Improving Social Media Strategy with Google Analytics

Published September 12, 2014
You’re tweeting, you’re posting, you’re linking and you’re following. You think social media efforts are going well for your company, but how do you really know? You know by using Google Analytics to help identify your wins and your failures, and then acting upon that insight to make improvements.
Assuming a key goal from your social media efforts is driving traffic to your website and converting visitors into customers, Google Analytics can help you create better campaigns by identifying the social media networks and content that send you the best traffic. Once you know, you can focus more attention to them and increase ROI.
Below, we offer a few tips and examples of how Google Analytics can help you to get the most out of your social media efforts.

improving social media strategy with google analytics


Get Familiar with the Social Media Reports in Google Analytics

Recently, we wrote about the social media reports provided by Google Analytics and the insights they provide. If you aren’t already familiar with those reports, take a look at that blog post for a quick overview of the social media insights available.

Choosing Which Social Media Networks to Invest In

Depending on the products or services you offer, some social networks may be a better fit than others. Articles like Which Social Network is Best for B2B Marketing? can provide some rules of thumb that may apply to your business. However, to know which social media network is best for you, you need to measure the results.

First, Make Sure Your Links on Social Media Are Properly Tagged

In order to accurately measure the traffic from the links you share on social media, you absolutely must tag your links. Many social media networks route outbound links through various redirection services making non-tagged links difficult to track. For example, traffic from Facebook may show up on your site as having come from any of these sources:


It is hard to pull numbers together in Google Analytics when the Facebook traffic is scattered across various sources. Worse, because a great deal of social network traffic comes from apps and mobile phone browsers, and the referrer header (the piece of data that tells Google Analytics where a visit came from) is often not correctly tracked by app and phone browsers, Google Analytics often categorizes this traffic as Direct.

To make sure all social media links work properly with Google Analytics, tag them as described in this blog post on tagging and campaign tracking.

By tagging your links correctly, you’ll get a good idea of the quality of traffic you are receiving from the various social media networks. You can find this information by looking at the report under Social > Network Referrals. Sort the data by the last column – Pages / Session.


google analytics social network referrals


Here you’ll see which social networks are sending you the most engaged traffic, sorted from highest to lowest. For now, skip over the data that has only a handful of sessions. In this case, Facebook Apps and Blogger. With less that 10 sessions, the engagement metrics can be easily skewed and aren’t giving a true measure of the quality of traffic from those sources.

You’ll notice Yelp and LinkedIn both show greater than four Pages / Session, meaning that visitors from these channels view more than four pages session on average. Facebook, on the other hand, shows 3.26 Pages / Session. Yet, you can see that this website received 482 visits from Facebook and only 24 and 18 from LinkedIn and Yelp, respectively.

Why? Because the company has been putting most of its social media effort into Facebook. However, the data indicates that they should consider focusing more attention on LinkedIn and Yelp – because those networks are sending more engaged traffic.

Second, Set up Goals

Pages / Session and Avg Session Duration provide a basic measure of engagement. But, what we really want to measure is conversion. We want to know which social networks send traffic that is most likely to convert into customers.

To measure that, you need to set up Ecommerce or Goals. Unless your users are likely to make purchases on their first visit, it is often better to use a Goals than Ecommerce to track the quality of your social media referrals. The reason is that the user’s second visit (after learning about you from social media) might be direct, or from organic search – or maybe from a different device (particularly if the first visit was from a phone). Google Analytics cannot connect that second visit back to the original one, so you won’t be able to tell that the converting user first found you through social media.

Instead, set up a goal that a valuable user is likely to hit during their first visit. Maybe it is filling out a contact form, opening a trial account, or even reading a specific page – like the pricing page (interest in pricing is often a good measure of likelihood to convert). For advice on setting up goals, see this post on translating business goals.

As social referrals often come from mobile devices, make the goal an action that can be easily accomplished in one click, as these goals work best on mobile. On Facebook, one of my favorites is to tie something valuable to a “Sign Up With Facebook” button that the user can click to create an account on your website. Provide a white paper, coupon, or something else of value in return for setting up the account. Of course, this works with other networks as well, as you can also have “Sign Up With Google,” “Sign Up with LinkedIn,” etc.

Once you have goals set up, you can check out the Social > Conversions report to see which social network is sending you the most conversions. At the top of the report, select “Assisted vs. Last Interaction Analysis.”


google analytics assisted vs last interaction


The report shows you both the “Assisted Conversions” and the “Last Click or Direct Conversions” for each social network sending traffic to your site. Assisted Conversions are when a social network assisted in the conversion by sending a visitor to your site, but where social media was not the last interaction. Last Click or Direct Conversions are those where the conversion came directly from a social network visit. Google explains the two types of conversion in more detail in this documentation.


google analytics social network assisted conversions


In the example above, you can see Facebook and Yelp both contributed two Assisted Conversions. Facebook also contributed one Direct Conversion, while Yelp yielded two. Now, this data is really telling us something, since Yelp sent only 18 visitors, whereas Facebook sent 482.

Although helpful, the Assisted Conversions statistic significantly undercounts the true number of assists because it is based on cookies. For example, Yelp only gets credit for an Assisted Conversion if the visitor comes via Yelp and then visits again – with the same cookie – from another source, and converts. Since users often visit from Yelp (and other social networks) on mobile devices, and then come back and convert on another device (tablet or desktop), the cookie changes and there is no credit for the assist.

For that reason, we tend to focus on Direct Conversions and, as discussed above, try to create goals based on actions a user is likely to take on a mobile device.

Focus on Conversion Rates to Select Social Networks

Looking only at Direct Conversions, the conversion rate for Yelp traffic is 2/18 = 11.1% whereas the conversion rate for Facebook is only 1/482 = 0.2%. Based on this data, it’s probably a good idea for this company to shift some of their marketing time and dollars from Facebook to Yelp.

Although the Social > Conversions standard report does not show conversion rates, it is not hard to create custom reports that do this. Here is one such custom report that you can add to your own Google Analytics account.


google analytics conversion rates from social networks


From this report, you can see all social networks, except for Pinterest and Twitter, have higher conversion rates than Facebook. It would probably be worthwhile for this company to explore investing additional effort in publishing content to some of these other networks. Bear in mind, however, that conversion rates usually come down as the activity from a network increases. That may be part of the explanation as to why the Facebook conversion rate is lower than most others. However, there is no way to know for sure without trying. In this case, the data definitely indicate it is worth trying some other social media networks.

Selecting the Best Content for a Social Network

As mentioned above, tagging the content you share on social media is essential. To measure content performance, you will want to use the Campaign Content parameter (utm_content) for tracking the type of content. At Megalytic, we frequently use that parameter to store the title of the blog post being shared. But, you can use this parameter in other ways, as well. As the Google documentation states, it can be “used to differentiate similar content, or links within the same ad. For example, if you have two call-to-action links within the same email message, you can use utm_content and set different values for each so you can tell which version is more effective.”

Here is another custom report. This is similar to the one shared above, but with an additional dimension that tracks the content type. Here, if you click on LinkedIn, you can compare the performance of content shared on LinkedIn. The Campaign Content parameter shows up in Google Analytics reports as “Ad Content” – even though, in this case, these are not ads but social shares.


google analytics ad content conversion rates


We’ve only been tagging this way for little while, so there is not much data at this point. The red arrows indicate the social shares we tagged with the blog title. As you can see, the one doing the best in terms of conversion rate is “Translating Web Analytics Requests.” We don’t really have enough data to draw conclusions here, but we are speculating that content dealing with business-level issues leads to more conversions than content focused on technical topics.

What if we haven’t been Tagging properly?

Much of the analysis we’ve shown here depends on good tagging. The reality, however, is that tagging doesn’t always get implemented properly. Often times, the folks doing the social media posting are different from the folks doing the analytics and it takes time to get everybody on the same page.

If you are in this situation, all is not lost! Here is a custom report you can use to see which content is doing the best on which social network. It relies on the Landing Page instead of tagging to identify the content being shared.

In this custom report, we have used a filter to restrict the landing page to our blog pages – as that is the content we most commonly share on social networks. You may need to adjust the report to suit your needs.


google analytics landing page and ad content conversions


Here, we have sorted the data by Goal Conversion Rate – the last column. The first column shows the landing page and the second shows the Social Network.

Usually, we ignore rows with low sessions – like the first one, with only three sessions – because high conversion rates derived from a small number of visits are often statistical anomalies.

We suggest you review this report with someone who knows your content well. One thing that jumped out at us was that the post /blog/bringing-analytics-to-your-digital-agency looks promising, although with only seven sessions, it could be an anomaly. Then we realized we failed to promote it. These days, Page posts on Facebook are getting very little exposure without paid promotion. We decided to promote it and we’ll see what happens.


If you’re spending time and resources in social media, you want to make sure you see a return on your investment. To get the best results from your social media campaigns, analyze the results with Google Analytics in the ways described here. Then, use the insights to improve your social media strategies. Focus on the social networks and content that are driving engagement and conversion on your website.


When the client first came to you, you talked up the value of Google Analytics. You emphasized the importance of seeing where your traffic was coming from. You went on and on about how Google Analytics can show traffic sources to pinpoint whether people came from search, social media or a specific site referral, and how valuable this data was. You sold them on it, so much so that your client looked forward to receiving that first report, the magical day when they would finally understand where visitors were coming from.
But then the report came, and it looked like this:



It showed that 10% of your client’s traffic came from “(direct)/(none)”. What does this label mean? How do you explain Direct traffic to your client? Better yet, how do you explain “none”?
Let’s take a closer look at understanding Direct traffic in Google Analytics and how we can address it with clients.
Digital marketers spend a lot of time focused on PPC and SEO campaigns in order to drive desirable traffic to a website. The phrases we’re ranking for and bidding on get meticulous attention, so much so that we often forget about some of the other ways that visitors find us.

We put a tremendous amount of the effort we put into reviewing organic search data and PPC campaign performance in analytics. But how closely do we monitor referral reports?

If that’s not a channel you review regularly, you may be missing out on seeing traffic that is coming directly from links you’ve obtained around the web, local business listings, news mentions, and more. Many times, links are only considered as a means to an end, a metric that Google uses in determining how to rank sites in the SERPs (search engine results pages). But the fact is, many of a site’s links may be directly contributing to its traffic.

In this article, we’ll review how to look at referral reports in Google Analytics, and some of the many ways to use that data to better inform your web marketing decisions.


Remember how your mom told you not to stand too close to the television because it might hurt your eyes?

The same rules can apply to data. If you’re too close, you may miss the patterns and trends that are crucial to understanding your website’s performance. You can’t judge a site’s performance looking at data in the bubble of a single day, you must consider any day’s traffic compared to the days before and after.

Google Analytics makes it fairly easy to analyze trends over long periods of time. But it also allows you to stand right in front of that TV, to look at more granular levels of time, right down to the hour.
There’s a better way to get that close to the data, without burning your retinas. We’ll cover how to analyze traffic effectively in today’s post.