The most common measurement failure I see isn’t a lack of data. It’s a lack of a baseline. Teams measure intensely after a launch and then compare the result to nothing, or to a number someone remembers from last year.
This is an open, ongoing effort to fix that: a simple, comparable baseline for launch campaigns.
What it records
For every campaign, before the first pitch goes out, I capture four things and freeze them:
- Coverage volume — total items, by tier of outlet.
- Share of voice — mentions against the closest three competitors.
- Sentiment mix — positive / neutral / negative, by the same coding rules every time.
- Message pull-through — using the framework from my related research.
Why a frozen baseline matters
A baseline you can move after the fact isn’t a baseline. It’s a story. Freezing the numbers before the launch removes the temptation to grade on a curve — and it makes the comparison defensible in a boardroom where someone is sceptical of communications spend.
The measurement frame
| Metric | Captured | Owner |
|---|---|---|
| Coverage volume | Pre-launch | Comms lead |
| Share of voice | Pre-launch | Comms lead |
| Sentiment mix | Pre-launch | Analyst |
| Pull-through | Post-launch | Comms lead |
Small enough to run without a dedicated analyst, structured enough to compare across launches.
Status
This is a working effort, refined across campaigns as I go. The coding rules for sentiment are the part most likely to change — they’re the source of most disagreement — and I’m documenting them as edge cases appear so the method stays repeatable for whoever inherits it.