This post is part of a series entitled The Four Pillars of Social Media.  This week’s topics revolve around the fourth & final pillar, Measurement.

Finding where relevant conversations around your brand or company are taking place can be an arduous task.  In order to succeed at finding the conversations when they are still fresh, a mixture of free and paid tools are typically utilized.  While many of these tools are still in their infancy, they generally do a fairly good job at finding conversations that are specific to keywords that you believe are relevant to your brand or company.

There is an additional tool, however, that you already have in place that you’re likely not using to help find relevant conversations.  That tool is your web analytics package.

What Advantages can a Web Analytics Package Provide?

Your web analytics package will obviously function differently than your free or paid social media monitoring tools yet it will still provide valuable information that will allow you to quickly engage in relevant conversations.

One key advantage deals with the type of data your web analytics package reports on.  Rather than looking for keywords that are used on social media sites, your web analytics package will be reporting on visitors being referred from social media sites to your site.

Another advantage of your web analytics package is that it likely is reporting the data in near real time.  That means you can immediately know when a conversation is taking place that’s referring visitors to you site.  With social media monitoring tools, you can look more broadly with the use of keywords, but the freshness of the data that’s returned is reliant on how quickly or slowly the tool finds the conversations.  In some cases it could be hours and in others in could be days or weeks, so augmenting the data from social media monitoring tools with your web analytics data can potentially decrease your response time to relevant conversations.

How can You Find the Relevant Data in Your Web Analytics Package?

In your web analytics package there is an enormous amount of data relating to your sites visitors.  Knowing how to sift through that data to key in on what’s relevant to your needs is a vital step to finding additional relevant conversations in the social media space.

For this post I’ll use Google Analytics as an example, but you could get similar data from any of the leading web analytics providers.

It’s essentially a two step process to get setup correctly.  The first will be creating a custom report and the second will be creating an advanced segment.

Creating the Custom Report

Basically, with a custom report you want to setup a way to find social media sources that are driving visitors to your site and then determine the actual referring path from each of the sources.  This is done by creating a custom report in Google Analytics.

As the dimension you’ll want to use Source and then Referral Path as a sub dimension.  In the metrics area you’ll want to at least add Visits, but you can also add additional metrics that can give you more insights into the visitors being referred.

Once you’ve saved the custom report, it will allow you to spot social media sites that are driving visitors to your site.  You can then click on any of the sources and see URL(s) within the social media site that’s referring the visitors.

As the report currently stands, all sources will be present when looking at the report.  To help you sift through all the sources you’ll complete the second step in the set up process.

Creating the Advanced Segment

Creating the required advanced segment can be done in two ways.  You can create an advanced segment that keys in solely on a defined group of social media sites or you can create an advanced segment that excludes your top non social media referring sites.  I prefer the later since it doesn’t limit the number of social media sites that are included in your advanced segment.

To create the advance segment, simply generate a list of your top referring sources.  Create a new advanced segment and add “Source” as the dimension.  For the condition you want to select “Does not match exactly” and then simply add in the first non social media source as the value.

Continue adding additional sources until you feel enough sources have been excluded to allow you to easily go through what remains and pick out the social media sources.  The result should look similar to below, but likely with additional sources added.

This can also be done using regular expressions in the value field, but for visual sake I’ve broken each source out in a separate OR statement.

Once you’ve completed these steps, you’re ready to combine them.  To do that, drill in to the custom report you created and then select only the new advanced segment.  You’ll now be able to spot the top social media sites that are driving visitors to your site.  Click on any of the sources and you’ll be able to see the actual page they were referred from.

You can then go directly to the page and determine if it’s appropriate to engage in the conversation that’s taking place.

Remember that this is in no way a replacement for a social media monitoring tool, but it can be used to augment what you get from such tools as well as potentially decrease your response time in certain cases.

While attending the eMetrics conference in the Washtington, DC area, Google’s Analytics Evangelist, Avinash Kaushik announced a whole slew of new features being applied to Google Analytics.  From my take on it from a social media perspective, this can help companies start to track some of their measurements they were doing manually for measurement in social media.

So what all did Avinash announce?

• Experimental API for Google Website Optimizer
• Unlimited unique user analysis (which also shows as trending)
  • Avinash emphasized it’s “True” unique user data
  • You also can do this by picking unique time frames, you don’t have to “add” all your data together like with other analytics packages
• Advanced Table Filtering – Avinash calls this “In Line Analysis
  • You can choose your segmentation values
• 2 New Behavior Types of Goal Tracking
  • Number of Pages View
  • Time
• Custom Variables
  • Setting up variables such as
    • Comments left on blog
    • Traffic coming in from specific types of sites (such as blogs)
  • You can track things at a visitor, session, page  (visit) level
• Free Mobile Application (Apps) Tracking
• Custom Alerts
  • You want to know about those people coming from blogs – you can be alerted now!
• Intelligence  – New Dashboard Additions
  • Automatic Alerts – these will appear automatically now when you log into GA and see your dashboard.  GA’s algorithm will look for anomalies in your data and alert you to them automatically

Avinash also went on to say that this new intelligence which is giving you a peek into the “unknowns” is only phase one of what Google’s planning to roll out.

So how does this help your social media strategy and measurement?  Well for starters as Avinash pointed out, you can now track comments in Google Analytics by setting up custom variables.  This is something currently you have to manually put into a spreadsheet to keep track of, now it can be easily integrated into your Google Analytics tracking.

The same could be said for monitoring how much traffic you are getting from blogs, or specific types of sites.  The custom alerts allow you to be notified and this could even help you discover unknown sites that are helping to disseminate your content.  There’s a lot between the custom alerts and custom variables that you can put into place to help you measure some of the things you are doing manually now, all within Google Analytics.

Then there’s the mobile app tracking.  To me, this is huge!  Before you’d have to guess someone was using a mobile app by the browser they come in on “iPhone” or “blackberry” being listed.  With this new announcement from Google Analytics, this can  help any company wanting to know how mobile applications are affecting the traffic to their sites.

If you’d like to read more about the specifics of each of these announcements, the Google Analytics blog has detailed information about how each of these new features work.  I highly suggest taking the time to read up on them and implement them into your own measurement strategy for social media.

While this isn’t the be-all end-all way of measuring for social media, these new features that Google is adding to Google Analytics can help take some of that manual counting and heavy lifting off of your plate, if implemented in the correct fashion.  One of the nice things about these new features is that as Avinash put it, you don’t need a “God” to code this stuff for you to have it work, its very easy to implement.

On an off note, wishing a speedy recovery to Avinash!  Hope that arm heals up fast!