I was having a look at one of my client’s rankings in the Home & Garden sector recently, and I found that although their rankings hadn’t changed *that much* the SERPs had changed completely. Where there were previously small businesses competing with them, this had now been replaced with big name brands. And it occurred to me that brand search or brand must have been a factor in it – I was aware that there had been an update, but it hadn’t “clicked” until I saw this massive change.
If you want an example of what I mean, check out the search “tyres” you will see it has Asda and Tesco tyres, as well as Kwik Fit, ATS and a few other lesser known brands (see screenshot below).
So I decided to do some analysis…
Here’s What I Did
I took the top 32 rankings across 85 keywords in the Home & Garden sector, I then looked up each domain (471 domains in total) and worked out their main brand target term, I then added the local search volume for that. I then used Statwing to analyse the rankings versus the brand search, and what I found was interesting.
Here’s a screenshot of the results from Statwing:
More specifically, rankings negatively correlate with brand search volume, or in plain English: increased brand search volume correlates with better rankings.
Note: Correlation does not mean causation, there is a good chance that this could be being caused by a number of factors, for example higher rankings causing higher brand search volume (although in the case of many of these brands, I don’t think that is the case – Tesco are known for being a supermarket, they haven’t built up their brand from using SEO).
- I only looked at one particular niche of the Home & Garden sector
- For better statistical analysis, I should have taken all the rankings (up to 999), this would likely result in us getting a better idea of how strong a correlation it would be, but I imagine it wouldn’t make a difference to the statistical confidence.
- I used local search volume rather than global search volume – I figured we don’t get US brands ranking, so it would be fair to assume that it’s based on local brand search volume
- I had to determine the most appropriate brand search on my own, so I may have made a mistake here and there, on the whole I think I did a good job
- I used exact match, rather than phrase or broad match search volumes – this may affect things with long tail brand search possibly being a factor
For those of you that are familiar with statistics, here is the “advanced” tab: