Posted by
Mordy Oberstein
Everyone, on whatever level, knows that marketing data analysis is important. We, in the SEO and digital marketing industry, are cognizant of this reality all the more so. However, not all data is equal, both quantitatively as well as qualitatively. Data is not merely the acquisition of statistical information. While obtaining such numbers and figures are important, it lacks the qualitative depth data can afford. In its essence, data helps paint a picture of health and performance, it is ironically holistic in nature. The question is how can rich data be accessed? How do we take data from being a linear experience to a holistic one that paints an overall performance picture? The answer is cross source data analysis.
Moving Beyond One Data Source
Moving beyond one source of data can give your data analysis a broader, more in-depth potency. In any data-set, there are various segments and dissections that can give you an understanding of your performance. The problem is, such data is relegated to one source and only to that source. How that data interacts with other data, how that data fits into a larger picture isn’t accessible when looking solely at one data-set. What I am going to show you here is how observing the ways different data-sets interact with each other offers a fuller and more complete picture, what I’ll call a holistic performance picture.
Cross Source Data to Compare Performance
One of the most foundational ways to use cross source data is to measure performance across different related mediums and platforms. In other words, when you are trying to do the same thing, just in different places, seeing both sets of data together can be both telling and powerful. To illustrate this point (and the others I will soon make) I’m going to employ our Insight Graph which has the ability to plot various data sets on the same graph.
Let’s begin with a simple straightforward case. Say your client is running both AdWords and Bing Ads campaigns, it would be powerful to show the performance in each, at once. If you really want to get a complete picture of where your best value is, you would be well served by comparing both sets of data at once. This is especially in consideration of the amount of time and manpower that goes into endeavors like PPC campaigns. Along these lines, if you see similar or even inverse trends across the two platforms, that could very well be relevant and insightful information.
The Insight Graph displaying a side-by-side data view of Bing Ads and AdWords data
The same could be done when it comes to the traffic to your site per se. Being able to compare traffic across various search engines not only tells you how you are performing but where you need improvement and if such efforts are even worth the time and money. The point is, being able to compare analogous data from multiple channels simultaneously is immensely valuable when it comes to qualifying performance. Seeing the similarities and differences in the data from analogous, yet separate data channels (i.e. AdWords vs. Bing Ads, or Google search vs. Yahoo search, etc.), is an important part in qualifying and understanding the effectiveness of your practices overall.
Cross Source Data to Understand Correlations
Another major benefit of looking at cross source data is the ability to understand correlations between various data-sets. In fact, I would go so far as to say that this may be the most substantial benefit cross source data analysis may offer. Combining two unique sets of metrics from two data sources can give you a glimpse into how various aspects of your SEO or marketing plans are coming together.
Think about it for a second, the most basic of all SEO data is rank. However is rank really the end goal? Of course not, you want rank to deliver traffic to your site, which you hope ends in some sort of goal completion. For an SEO, this is the ultimate correlation of data from various data sources. Seeing these correlations is vital to your success. If your rank is up, but your traffic is down, then there’s a disconnect that needs to be rectified. If the inverse is true, think about how much more potent your traffic and conversions could be if your rankings were higher.
A cross source data correlation between rank, organic traffic, and new user goal completion
For those times where you’ve undertaken various initiatives, seeing the payoff may depend on your ability to see data from various sources at once. For example, you’ve gone ahead and optimized everything you can for placement in Google’s Featured Snippets (which is quite the rage these days). Wouldn’t you want to know if there is a correlation to the Featured Snippet optimization you just undertook and your site’s traffic? Combining the prevalence of the Google SERP feature on a chart that indicates your organic traffic, could help you to know if the hours you spent on optimization had any impact, or if you may want to spend your time on other priorities.
A significant spike in Featured Snippet trends on mobile shows no true correlation with a specific site’s mobile traffic per the Insight Graph
Specific instances aside, being able to see data from various data sources at once, can prove invaluable in understanding the correlations between your multifaceted SEO and marketing undertakings.
Cross Source Data to Fill Information Gaps
Moving beyond showing correlations, cross source data can help fill in the missing data needed to create a whole and complete picture. That is, the data you have from any one source may only be a part of the picture. The clearest example of this is the separation of Google Search Console and Google Analytics. So you’re showing up on the SERP often enough, but how does that translate into conversions? Combining data from Search Console and Analytics can help you to qualify the importance of the metrics within each data source to your business operations.
Search Console data reunited with Google Analytic data showing the impact of SERP impression on goal conversion
Without data from multiple sources, it can be difficult to qualify the figures before you are saying. Should for example I know that a lot of my site’s traffic is from social media, that may not be enough for me. If I have limited time and limited resources (who doesn’t), I need to know where to focus my efforts. Where is my time best spent, Facebook, Twitter, etc.? If I can combine various data sets, if I can see my social traffic, the number of users liking my Facebook page, all while seeing how many favorites I’m garnering on Twitter, I may be able to determine which social source is most valuable to me, and where I should spend the bulk of time and effort. I can see which platform is having an impact on my site’s traffic.
Cross source data indicating a site’s social traffic being more strongly correlated to Twitter than Facebook performance
Again, there are endless variations of how seeing multiple data source figures can be vital in determining courses of action and in evaluating performance. The important takeaway are not the specifics I’ve outlined here, but how rich the concept of cross source data viewing really is.
Cross Source Data – A Whole New World
What I’ve presented here are just a few general ways you can capitalize on what cross source data has to offer. In fact, my intent was not to overwhelm you with intricate ways in which one minute metric can be plotted against another such intricacy from another data source. Rather, my aim was to highlight just how foundational cross source data analysis is (which is why we’ve integrated third party data sources such as Bing Ads, Bing Webmaster Tools, CallTrackingMetrics, Google Analytics, Google Search Console, Google Drive, Social Analytics, Yext, etc., into a blended metric graph). Really, the possibilities are endless and that’s sort of the point… utilizing cross source data can open up new worlds of data analysis. It opens up a rich world of holistic data where you can determine real performance impact that reflects real-world value that exists outside of a particular data category.
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