Stop chasing perfect measurement — start making better decisions
Today’s media landscape is expanding and evolving across channels, platforms and formats. Supercharged by AI advancements, it demands ever-increasing levels of attention and agility for advertisers to manage, while simultaneously offering data and feedback that would make John Wanamaker salivate for finally resolving the oft-cited conundrum: “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.”
That’s why media measurement captivates the industry’s attention. It’s the primary value proposition of global consultancies and boutique analytics firms, the thesis of conference keynotes and the source of the long-fabled KPIs that unite both the CMO and CFO. It has made the bona fide leap to strategic necessity.
But measurement that’s oversimplified or overcomplicated can quickly become mere overhead for an organization. If measurement investment doesn’t inform where budget should be reallocated across channels, unlock creative freedom by virtue of understanding and automating fundamentals, or inspire change based on insight — you’re doing it wrong.
So how can you get measurement right?
1. Beware trendy measurement myths
Resist the siren’s call for a single measurement metric. Instead, envision the humble triangle, nature’s strongest geometric shape.
In measurement, attribution shows influence; marketing mix modeling (MMM) shows contribution; and incrementality testing shows causality. The three methods yield three distinct yet complementary KPIs, creating geometric strength in your holistic media strategy.
If you’re doing it right, you’re using all three to identify solutions, such as:
— Attribution facilitating in-flight optimization across campaigns, powered by real consumer responses to weekly tactical decisions.
— MMM enabling large budget decisions across media channels and the ability to simulate scenarios via tools like Circana’s Marketing Foresight.
— Incrementality (lift) testing providing the ability to experiment and optimize within a campaign or platform, and calibrating MMM and attribution in classic flywheel benefit.
In so doing, you will find that all three models — while delivering far from identical results given their respective use cases — harmonize to ensure the brand’s strategy sings. Where discord appears, lean into the friction. Friction in measurement is often where insight lives.
2. Chase long-term momentum, not hourly metrics
Dashboard refreshes on an hourly basis are closer to vanity than value. In reality, ad performance is subject to lag and decay. Checking your MMM daily with the intention of making high-frequency, wide-sweeping strategic changes exacerbates the risk of poor decision-making — like trying to steer the cruise ship of media investment’s impact with a joystick.
If you’re doing it right, you’re using insights, simulation tools and ultimately optimization capabilities while recognizing that you’re building a high-performing brand — not day-trading. You’re accounting for a 30-to-90 day halo effect and giving your slowest camper media channels and sales cycles time to catch up. Above all, you’re ensuring that, amid this patient approach, you have democratized access to salient KPIs for micro decision-making across your team, such as in-flight optimization signals that allocate campaign spend based on tactic performance and outcomes or campaign-level incrementality analyses that inform how to spend your next campaign’s budget more wisely.
3. Incrementality is an organizational maturity test
Incrementality is the causal anchor of media performance, but risks exposing difficult truths: seemingly high-performing channels may contribute vanishingly small amounts of new buyers; or may cannibalize and redistribute credit from other channels; or may only be considered incremental at unsustainably high frequency. In many marketing departments, investment inertia outweighs a desire for recurring, dispassionate assessment of incrementality, and thus growth is stifled.
If you’re doing it right, your organization invests in always-on experimentation agendas to ensure the feedback loop between insight and action is as short as possible. Circana’s in-platform integrations like “Lift on Demand” with The Trade Desk make this effort remarkably easy to implement on an ongoing basis and deliver biweekly reads. Methodological rigor, organizational alignment and willingness to interrogate long-standing norms illuminates both department blind spots and new sources for higher ROI.
The common denominator to all of this — the triangulation of models, the patient evaluation and calibration of results, the investment in always-on experimentation — is having the right data. As AI amplifies every signal, the value extension of good data compounds exponentially, and the cost of flawed data does the same. Verified, consistent data in the right environments, connected to the right systems, also facilitates consistent taxonomy, classifications and stable cross-measurement mapping to enable clean model calibration.
If you’re really doing it right, the combination of data quality and the measurement approaches above will holistically inform better decisions. And this — the fundamental ability to understand that media measurement is only as good as it helps you accurately assess and make decisions — cascades from plan to performance, bridges upstream product strategy to downstream results and is your best predictor of value for your next dollar spent.
This op-ed represents the views and opinions of the author and not of The Current, a division of The Trade Desk, or The Trade Desk. The appearance of the op-ed on The Current does not constitute an endorsement by The Current or The Trade Desk.