A world devoid of Product Managers results in ‘capability-driven’ rather than ‘user-driven’ products that nobody wants.
However, the game has changed. AI is a powerful tool that all Product Managers must learn to leverage to be more effective in their roles. Or risk falling behind.
It’s helpful to think about leveraging AI across five key steps of the Product Lifecycle: Understanding, Strategizing, Ideating, Defining and Optimizing. Doing so can help you build better digital experiences while unlocking product value for both your users and your business.
Companion Tools
- App Store Review Analyzer — Custom GPT for analyzing App Store Reviews (Step 1: Understand)
- Product Manager in a Box — Custom GPT that walks you across the entire product lifecycle