Once we've chosen the right engagement, we'll agree on the decisions you're trying to make and what you most need to learn. Then I connect and analyze all of your existing customer language against those decisions, show you what you already know, and design the research to close the gaps so you can decide with confidence. We'll work together in Slack, with calls on a rhythm that fits the engagement.

No. Research always turns up more than it set out to answer. When we find something outside the scope that could lead to growth, we'll share it with you. We just don't build the engagement around those extras, so the work stays focused on the decisions you brought us in for.

No. Signal is built with brands in mind, but the thesis came out of agency partnerships and the value there is just as strong. The same evidence gap shows up across a whole client roster rather than one brand. If you are an agency, say so when you get in touch and we will talk about your roster rather than a single brand.

Good, keep running it. Whatever platform you use, Fairing, KnoCommerce, Zigpoll, Okendo, Alia or your own post-purchase flow, we work inside it and start from the responses you already have. Survey and research design is a large part of this, and it is most of what I did for four thousand brands before Signal. The difference is what happens next: connecting those responses to what customers actually buy, and turning them into specific messaging, offers and personas your team can use. Most survey programs stop one step before the part that pays. Having one running already is the main thing that makes a brand a good fit, because I would rather spend the first weeks finding growth than building a research program from zero.

You probably know them better than I will for the first few weeks. The question is not whether you know your customer, it is whether you know which of the things you believe about them actually changes what they buy when you put it in front of them. Those two overlap less often than anyone expects, and the gap is usually worth real money.

Every experiment we launch carries an identifier tied to the insight and persona behind it: a naming convention on ads, a tag on email campaigns, or a URL slug on landing pages. That lets us trace revenue back to the specific insight and see whether it's paying off the way we expected. Where we can, we also compare against a version without the change, so you know it's the insight working and not just a good week. Where we can't, we'll say so and treat the result as a strong signal rather than proof.

Yes. Odds are you already have more than you know what to do with, because it compounds across sources. A few hundred reviews, a year of support conversations, a survey that has been running quietly and your full purchase history is a great deal to work with, even when none of them feels like enough on its own. If you are clearly under the floor, I will tell you on the first call rather than take your money and find out in week three.

Then you're one of the rare few. Out of thousands of brands, I've only met six with a dedicated data team. In that case my role shifts: I run the customer research myself and act as the bridge between marketing and data, so both teams work from the same findings and act on them together.