The need I feel—the fruit of many years working in this field—is to affirm the decisive importance of basic scientific rigour in analysing traffic data, so that we can calibrate our SEO interventions with accuracy, and not merely “by gut feeling” (even though feelings do matter!).
The tools available to the SEO professional are countless, and yet it is undeniable that a sense of disappointment lingers within us. Too often we deal with data of apparent strategic importance that turn out, when put to the test, to be fallacious or imprecise—mere red herrings.
Raise your hand if you have never felt a sense of frustration using any—truly any—competitive analysis tool, to give a concrete example.
Wittgenstein stated that whereof one cannot speak, thereof one must be silent.
Too often we draw conclusions based on utterly unreliable data. The trap represented by eye-catching graphs, conclusions just a click away, special effects—it is always with us. The tool that serves up the ready-made analysis we need, ready to use, simply does not exist.
Too often SEO is treated by its practitioners not so much as an art (that would be useful and is even necessary, though not sufficient) but as a sort of bag of tricks for apprentice storytellers, or as a stage for conjuring acts based on evanescent numbers. A sum of a few SEO tools and report templates good for every occasion. Or sometimes shamanistic practices combined into miracle recipes.
Back to statistics. SEO is obviously not just statistics, but it rests on numbers. Basic statistics, to begin with. The ABCs of descriptive statistics.
Let us examine what the only solid data we have tell us—the data that come from our own sites. Not sampled data, not data derived from presumed traffic based on average positions in search engine indices, without clinging to fanciful correlations presented as certainties on the basis of r values close to 0…
Our data. Let us look at what our data tell us.
Sometimes it seems that reasoning in “simple” terms—median and five-number summary—boxplots and histograms, hypothesis testing and moving averages—is reductive. Other times I meet professionals who consider even a basic grounding in statistics superfluous, ignoring the fact that statistics has a fundamental, irreplaceable virtue: it makes us sceptical, and exceedingly doubtful.
We know little, in truth. Little can be understood by looking at numbers generated mostly by what an algorithm—unknown in composition and in how its variables are weighted—compresses into positions in an index. That little, however, must be reasonably supported by data and by common sense.
The rest is art, precisely. Intuition, experience, and more. Only by tracing the boundaries between what is reasonably (statistically) expressed by the data in our possession and what our experience suggests can the insight, the decisive experiment, emerge.
Only in this way, I believe, can we provide a service of genuine value.
SEO is an intrinsically treacherous subject. Approaching it requires experience, a certain dose of courage, and a necessary sense of one’s own limits.
You might also like
- The Data: The 4 Scales of Measurement
- Descriptive Statistics: Measures of Position
- Guide to Statistical Tests for A/B Analysis
Further Reading
For a brilliant, accessible exploration of why statistical thinking matters—and how it protects us from misleading data—The Art of Statistics by David Spiegelhalter shows how to reason clearly with numbers in a world full of uncertainty.