Gabb

Elijah Ellsworth brings expertise in performance marketing, brand strategy and measurement. His work focuses on connecting acquisition, experimentation and customer trust to build sustainable growth.

Making Trust a Business Outcome

Trust already shows up in the numbers a business runs on, whether or not marketing claims it. As a marketing objective, trust can live on a brand tracker without requiring action outside the marketing team. As a business outcome, it influences whether customers stay, what they commit to and what it costs to acquire them.

At Gabb, we made that connection concrete by changing how we measure acquisition. We stopped making spend decisions based on blended CAC and broke it out by SKU, plan, contract length and channel.

A customer who chooses a longer contract shows more confidence than a click-through rate can measure. Our buyer is a parent deciding how much independence their child is ready for, and much of the trust we earn or lose happens after the sale through the product and support experience.

That also makes ownership important. If trust is only a marketing objective, marketing owns a number it cannot fully control. When we treat trust as a business outcome, we recognize the role that the entire customer experience plays in earning it.

Using Evidence to Guide Growth

Measurement helps us understand whether growth initiatives strengthen or weaken that trust. We measure incrementality to determine whether a channel actually causes a sale, but that does not tell us whether the customer is worth acquiring.

Because we break CAC out by SKU, plan, contract length and channel, we can identify when a channel looks efficient for the wrong reason. A channel may produce a low cost per new line, our term for an activation, while bringing in customers who choose the shortest commitment we offer. That can signal a gap between the promise in an advertisement and what the customer finds after signing up.

Three measurement tools work together in that process. MMM helps us understand what the overall marketing mix contributes. MTA helps with diagnosis, but does not serve as the final verdict. Incrementality helps settle the question when those approaches disagree. We bring those inputs together through an allocation model that turns evidence into a budget decision.

 

Measurement and experimentation also keep long-term work fundable. Performance marketing can prove itself within a week, while brand work often needs more time. When a quarter gets tight, brand investment can therefore become an easy target.

Models need enough history before they produce results worth betting on, yet there is always pressure to act before that history exists. Agreeing on the allocation model in advance helps us decide what a result means before we see it. Otherwise, a test can quietly become a search for permission to do what we already wanted to do.

Learning from the Data without Losing Judgment

Performance Max in Google Ads gave me a clear lesson in the difference between reported performance and actual impact. It looked like our efficiency engine. Clicks cost about a third of what Shopping cost us; volume was high, and every dashboard suggested that I should increase spending.

Then, incrementality showed that our cost per incremental new line on Performance Max was roughly four times that of Google Shopping. The clicks were cheap because many came from cross-network placements that took credit for demand already coming our way.

When data and instinct disagree, they may simply be answering different questions. Platform-reported ROAS tells us what received credit, not necessarily what caused the sale. Instinct also provides evidence, but it has not been audited yet.

Leadership matters in those moments because teams watch how leaders respond when the numbers become uncomfortable. If we say we test our way to decisions but ignore the model whenever we dislike the answer, we teach the team that testing is only decoration.

Sustainable growth also requires us to look beyond acquisition numbers. We put a downstream measure next to cost metrics, whether that means retention, contract length or repeat purchase. A cheaper acquisition should never receive praise before we understand who showed up.

The same discipline applies to our marketing promises. I start by looking at what the product actually promises in the words a customer would use and then compare that promise with our highest-spending ads. The gaps are where trust can leak. They often develop gradually as slightly bolder headlines perform better and nobody notices the drift.

The tactics we choose not to use matter as well. There is plenty of fear available in our category, and fear converts. Choosing not to use it can cost us in the short term. What a company refuses to do is often the clearest statement it makes about what it believes.