BYL DIGITAL

Data & Analytics

Reading the Numbers: A Practical Guide to Ad Data and Analytics

18 Oct 202310 min readMuhamad Inwann
Reading the Numbers: A Practical Guide to Ad Data and Analytics

Data is not a report; it’s a decisions engine. Dashboards should change what you do by 9:15 a.m., not decorate a slide at the end of the month. The trick is to measure journeys, not channels, and to define success where money changes hands—not where clicks happen.

We start with a single source of truth. That means reconciling ad platform data (which is great at direction) with your CRM and revenue (which is truth). Attribution is a debate, but indecision is worse. We pick a model, document it, and stick to it for a quarter so we can learn from signals instead of chasing ghosts.

Our core ladder looks like this: thumb-stop rate → cost per qualified visit → form start rate → form completion rate → first reply time → booked call rate → show-up rate → win rate → CAC → payback → LTV. Each rung answers a different question and belongs to a different owner. Creative owns thumb-stop. Landing owns qualified visits. Ops owns first reply time. Sales owns win rate. Finance owns CAC and payback.

We also track time, because time kills deals. A 3-minute reply beats a 30-minute reply even with the same script. So we graph median time-to-first-reply and time-to-handoff. If those lines rise, no creative fix will save you. Speed is a compounding advantage.

ROAS is only honest with the full picture. We pair it with contribution margin and cash payback. It’s fine to run an ad at 1.8x if upsells lift LTV and cash comes back in 30 days. It’s a trap to brag about 6x on retargeting while new-customer growth stalls. Decision frameworks beat hot takes.

Finally, we make the dashboard tactile. Numbers that don’t trigger actions are trivia. So every widget has a counterpart play: if thumb-stop falls, rotate hooks. If qualified visit rate drops, test hero copy. If booked calls dip, audit calendar friction. And once a week, we archive learnings so the team never solves the same problem twice. Over time, the data stops shouting and starts guiding—quietly, consistently, profitably.