Headline factor counts are easy to claim and hard to verify. Most tools publish a number and stop there, which leaves you no way to tell a measured catalogue from a marketing figure. So here is ours, opened up: what the 870 factors are, how they group, how they are measured, and what the shape of the catalogue does not entitle anyone to conclude.
The catalogue in one table: 22 families, 870 factors
Every RankGear factor carries a stable Factor ID of the form RG-XXX-NNN, where the three-letter prefix is its family. Counting the published factor references by prefix gives 22 families totalling exactly 870 — the same figures reported on the methodology page.
| Family | Factor ID prefix | Factors | Share |
|---|---|---|---|
| Structured data — JSON-LD | RG-SCJ | 269 | 30.9% |
| Keyword usage & density | RG-KWD | 101 | 11.6% |
| Search result (SERP) | RG-SRP | 51 | 5.9% |
| Headings | RG-HDG | 51 | 5.9% |
| Structured data — Microdata | RG-SCM | 49 | 5.6% |
| Social links & signals | RG-SOC | 39 | 4.5% |
| Tech & platform | RG-TEC | 34 | 3.9% |
| Affiliate & ads | RG-AFF | 31 | 3.6% |
| Schema.org | RG-SCH | 28 | 3.2% |
| Size & length | RG-SIZ | 25 | 2.9% |
| Structured data — MicroFormat | RG-SCF | 24 | 2.8% |
| Metadata & meta tags | RG-MET | 24 | 2.8% |
| Links on the page | RG-LNK | 24 | 2.8% |
| Backlinks & authority | RG-BLK | 23 | 2.6% |
| Title | RG-TTL | 21 | 2.4% |
| Entities | RG-ENT | 19 | 2.2% |
| Readability & questions | RG-RDB | 16 | 1.8% |
| Related terms (LSI) | RG-LSI | 11 | 1.3% |
| Trust & contact signals | RG-TRS | 10 | 1.1% |
| Page structure | RG-STR | 9 | 1.0% |
| Media & embeds | RG-MED | 8 | 0.9% |
| URL & domain | RG-URL | 3 | 0.3% |
| 22 families | 870 | 100% |
The distribution is uneven by design. The four largest families account for 472 of 870 factors (54.3%), while the smallest, URL & domain, holds 3. Families are grouped by what is being read, not by how much any of it is presumed to matter.
Structured data accounts for 42.5% of the catalogue
Four families measure structured data — JSON-LD (269), Microdata (49), Schema.org (28) and MicroFormat (24) — totalling 370 factors, or 42.5% of everything catalogued. JSON-LD alone is 269 factors, 30.9% of the catalogue and the largest single family by a wide margin.
That weighting follows from what structured data is. A declared @type is either present in the rendered HTML or it is not, which makes it reproducible across runs with no judgment call in the middle. Prose quality resists that kind of measurement; markup does not. The catalogue is therefore densest where the evidence is cleanest, which is a statement about measurability rather than about importance.
58.9% of factors are binary presence checks, not scores
Sorting all 870 factors by how they return a value shows a catalogue built mostly out of yes/no observations:
- Binary presence — 512 factors (58.9%)
- Returns 1 or 0: the pattern is in the rendered page, or it is absent. The single most common measurement in the catalogue.
- Counts and occurrences — 308 factors (35.4%)
- How many times something appears: affiliate links, headings, JSON-LD blocks, keyword variations.
- Rates, sizes and derived values — 50 factors (5.7%)
- Everything else: densities, percentages, byte and character lengths, positional measures, and values computed from other measurements.
Presence and counts together are 94.3% of the catalogue. That is a deliberate trade. Binary and count measurements are stable enough to compare across weeks, which is what makes Diff and Trends able to show one number moving rather than re-deriving a different number each run. A catalogue built mainly from subjective scores could not do that.
Why 856 and not 870 on a standard run
870 is the catalogue; 856 is what a standard run measures. The 14-factor gap is not a rounding artifact or a licence tier. Some factors are minted at runtime and depend on the page set being analyzed, so they exist as definitions in the catalogue but only materialize when the field actually contains what they measure. Reporting the catalogue figure as though every run produced it would overstate what any single run did.
What this distribution does not tell you
Counting factors by family says what RankGear measures. It says nothing about what Google weights, and the two must not be read as the same claim.
JSON-LD holding 30.9% of the catalogue does not mean structured data is 30.9% of ranking. It means structured data decomposes into many separately checkable properties, while a signal like topical authority may be enormously influential and still occupy a handful of factor slots because it resists decomposition. Catalogue share is a measurement-density figure, not an importance ranking.
The same caution governs every correlation RankGear reports. A factor that tracks position strongly across a measured field is evidence about where to look first — not proof that changing it moves a ranking. Correlation is how a backlog gets prioritized, not how an outcome gets promised. That distinction is covered in full in correlation vs causation in SEO.
How to verify every number on this page
Each of the 870 factors has its own reference page stating what it measures, how RankGear measures it, how to read the value, and its caveats. The counts above are the row count of that reference set grouped by Factor ID prefix, so the claim and the evidence are the same object: recount the factor reference and you either reproduce 870 across 22 families or you have found an error worth reporting.
Stable IDs are what make that check durable. A factor keeps its ID across releases, so RG-SCJ-001 refers to the same measurement next quarter as it does today.
Questions, answered
- How many ranking factors does RankGear measure?
- RankGear catalogues 870 factors across 22 families and measures 856 on a standard run. The 14-factor difference is made up of factors minted at runtime that depend on the page set being analyzed.
- What is the largest factor family?
- JSON-LD structured data, at 269 factors — 30.9% of the catalogue. Including Microdata, Schema.org and MicroFormat, structured data totals 370 factors, or 42.5%.
- Does a larger family mean that signal matters more to Google?
- No. Family size reflects how finely a signal can be decomposed into separately checkable measurements, not how heavily any search engine weights it. Catalogue share is a measurement-density figure.
- Are these factors confirmed Google ranking signals?
- No. They are page and result-set properties RankGear measures across the field winning a query, then tests for correlation with position. Correlation supports prioritization; it does not establish causation or guarantee a ranking change.
Method: counts derived on 2026-08-27 from the 870 published RankGear factor references, grouped by the family prefix of each stable Factor ID. Catalogue totals reconcile with the methodology page. Correlation is measured per run against the live field, not asserted from this catalogue.