Every April, something fascinating happens in the desert. Brands spend millions activating around Coachella. Then they spend the next three months trying to figure out if any of it actually worked.
This isn’t just a festival problem; it’s a reflection of our industry’s broken approach to measuring media effectiveness. And while it’s true, it isn’t new.
The great reach inflation
Walk into any post-Coachella debrief and you’ll hear the same story: “We reached 47 million people across all touch points.” It sounds impressive until you realize that number is meaningless.
Here’s a dirty secret: Many traditional measurement systems inflate reach numbers. And advertisers indicate they would rather have independent measurement than walled-garden solutions from Big Tech publishers.
Your main stage activation, livestream pre-roll, influencer partnerships and social amplification are almost certainly hitting the same core audience repeatedly. But legacy measurement tools count each exposure on each channel (or each walled garden or silo) as a separate person because that’s how media has always been bought and sold.
The result? Brands think they’re casting wide nets when they’re fishing in the same small pond with increasingly expensive bait.
The attribution shell game
Are we accidentally equating correlation with causation? Brands believe that their dreamy Instagram pictures led to viral shares from fashionistas, which then resulted in an uptick in website traffic during Coachella weekend. The brand assumes festival activation drove that traffic, so it increases festival spend next year.
But what if that traffic came from a competitor’s poorly timed campaign that made people search for alternatives? Or maybe the traffic wasn’t related to Coachella at all? And by the way, did the increased traffic have any measurable impact on brand results?
Without proper cross-channel attribution, brands are essentially playing a very expensive guessing game.
The data Frankensteining problem
The average large brand uses somewhere between 12 and 20 different measurement vendors to track media efficiency and effectiveness. The brand could be looking at currency data that’s siloed for each media channel, while also separately considering TV data from one or more companies, digital data from another, social data from a third and out-of-home data from a fourth. Then the brand tries to stitch it all together with statistical modeling and call it “unified measurement.”
This approach doesn’t just miss the forest for the trees; it creates forests where half the trees are missing. Which puts marketers in the impossible position of making million-dollar spending decisions with incomplete data.
When measurement comes from different panels, different methodologies and different definitions of basic terms like “exposure” and “reach,” you’re not getting a complete picture. You’re getting a statistical patchwork that serves everyone except the person trying to make informed budget decisions.
The brand lift mythology
Perhaps the most outdated solution in modern measurement is the post-campaign exposure claimed in a brand lift effectiveness study. Brands spend months and millions on complex activations, then measure “success” by asking 500 people if they remember seeing an ad.
These studies are designed for a bygone media era, with one-to-many campaigns blasted across only five or so key media channels. We now have many more media channels, and many-to-many media environments have become more common in the era of creator-led content.
Today, real brand impact happens in real time. Advertisers need to understand each touch point, driven by accumulated exposure patterns that traditional brand lift studies can’t capture.
The cultural moment tax
Events like Coachella expose another industry inefficiency: the cultural moment tax. Brands pay 300%-500% premiums for festival-adjacent inventory, then measure success using the same blunt instruments they’d use for a Tuesday night cable buy.
It’s like buying a Ferrari and measuring its performance with a stopwatch that only tracks minutes, not seconds. You’re paying for precision and getting approximation.
Plus, the real cost of outdated measurement isn’t just an academic problem. Poor measurement creates a cascade of bad decisions that compound over time. Budgets flow to channels that appear effective but turn out not to be worthwhile once marketers dig into the data. And when smart CMOs pick holes in the methodologies, such discrepancies can reflect poorly on the entire industry.
In addition to channel strategies, creative measurement is also a major component of ad campaigns. But creative strategies are optimized for metrics that don’t correlate with business outcomes. Teams get rewarded for hitting numbers that don’t matter.
New advanced cross-platform capabilities can track ad exposure at the individual level across all platforms and measure incremental brand lift. Yet many marketers are using legacy systems because they’re following their peers or they aren’t provided with alternatives. Progress requires admitting that the current approach of siloed measurement isn’t suited to today’s fragmented landscape.
Beyond festival and creator advertising
Smart marketers are starting to use tentpole events like Coachella as measurement stress tests. If your attribution system can’t handle cross-platform amplification during a compressed cultural moment, it probably can’t handle the everyday complexity of modern media.
The same measurement challenges that become obvious during Coachella weekend exist year-round in less visible ways: fragmented audiences, cross-platform journeys, real-time content creation and the complete inability of legacy measurement systems to keep up.
The brands that figure this out first don’t just win at Coachella; they build systematic advantages that compound across every campaign they run.
The next cultural moment is already on the calendar. The only question is whether you’ll measure it like it’s 2015 or like it’s 2025.
“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
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