Defending a finding with ten minutes on the agenda: Ten minutes forces hard choices about what to leave out. What survives the cut, what goes in the appendix, and the two sentences that have to open it.
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Attribution by the numbers
Avg ad spend wasted
Meta ROAS inflation
Cost to find out
Setup time
Ten minutes is enough if you decide in advance what you are not going to say. Most presentations fail by covering the method thoroughly and running out of time before the decision.
The ten minutes
| Minutes | Content |
|---|---|
| 0 to 1 | The design and its limits, in two sentences |
| 1 to 4 | The per-channel table, read aloud once |
| 4 to 6 | The gap against platform numbers, with the ratio |
| 6 to 8 | The decision you are asking for |
| 8 to 10 | Questions |
The two opening sentences
The first names the design: this is an observational causal estimate, not a test. The second names the limit: three channels could not be measured at their current spend, and they are listed at the bottom.
Getting both out in the first minute does two things. It pre-empts the objection that would otherwise arrive at minute seven, and it establishes that you are the person in the room least likely to overstate. Everything afterwards is read in that light.
The table
Per channel: estimate, confidence interval, coverage share. Read it once, aloud, slowly. Do not walk through the method for each channel; if someone wants that, it is minute eight.
Point at the widest interval yourself before anyone else does.
The gap slide
Have the ratio ready: the sum of platform-claimed revenue for the window divided by what the store actually took. Above one is expected and the size is the point. This is the two minutes that most often changes how a room reads its dashboards afterwards, and it needs no statistics. Method in the claim ratio.
The ask
Make it specific and small. Not "we should change our attribution philosophy" but "hold this channel's budget steady for four weeks so we can read it properly", or "reduce this one by a third and re-read in a month". A small concrete ask survives a short meeting; a large abstract one does not.
The structure for a cut recommendation is in which channels to cut, for the CFO.
What goes in the appendix
The method. The window justification. The channel-by-channel notes. All of it belongs in a document you can send afterwards, and almost none of it belongs in ten minutes.
What to hand out
One page, the same one you would send to finance: per channel estimate, interval, coverage, design label. That is what a €99 one-time read on a Google Analytics export returns, refundable if it does not move a budget decision, and it is deliberately one page.
The interactive demo is a useful thing to send round beforehand, with no signup, so the format is familiar before the ten minutes start.
The failure mode to avoid
Spending seven minutes establishing that the method is sound and two minutes on the finding. The room does not need to be convinced of causal inference. It needs a bounded claim and a specific ask.
Related answers
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Key Terms in This Article
Analytics
Analytics is the systematic computational analysis of data. It reveals customer behavior and measures campaign performance.
Attribution
Attribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive conversions.
Attribution Debt
Attribution debt is the gap between what your ad platforms claim drove revenue and what actually caused it, carried quarter after quarter into the budget. It is how marketing debt accrues: allocate on claimed conversions long enough and the plan itself becomes the liability.
Causal Inference
Causal Inference determines the independent, actual effect of a phenomenon within a system, identifying true cause-and-effect relationships.
Causality
Causality is the relationship where one event directly causes another, essential for identifying specific actions that drive desired outcomes in marketing.
Confidence Interval
Confidence Interval is a statistical range of values that likely contains the true value of a metric. In marketing analytics, it quantifies uncertainty around estimates, indicating the precision of an outcome or causal effect.
Dashboards
Dashboards are graphical user interfaces that provide at-a-glance views of key performance indicators (KPIs). They monitor campaign performance and visualize attribution insights.
Google Analytics
Google Analytics is a web analytics service that tracks and reports website traffic.
Related Articles
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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