Media & Performance
Performance Marketing
We manage your paid channels as one system tied to a commercial target, and we move budget according to margin and proven contribution.
The problem
Every channel reports a win, but the total in your books doesn't add up to them.
Each platform claims the same sale under its own attribution rules. Add the dashboards together and you can count more revenue than finance recorded. Those reports were built for optimizing inside a platform, and they were never meant to referee between platforms.
Averages mislead too. A channel can hold a healthy ROAS while the last chunk of budget earns very little. Teams scale on the average and spot the falling marginal return months later.
Then there is ownership. Specialists defend their own numbers, and no one answers for the blended result.
You may recognize this
- Platform-reported revenue adds up to more than your books show.
- Nobody can state the acquisition cost each product can afford.
- This month's budget is last month's split with small adjustments.
- Several agencies claim the same customers, and none owns the total.
How we work
Model the unit economics
Margin, returns, repeat purchase and LTV by product or segment produce a break-even ROAS and an allowable CAC. Every target traces back to that model.
Build one scorecard
MER, new customer counts and platform data sit in one weekly view, with written rules on which number settles which question.
Run incrementality tests
Geo holdouts and platform lift studies measure what each channel adds, which calibrates how far to trust its reporting.
Allocate on marginal return
Spend moves in steps while we watch what the extra budget earns. When a channel saturates, money shifts to the next best opportunity.
What we deliver
- Unit economics and target model
- Cross-channel budget allocation plan
- Single-source performance scorecard
- Incrementality test calendar
- Weekly decision memo and monthly leadership summary
How we measure
- MER (total revenue divided by total media spend): double counting can't inflate it.
- New customer CAC and payback period: these tie growth to cash.
- Contribution margin after media: the money that actually remains.
- Incremental revenue by channel: shows where a budget cut would really hurt.
A home goods retailer on several channels
Illustrative scenario: An online home goods retailer runs Google, Meta and marketplace ads through separate teams, and each one reports success. The work starts by setting break-even targets from product margins. A geo holdout on Meta follows, and its readout frames the next budget conversation.
Common questions
How is this different from Google Ads or Meta Ads management?
Those services work inside one platform. This one sits above them: where the next unit of budget goes, what each channel is for, and whether the whole program makes money.
Can we trust platform data at all?
Yes, for decisions inside the platform, such as which ad is working. For budget across channels, we read it alongside MER and test results.
We are too small for geo tests. What then?
Small budgets make those tests noisy. Planned on-off periods for one channel, read against MER, give a rougher answer that still beats trusting attribution alone.
Before we work together, let's think together.
Requests are answered by the founder.