Content Marketing: Reliable Assessment of Content Performance on Social Networks

 

Sincere thanks to Tim Bayer and Stephen Davies, whose collaboration and expertise made this piece possible. Content marketing is hard; data-driven analysis of sharing activity makes it easier. Online content is now a multi-billion dollar industry. One recent example: in August, NBCUniversal invested $200M in Buzzfeed, whose founder and CEO Jonah Peretti had previously discussed (in a 2014 interview) the ways his company uses data science to analyse and improve content. When developing content, keep in mind that compelling content is designed to be shared. Content can be shared directly (using an embedded “share this with your friend” button) or indirectly (using a permalink or other copyable URL). Good content, when widely shared, can be a terrific tool for driving traffic to your main site or platform. Social shares validate the quality of your content. People often share content that reflects their personal beliefs, preferences, lifestyle, etc. On indicator of effective messaging is that members of your target audience feel your content is worth sharing within their social network. Several content tracking solutions offer insight about which pieces of content are shared, where they are shared, and which ones are the best is the drivers of site traffic. SharedCount’s Full Picture SharedCount helps content producers understand where a blog post, article, photo or video has been shared since its original publication. SharedCount tracks which social networks viewers have chosen to share your content with their friends or followers. Though not completely free, this solution is adequate if used on a small scale.

Sincere thanks to Tim Bayer and Stephen Davies, whose collaboration and expertise made this piece possible.

Content marketing is hard; data-driven analysis of sharing activity makes it easier.

Online content is now a multi-billion dollar industry. One recent example: in August, NBCUniversal invested $200M in Buzzfeed, whose founder and CEO Jonah Peretti had previously discussed (in a 2014 interview) the ways his company uses data science to analyse and improve content.

When developing content, keep in mind that compelling content is designed to be shared. Content can be shared directly (using an embedded “share this with your friend” button) or indirectly (using a permalink or other copyable URL). Good content, when widely shared, can be a terrific tool for driving traffic to your main site or platform.

Social shares validate the quality of your content. People often share content that reflects their personal beliefs, preferences, lifestyle, etc. On indicator of effective messaging is that members of your target audience feel your content is worth sharing within their social network.

Several content tracking solutions offer insight about which pieces of content are shared, where they are shared, and which ones are the best is the drivers of site traffic.

SharedCount’s Full Picture

SharedCount helps content producers understand where a blog post, article, photo or video has been shared since its original publication. SharedCount tracks which social networks viewers have chosen to share your content with their friends or followers. Though not completely free, this solution is adequate if used on a small scale.

Google Analytics also provides useful reports that allow you to track referral via social networks. There are caveats, however, and several existing articles discuss how best to track social referrals (e.g. here, by Megalytic or here, by Kissmetrics). In our example, using our own content, we’ll assume that we are tracking properly with the right Google Analytics parameters. We’ll cover in a separate blog post methods for optimizing tagging and reporting on social media traffic.

For the two pieces of content we tagged, Google Analytics provided us with the following referrals volume report:

The key to understanding Google Analytics and SharedCount is to compare Referral Rate with Number of Shares

A bit of relabeling and some basic Excel analysis depicts a different story.

For a particular piece of content shared on particular social network, the Referral Rate is defined as the ratio of number of sessions to number of shares. This simple ratio measures the efficiency with which the content is driving traffic back to your site.

 

My blog post “Great Digital Announcement” was shared frequently on both Twitter and LinkedIn but less so on Facebook. However, Facebook was still the main driver of traffic back to our site.

In contrast, my blog post “Digital Transformation in FinTech” was shared on Twitter three times less often. However, in this case Twitter was the chief driver of traffic.

For both blog posts, LinkedIn was used for a large number of share, but this sharing activity generated only a tiny stream of referral traffic.

 

 

Large-Scale Possibilities

Using proper taxonomy for tagging each piece of a large amount of content can be a powerful tool. Subdivision of complex content according to theme, content category, top keywords, dates of publication, etc. can allow large-scale analysis. With enough history and variety of content “slices”, one can very quickly understand which piece of content works on which social network. Comparison of number of shares vs. referral rate offers useful insights about which content is best for which channel.

 

Latest Update

On 8 September 2015Steve Rayson published an interesting long study on content marketing and the relationship between shares and links. The article, titled "Content, Shares, and Links: Insights from Analyzing 1 Million Articles" is well written and complements our own findings.

On 28 September 2015, I performed some minor edits on this piece, based on readers’ feedback who caught some misspelling and/or who thought some of the explanations were not that clear.