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To See Why Last-Click Doesn’t Work, Try My Pizza

A thought experiment explaining the crucial importance of establishing a baseline. 

 

Often, marketers overestimate the impact of their lowest-funnel channels – giving outsized credit to “last-click” or “last touch” outlets that are easiest to measure, and overlooking the real impact of higher-funnel, harder-to measure channels at the same time. To help marketers think beyond this error, I’d like to present a framework for a holistic, whole-funnel approach for measurement – with the help of some local food (or sunglasses). 

 

On Marketing Measurement and Cheese Pies 

Let's say I opened a pizza shop in my neighborhood. The pizza shop is located in an area with a lot of foot traffic – and so to attract new customers, I decide to wait outside the door and offer coupons to anyone within reach. The coupons are generous: half-off on your first slice or pie. To my delight, 10% of the coupons I hand out are used. 


At the same time, I hire workers to stand outside another high-trafficked spot: a shopping mall a few blocks away. Being a measurement-minded marketer, I make sure the coupons are color-coded to easily distinguish shopping mall coupons from the store entrance ones. That color-coding lets me see that the mall coupons were cashed in at a far lower rate: just 1% of those coupons were used. 


Three months later, business is doing well (not surprising: the pizza is delicious!) – and it’s time for another sidewalk campaign. At this point, I have a critical question to answer: Where should I station my coupon distributors? (Let’s assume, for the sake of simplicity, that by the storefront and near the mall are the only two viable options.) 


Looking at coupon usage, I might say that the answers are clear. Given the far better conversion rates from just outside the store, I’d do best to focus coupon activity in that area alone. After all, 10% is clearly a much better rate than 1%.   


That assumption seems plausible, is data-driven, and is quite possibly entirely wrong. Yes, the data I’m using to evaluate success – coupon conversion rates – clearly suggests a “winner” between the two outlets. But maybe, by looking at the most readily available information, I’m actually drawing the wrong conclusions.  


After all, there’s a fair chance that a certain percentage of the near-the-storefront coupons – perhaps even most of them – went to customers who were literally about to walk in and make a purchase. What looked like enticing locals into my store may actually have been an exercise in slashing organic revenue by half. Meanwhile, perhaps many people who picked up a coupon by the mall would never have come to my shop, or even have heard of it, otherwise. Yes, few people cashed in on the coupons. But maybe the coupon initiative intrigued mallgoers so much that, even after misplacing their coupons or forgetting them at home, they still came to my pizza shop and paid full price.   


To draw the right conclusions about my coupon campaign, I need to look far more holistically. I need to first establish an overall baseline – an understanding of what groups would come to my store based on organic intent alone –to know how any of my coupon marketing has impacted them. Anything less is just making an assumption in the dark.  



Marketoonist Cartoon, at a sunglass shop, "You Should get sunglasses. "Um, I know... that's why I'm here." Next strip, "What are you doing?" "Ever hear of last touch attributions?" Caption is Don't Let your Last Click Be Your Last Dollar Spent

 

The Right Recipe for Marketing Accuracy 

Even if you’re not marketing bricks-and-mortar restaurants, this story is worth considering as you’re thinking out your own measurement approach. After all, you’re likely using some combination of low-funnel outlets—from doorway coupons to search ads – alongside higher-funnels channels that catch customers far from the point of conversion, whether that’s a few blocks down the road or scrolling the TikTok feed. To understand the real impact of any of these outlets, it’s critical to establish a baseline for an understanding of real marketing impact. You need to look to historical models constructed from the data you have, and experiments that answer questions empirically when data is lacking. How to construct those models and experiments is a far vaster topic than I can cover in just one post. But regardless, it’s crucial to keep in mind that in measuring marketing impact, looking at last touch alone means missing most of the pie.

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