Correlation is not causation is the principle that a measured relationship between a factor and ranking can point you toward something worth investigating, but it cannot prove that changing that factor will move your rankings.
| Term | Correlation Is Not Causation |
|---|---|
| Category | Statistics and Evidence |
| Also known as | Association Is Not Causation |
| Where it appears | Strategic report explanations |
What it means in RankGear
Every correlation RankGear reports is measured against the pages currently ranking for your keyword: it observes that pages with more of some factor tend to sit higher, or lower, in that particular result set. The strategic explanations attached to a report carry this caveat deliberately. A strong association tells you the top pages and the factor move together; it does not tell you that the factor is the reason they rank, nor that adding more of it to your page will pull you up. Google’s ranking systems are not visible, and a correlation is a description of what the current results look like — not a lever the algorithm has confirmed.
How to interpret it
Treat a correlation as a lead to test, not a verdict to act on blindly. Weigh it against the sample size behind it — a handful of ranking pages can produce a striking number by chance — and against whether the relationship makes editorial sense for your topic. The most useful correlations are the ones that survive scrutiny: they hold across a reasonable sample, they align with what genuinely helps a reader, and they point at changes you would be comfortable making regardless of the score. When an association is strong but the mechanism is unclear, that is a signal to investigate, not a mandate to match the number.
Example
Suppose a report shows a strong positive correlation between the count of a specific term and higher positions for your keyword. The honest reading is not “stuff that term onto the page and rankings will rise.” It is that the top pages, which are already comprehensive, happen to use that term often. Adding the term to a thin page copies a symptom of quality without the quality itself. The correlation earns its keep when it prompts you to ask why those pages cover the term — and to answer that with real depth.
Important considerations
- Statistical association never establishes causation on its own; a correlation describes the current results, it does not reveal what the ranking algorithm rewards.
- RankGear’s metrics are comparative indicators drawn from the pages ranking now — they are not Google scores, and no factor or metric “makes pages rank.”
- Small SERP samples can be unstable: a strong-looking relationship built on only a few pages may not hold, and re-running the analysis can shift it.
- A correlation can reflect a shared cause — overall page quality often drives several factors at once — so matching one number in isolation rarely reproduces the result.
Related terms
Part of the RankGear glossary · how RankGear measures · the 870 factors.