How to leverage AI to build a Satellite Strategy for your Product Phase 3 – Validate Pilot and Pricing

In my last two Newsletters I shared

Phase 1 – Set the Stage – https://www.linkedin.com/pulse/how-can-you-leverage-ai-build-satellite-strategy-your-jaising-cst–p1qce

and Phase 2 – Define Strategy – https://www.linkedin.com/pulse/how-can-you-leverage-ai-build-satellite-strategy-your-jaising-cst–a5mze/

Today I am going to continue with Phase 3 – Get Started which means running your pilot program. I will continue to use the example of Canva and explore building a satellite strategy for my company Concepts & Beyond Inc. using AI

Phase 3: Validate Pilot and Pricing Structure

Step 7: Validate Pilot Program

Each satellite feature begins as a limited test:

Example: Before fully launching Canva Websites, they released a beta version with limited templates to 10% of users, gathering feedback on usability. This identified that users needed more customization than initially provided but less than what Adobe XD offered—finding the sweet spot for their audience.

I have been teaching for nearly two decades and at Concepts & Beyond for the last 7 years. One of our product lines is out training and we teach Certified Scrum Master® (CSM®), Certified Scrum Product Owner® (CSPO®) and all the advanced courses that lead to a Scrum Alliance Certification. These courses are taught live both in person and online.

Recently I have been really impressed at several on demand and cohort based classes delivered on platforms like Maven Teachable and Kajabi. Maven has particularly stood out as I have signed up for courses on Maven.

The courses in Maven provide the best of both worlds: a combination of on-demand materials and time spend with the instructor. The materials are available to the learners for life. Maven also helps creators sell the course for a 10% fee.

This sparked ideas for creating micro courses in Maven teaching niche topics. One such topics comes from teaching thousands of Product Managers across the world. One thing I have realized from interviewing them is that although they are really good at the tactical work, doing product backlog management and running execution with technology teams, they are really looking to learn strategic product management and product leadership.

So a satellite could be having several micro courses on product management and leadership starting with the first pilot. Another Satellite could be writing a book, Another could be a paid newsletter and potentially a consulting program.

Visualizing what experiments can I run using the Opportunity Solution Tree by Teresa Torres and her book Continuous Discovery Habits

I used the below prompts to get help with my initial opportunity solution tree

“You are a product experimentation coach you are skilled at creating opportunity solution tree made famous by Teresa Torres in her book Continuous Discovery Habits. The outcome I seek is “Increase Product Strategic and Leadership Practioner Skills” What are opportunities for my company Concepts & Beyond Inc. What are solutions for each opportunity and what experiments can I run for each solution? Here are some examples Opportunity 1. “As a PM I dont know what strategic skills should I learn and how can I integrate AI to augment what I do” Possible solutions could be 1. Develop a micro course that teaches strategic skills augmented with AI, 2 Write a book that takes the PM how to develop as a product leader and gain AI skills and 3. Develop a paid newsletter that teaches PMs strategic skills in bite sized weekly newsletters

Can you identify 3 opportunities that https://www.conceptsandbeyond.com should prioritize to maximize revenue channels and the strategic knowledge become viral among the Product Manager community”

I captured a subset of ideas in the image below

Of course before I create a course or run any other experiment is important to validate these ideas. Before validating it with potential customers I wanted to see what AI thinks of me building a course.

So I used a prompt that Bernie Maloney my collaborator in building all my advanced courses shared with me. The prompt came from a webinar by David Bland David Bland is the author of the book Testing Business Ideas.

“You are a product experimentation coach. I will provide you with a product idea and a target user. Please do the following: Generate a list of risky assumptions that would have to be true for the product to succeed. The assumptions should be categorized into three groups: Desirable, Viable, and Feasible.

Categories & Questions to Consider Desirable (Do they want it?)

What evidence suggests that users have this problem and want a solution? Could the product’s value proposition be too weak or misaligned with user needs? Are users willing to switch from their current solution to this one? Could there be adoption barriers such as habits, preferences, or lack of urgency?

Viable (Should we do this?)

Can this product generate enough revenue to sustain itself? Will users be willing to pay (or generate indirect value through engagement)? Could customer acquisition costs be too high compared to lifetime value? Are there business model risks that could impact profitability?

Feasible (Can we build and scale it?)

Do we have access to the necessary technology, data, or infrastructure? Are there major technical risks or dependencies that could delay or prevent development? Will it be scalable if it gains traction? Are there legal, regulatory, or compliance risks?

Structure the assumptions in a table with the following columns: Category (Desirable, Viable, Feasible) Assumption (starting with “I believe…”)

Provide 5 to 8 assumptions per category in separate tables. Ask for feedback on the assumptions, prompting: “Is there anything missing, incorrect, or unclear in these assumptions?”

The Claude 3.7 Sonnet Reasoning model responded that it understood and I should share my product idea and target user, and it will create a tailored set of assumptions that could make or break your product’s success.

I prompted it with: My product idea is “Creating a course for product managers to create product strategy and validate the strategy using AI” the target user for this course are “senior Product managers and Product Leaders”

It responded with the below

Desirability Assumptions (Do they want it?)

1. I believe senior Product Managers struggle with creating comprehensive product strategies efficiently and would value AI assistance.
2. I believe Product Leaders are actively seeking ways to integrate AI into their workflow but lack structured guidance on how to do so effectively.
3. I believe the current methods of strategy validation are time-consuming and senior PMs would welcome AI-powered shortcuts without sacrificing quality.
4. I believe Product Leaders are willing to invest time in learning new AI-powered approaches rather than sticking with traditional strategy frameworks.
5. I believe senior PMs are frustrated with the subjective nature of strategy validation and desire more data-driven approaches.
6. I believe Product Leaders recognize a skills gap in AI-powered product strategy within their teams and want to address it.
7. I believe senior PMs trust AI enough to incorporate it into high-stakes strategy decisions after proper training.
8. I believe Product Leaders prefer learning these skills through a structured course rather than through self-directed exploration.

Viability Assumptions (Should we do this?)

1. I believe senior Product Managers and Leaders are willing to pay premium prices ($500-2000) for specialized AI strategy training.
2. I believe the customer acquisition cost for reaching senior Product Leaders will be sustainable compared to their lifetime value.
3. I believe this course can be differentiated enough from free AI resources and general product strategy courses to justify its price point.
4. I believe there is sufficient market size of senior PMs actively looking to enhance their strategy skills with AI capabilities.
5. I believe companies will sponsor or reimburse this training as part of professional development budgets even during economic uncertainty.
6. I believe the content can remain relevant despite rapid AI evolution without requiring complete course rebuilds every 6-12 months.
7. I believe offering tiered pricing or enterprise licensing will increase overall revenue without cannibalizing premium individual purchases.
8. I believe positive outcomes from early adopters can be effectively documented and leveraged for testimonials to drive further sales.

Feasibility Assumptions (Can we build and scale it?)

1. I believe we can create practical exercises that demonstrate real-world AI strategy validation that works consistently across different product contexts.
2. I believe we have sufficient expertise to teach both advanced product strategy and appropriate AI implementation methods.
3. I believe we can develop course materials that remain relevant despite rapid changes in AI capabilities and available tools.
4. I believe we can provide sufficient hands-on practice with AI tools without requiring excessive technical knowledge from participants.I believe we can effectively evaluate and measure participants’ improved strategy skills to demonstrate course effectiveness.
5. I believe we can secure partnerships with AI tool providers to offer integrated access as part of the course experience.
6. I believe we can scale the course delivery method beyond initial cohorts without diminishing the learning experience.
7. I believe we can effectively navigate concerns about data confidentiality when product managers use real strategy examples with AI tools.

Another follow up prompt from David Bland was

“Generate a 90-day product experimentation plan based on the riskiest assumptions. Plan Structure Summary of the Product Idea Table of Riskiest Assumptions (with category, assumption, importance, and evidence strength) Experiments, Categorized by Purpose: Discovery Experiments: To explore user needs, pain points, and behaviors. Validation Experiments: To test if users will adopt and engage with the product. For Each Experiment, Include: Assumption being tested Experiment Type (e.g., prototype test, A/B test, user interview, pre-sale, etc.) Metrics & Measurements (e.g., click-through rates, user engagement, retention rates) Success Criteria (What would validate or invalidate the assumption?)

Generate a timeline for running the experiments, starting with discovery experiments (light evidence) first, then validation experiments (stronger evidence).”

This generated a bunch of great ideas on how I could validate my idea, the metrics I would track and also a week by week plan of how and how much to validate.

I don’t think all the methods it shared was for me but I could pick two to three that really appealed to me such as below:

Experiment 1: Product Leader AI Perception Survey

Assumption being tested: I believe senior PMs trust AI enough to incorporate it into high-stakes strategy decisions after proper training.

Experiment Type: Quantitative survey with qualitative follow-up interviews

Metrics & Measurements:

• Survey response rate
• Percentage of respondents expressing trust/distrust in AI for strategic decisions
• Qualitative themes around concerns and confidence factors
• Current usage patterns of AI in strategy work

Success Criteria:

• At least 60% of senior PMs express willingness to use AI for strategy validation with proper training
• Clear patterns emerge around specific trust barriers that can be addressed in the course

Experiment 2: AI Strategy Workshop Pilots

Assumption being tested: I believe we can create practical exercises that demonstrate real-world AI strategy validation that works consistently across different product contexts.

Experiment Type: Mini-workshop sessions with diverse product teams

Metrics & Measurements:

• Effectiveness ratings of exercises across different product domains
• Consistency of outcomes when applying the same exercises to different strategies
• Qualitative feedback on exercise relevance and practicality
• Time required to complete exercises successfully

Success Criteria:

• Exercises yield useful insights across at least 3 different product categories
• 75% of participants rate exercises as “highly practical” for their specific context
• Common patterns of success/failure emerge that can inform course development

As we begin our pilot program, I plan to share the results in my future newsletter

Step 8: Validate Pricing Structure

Canva’s freemium model represents perhaps their most strategic satellite feature, creating both acquisition and revenue channels:

Free Tier Strategy:

• Offers enough value to be genuinely useful (over 250,000 templates, basic features across all products)
• Creates the largest top-of-funnel in the industry (over 100 million users)
• Serves as a viral marketing channel (free designs include Canva branding)
• Functions as a product education platform (users learn the interface before upgrading)

Competitive Advantage vs Adobe:

• Adobe offers limited free trials but no permanent free tier
• Adobe Creative Cloud costs 52.99/monthversusCanvaProat12.99
• Adobe requires separate applications for each function versus Canva’s all-in-one platform
• Adobe’s learning curve creates switching costs; Canva’s consistency across features removes them

Example: Data shows 15% of Canva’s free users eventually convert to paid plans—a conversion rate nearly 3x the industry average. The extended “try before you buy” period creates higher satisfaction and retention among paid users (92% annual retention versus Adobe’s estimated 85%).

I used the below prompt to get options for pricing plans and options that will help build revenue channels

“What plans and pricing can help me structure my course to increase acquisition channels and revenue channels”

The result was verbose but I did like a few ideas that I can explore. I am sharing below.

Tier 1: Free Community Access

Purpose: Acquisition channel that builds credibility and showcases premium value

What to Include:

• Mini-course (30 minutes): “AI Strategy Fundamentals”
• 3 downloadable AI prompt templates for strategy work
• Weekly newsletter with AI strategy tips
• Access to public community discussions
• Free strategy assessment tool (limited version)

Positioning:

• No credit card required, email signup only
• Optimize for SEO to attract organic traffic
• Make elements shareable (templates include attribution)
• Implement strategic “upgrade moments” when users hit limitations

Tier 2: Strategy Foundations ($249)

Target: Individual PMs looking to enhance skills

What to Include:

• 4 core modules on AI-powered strategy development
• 20+ AI prompt templates for common strategy tasks
• Monthly group Q&A sessions
• Basic strategy validation framework
• Digital completion certificate
• 30-day access to course materials

Positioning:

• Position as “essentials” package
• Perfect for individual skill development
• Low enough price point for self-purchase

Tier 3: Strategy Mastery ($699)

Target: Senior PMs serious about transformation

What to Include:

• Everything in Foundations tier
• 8 comprehensive modules (12+ hours of content)
• AI strategy validation simulator
• Personal strategy project with feedback
• Private community access
• 6 months of access to all materials
• Bi-weekly office hours for questions

Positioning:

• Position as complete professional transformation
• Ideal for company-sponsored professional development
• The go-to choice for most serious students

Tier 4: Strategy Leadership ($1,499)

Target: Product Leaders and Directors

What to Include:

• Everything in Mastery tier
• 2 private coaching sessions
• Advanced leadership modules
• Team implementation playbook
• AI readiness assessment tools
• Lifetime access to course materials
• Early access to new content and updates

Positioning:

• Premium experience for leaders
• Focus on implementation and transformation
• Emphasize ROI through strategic improvement

Conclusion

How can you get started with minimal investment to validate your idea and create a pricing or subscription plan? I am of course going to keep you updated as I try these ideas and share my results with you.