Measuring Social Media Impact with Web Analytics

Cardinal Path articleMeasuring the impact of social media on your bottom line is one of the most pressing challenges that marketers have when they first dive into their data. Without clear social media goals and KPIs, analysts find themselves spending hours in front of the screen scratching their heads and asking “where do I start?”

Today, we will take a deep dive into our analytics reports and look at how we can slice and dice our data to get more value out of our social media. But first, let’s get a few definitions out of the way so we know how we classify our traffic.

Defining Social Media Variables

Social Networking – sites where individuals can share, comment and converse about stories (Facebook, LinkedIn, Google Plus, etc.)

Social News – sites where news articles are published and shareable with peers (Twitter, Reddit, Digg, etc.)

Social Reviews – sites where individuals can leave reviews about your business (Yelp, UrbanSpoon, Amazon etc.)

Social Bookmarking – sites that allow users to organize, store and manage bookmarks on the web (StumbleUpon, Delicious)

Social Media Sharing – sites that allow users to share media content (YouTube, Pinterest, Slideshare, etc.)

Social Knowledge – sites that have a purpose for collaboration on projects (Wikipedia)

Guest and Partner Blogs – sites that your organization has a direct relationship for sharing content via guest blogging

When we have a clear cut definition for each of our categories, we can now assign each social site to their respectful group.

Social Media Advanced Segments With Google Analytics

Segmenting social media traffic is like dividing up Smarties with your friends by color. Each have a similar characteristic (the color), but the things that differentiate them are things that we find out later (taste). This is concept is the same with social media sites, which may not be as apparent to start, but gradually you will understand their similarities and differences.

For example, here’s a screenshot from Google Analytics taken with four of our social media groupings turned on (learn how to do it):

Social Analytics

What does this tell us? Social News and Guest and Partner Blogs bring in the greater chunk of traffic from all social media sites. On May 7, there was an article that hit the Social News sites and took off; people had the urge to click through to read the full article.

If we looked at how people are spending their time on the site, we get the following:

Social Metrics

What does this tell us? Guest and Partner Blogs bring in the highest quality of traffic (2.53 pages per visit and only 44% of them bounce compared to 72% for social news).

Grouping Social Media Traffic – The Possibilities Are Endless

Most of the time, people discover you through an article that was shared by someone they follow. They read the article and leave. Later, they decide to visit your site again and sign up for a course because of the trust they saw in your brand. We can’t attribute this back to the social media site… or can we? Multi-channel funnels in Google Analytics make this possible, as well as Marketing Channels in Site Catalyst.

Similar to how you would divide out brand and non-brand keywords in the multi-channel funnel reports, add in the social media sites instead under the Channel Grouping in the Assisted Conversions Report. Here is what we get:

Social Channels groupings

This tells use two things:

  1. Of the 6 social groups we set up, 2 fell into the top 5 of assisted channels that triggered a conversion; Guest and Partner Blogs and Social News sites.
  2. Instead of reporting 132 conversations from Guest and Partner Blogs, we now know that 51 conversions triggered because of a visit from a blog that we’ve partnered with.

Closing Thoughts

There is a mountain of data that we need to prune through and to identify what to measure is a challenge that we all face every day. Social media data is not an exception in this case and it the mountain will begin to look endless as you approach the top of it. Focus on defining who your visitors are, assign them to a group and begin to analyze their behaviours.

Is this how you report on social media? What other groupings would you include here? Please share your thoughts and comments below.

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