Four ways we measure what your ad spend does.

Each one checks the others, so the number your marketing team sees is the one finance can sign off on. Anil and our analyst do the work; you get the findings and a plan.

Marketing mix modelling

How much of your sales each channel actually caused, once seasonality, festivals, discounts and slow-burn effects are taken out. Every number comes with a range, so you can see how sure the model is.

What each channel really adds: Google, Meta, YouTube, marketplaces and offline, measured against your real sales rather than each platform’s own report.
Credit for slow-burn spend: YouTube, TV, print and hoardings keep working for weeks after they run. The model counts that, so brand spend isn’t undervalued.
Where spend stops paying off: The point in each channel where the next unit of spend returns less than the last, shown as a range.
Checked before you see it: The model has to predict weeks of sales it hasn’t seen before we share any finding.

Incrementality and geo-lift tests

A simple experiment that shows what would have sold if a campaign hadn’t run, for example by changing spend in a few cities and comparing them with the rest.

Campaigns keep running: We compare what sold with the ads against what would have sold without them. You don’t have to go dark.
Designed to give a clear answer: We pick the cities or audiences and the length of the test so the result is reliable enough to act on.
A clear go or no-go: If Meta reports a return of 4 and the test shows 1.8, more than half of those sales were coming anyway. You’ll know which number to plan with.
Results make the model sharper: Each test result goes back into the mix model, so every refresh is better than the last.

Budget planning and forecasts

Next quarter’s split by channel, built from what the model measured rather than last year’s plan or platform reports, with the expected range of sales for each option.

Built around your goal: More sales, a better return on ad spend or a lower cost per customer. You choose, and the plan is built for it.
Limits you set: Minimum and maximum spend per channel, so the plan respects commitments you’ve already made.
Stops short of the ceiling: We won’t recommend pushing more money into a channel past the point where it stops paying off.
Compare a few budgets: For example flat, 20% more and 20% less, with a best, expected and cautious case for each.

Attribution and repeat customers

Fair credit across the steps a customer takes before buying, checked against the mix model, and which channels bring customers who come back.

Beyond the last click: Credit is shared by what each step contributed, not just given to the final ad someone clicked.
Double counting removed: When Google and Meta both claim the same sale, we count it once.
Where the two methods disagree: We show where attribution and the mix model differ, and why. That’s usually where over-credited retargeting shows up.
Repeat rate by channel: Which channels bring one-time buyers and which bring customers who order again, including marketplace and quick-commerce sales.

Every report, walked through with you

Each refresh comes with a short written summary of what moved and what we’d change next month, and a call with Anil and our analyst to go through it.

See how a project runs and the data we need.

See where your own spend stops paying off

Thirty minutes with Anil. You’ll leave knowing whether analytics is worth it for you, which option fits and what it would cost.

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