My Google Business Profile is new, and a new profile’s numbers grow by themselves as Google learns about it. A simple before-and-after test would look like a win even if posting did nothing. So this test is designed to avoid that.
The plan, fixed before any data
| Phase | Dates (inclusive) | What happens |
|---|---|---|
| Settling | 29 Sep – 26 Oct 2026 | No posts, no edits. Numbers are not analysed. |
| A1 | 27 Oct – 9 Nov | No posts. |
| B1 | 10 Nov – 23 Nov | One post a week. |
| A2 | 24 Nov – 7 Dec | No posts. |
| B2 | 8 Dec – 21 Dec | One post a week. |
What counts as a win
Profile views in the posting weeks are at least 1.5 times the no-post weeks around them, in both posting phases. B1 is compared with the average of A1 and A2, and B2 with A2. If the profile gets fewer than 20 views in any measured week, the result is “inconclusive, too little data”, not a win. Website clicks are a supporting check: if they are too few to compare (under 5 a week), only views decide the result.
What I measure
Weekly profile views, website clicks, calls and messages from the Performance page of my Google Business Profile, one exact week at a time. Google’s data can lag by a few days, so the earliest honest result is about 27 December 2026. Website clicks are also checked in Google Analytics through a tracked link on my profile’s website button.
What can muddy the result
- I plan to start paid Facebook and Instagram ads during the test window. If they start, I log the date, and any change around then is reported as “coincides with”, not “caused by”.
- My other marketing work, which may send people to the profile.
- Me searching for my own profile. I don’t.
- This Lab page itself, which may send people to the profile.
- New customer reviews or photos, and any edits Google makes on its own. Each is logged with its date.
Rules I set on myself
The name, categories, service areas, hours, description, services, phone number, website link and my own photos don’t change until the test ends. If the result is null, I publish it as a null result. Why a null result is plausible: Sterling Sky, a local-SEO agency, tested Google posts and found no measurable effect on rankings. That test looked at rankings, not views, but it is a reason to stay sceptical.