Cracking the Code of Brand Touchpoints
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Customers don’t just buy products—they buy brands. And brands are built through experiences, scattered across a vast landscape of touchpoints: media, digital, social, and real life. But understanding how these touchpoints shape customer perception isn’t straightforward. It’s tough to get a 360-degree view of an individual prospect, especially when people themselves don’t always remember the experiences that influence them.
So how do you manage brand experiences if you don’t fully understand what each touchpoint does?
The Touchpoint Paradox: When Data Misleads
Flashback to 2015. I was sitting with executives from a major telecom company, reviewing our touchpoint analysis. The data told us that online shops were driving sales, but advertising wasn’t. That didn’t sound right.
Sure, most contracts were closed online—the final touchpoint was often the e-commerce site. Even after eliminating it, search ads still seemed to drive sales, while TV had little measurable impact.
But was that the full story? Not at all. TV wasn’t just influencing brand awareness; it was quietly fueling long-term sales. Prospective customers saw an ad, became curious, searched online, clicked an ad, and eventually bought. It was a journey. A messy, nonlinear one.
Traditional analytics miss this complexity. Here’s why.
Issue #1: The Last Touch Gets All the Credit—And That’s a Problem
For a utility provider, we found that conversations with friends and local events had the biggest impact on brand perception—yet these touchpoints weren’t even on their radar.
Why? Because brands rely heavily on first-party data. They track every click, every email open, every website visit. But offline interactions? That’s where things get tricky.
Even with sophisticated tracking panels that can pinpoint someone standing in Trafalgar Square, you still don’t know if they actually looked up from their phone to see your billboard.
Without a complete view of brand experiences, companies risk misattributing effects—potentially making costly decisions based on incomplete data.
Issue #2: Data Silos Block the 360° Customer View
Take Just Eat. When analyzing their touchpoint drivers, we found something unexpected. Branded delivery cars had a positive impact. But bicycles and delivery personnel? Negative impact.
At first, this seemed odd. Delivery staff are essential to the service, so why the negative perception?
Then it clicked: Customers unconsciously associated bicycle couriers with tough working conditions—long hours, low wages, and bad weather. The brand wasn’t just delivering food; it was (unknowingly) evoking empathy and concern.
Similarly, outdoor billboards placed in chaotic, high-stress locations—think crowded streets or train stations plagued by delays—often created unintended brand associations. If a customer’s environment is stressful, your ad might absorb that negativity.
It’s not just about measuring the presence of touchpoints—it’s about understanding how they shape emotions.
Issue #3: How Emotions Shape Brand Perception—Even When You Least Expect It
Sometimes, the most powerful insights come from unexpected places.
We ran an in-game ad placement study, measuring perceptions explicitly and through implicit association tests. The results were surprising: Gamers often didn’t recall seeing the ad, yet implicit testing showed a significant brand lift. Not only that—it directly impacted brand consideration.
This is why we started measuring all brand touchpoints implicitly. Unlike traditional analytics, implicit testing captures subconscious impressions, providing a more complete picture of brand influence.
Key Learning #1: Use implicit association testing for a true 360-degree view of brand touchpoints.
Causal AI: The Missing Link in Touchpoint Strategy
Once we have great data, we need to measure impact. Sales are a short-term effect, but brands don’t just compete on price—they compete on perception.
Brand image and brand consideration unfold over time. This involves both functional perceptions (which vary by category) and emotional resonance (which can be mapped through frameworks like the twelve brand archetypes).
But raw data alone isn’t enough. We need to quantify cause-and-effect relationships—which is where Causal AI comes in.
Causal AI helps untangle the web of influence between paid, earned, and owned media. It reveals:
The hidden nonlinearities, such as the powerful impact of a customer’s first touchpoint.
The direct causal link between a friend’s recommendation and a purchase.
The indirect impact of brand exposure on image and consideration over time.
Key Learning #2: Use Causal AI to reveal the true impact of brand touchpoints.
10x Touchpoint Impact—At a Fraction of the Cost (The 10x Touchpoint Strategy—Less Spend, More Impact)
Here’s what to expect:
You’ll discover that many of your touchpoints don’t move the needle at all.
Some touchpoints will be everywhere—but barely influence purchase decisions.
A few will be insanely effective—yet underutilized.
With these insights, you can:
Reallocate budgets from low-performing touchpoints to high-impact ones.
Optimize high-reach touchpoints to make them more effective.
Multiply brand impact—without multiplying spend.
Every brand has unique touchpoint challenges. The key is customization—tailoring strategies to fit your brand’s specific needs and market dynamics. If you’re looking for an affordable way to prove the concept, check out SUPRA’s group study: www.supra.tools/touchpoint.ai
Don’t wait. Get your feet wet, but get started.
THIS is how you 10x insights.