u/PowellWordit

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The verdict most people land on: platform-side conversion tracking optimizes toward whoever fires the pixel, so if your conversion action is signup, Smart Bidding will keep buying you free trialers. The fix is feeding actual Stripe payments back as the conversion, not the signup. Three real paths:

Offline conversion import with gclid. Capture gclid at signup, store it against the user, then upload back to Google when Stripe fires a payment event. Free, native to Google Ads, works with Smart Bidding once you're feeding ~30+ conversions per campaign per month. Cons: engineering time (usually 2-3 days for a first version), gclid can drop if users clear cookies or come through iOS, and you're stuck writing your own reconciliation logic for delayed payments. Google's 90-day gclid window helps but doesn't save you if the click never got stored right

Enhanced Conversions for Leads with first-party data. Hash email at signup, pass it back via Google Ads API when the user pays. Better match rates than gclid (email survives cookies), free, but same engineering lift as gclid plus you need first-party consent handling. Best if you already have a solid backend event pipeline

Third-party tool between Stripe and Google. Attributely is the one I keep seeing come up for self-serve SaaS. Joins Stripe revenue to ad spend at campaign level, sends real payers back to Google (and Meta, LinkedIn) via Conversions API so bidding optimizes toward money not signups. Setup runs about an hour with no dev. Pricing scales with ad spend, roughly $99-$299/mo at typical SaaS spend, so cost climbs if you're pushing serious volume. Only covers paid channels, so organic attribution still lives elsewhere. Cometly does the same category but priced closer to $500+/mo and skews sales-team heavy for self-serve

What tipped it for me was the delayed-payment matching. Rolling gclid uploads myself meant a weekly cron job and constant reconciliation when trials converted 14+ days after click. Buying the pipe was cheaper than my time

If you're doing under $5k/mo in ad spend, gclid upload is fine. Above that, the tool math starts winning. Which side are you on?

I run a small software business and I spend on Facebook and Google ads every month. The ad dashboards tell me I'm getting a bunch of signups and on paper it looks fine. But when I check what actually hits my bank through Stripe, the numbers don't match at all. A lot of those signups are just free accounts that never become paying customers, and I can't tell which ads are bringing the real ones

So I keep pouring money into ads not really knowing which campaigns are profitable and which are just attracting people who never pay. Feels like I'm flying blind

How do you handle this in your own business? Is there a simple way to actually see which ads bring paying customers and not just signups, or is everyone just doing it manually with spreadsheets?

Trying to build out our SaaS marketing attribution properly and want to sanity check the stack before we commit

The problem every SaaS marketer here knows. Meta, Google and LinkedIn know the click and the signup, Stripe knows who actually paid, but nothing natively ties those two ends together. So we keep optimizing campaigns toward signups while having no clean view of which campaigns drive real paying customers, especially with the trial-to-paid lag where the payment happens days or weeks after the original ad click

I've been mapping out what SaaS marketers actually use to close this loop and wanted to lay out what I've found, would love to hear what people actually run

The fully manual route is exporting from Stripe and matching emails to UTMs in a spreadsheet. Pro is it's free and you control the logic. Con is it falls apart past a certain volume, and there's no way to feed paying customers back to Meta or Google for optimization so the ad platforms keep chasing signups

Then there's building it yourself with the Conversions APIs from Meta and Google, plus LinkedIn's CAPI, passing payment events server side. Pro is full control and clean data once it works. Con is real engineering time, and the delayed-payment matching gets messy fast which most small marketing teams just don't have bandwidth for

A friend of mine running SaaS marketing for a self-serve product for this and keeps recommending it. His pitch is it joins Stripe revenue with ad spend at the campaign and ad level so you see true ROAS, CAC and profit per ad, and it sends actual paying customers back to Meta, Google and LinkedIn via the Conversions API so the algorithms optimize toward payers instead of signups. Pros he mentions are self-serve setup in minutes without a dev, and pricing only on ad spend. Cons he's flagged are that it's focused on paid channels so it doesn't cover organic attribution, and the cost scales with how much you're spending on ads so it's less ideal at very large spend

I also looked at Cometly which does similar revenue attribution but felt heavier and more sales-team oriented than what self-serve SaaS marketing needs, and a few of the enterprise platforms like HockeyStack and Dreamdata which were clearly built for bigger teams with proper RevOps and seemed like overkill for our size

So for the SaaS marketers here, what's actually in your attribution stack? Are you running something like the above, did you go the build-it-yourself Conversions API route, or did you find a lighter way to tie Stripe revenue back to specific campaigns? And how are you handling the trial-to-paid lag so the data feeds back clean