Google Maps Profile Completeness Score: 2026 Study
“Profile completeness” is often discussed as if it were one universal metric. It is not. Google does not publish the score used in this article, and this is not a Google ranking factor. It is a transparent diagnostic we created to compare the observable contact and trust fields available in a 3,147-listing dataset.
The result: the average was 88.2 out of 100, and 1,787 records—56.8%—received all 100 available points. The useful insight is not the average itself; it is which field is missing and what that prevents a customer or researcher from doing.
The six-field formula
| Field | Points | Why it matters |
|---|---|---|
| Phone present | 25 | Enables direct business contact |
| Website link present | 25 | Adds context and an asynchronous destination |
| Positive rating | 15 | Shows an observable rating signal |
| At least one review | 15 | Shows recorded review activity |
| Category present | 10 | Supports relevance and segmentation |
| Coordinates present | 10 | Supports location and territory checks |
The formula rewards presence, not correctness. An outdated phone still receives 25 points; a website redirect still receives 25; an overly broad category still receives 10. That is why the score must be followed by verification rather than used as a final quality label.
Distribution across 3,147 records
| Score | Records | Interpretation |
|---|---|---|
| 100 | 1,787 | All six observed signals present |
| 85 | 436 | Commonly missing review activity |
| 75 | 605 | Commonly missing website link |
| 70 | 22 | Multiple field gap |
| 60 | 115 | Multiple field gap |
| 50 | 103 | Low contact/trust coverage |
| 45 | 34 | Low coverage |
| 35 | 19 | Very limited coverage |
| 20 | 26 | Category and coordinates only |
The top three scores account for 2,828 records, or 89.9% of the sample. The remaining 319 records scored below 75.
You can reproduce the field counts from the country aggregate CSV and category aggregate CSV. Individual records are not republished.
What the score can tell you
For a business owner, it is a checklist: can a customer call, learn more, see activity and confirm the location? For a data buyer, it is a source-quality diagnostic: which fields are consistently returned, and which are absent in a target segment?
For prospecting, the missing field can be more useful than the total:
- Missing website link: potential phone-first segment; see the website-gap study.
- Missing phone: requires website research or another published business channel.
- No reviews: do not assume inactivity; verify listing age and category norms.
- Missing both phone and website: manual-verification queue, not an outreach queue.
Two listings can both score 75 for different reasons and require completely different next actions. Store the component flags alongside the total.
What the score cannot tell you
This compact dataset does not include all fields that matter to a real Business Profile audit. The score does not assess:
- Opening hours or holiday hours.
- Photos, products, services or menu links.
- Description quality or category precision.
- Whether the owner verified the profile.
- Duplicate or suspended profiles.
- Website performance, security or conversion quality.
- Phone validity, consent or response rate.
- Local-search rank.
It also does not prove that adding a field causes better ranking. Google’s guidelines for representing a business should guide profile accuracy; this editorial score is only a way to organize a field audit.
Use a score without gaming it
A good workflow is:
- Calculate component flags from the raw export.
- Use the total to sort, not to judge.
- Open a sample of high and low scores for manual verification.
- Track errors separately from missing fields.
- Recalculate after a defined refresh interval.
- Report the sample, collection date and formula whenever you publish an average.
Avoid silently changing the formula between markets. If phone is irrelevant to a specific use case, create a named variant rather than moving its points without documentation.
Methodology and sample bias
The source snapshot was generated May 2, 2026 from completed BasedOnBusiness tasks during roughly the prior three days. It covers 3,147 records in 20 countries and 58 cities, dominated by dental and restaurant searches. It is not random or population-weighted.
Every record included a category and coordinates, so those 20 points do not differentiate this particular sample. They remain in the formula because their absence would matter in another source. Ratings and reviews are volatile; the values describe the collection window only.
For a broader view of the fields, read the digital presence study. To audit your own export, use the lead-list quality scorecard.