Two marketers run the same kind of campaign. One checks response every week, sees soft early numbers, and cancels what turns out to be his most profitable campaign. The other sticks with an offer whose leads take longer to convert, and it becomes a top performer. The only difference between them is that one understood how long his leads actually take to buy, and the other did not. That single piece of knowledge, your real time-to-convert, quietly determines whether you scale your winners or kill them by accident.
Most marketers have no idea how long their leads actually take to become customers. They assume a week, maybe two, because that is the window their dashboard defaults to. But plenty of leads take a month or more, especially for considered purchases, higher price points, or longer B2B-style cycles. If your customers routinely take 30 or 45 days to buy and you judge campaigns at 7, you are grading every campaign before the results are in.
Knowing your real time-to-convert tells you three things you cannot operate well without: how long the customer journey actually is, when you should evaluate a campaign's results, and how many of your leads ever go on to purchase at all. Without it, you are guessing at the one variable that decides whether your measurement is fair.
The longer a lead takes to buy, the less reliable last-click attribution becomes, and it is already the weakest way to measure. Last-click credits only the final touch before the sale, so it is blind to the channel that originally generated the lead and to every email, SMS, and content touch that nurtured them in between. When a purchase happens weeks after the first click, last-click has completely lost the thread of how that customer actually got there.
In a privacy-first world, this gets worse still. As cookie windows shrink and cross-site signals disappear, the gap between the first click and a delayed sale is exactly where platform reporting goes dark. Meta's own reporting cannot see a purchase that happens well outside its attribution window on another channel. So the campaigns most likely to be misjudged are your long-tail winners, the ones that start valuable journeys that pay off slowly. Trust last-click on those, and it will actively steer you to kill your most profitable, slow-converting campaigns.
The fix is to measure the full journey over your real buying cycle, not the first convenient week. That means a few things in practice. Track leads from the first click through every subsequent touch to the eventual purchase, so you can see the whole path rather than just the last step. Set your evaluation window to match how your customers actually buy, not the platform default. And look at revenue over time, so a campaign that is slow but profitable gets the runway to prove it before you judge it.
This is the same truth that runs through honest attribution generally: value shows up over time, and the tools that only look at the last click or the first week systematically misjudge it. When you know how long your leads take to buy and you measure over that real window, you stop cancelling winners early and start replicating what actually drives revenue. See how it works on the platform overview, or book a demo to see your own time-to-convert on real data.
Knowing how long your leads typically take to convert stops you from prematurely cancelling campaigns that are profitable on a longer timeline. It lets you evaluate results only after a full buying cycle has passed, so you can accurately identify and scale the channels that drive revenue over time rather than killing them on early numbers that were never going to look good yet.
Last-click credits only the final touch before a sale, ignoring the initial ad or email that generated the lead and all the nurturing in between. The longer a lead takes to convert, the more of that journey last-click misses, and the more likely it is to misattribute or lose the sale entirely, especially as privacy changes shrink tracking windows. That makes it unreliable for exactly the slow-converting campaigns that are often most profitable.
Track each lead from the first click through every interaction to the final purchase using multi-touch attribution, and set your evaluation window to match your actual buying cycle rather than a platform default. Looking at revenue accumulated over time, rather than just the first week, lets you see which channels drive lasting revenue and gives slow-but-profitable campaigns the runway to prove themselves.