Upper funnel vs lower funnel comes down to timing: brand equity builds over months; performance is measured in days. This matters because experiments and mix models are built for that short window, not brand’s much slower one. Without enough data points, brand effects are hard to isolate, a year of daily data is only 365, quarterly just four. This video explains why measuring brand’s effect on performance remains genuinely unsolved.
Why Upper Funnel vs Lower Funnel Is Still a Genuinely Unsolved Question
Upper funnel vs lower funnel is still a genuinely unsolved question because building brand equity is a slow psychological process, while nearly every measurement tool marketers have was built to work on a much shorter clock. In this video, Jon Lorenzini, Chief Marketing Science Officer at LiftLab, draws on his time at Meta and Google to unpack a question he says has followed him his entire career: how does upper-funnel activity actually affect lower-funnel performance?
Lorenzini frames the answer through Kahneman’s Type 1 and Type 2 thinking, illustrated by his own experience grocery shopping in London, where without the visual shorthand he’d built up in the U.S. (red versus green packaging meaning salted versus unsalted butter), every purchase suddenly required active, conscious thought. Brand building is exactly that shorthand: repeated exposure that eventually makes a brand part of someone’s automatic choice set the moment a need arises. The problem is timing: that kind of equity takes months or quarters to build, while performance marketing is typically measured in days, weeks, or at most a 21-day attribution window. Neither marketing mix models nor standard experiments are built to capture something that slow, and the honest fix, longitudinal studies of brand awareness, consideration, and price elasticity, runs into a hard data constraint: a full year of daily data is still only 365 points, and quarterly data is just four, nowhere near enough to reliably isolate cause and effect once distribution, price, purchase frequency, and brand maturity are all varying at once. Lorenzini is candid that this remains a genuinely unsolved problem, not a solved one LiftLab is simply explaining.
In this video, you’ll learn:
The fundamental psychological difference between brand and performance marketing
Why traditional short-term experiments often fail to capture long-term brand value
The limitations of current data sets in tracking longitudinal brand effects
Key variables that complicate the direct relationship between funnel stages
Why emerging and established brands require different measurement approaches
TIME STAMPFull Video Transcript: Long-Term Brand Value and the Upper-Funnel Measurement Puzzle Explained
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Jon Lorenzini explains why long-term brand value is so hard to connect to lower-funnel performance, and why the data available to study it is genuinely too sparse.
[0:00 – 0:17] The Challenge of Connecting Funnel Stages
One of the questions that I typically get from advertisers is, how does my upper funnel performance impact my lower funnel performance. This is a challenge that’s plagued me from when I was at Meta, when I was at Google. This was always on the learning agenda and always a topic.
[0:17 – 0:47] Personal Experience: Brand Awareness in London
One of the things that happened to me that made me realize how important long-term branding and equity building was, was when I did a rotation in London. When I was there, I went grocery shopping, and I had to read every label, understand what everything was if I wanted to purchase the right things. You know, in the U.S., I know red versus green is salted versus unsalted Land O’Lakes butter. I knew visually the representations and what they were, so I wasn’t thinking as hard to make those decisions.
[0:47 – 1:26] The Role of Type 1 and Type 2 Thinking
In the book Thinking, Fast and Slow, this is definitely a big theme, your conscious and unconscious, or your Type One and Type Two brain, where you’re either passively just automatically doing stuff versus actively thinking. I believe this is really the difference between the brand and performance argument, which is your upper funnel, your branding, your high-value units that really make you understand the value prop, has to sink in and kind of create this level of, “oh, I need butter, I need Land O’Lakes.” So when I’m in the need state to do so, it’s part of my competitive set.
[1:26 – 1:56] The Disparity Between Brand and Performance Timelines
With this, especially high-value goods, infrequent goods, other things along those lines, it takes months and quarters to start building that brand equity. Performance marketing is measured in days and weeks. You know, maybe a month, depending on what your click-through or your last-click attribution is. You could do a 21-day window for ad stock effects that could carry over a couple weeks, but really it’s a much more short or finite period of time.
[1:56 – 2:30] Why Traditional Measurement Fails
So when we run experiments, when we’re looking at outcomes, we’re definitely focusing a little bit more on the bottom funnel. But that undervalues what is happening to your brand over the long term. And the answer to that is not marketing mix models, it’s not experimentation, but rather it’s understanding your brand awareness, your consideration, the price elasticity. All those pieces are something that requires long-term, longitudinal tests or studies, and with that, your old data is sometimes irrelevant, or less relevant, than your newer data.
[2:30 – 3:39] Data Sparsity and Measuring Success
So we have some professors, some people who are measuring these impacts of branded effects over longer windows, but it’s a very sparse data set, because you get 365 days’ worth of data if you’re doing daily data, 52 if you’re doing weekly data, 12 if you’re doing monthly, 4 if you’re doing quarterly. So that’s a really small sample to be able to start extrapolating how your brand-building activities are impacting your bottom-line performance. It’s a very tricky question, and it’s something that I see a lot of posts on LinkedIn about, and I’m always curious to see how people are solving this problem. The direct one-to-one relationship isn’t as clear, because there are just so many different considerations that go into this: what’s your distribution, how much is your product, how frequently do people purchase, where are you in your product life cycle in terms of are you an emerging brand or an established brand. All these questions really impact how this can be measured, or can’t be measured. It’s a very inconsistent thing that I think we’re still early on cracking the code for.
Key Lessons: Why Brand Effects on Performance Are So Hard to Measure
Brand vs. performance dynamics: Branding influences long-term automatic purchase behavior, whereas performance marketing focuses on immediate, finite conversion windows.
Measurement challenges: Standard marketing mix models and short-term experiments struggle to account for brand equity, requiring more complex longitudinal studies instead.
Data sparsity issues: The limited frequency of data points makes it difficult to draw statistically significant correlations between brand-building efforts and bottom-funnel performance.
Contextual variables: Factors like distribution, product pricing, and purchase frequency create highly inconsistent results when attempting to generalize funnel relationships.
