One of the most common marketing analysis practices is market benchmarking. Let’s suppose your marketing team was 5 percentage points short of fulfilling the plan. If the market during the period in question shrank by 15%, then your marketing team may still have shown a positive result. But if the market grew by the same volume, then your marketing isn’t going so well.
There are a lot of tools for competitor benchmarking. Each of them collects traffic data and processes it differently, however. And you can’t expect 100% accuracy from them. Given that, which tools are sufficiently accurate so you can use the results to perform meaningful analysis?
We conducted some research to find out how precise two popular traffic analyzers — SEMrush Traffic Analytics and SimilarWeb — are. As a baseline for comparison, we used data from Google Analytics accounts of 787 anonymized websites observed by OWOX BI.
Before we share our results, let’s consider how traffic analysis services work.
SimilarWeb uses the following data sources:
SEMrush Traffic Analytics reports are also based on anonymized data gathered from third-party sources and processed with the help of artificial intelligence algorithms. This data is collected and approximated based on anonymized behavioral data on millions of internet users.
Over the last 10 years, SEMrush has launched a few tools that reveal not only data on competitors’ search positions but also what competitors are doing in their paid search, PR, content marketing, and social media along with detailed data on their website traffic. SEMrush uses the most relevant data sources for each marketing sphere (SEO, PPC, content, SMM).
Both SEMrush and SimilarWeb can be used for evaluating competitors, leads, and traffic generated by partners. As we have access to the anonymized Google Analytics data of OWOX BI users, we assumed we had reasonably precise data on visitors for a number of anonymized websites. We then compared data provided by SEMrush and SimilarWeb for those same anonymized websites against the Google Analytics data. Our task was to describe the inaccuracies in particular business spheres and see how large they are for each service.
The data sample
Our sample consisted of data collected from Google Analytics, SEMrush, and SimilarWeb for all sessions in January 2020 on each of 787 websites. These websites are based in Australia, Canada, the US, the UK, and Germany and were grouped by business sphere:
Comparison approach
To find out the accuracy of competitor traffic calculations by SimilarWeb and SEMrush, we merged the following data into one table:
We excluded websites with low traffic that might be caused by filters for properties.
Then we calculated the absolute value of the deviations between data provided by SEMrush and SimilarWeb compared to Google Analytics.
As deviations might be positive or negative and we were interested only in accuracy, we used the absolute value. This also saved us from a potential mistake with calculations in which positive and negative values could result in zero.
Then we segmented our websites by number of sessions per month:
The higher the standard deviation, the larger the inaccuracy in data from the given service as measured against the Google Analytics benchmark. The deviation for SimilarWeb was between 57% and 61% and did not correlate with website traffic volumes. SEMrush data showed a clear tendency: websites with huge amounts of traffic (1,000,000 sessions or more) showed greater accuracy and a smaller deviation (45%) from Google Analytics data.
For websites with 500,000 sessions or more, the numbers were 9 to 12 percentage points more precise in SEMrush. For projects with little traffic, SimilarWeb worked slightly better, but both services demonstrated large inaccuracies among this group of websites.
These differences in accuracy are caused by the collection and processing algorithms of SimilarWeb and SEMrush as well as special aspects of clickstream data. Traffic analysis services use artificial intelligence and machine learning algorithms to approximate data on all website visitors based on clickstream data, which is data on samples of website traffic. Thus, the smaller the website, the less accurate the approximations based on clickstream data.
What should you do if your website and your competitors’ sites have low traffic and the accuracy of your data is extremely low? In this case, you should benchmark against bigger competitors in your market. If you compare some big market players, you’ll see not only their performance but also the general market trends. And by comparing performance and trends revealed by SimilarWeb or SEMrush with your own achievements, you’ll be able to see the efficiency of your marketing.
The graph below describes the share of observations — the percentage of websites within each segment for which SimilarWeb and SEMrush respectively were closer to the Google Analytics benchmark. For example, in the 1,000,000+ sessions segment, SEMrush gave more accurate data than SimilarWeb for 57% of analyzed websites:
By comparing the 100,000 to 500,000 sessions segment in the Standard deviation and Share of Observations graphs, we discover an interesting insight: SEMrush data has a higher standard deviation, which tells us that the session approximations are generally less accurate. At the same time, SEMrush is still more precise in 53% of cases. Long story short, SEMrush makes fewer mistakes but the mistakes it does make tend to be massive.
The accuracy of data depends on a variety of factors:
The next two graphs demonstrate the standard deviation and share of more accurate data from both services segmented by business sphere.
As you can see, the deviation of both SEMrush and SimilarWeb depends on the business sphere:
The percentage of websites for which SimilarWeb and SEMrush were closer to the Google Analytics benchmark also depends on the business sphere:
For example, in the Computers sphere, SimilarWeb was more accurate for 58% of websites and SEMrush was more accurate for 42% of websites (the first column in the graph above).
This dot graph shows the positive and negative deviation values for SEMrush (blue dots) and SimilarWeb (green dots):
Even visually, you can conclude that the lower part of the graph has more green dots, which means that SimilarWeb is more likely to show values lower than the real traffic data from Google Analytics.
We found that:
What’s important to remember is that neither SimilarWeb nor SEMrush will guarantee you 100% accuracy. To analyze your own website data, you have Google Analytics. But SimilarWeb and SEMrush are enough for independently comparing websites and recognizing trends. When using any analytics tool, however, you should understand the origin of the collected data and the deviations of measurements.
SEMrush is primarily focused on SEO and SEM metrics, while SimilarWeb provides insights on audience behavior, traffic sources, and competitors.
SEMrush has a dedicated Keyword Research tool that provides comprehensive data on search volume, keyword difficulty, and competitive density. SimilarWeb, on the other hand, does not offer specific keyword research features.
Both SEMrush and SimilarWeb offer integrations with popular SEO tools like Google Analytics, Google Ads, and Google Search Console, as well as project management tools like Trello, Asana, and Basecamp.