USA Today Sports · Ad tech and data platforms

Grew ad revenue from the same audience.

Where an ad appears matters more than how many run. I moved from the commercial side into product and built around that.

+30%Programmatic revenue marginsDigital Partner Account Manager, then Product Manager, AdTech and Data Platforms
A Sportsbook Wire page from the USA Today Sports network on a laptop
A page from the USA Today Sports network (Sportsbook Wire). Screenshot.
01The user

Who we built for.

Who

A sports reader, and the advertisers buying that audience.

What they need

Read and watch without the page fighting them.

The moment

A story, game update, or video, often on mobile, with plenty of other sources a tap away.

Business objective

Higher margins and video revenue from the audience the network already has.

02Pain points

What got in their way.

  • 01Low ad toleranceReaders leave when ads are slow, disruptive, or overwhelming.
  • 02More units, less valueEvery extra unit lowers what the inventory is worth.
  • 03Easy to leaveThe same story is a tap away somewhere else.
More ads: the page fights the reader, and each unit is worth less.Illustrative, not real data.
03What we shipped

One system, four moves.

  1. Read

    Keep readers on the page.

    Stories · Video · Multi-sport network

  2. Place

    Place ads on evidence.

    A/B tests on content and ad placement

    +40%revenue lift from tests
  3. Demand

    Bring in better demand.

    Programmatic advertising engine

    +30%programmatic revenue margins
  4. Video

    Grow video as its own line.

    Video ad stack · Third-party partner integrations

    +150%video views
04The call

What we prioritized, and what it cost.

Where an ad appears matters more than how many run. Test placement before rollout, so changes ship on evidence.

We chose
  • Build the programmatic engine
  • Expand the video ad stack through partners
  • Test placement before rollout
We gave up
  • Speed: new units rolled out slower
  • Integration work for each partner
05What we tested

What we believed, and what moved.

Pick an assumption to see how we tested it.

Test before rollout. Run the test.

VARIANT A
VARIANT B+40% revenue

Layouts are a sketch. The +40% is the measured revenue lift from content and ad placement tests.

Everything that shipped.

  • Programmatic advertising engine
  • Video ad stack
  • Third-party partner integrations
  • Content and ad placement A/B tests
  • Dashboards in SQL and Tableau
06How we validated

Tools and methods.

  • A/B testingTestingContent and ad placement, tested before rollout
  • SQLDataQueries behind every dashboard
  • TableauDataDashboards linking audience behavior to revenue
  • DOMODataDashboards and reporting
  • Partner integrationsDeliveryThird-party video demand
  • JiraDeliveryBacklog, sprints, and release tracking
07Outcome

What moved.

North Star metricRevenue per pageMoved by the results below
  • +30%Programmatic revenue margins
  • +150%Video views
  • +40%Revenue lift from placement tests
  • $30MMonthly revenue from the video ad stack
  • −50%Churn, via analytics dashboards

Building an ad, video, or monetization product?

I lead product strategy and delivery with cross-functional teams across growth, retention, monetization, and customer experience.

Next case: Ticketmaster →

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