Universal Music

The challenge

A specialist music streaming app launched during the pandemic, into a market that had changed by the time it needed to grow. Live events were back, the cost of living had risen, and entertainment apps had multiplied. Conversions were struggling, subscribers were leaving, and price was one of the reasons they gave.

Leadership, product and commercial teams shared a firm view: a premium product at a premium price. But nobody could say where users' price tolerance actually sat, or whether the current price fell inside it.

What I led

I reframed the question. Not "is the app too expensive?" but "where does an acceptable price begin and end?"

I designed and led a pricing study that combined two methods. Van Westendorp price sensitivity analysis mapped the range users would accept, from too cheap to trust to too expensive to consider, and found the optimal price point. Conjoint analysis tested combinations of features and price plans. It answered a question the business was already asking: would a basic tier plus a premium tier earn back the engineering investment?

I presented the findings to the cross-functional leadership team, structured to settle the debate. They showed exactly where the premium position held and where it didn't, so the team could decide from evidence rather than conviction.

The outcome

The evidence moved leadership from a fixed position to three decisions:

• A lower price point for LATAM and CEE, the most price-sensitive markets
• A point-of-churn discount for subscribers cancelling over price
• An A/B test on the subscription page across the US, UK and Eurozone

The same evidence stopped a costly decision. The projected return on tiered pricing didn't justify the engineering investment, so the business closed that option before committing resources.

Where this fits

This is the thinking behind the AI Opportunity Sprint: test what will pay back before you build it.