What is a Digital Visibility Score?
A Digital Visibility Score is a 0–100 measure of how findable a business is online, calculated from six weighted groups of publicly observable signals and published alongside every one of its inputs.
It is the headline figure in every Local Digital Visibility Index. This page defines the term; the methodology sets out the rules in full.
Every figure below is computed from the published datasets when this page is built, so the definition cannot drift from the thing it defines.
What it measures
Section titled “What it measures”Whether a business can be found by someone looking for what it sells, and whether what they find is worth arriving at.
That is narrower than it sounds, and the narrowness is the point. It is not a measure of the business, its work, its staff or its customers. It is a measure of six things about its digital presence that anyone can check from outside, without access to its analytics, its accounts or its Search Console.
The scale
Section titled “The scale”Nobody scores above 93. 46 of 1371 reach 75. A score is hard to get because it requires being findable as well as technically sound.
The score runs 0–100. Across 1371 businesses in 34 indices the median is 51, half fall between 45 and 58, and the highest anyone has scored is 93.
Read a single number against that spread rather than against 100. A 51 is not a failing grade — it is the middle of the measured population. 595 of 1371 businesses score below 50.
How it is calculated
Section titled “How it is calculated”Six pillars, each scored 0–100 on its own, then combined by fixed weights:
| Pillar | Weight | Current median | What it asks |
|---|---|---|---|
| Speed & CWV | 20% | 64 | Core Web Vitals and load performance on mobile. |
| Technical | 20% | 88 | Crawlability, indexation, structured data and duplication. |
| Local presence | 20% | 76 | Google Business Profile completeness, reviews and map coverage. |
| Visibility | 15% | 4 | Organic ranking across the sector keyword set. |
| AI search presence | 15% | 0 | Whether AI answer engines cite the business by name. |
| Content & trust | 10% | 49 | Depth, credentials and citation-worthiness of the site. |
The arithmetic is deliberately plain: ratios, weighted sums and a clamp to 0–100. No model, no judgement and no proprietary step sits between the raw signals and the published number, which is what makes it reproducible by someone who does not trust us.
When a pillar cannot be measured
Section titled “When a pillar cannot be measured”If a signal genuinely cannot be read — a site that blocks crawlers, a business with no Google profile — that pillar is excluded from the score and the remaining weights are renormalised. It is never scored as zero.
This matters more than it sounds. Scoring an unmeasurable pillar as zero would punish a business for our inability to see it, and would make a missing measurement indistinguishable from a genuine failure. 207 of 1371 businesses currently have at least one pillar excluded, and each scorecard names which. A score built on five pillars is ranked against scores built on six, so read those with the caution the scorecard flags.
What the number does not mean
Section titled “What the number does not mean”Six things it is routinely taken to mean, and does not:
- It is not a measure of the business. A superb builder with a neglected website scores badly. That is a fact about the website.
- It is not revenue, leads or customers. Nothing here observes a transaction. A firm that gets all its work by referral can score 20 and be thriving.
- It is not a Google ranking. Ranking for a fixed keyword basket is one pillar of six, worth 15%.
- It is not comparable across sectors without care. Cohorts differ in ways the score does not fully adjust for — review culture varies enormously by trade, for one. The cross-index comparison sets out how much trade and town actually explain.
- It is not a permanent property. It is true on the measurement date printed on every page and no other.
- It is not an opinion we can be persuaded to change. It can only be changed by the inputs changing, or by us finding a fault in how they were read — which happens, and is logged publicly when it does.
Who calculates it
Section titled “Who calculates it”PYC, an SEO consultancy. That is a conflict of interest worth stating plainly rather than burying: we publish a league table in a field we sell services in.
The defence is not that we are trustworthy. It is that you do not have to trust us: the data is open under CC BY, the pipeline is open source, the method is published, and every correction — including the ones that made our own method look careless — is dated in public. We have also published a finding that our own weighting is probably wrong, which is not something a marketing exercise does.
Reproducing a score
Section titled “Reproducing a score”Every published figure can be recomputed from the open dataset:
collect.mjs → score.mjs → backfill-enrichment.mjs --with-paid → generate.mjsEach quarter’s snapshot is tagged in the repository, and superseded datasets are kept alongside corrected ones so a figure cited last month remains checkable. If you recompute a score and get a different answer, that is a bug in our work and we would like to hear about it.
Citing it
Section titled “Citing it”Digital Visibility Score: a 0–100 measure of how findable a local business is online, built from six weighted pillars of publicly observable signals. PYC Local Digital Visibility Index, Q3-2026. https://hub.pyc.agency/indices/ · CC BY 4.0