Surevisible vs the monthly spreadsheet
The spreadsheet works. It works for one afternoon a month, forever, and it stops being reproducible the moment the person who built it is on holiday.
The problem
A spreadsheet is the honest incumbent for most portfolios, and its real cost is not the afternoon. It is that nobody can reproduce a number in it three months later, and that the reconciliation of definitions happens in someone's head.
What we mean
The same reconciliation, done once at ingest and written down as a schema. The afternoon disappears and, more importantly, so does the un-auditable step in the middle.
Honestly
What each one is actually better at
A spreadsheet wins on
- Infinitely flexible: any calculation you can think of
- Everyone already knows how to use one
- Free, and works offline
- Perfect when the analysis is genuinely one-off
Surevisible wins on
- Reproducible: every number traces to a query
- Definitions applied once, not re-remembered monthly
- Revisions from Google land automatically
- The afternoon goes away
The verdict
For a genuinely one-off analysis, use a spreadsheet. For the same analysis every month, the spreadsheet is a job description.
In practice
What changes
- 01
No exports
The data is already in one place.
- 02
No manual joins
Done at ingest.
- 03
No stale copies
Charts are live queries.
- 04
Still exportable
When you do need a document.
With A spreadsheet
An afternoon of exports and paste.
With Surevisible
The boards were already current.
With A spreadsheet
Nobody can say which filters produced it.
With Surevisible
Open the chart and read the query.
1 afternoon
per month, returned
The recurring part of the spreadsheet stops recurring. The one-off part stays in the spreadsheet, where it belongs.
Other comparisons
vs GA4
Keep GA4. Add Surevisible when the question stops being about one property.
vs Looker Studio
If you already have someone who maintains the blends and enjoys it, Looker Studio is free and flexible. If that person is you and you would rather not, this removes the job.
vs a BI stack
If you need marketing data joined to revenue, build the stack. If you need marketing data to be consistent across brands, this is that, without the quarter.
vs a generic AI chat
A general chatbot is a good analyst on data you have already verified. The verification is the part this replaces.
See the whole brand
Search, analytics, ads, revenue, CRM and support, pulled into one view per brand and kept current. Connect the first source in a few minutes.