Freemium Product Portfolio Strategy
This project focused on optimizing the structure of a freemium cybersecurity product portfolio to maximize paid conversion and overall revenue. The challenge was to understand how tiering, pricing, and feature design interact within a realistic purchase journey, and how to design a portfolio that encourages both entry and upsell.
Context and brief
This project focused on optimizing the structure of a freemium cybersecurity product portfolio to maximize paid conversion and overall revenue.
The challenge was to understand how tiering, pricing, and feature design interact within a realistic purchase journey, and how to design a portfolio that encourages both entry and upsell.

Role and responsibilities
I led the design of the research and ensured outputs could directly inform portfolio strategy.
This included:
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Defining the experimental framework and success metrics
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Overseeing the design of the simulated purchase journey
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Translating behavioral data into commercial recommendations
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Working with stakeholders to connect findings to product strategy
Approach and methodology
We designed a large-scale behavioral pricing experiment with ~10,600 participants across the US and UK.
Participants moved through a simulated purchase flow, including:
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Marketing page exposure
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Product tier selection
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Add-ons and device coverage decisions
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Checkout
This allowed us to model real-world decision-making rather than relying on stated preference alone.
Key analysis & Key insights
The analysis focused on:
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The impact of tier structure on conversion rates
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Price sensitivity across different product configurations
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The role of add-ons and upsell mechanisms
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Behavioral patterns within the purchase journey
We modeled both conversion and revenue outcomes to understand trade-offs between volume and value.
The research showed:
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Offering 4–5 tiers increased paid conversion by improving perceived choice and fit
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Price was the dominant driver of product selection, outweighing detailed feature comparisons
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Consumers paid limited attention to specific feature lists during decision-making
Additional revenue dynamics included:
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Add-ons created meaningful opportunities to increase ARPU
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Device coverage options acted as effective upsell levers
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Premium tiers attracted a smaller but disproportionately valuable segment

Recommendations
Based on the findings, we recommended:
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Maintaining multiple tiers to support conversion across different customer segments
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Focusing differentiation primarily through pricing structure rather than feature complexity
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Using add-ons strategically to increase average revenue per user
Impact
The work provided a clear evidence base for restructuring the freemium portfolio, improving both conversion performance and revenue potential through more effective tiering and monetization design.