What a founder can set up before peak, alone
Three things one non-technical person can finish in an afternoon before the window opens, and two that need more lead time than you have left.
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By Joris van Huët, Founder & CEOUpdated 3 min read
Three things fit in one afternoon and one person. Two do not, and knowing which is which saves you from starting the wrong one.
Achievable this afternoon
| Task | Why it matters | Time |
|---|---|---|
| Check your analytics retention setting | It expires, and takes the peak detail with it | Two minutes |
| Freeze channel grouping and lookback, in writing | Mid-window changes cannot be undone | Twenty minutes |
| Take a baseline read on a normal month | Peak numbers are uninterpretable without one | Half an hour |
Retention
A setting in Google Analytics governs how long detailed data stays queryable. If yours is short, the granular record behind peak can expire before you get to analyse it, and nothing recovers it. Check it first because it takes two minutes and it is the only irreversible one. The retention trap has the detail.
Freeze the definitions
Write down your channel grouping, your lookback window and your timezone, and date the document. If any of them changes during the season, the before and after cannot be compared, and that damage is permanent.
The baseline
A read on an ordinary trading month is what makes the peak read mean anything, because peak is strong for reasons that have nothing to do with your channel mix. A €99 one-time read on a Google Analytics export does it, refundable within 30 days, no questions asked, with no install and nothing added to your store.
Not achievable now
A geo holdout test needs a pre-period and weeks of running, so starting one close to the window measures the window rather than the channel. The last day to start a holdout puts a date on it.
Changing measurement method mid-season is the other one. You will not be able to tell a change in the numbers from a change in the instrument, and the confusion lasts into the following year.
What to do during the window
Almost nothing measurement-wise. Watch spend pacing and site errors, which are counts and are actionable. Ignore reported ROAS, which is structurally inflated during peak, and ignore causal estimates, which cannot resolve on a few unusual days. The reasoning is in why the gap widens at peak.
Keep a note of what you would have changed and why. Checking those notes against the post-window read is genuinely useful and costs nothing.
The one to diary
The post-window read, in the two weeks after it closes. Put the date in your calendar now, because January is when nobody remembers. The full sequence is in Black Friday measurement deadlines.
Related answers
Frequently asked questions
What can one person set up before peak season?
Check the analytics retention setting, freeze channel grouping and lookback in a dated document, and take a baseline read on an ordinary trading month. All three fit in an afternoon and all three are impossible to do afterwards.Why do I need a baseline read before peak?
Because peak trades strongly for reasons unrelated to your channel mix, so a peak read without a normal-month comparison cannot tell you whether a channel performed because of what you did or because of the season.What should I watch during the window itself?
Spend pacing and site errors, which are counts and are actionable now. Reported ROAS is structurally inflated during peak and causal estimates cannot resolve on a few unusual days, so neither should drive an in-window decision.
Go deeper: Causal attribution, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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Keep reading
Terms in this article
- AnalyticsAnalytics is the systematic computational analysis of data. It reveals customer behavior and measures campaign performance.
- AttributionAttribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive conversions.
- Black FridayBlack Friday is the day after Thanksgiving in the United States. It marks the start of the Christmas shopping season and is a major sales event for retailers.
- Google AnalyticsGoogle Analytics is a web analytics service that tracks and reports website traffic.
- Holdout TestA holdout test is an experiment that keeps a random part of an audience from seeing a campaign and compares its results with those of the part that could see it. The held-out part is the control group, so the gap in outcomes estimates what the campaign added.
- IncrementalityIncrementality is the part of an outcome, such as orders or revenue, that a marketing activity caused: the extra results compared with what would have happened without it. It is a causal effect, not the number of conversions credited to a channel.