Dimension Widening USE-CASE: Integrate Your Off-Page SEO Data Into Universal Analytics

(You are reading part 3 of a three post series on Dimension Widening USE-CASE.  We also recommend you to read part 1 & part 2 in the series)

One of the interesting features of Universal Analytics is Dimension Widening.

Universal AnalyticsAs Ravi spoke about it during an Interview at Superweek, Dimension Widening can open floodgates of having interesting data integration into Google Analytics. Using Dimension Widening one can easily import data sets into Google Analytics.

Today, I will show you how to integrate various Off-Page SEO factors into Google Analytics and generate insights. If you are new here, please review part-1 of this blogpost to understand what is dimension widening & part-2 of the post to learn how to integrate you On-Page SEO factors into Google Analytics.nalytics and add value to their existing data.

SEO Off-Page Data Integration with Google Analytics

Both on-page and offpage data plays an important role in the success of online business. Off-page SEO refers to your website’s overall authority on the web determined by what other websites say about your site. Off-page optimization is a long-term process and takes time to improve.

Off-page optimization efforts are not visible on the website itself but does the backend work for a better search result.

Important factors taken into consideration for this use-case are:

  • Page Rank: It is assigned as a number or rank to each hyperlinked web page online. The basic purpose of PageRank is to list web pages as per its importance. This will reflects on a search engine results page when any search occurs.

  • Page Authority: It is a metric for how well a given webpage is likely to rank in Google search results. It is based on the relevance of information and links within your site pages. If you have a higher page authority,  there is more chances of your page showing up on search engines.

  • Backlinks: A link from an external page (with different domain) that refers to your website are know as backlinks. Backlinks tells search engines about the popularity of your website.

  • Referring domains: is a domain from which a backlink is pointing to a page or link.

  • Citation flow: Citation flow metrics judge how influential a website is by the number of third party sites linked into it. A high number of inbound links determines that the website is a trusted source. It is a number of predicting how popular a URL might be based on how many sites are linked to it.

  • Trust flow: Trust flow is a number predicting how trustworthy a page is based on how trustworthy sites tend to link to trustworthy neighbors.

Now let us see how to import Off-Page data into Google Analytics.

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Steps to Integrate Your Off-Page SEO Data into Google Analytics

  1. Extracting SEO data

    To get the SEO off page data, you can use any SEO tool that provides all the above mentioned off-page data points. We used seoClarity to generate the off page SEO data. Now create a csv with all these data points.

  2. Create Custom dimensions

    All the above mentioned off-page factors are not available in Google Analytics, so we need to create custom dimensions for each of them.

    Creating Custom Dimension: Page Rank Creating Custom Dimension: Page Authority

    The above image shows two offpage data points. We need to create such custom dimensions for all of the data-points.
    Once the custom dimensions are created, use the same naming conventions which GA provides in the CSV prepared in the first step. For example  “ga:dimension15” for “Page Rank”. Now you might be wondering that why these data points are to be entered as custom dimensions rather that custom metrics. It so happens that all these data-points are in the form of integer values which means they should be set as  custom metrics in Google Analytics. But, when we were in process of implementing this use-case, we found that if the data points are created as custom metrics in GA on hit level, the metrics is multiplied with the number of pageviews. This leads to incorrect numbers of the on-page factors. To solve this problem, we have used custom dimensions instead of custom metrics for all these data points.

  3. Create and upload the data set

    The steps for creating and uploading this data in Google Analytics and creating data set are explained in my previous blog.
    While creating the data set, make sure you make ga:pagePath as the dimension key and all the other factors as custom dimensions .  Below image shows the custom dimensions created for this use case.

    List of custom dimension created for the Dimension Widening USE-CASE

  1. View data in custom Reports

    Below is the custom reports which shows the off page factor – Trust Flow along with the page.

Custom report showing pagepath and trust flow for the Off-Page Dimension Widening USE-CASE

Full Report :

Full report showing pagepath along with all the custom dimensions for the Off-Page Dimension Widening USE-CASE

You can also create a similar full on-page report using data feed query explorer

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Insight from the Use-Case

To generate insights we carried out couple of analysis to prove some already well known facts.

1)  High Trust Flow & High Citation Flow equates with High Number of Pageviews (filtered by search traffic)

We carried out an analysis on a small sample data and found that the number of page views (filtered by search traffic) increased with the increase in Trust Flow (TF) & Citation Flow (CF) of the page. The analysis proved that a high TF and CF (indicates a good backlink profile) and helps in performing better in search engine.

We plotted a bubble graph between trust flow, citation flow and pageviews from the google analytics data to explore the relationship between them and it looked as shown below:

Bubble graph showing relationship between citation flow, trust flow and pageviews from Dimension Widening USE-CASE

From the graph, we were able to infer that the size of the bubble (i.e. pageviews) does have a relationship between trust flow and citation flow. If we see the last two bubbles (780 & 551) and first three bubbles (161, 177. 189) it shows that Pageviews increased with increase in Citation Flow and Trust Flow.

 2) High Backlinks Does Not Necessarily Mean High rankings

Second analysis we carried was to check the relationship between Organic searches and Backlinks for a given page. And what we discovered was not something new:-

Line graph showing relationship between backlinks and pageviews in Off-Page Dimension Widening USE-CASE

We discovered that there was least co-relation between no. of backlinks point to a page compared to its pageviews. It was clear from the above graph, that high number of backlinks does not indicate that you will rank high in search engine and will receive high organic searches.

Conclusion:

In the following blogpost, we learned how to use Dimension Widening Feature of Universal Analytics to import the Off-Page SEO factors into Google Analytics and carried out analysis to generate insights.

I hope that the blogpost inspires you in using the Universal Analytics Dimension Widening Feature and helps you in understanding the relationship between various off page factors. If you have any questions or feedback, feel free to reach me out on bhoomika(at)tatvic.com or Twitter

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(You just completed reading part 3 of a three post series on Dimension Widening USE-CASE. We also recommend you to read part 1 & part 2 in the series)

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Yaman Patel

Yaman Patel

Yaman Patel is Solution Consultant guiding Organization in Marketing Analytics Usecases. He is focused towards solving genuine problems in MarTech Space. Being a Developer by heart, He is one of the proud pioneers of Tatvic's dataLayer automation tool(DLAT). He is keen on learning business intelligence technologies.He loves to travel and explore new places.
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