Analyze Pillar · Media Mix Modeling

Media mix modeling for mid-market teams without the full MMM overhead.

We design a media mix and incrementality approach for mid-market teams—robust enough to guide real budget decisions, lean enough to run with the team you have today.

Get beyond last-click without overcomplicating your stack.
Use experiments and directional models to inform budgets.
Align growth, finance and leadership on how to read results.

Talk about media mix for your team See the decision framework

Especially useful once annual budgets and quarterly targets kick in.

Why media mix feels hard

The problem isn't that you're "bad at attribution" — it's that the tools don't match your reality.

Mid-market teams are stuck between simplistic last-click and heavyweight MMM. We help you build something in the middle that your team can actually run and trust.

Platform attribution is all over the place.

Each channel claims more credit than total revenue. Leadership can see the math doesn’t add up, so they stall on budget increases.

MMM feels out of reach.

You don’t have the data history, team or budget to run a full-blown media mix model, but you still need a better way to allocate spend.

Brand vs performance fights never stop.

Nobody can agree how to value top-of-funnel, organic lift, or halo effects. Everything that isn’t last-click looks like a cost centre.

Budget decisions get made on instinct, not evidence.

Teams shift spend based on short-term swings or whoever shouts loudest, not on a coherent, shared view of how channels work together.

A media mix approach you can actually run

Lightweight, explainable, and good enough to move real money.

We're not trying to win econometrics awards. We're trying to give your team a better way to decide where the next dollar goes, without pretending the data is perfect.

Evidence hierarchy

Not all data is equal.

Define how you weigh experiments, platform data, GA4 and finance.
Set clear rules for when anecdotal evidence is allowed to influence spend.
Create a playbook for resolving disagreements between data sources.

Experimentation spine

Structured tests instead of random "trials."

Design always-on tests for key channels and tactics.
Use simple, interpretable designs: geo splits, holdouts, staggered launches.
Document and socialize learnings in ways teams can reuse.

Directional models

Just-enough modeling for better decisions.

Use regression-style or heuristic models where data allows.
Build simple "if we add X here, expect Y there" budget tools.
Keep models transparent so they can be updated as you grow.

Decision rituals

Turn insights into budget moves.

Set quarterly and monthly forums where media mix is reviewed.
Tie model and experiment outputs directly into spend changes.
Codify who owns which decisions and what data they must review.