PathX measures what actually moved: store by store, SKU by SKU, from retailer POS data.
Not modeled. Not proxied. Actual incrementality you can defend in the next JBP.
Bring joint business planning retailer-ready incrementality evidence: not modeled lift, not survey panels.
Store-level POS truth your category buyer can't dispute.
When your category captain asks what justified that placement, correlation won't hold. Causation will.
PathX isolates what you drove from what was coming anyway.
Don't just report the headline number. Separate the baseline from the lift, at the SKU and store level.
Refreshed every week, so the answer is ready before the question.
PathX doesn't hand you a dashboard to interpret. It gives you the four things you need to walk into a buyer meeting and not get asked a question you can't answer.
By store, by SKU, by retailer. Not rolled up into a single number you can't break down.
What was coming anyway versus what you actually drove: the line and the gap, every week.
Defend the methodology in the room, not just the result. Show the rigor behind the number.
Formatted for JBP and planogram conversations, not an export you still have to translate.
Difference-in-difference isolates what you caused from what was happening anyway. Your retailer already knows the category was up. What they want to know is how much of that was your campaign: and whether it holds at the store and SKU level.
That's not a reporting problem. It's a methodology problem. DiD solves it, and PathX makes it accessible without standing up a data science team.
Pathformance doesn't sell media. We don't run ads. We have no stake in your campaign performing, which is exactly why our measurement holds up when your retail partner is sitting across the table.
Tell us the campaign, the retailer, and the meeting you're walking into. We'll show you what a PathX study design looks like for your exact situation.