AttributionPractical guides on attribution, customer journey analytics, and conversion tracking — for marketers and founders who already know what converted and want to know why.
You already know who converted. Attribution is how you find out what actually got them there — not just which platform claimed the last click.
Every agency eventually gets asked "so what did we actually get for this spend?" Here's how to answer that with the customer journey instead of a vanity metric.
The lead converted three months after the click. By the time it's a closed deal in your CRM, the ad platform has long since forgotten it existed. Here's the fix.
A customer who switches devices mid-journey doesn't stop being one person — but most tracking setups will count them as several, unless you connect the dots.
"We got 50 conversions" is a number. Customer journey analytics is the story behind each one — every visit, campaign, and gap in between.
Someone hears about you on a podcast, forgets the name, googles your category three weeks later, and converts from "organic search." That's the dark funnel.
A third of your traffic showing as "direct" isn't a compliment — it's usually a tagging problem wearing a disguise. Here's what's actually causing it.
A customer clicks a TikTok ad, forgets about it, comes back from an email three days later, and buys. Which channel gets the credit? Here's how to actually answer that.
First-touch tells you what got their attention. Last-touch tells you what closed the deal. Neither tells you the whole story — here's why that gap matters.
GA4 quietly switched everyone to data-driven attribution. Here's what that model does, the one requirement that determines whether it even works, and how to read the reports.
A gclid or fbclid in your URL bar looks like junk. It's actually the one piece of data that lets a platform match a click to a conversion that happens minutes, or months, later.
Google Ads is very good at reporting what happened inside Google Ads. Here's what its attribution can't show you — and how to fill the gap.
Most attribution software demos look identical. Here's what to actually check before buying — the questions that separate a real journey view from a repackaged dashboard.
HubSpot's attribution reports are only as good as the contact record underneath them. Here's what the report actually shows, and the one requirement that breaks it silently.
Attribution assumes every touchpoint you can see mattered. Incrementality testing checks that assumption — by seeing what happens when you turn a channel off.
If your attribution report treats every lead as equally valuable, it's optimizing for the wrong thing. Lead scoring is what makes it optimize for the right one.
Every attribution model tells a slightly different story about the same data. Here's what each one actually optimizes for, and a simple way to choose.
One measures channels from 30,000 feet using no personal data at all. The other follows individual customers touch by touch. Most mature marketers eventually need both.
Meta says it drove 40 purchases. Shopify says 25. Neither is lying — they're measuring different things, on different windows, from different data.
Ad blockers, Safari's ITP, and iOS privacy settings all quietly eat Pixel data. The Conversions API is Meta's answer — here's what it fixes and what it doesn't.
A channel with high assisted conversions and low last-click conversions isn't underperforming — it's doing a completely different job than the report makes it look like.
One touchpoint rarely closes a sale. Here's how multi-touch attribution spreads the credit across the whole journey — and how to choose a model that fits your business.
Your ad platform is optimizing for form submissions. Your business runs on qualified leads and closed revenue. Offline conversion tracking closes that gap.
The deal closed in Salesforce four months after the ad click. Connecting those two facts isn't automatic — here's what actually has to happen for it to work.
Every browser-side tag is one ad blocker away from never firing. Server-side tracking doesn't fix your attribution model — it fixes the data the model is built on.
Shopify can tell you an order happened. It can't always tell you the TikTok ad, the email, and the branded search that all led up to it. Here's the gap and how to close it.
Optimizing purely for first-order attribution can quietly reward channels that bring in one-time buyers over channels that bring in customers who stick around.
Most people don't click a TikTok ad and buy immediately — they see it, scroll on, and come back later. Click-only attribution misses that entire pattern.
A UTM naming convention that only works if everyone remembers it perfectly, forever, doesn't work. Here's a simpler structure built around what people actually forget.
UTMs are the plumbing under every attribution report you'll ever look at. Get them wrong and everything downstream — funnels, journeys, revenue by channel — breaks quietly.