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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

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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.

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Role and responsibilities

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I led the design of the research and ensured outputs could directly inform portfolio strategy.

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This included:
 

  • Defining the experimental framework and success metrics

  • Overseeing the design of the simulated purchase journey

  • Translating behavioral data into commercial recommendations

  • Working with stakeholders to connect findings to product strategy

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Approach and methodology

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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:
 

  • Marketing page exposure

  • Product tier selection

  • Add-ons and device coverage decisions

  • Checkout
     

This allowed us to model real-world decision-making rather than relying on stated preference alone.

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Key analysis & Key insights

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The analysis focused on:
 

  • The impact of tier structure on conversion rates

  • Price sensitivity across different product configurations

  • The role of add-ons and upsell mechanisms

  • Behavioral patterns within the purchase journey
     

We modeled both conversion and revenue outcomes to understand trade-offs between volume and value.

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The research showed:

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  • Offering 4–5 tiers increased paid conversion by improving perceived choice and fit

  • Price was the dominant driver of product selection, outweighing detailed feature comparisons

  • 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

  • Device coverage options acted as effective upsell levers

  • Premium tiers attracted a smaller but disproportionately valuable segment

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Recommendations

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Based on the findings, we recommended:
 

  • Maintaining multiple tiers to support conversion across different customer segments

  • Focusing differentiation primarily through pricing structure rather than feature complexity

  • Using add-ons strategically to increase average revenue per user

 

Impact

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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.

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