Continuous reads let you test more often
Once a read costs nothing, the bottleneck stops being measurement and starts being design. What to do with the cycles that frees up.
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By Joris van Huët, Founder & CEOUpdated 3 min read
When a read costs an afternoon, you test quarterly. When it costs nothing, the constraint moves to experimental design, which is a much better place for it to sit. The extra cycles only pay off if you spend them on structure rather than on looking.
What changes at each cadence
| Cadence | Tests per year | What you can learn |
|---|---|---|
| Quarterly | Three or four | Whether a large structural change worked |
| Monthly | Ten to twelve | Per-channel behaviour across a season |
| Fortnightly | Twenty or more | Limited by purchase cycle, not by measurement |
The bottom row has a ceiling that is not about tooling.
Find your own repeat interval in your order data and set the cadence from it rather than from what the pipeline can do.
How to spend the extra cycles
One change per cycle, held for a full window, with the prediction written down before the data arrives. That is the entire method, and it converts spend into evidence rather than into activity. The mechanics are in the attribution loop.
Rotate which channel you move. Over a year that gives you a per-channel history of deliberate changes and their outcomes, which is worth considerably more than twelve reads of an unchanging business.
The trap of looking more often
More frequent reading with unchanged spend produces a series that moves for statistical reasons and tempts a reaction to each move. That is the failure described in the cost of reacting to attribution noise.
The rule that prevents it: if you did not change anything, the read is a confirmation, not a signal. Note it and move on.
What a year of this looks like
Twelve reads, ten deliberate changes, ten written predictions, and a retrospective in December comparing predictions against outcomes. That retrospective is the single most useful marketing document a DTC brand can produce, and it is impossible without the cadence.
Where the tiers sit
The €99 one-time read on a Google Analytics export is the way to see whether the output supports the loop, refundable within 30 days, no questions asked.
The honest ceiling
None of this makes an observational read into a test. It makes it cheap enough to run alongside real tests, which is its correct role: triage that tells you where to spend a geo holdout. The comparison is in incremental ROAS without a geo test.
Related answers
Frequently asked questions
How often should I read attribution?
Set the cadence from your purchase cycle rather than from what the pipeline can do.What should I do with more frequent reads?
One deliberate change per cycle, held for a full window, with the prediction written down first, rotating which channel you move. That builds a per-channel history of changes and outcomes rather than twelve reads of an unchanging business.Is there a downside to reading more often?
Yes, if spend is unchanged. The series will move for statistical reasons and tempt a reaction to each move. The rule that prevents it: if you changed nothing, the read is a confirmation rather than a signal.
Go deeper: Causal attribution, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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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.
- Google AnalyticsGoogle Analytics is a web analytics service that tracks and reports website traffic.
- 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.