We all know that customer journeys are messy. People click an ad, leave, come back via email, search you on Google, maybe see a social post—and then decide to buy. That’s why understanding which channels actually drive conversions is such a tough (but important) job.

Many marketers turn to Markov models for help. These models look at how people move between channels and try to figure out which ones are truly influencing conversions. It’s already a big step up from basic rules like “first-touch” or “last-touch” attribution.

But here’s the catch: most Markov models still assume that every customer is the same—that their behavior depends only on the sequence of channels they touch.

And we know that’s not how real-world marketing works.

Customer journeys aren’t shaped by channels alone. They’re influenced by who the user is and how they interact—things like their country, device type, segment, or even how long they take to convert. These factors play a huge role in how people respond to different touchpoints.

If your attribution model isn’t taking that context into account, you’re only getting part of the story.