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Jdate / ChristianMingle / 2010–2013

The economics behind a subscription business.

Role: Analytics lead reporting to the CFO, in-house, 2010–2013

Pricing, acquisition targets, and three-year lifetime value forecasts for an executive team.

StrategyAdobe Analytics · Lifetime value modeling · Forecasting · Pricing experiments
3 yearslifetime value forecast horizon

4 analysts · 40+ analytics properties

The business question

What can we afford to spend to acquire a customer?

01 / The challenge

Start with the decision.

At Spark Networks, decisions about pricing and acquisition depended on understanding what subscribers would be worth over time. Jdate, ChristianMingle, and more than 30 other sites operated across two platforms and three languages, creating a substantial measurement and analysis remit.

02 / What I built

Connect the pieces.

I led four analysts and owned more than 40 Adobe Analytics properties. Reporting to the CFO, I built three-year LTV models, tracked forecasts against actuals, and set monthly volume, acquisition-cost, and LTV targets by channel. I ran pricing tests and the standing analytics review with the CEO, GM, and CFO.

Subscriber behaviorLTV & acquisition economicsPricing & channel decisions

03 / What changed

A more useful answer.

Acquisition, subscription, and marketing profitability forecasts became part of the operating rhythm. Alongside that finance work, I built the television models that contributed to ChristianMingle’s national TV, radio, and billboard launch.

A lifetime value model earns its place by changing a decision. Connecting the forecast to acquisition targets, pricing tests, and actual performance turns an analytical exercise into a management tool.

Next case study / Live Nation

Two businesses. A shared picture of performance.

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Currently seeking a full-time analytics or measurement role.

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Based in Las Vegas; open to Southern California.