By Laura Grover, SVP Head of Client Solutions at EDO & John Cripps, SVP Decision Science at EDO
TV marketers have access to more data than ever, but decision-making hasn’t gotten much easier. If anything, the added complexity of cross-channel marketing in a Convergent TV world has made it harder to choose the right media, target the right audience, and pair them with the right creative.
Today, TV advertisers receive terabytes of data from a multitude of partners, enabling them to examine their performance from countless angles: by publisher, creative, demo, daypart, and more. But the point isn’t to just describe and report your marketing performance — it’s to optimize it. And it’s hard to do that when you’re drowning in pivot tables and spreadsheets.
As Vertical AI technology makes it faster and easier to separate the signal from the noise in large, industry-specific data sets, TV marketing is on the precipice of a new era of measurement and optimization. In this new world, a measurement partner that delivers data is merely table stakes — the real differentiator is actionable recommendations and the business-driving decisions you make with them.
Stop focusing on what happened — and start figuring out what to do next
In the early days of streaming TV, granular reach and frequency data was a godsend for marketers. For the first time, they could see exactly who their TV ads reached, and how often they reached them.
However, this ad delivery data stops at the point the impression is served. In other words, most marketers have no insight into whether the ad actually moved the consumer to search for the brand online, visit its website, download its app, or take another action indicating their interest in the brand. It’s nice to know who saw your ad, but it’s far more important to know whether it worked.
As measurement providers seek to support clients in an increasingly complex TV ecosystem, their efforts can’t end at ad delivery. The new world demands insights geared toward decision-making and activation, rooted in the scalable, ad-driven outcomes that are most predictive of future sales.
TV marketers need recommendations, not spreadsheets
The new frontier in marketing TV optimization lies in a suite of decision science tools, Vertical AI-powered algorithms that analyze campaign performance data and instantly provide guidance on advertisers’ most pressing questions. The output of these modules is a clear, immediately actionable set of recommendations — not a pivot table in a spreadsheet.
Right now, savvy marketers are using these modules to find out what levers they can pull to improve Convergent TV performance — either while their campaigns are in flight, or as they plan their next one. The end result is that these modules shorten the distance between insight, optimization, decision-making, and in-market testing.
Here are a few examples of specific tools within EDO’s Decision Science Suite (DSS):
- Publisher Optimization: Modules analyze publisher ROI performance and recommend optimal allocations across partners.
- Optimal Frequency Capping: Modules balance marginal gains from additional frequency vs marginal cost, and set optimal caps by publisher.
- DMA or Zip-Based Geo-Targeting: Modules identify high-response locales and recommend where marketers should increase or decrease allocations.
- Creative Rotation Optimization: Modules recommend how to reallocate media weight across creatives in flight as they wear in and out over time.
Crucially, these tools are based not on surface-level metrics like reach and frequency, but on predictive outcomes like brand searches and website visits that are proven to precede sales lift. When marketers leverage the right methodology with actionable recommendations, results follow.
Why settle for a report card when you can have a decision engine?
Ultimately, the most advanced marketers will harness their decision analytic modules to build continuous feedback loops that power smarter decisions and more effective campaigns.
Rather than settling for a backwards-looking report card, these advertisers will turn their marketing measurement into a forward-looking optimization engine. And when these optimization engines are synced to an advertiser’s DSP, the result is a completely frictionless journey from insights to activation & testing to optimization.
The ideal workflow for an advertiser and its decision-science partner might look something like this:
- Analyze & Decide: The advertiser’s DSS tool generates a clear set of decisions to test (e.g., “Scale up Publisher A by 15%”, "Increase weight of Creative B by 30%," "Set frequency cap to 4 for Publisher A," "Target these 30 DMAs").
- Activate & Test: These decisions are available and exportable for immediate use. A media buyer can log into their DSP the very next morning and implement these changes as a new small scale test.
- Optimize & Scale: As the test proves successful, the "winning" decisions are scaled across the broader campaign. And scalability is tested as well.
In the fast-moving world of Convergent TV, the most effective brands will be the ones most capable of completing this three-step journey with speed and precision. In other words, it no longer matters who has the most data — it’s about who makes the best decisions, fastest.