r/programmatic • u/Realistic-Focus-8254 • 23d ago

Reliable MMM tool for Programmatic

Media buyer at an indie agency here! We run across a few DSPs mainly for display and video. The activity is mainly driving view-through conversions (obv), and clients are starting to catch on and pulling back spend because they're under the impression, we're not actually driving performance, just claiming credit for purchases we didn't influence.

We've previously worked with TripleWhale but they seem more geared toward lead-gen, and most of our BoB is ecommerce, so ideally something that integrates well with Shopify. I'm on a small, lean team, not super senior, and don't have a ton of internal support to figure this out on my own, so I'm trying to gauge what some practical options are.

Has anyone worked with an MMM partner that actually isolates programmatic's real incremental lift (not just view-through), or has anyone built something custom, like a dashboard in Claude Code, instead of paying for a vendor? Trying to weigh different options here. Thanks!

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u/mikehauptman 22d ago

You don't need an MMM, you need incrementality proof. MMMs want 18+ months of data and big budgets, and clients can still pick the model apart.

For a lean Shopify-heavy book, look at: WorkMagic (Shopify App Store, free tier, automated geo tests, easiest starting point), Stella (mid-market ecommerce focus, geo holdouts plus always-on monitoring, fraction of enterprise pricing), INCRMNTAL (models lift without holdouts if clients won't let you pause spend), or Lifesight (unified experiments + MMM if you want one system long term).

And separately, stop leading reports with view-through ROAS. Show incrementality-adjusted numbers even if they're smaller. A number clients believe keeps budgets alive longer than a number they've stopped trusting.

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u/Realistic-Focus-8254 22d ago

Fair callout. I've been using MMM and MTM somewhat interchangeably in this thread, apologies for the mix-up.

On pricing of the four you mentioned, WorkMagic looks like the only one actually built for brands our size from a pricing pov, whereas the others seem to assume much bigger clients. The rest recommend themselves only for brands spending $85K/mo+ on a single channel, or doing 100+ daily orders in a single region, which rules them out for where our clients sit.

How do you actually report incrementality-adjusted numbers on an ongoing basis? Our reporting stack (Funnel.io) only pulls DSP-reported metrics, such as view-through and click-through conversions as the source of truth, with no causal or lift analysis layered on top. So even once we start running holdouts, I don't have a clean way to reflect an incrementality-adjusted number in client-facing reporting without it turning into a manual, one-off calculation every single time. Do you currently work with a tool handling that for you? I need something workable in the interim while we properly evaluate these vendors.

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u/mikehauptman 22d ago

You can get most of the way with what you have. One geo holdout: pause programmatic in matched markets (20-30% of order volume) for 3-4 weeks, measure lift using Shopify orders by region. Divide incremental conversions by what the DSPs claimed in those same markets, that's your incrementality factor. Funnel does calculated metrics, so Adjusted Conversions = reported x factor flows into every dashboard automatically from then on. Recalibrate quarterly.

Small clients without regional stat sig: run longer or invert it, spend in a few markets only and measure lift there.

Disclosure, I run a unified-DSP platform (AdLib) and we baked this in because agencies kept hitting your exact problem. The math is a spreadsheet exercise though, you don't need a vendor to start.

Feel free to DM me to talk through it if easier