Upper-funnel campaigns such as video, display, connected TV and social prospecting have a reporting problem, not necessarily a performance problem. They are designed to build awareness and interest in people who aren’t ready to buy yet. Yet they’re usually judged with tools designed for the last step before a purchase. The result is predictable: they look expensive and ineffective, budgets move steadily toward the bottom of the funnel, and growth slows months later without an obvious cause.
Fixing this doesn’t mean trusting upper-funnel spend blindly. It means measuring it in a way that can actually see what it does.
Why click-based reporting undervalues awareness
Three biases work against upper-funnel channels in standard reporting.
The click bias. Most attribution and analytics setups record clicks and sessions. People rarely click a pre-roll video or a display banner, but many of them remember the brand. When they later search for it or type the URL directly, the credit goes to search or direct traffic. The channel that created the demand gets none.
The time-lag bias. Awareness takes time to turn into purchases. Someone who sees a campaign today might buy in three or six weeks. Short attribution windows and weekly performance reviews cut that link off, making upper-funnel spend look like cost without return.
The last-touch bias. Lower-funnel channels, especially retargeting and branded search, sit right before the purchase. They collect the conversion, even when the buyer was already decided. Their efficiency looks outstanding, partly because they’re harvesting demand that upper-funnel campaigns created.
Put together, these biases produce a consistent pattern: the further a channel sits from the purchase, the worse it looks in the report, regardless of its actual contribution.
The cost of getting it wrong
When reporting systematically favors the bottom of the funnel, budget follows. Every quarter, a little more money moves into search and retargeting because their numbers look better. For a while nothing seems to break. Then the pool of people who already know the brand starts to shrink, branded search volume flattens, retargeting audiences get smaller, and cost per acquisition rises across the board. By the time it shows up, the cause is months in the past and the connection is hard to prove.
How to measure what upper-funnel campaigns do
Measuring upper-funnel impact properly means capturing exposure, not just clicks, and connecting it to what customers do later. Several approaches work, and they’re strongest in combination.
Collect impression data where you can. For display and programmatic campaigns, impression-level data can be collected through the buying platforms and connected to later site visits and conversions, without relying on third-party cookies. This brings exposure into the customer journey instead of leaving it outside.
Model the exposure you can’t observe. Walled gardens like Meta, TikTok and YouTube don’t share user-level impression data, so direct collection isn’t possible. The alternative is to estimate which journeys were likely exposed, based on campaign reach, targeting and timing, and add those modeled touchpoints to the journey. This approach to measuring the impact of upper-funnel campaigns lets awareness spend be judged alongside clicks within the same attribution model, rather than through each platform’s own self-reported view-through numbers.
Watch the leading indicators. Branded search volume, direct traffic and new-visitor share often react to upper-funnel activity before sales do. Tracking them week by week against campaign flighting gives an early signal of whether awareness spend is working.
Test it. Geo holdouts are particularly well suited to upper-funnel channels. Run the campaign in some regions and not in comparable others, then compare sales, branded search and new customers over a long enough period to capture the delay. A single well-designed test often does more to secure future budget than months of dashboards.
Extend the window. Whatever method you use, give upper-funnel channels a lookback window that matches your real consideration cycle. Judging a video campaign on seven-day results is like judging a new store on its first morning.
Making the case internally
The goal isn’t to argue that upper-funnel spend always works. Some campaigns don’t, and good measurement will show that too. The goal is to judge every channel on the same evidence. When impressions and clicks sit in one model, and when experiments back up the attribution, budget debates become about which campaigns earn their place rather than which part of the funnel has the most flattering report.
That shift tends to change behavior quickly. Teams stop defending channels and start optimizing them, including the awareness campaigns that were previously first in line for cuts.
