Why Top-of-Funnel Visibility Is Undervalued in Startup Marketing
Many startups abandon their first paid campaign after two weeks. The numbers in the dashboard aren’t lying, after all, it’s obviously “not working.” But what’s far more likely is that a faulty assumption – the assumption that last-click revenue should be the measure in the first place – obscured the chance to make a successful investment. Instead, the mistake was made permanent. The first campaign was never meant to be a revenue engine. It was supposed to be a research project. And in its wake comes the single most expensive mistake early-stage marketing teams make.
Last-click attribution is lying to you
The truth is, every major standardized model we currently use to measure marketing performance is biased against the way early-stage display actually works. Last-click is biased against it by design. Linear is biased against it because it treats every touchpoint as equally responsible for a conversion. Time decay is biased against it because it gives the most recent touchpoints the majority of the credit. Data-driven is biased against it because early-stage display’s contribution is almost always going to come back as $0. The data isn’t there to begin with.
This is because building a model that credits higher-funnel touchpoints with bringing in demand is harder than building one that steals that credit for the touchpoints closer to the bottom of the funnel. You can get away with last-touch attribution in a way you can’t get away with first-touch, because it feels natural to assume that if someone Googled your brand name and then bought something, they only bought something because they Googled your brand name. (If you assume people Google brand names when they’re already going to buy, this makes perfect sense – it’s a customer behavior conclusion disguised as a modeling decision.)
The campaign’s real output is data, not revenue
Here’s the mindset shift that changes everything: Your first paid campaign isn’t a sales channel yet. It’s a tool. Its role is to indicate to you which segments are receptive, which positioning statements are effective, and which offer falls flat. Revenue is a delayed indicator of all these factors. If you expect revenue immediately, it’s like asking a thermometer to prepare your dinner.
This doesn’t imply throwing money to the wind. It does suggest you should treat the campaign as if it were an experiment, which it is. Before you do anything else, write down your assumptions. For instance: “We assume that early seed SaaS startup founders would be more responsive to a pain-based headline than a feature-based one.” Or: “We believe more B2B mid-market teams rather than enterprise teams fit our ideal customer profile, as opposed to current assumptions.” Put a plan in place that would prove these statements right or wrong, and allot enough time and budget to achieve the desired response.
Most first campaigns don’t fail because they actually don’t “work”. It is because the team never took the time to write down what they hoped to validate or invalidate, who they were targeting to get this information, and what the minimal favorable outcomes would be. If you don’t have a hypothesis, the campaign did not fail, and everything is just noise. If you have one, you can arrive at the end of a “failed” campaign and still learn something incredibly valuable from the marketing campaign data.
Why display is the cheapest place to start learning
If the objective is to gain insights about the audience and not an immediate conversion, then you need to choose a channel that optimizes reach and cost per data point, rather than click intent. In this case, display network ads are a good choice for a startup’s first campaign. CPMs (cost per thousand impressions) on display inventory are generally much lower than what you would find on search or social channels. This allows you to get many more impressions for the same amount of money, and more impressions equal more signal – more segments of the audience to compare with, more creative variations to test, and more information about your audience before you start spending real cash.
Paid search is not the right choice at this point, although it is often the default for most founders. Search captures existing intent, it doesn’t help you find out who your audience is and how they perceive the problem you are addressing. It’s a bottom-of-funnel channel that you are trying to use at the top-of-the-funnel stage, and it’s quite costly for that. On the other hand, display networks allow you to expand your reach. You can have three completely different value propositions for your product tested with three distinct audience segments, and the cost will still be lower than what you would pay for competitive search terms for a week. And you will end up with actual comparison data.
Impression share is also important when using display networks. If your campaign is only getting a small percentage of the available impressions from a segment, you are not really testing that segment, you are not getting enough data to make any conclusions. Increasing your budget or slightly adjusting your targeting can give you a better view of your segment, and in the early stages of a campaign, this is usually worth it, even if it brings down your efficiency.
View-through conversions and the false negative problem
Imagine this situation: someone views your advertisement on a news website. They do not click on it. But, two days later, they search for your brand name directly and register. Under final-click attribution, the display ad receives no credit, and the search campaign is credited with bringing in a new customer even though that’s not the case. This is a view-through conversion. Ignoring it is how startups convince themselves that top-of-funnel spending “did not work” when in fact, it was doing exactly what it should.
Most advertising platforms can provide data on view-through conversions if you delve into them, however, these conversions typically have a smaller window of attribution than the click-based variety. Take the data. Pit it against your branded search volume and a graph of direct traffic before and during the campaign. If you notice that both are shooting up while your click-through rate stays flat, that is definitely not a flop. That’s the lift in branding playing out in exactly the region last-click attribution misses.
This is where marketing mix modeling comes into play, even for tiny young teams not in a position to pay for the whole kit and caboodle. You don’t need a number-crunching squad to borrow the logic: track the cumulative results for a few weeks, not the individual click paths for a few days. The outcome of top-of-funnel spending is indirect. Assessing it within a 48-hour window of the final click ensures you’ll be underrating it every single time.
What to actually measure instead
Vanity metrics are called that for a reason. CPM, raw impressions, and CTR may be impressive numbers to present, but they do not indicate whether a campaign influenced people’s behavior. For example, a high CTR on a display ad could simply mean that the ad was confusing, prompting people to click and try to understand it, rather than being effective. While these metrics are useful for identifying issues, they should not be the sole measure of your success.
The following are some better indicators, listed from most to least effective for your first campaign:
Branded search lift: Monitor the number of branded queries each week before the campaign begins. A significant increase while the campaign is running, especially after steady ad spend, is one of the best early indicators that your campaign is increasing brand awareness.
Direct traffic: In the same vein, people who still remember your name well enough to type the URL directly were probably reminded of you by something.
View-through conversion rate, tracked separately from click-through conversion rate, rather than lumped in together.
Ad frequency versus response curve: If site visits or branded search continue to climb for the first three or four exposures and then flatten or drop, your optimal frequency is somewhere within those first three or four exposures you’re already serving.
Incrementality, even if you measure it in the extremely crude way of just blocking a geo or audience from seeing any ads and seeing whether they convert at usual organic rates.
None of these are much harder to measure than the dashboard readouts you’re already used to. They’re just different.
Turning first-campaign data into compounding advantage
The insights and audience from a well-run first campaign should be used for subsequent campaigns. They provide the basis from which you can build new strategies. Those target groups that didn’t convert but showed good interactions can be used for retargeting. Those users that visited your site and/or converted can be used to find similar people on another channel.
Also, the copy that worked well in the first flight is likely to work well in paid search or retargeting, too. Post-impression feedback can help you catch those compounding benefits.
The bottom line is awareness can be very expensive when you are not looking. If you are an early startup, your top-of-funnel budget should be somewhere in the range of 10 – 20%, not because it’s the perfect number but because zero is the wrong number. Zero spend on awareness means zero audience data, and audience data is the thing that eventually lowers your customer acquisition cost across every channel you touch. Treat that slice of budget as R&D. Judge it on hypotheses tested and signal quality, not on immediate return.
The orthodoxy that’s actually holding startups back
The typical startup advice would be to “only spend on what converts today.” It may sound disciplined. It is, in fact, a nice method to remain small. Performance channels convert demand that already exists; they don’t create new demand, and eventually they saturate the audience that was already ready to purchase. Without a parallel investment in awareness, CAC on your performance channels will increase every quarter while you fight with others for the same pool of high-intent searchers.
View the first paid campaign as a learning engine, rather than a revenue event, and that cycle breaks while it’s still early. With the marketing campaign data, you will have a clearer view of your target customers coming out of it, creative that has withstood real attention in the marketplace instead of guessing, and first-party marketing campaign data that helps the next campaign on every channel convert better. This isn’t a nice thing you get as the consolation prize of a campaign that “didn’t convert.” This is what a campaign is for.