A turnkey targeted advertising launch: I set up campaigns around your goal plus accurate tracking, so the algorithm learns from clean data and you see the real path from click to revenue — not a "black box".
I build the structure (campaigns → ad sets → ads) around your chosen objective: leads, sales, or payback. Each goal has its own logic: for leads, Meta looks for people likely to submit a form; for sales — people likely to buy; for payback — purchases with higher value.
I install/verify the pixel and configure exactly the events that carry value (lead, purchase, add to cart), so the algorithm learns from the right actions.
I set up event delivery straight from the server, so conversion data doesn't get lost to ad blockers and privacy settings. The more accurate the data, the better the algorithm performs — and the cheaper the result.
I bring data from ads, the website, and leads together into one picture, so you see not just "clicks" but the real journey: where the customer came from → what they did → whether they bought. This removes gut-feel decision-making.
I launch the campaigns, guide them through Meta's review, and monitor delivery in the first days to make sure spend behaves correctly.
Without accurate tracking, advertising turns into a "black box": money gets spent, leads seem to come in, but nobody knows which campaign delivered them or whether they pay off. Meta's algorithms learn from conversion data — if that data is incomplete or "dirty", the system targets the wrong people and the cost per result climbs. Proper tracking (pixel + CAPI + end-to-end analytics) is your marketing's eyes: it lets you make decisions based on facts rather than guesses, and gives the algorithm quality "fuel" to learn from.
The browser pixel loses a share of conversions to ad blockers and privacy settings (especially on iPhone). CAPI recovers that data from the server. Together they give Meta a fuller picture — the algorithm finds buyers more accurately, and you see real numbers instead of undercounted ones.
We could launch fast, but without tracking in place you won't know what's working. A few days spent on the pixel, events, and analytics pay for themselves: every budget that follows is spent deliberately, not into a void.
That's the learning phase: the algorithm is testing audiences, placements, and timing to find your buyers. Until it collects around 50 conversions in 7 days, the cost per lead/sale fluctuates. It's not broken — it's a necessary stage.
The first leads can come within a few days, but stable costs and reliable conclusions should only be judged after the learning phase ends (often 1–2 weeks). Drawing conclusions after 2–3 days is a mistake that often leads to premature changes and a learning reset.
A service business was getting leads, but half of them went cold and nobody could see why. Once end-to-end analytics was in place (GA4 + automation via Make), the picture became clear: most of the expensive leads came from a single ad combination (audience + creative + setup) that produced almost no deals, while a cheaper combination was bringing in real customers. Without tracking, this was invisible. Shifting the budget to the working combination lowered the real cost per customer — without increasing spend.