The New Way to Identify Your Twitter Influencers
I am really excited about this second post in my series on social media analytics best practices. If you recall, my first post presented the framework for how to think about the scope and execution of social media analytics. With this post I am going to focus on one very specific opportunity for identifying your Twitter influencers. And I am not talking about knowing how many followers they have or the number of times they are retweeted. I am talking about what their actual influence is on your business — in terms of revenue or whatever other metric(s) you are focused on as a proxy for revenue.
The combination of Twitter’s new “t.co” link service and the efforts of one of my ridiculously talented consultants, Steve Wirig, makes this possible. Even without the fabulousness of what follows below, Twitter’s new link service is huge from an analytics perspective. Prior to this release, there was literally no way to have total visibility into the traffic that Twitter was driving to your website. Even if you managed to aggregate all of the hosted Twitter client domains you would still be missing any non-hosted Twitter client traffic (e.g. from Tweetdeck) as well as any mobile app traffic. In the latter two cases any referring information would be stripped. Of course if you were following general digital marketing best practices by using unique query string parameters as tracking codes, you were in great shape and should ABSOLUTELY continue to do this (and please start to if you’re not — seriously… I’ll keep bugging you if you don’t). You should continue to do this so you can differentiate between the types of tweets that are more/less effective in driving the desired behavior and refine your messaging strategy accordingly.
So let’s talk about customers who are spreading the love via tweeted URLs. What are they really doing for you? Are their followers clicking through to your site and transacting in some way and/or retweeting to their followers, resulting in additional clicks and transactions? These are questions we can now answer in a way that attributes said transactions to the individual tweeters (is that an official word yet?).
Let’s say one of your superfans (I am from Chicago…) tweets or retweets a link back to your site. One of her followers follows that link, and regardless of the structure of the link in the tweet, the referring domain that SiteCatalyst picks up is a t.co link that looks something like this: http://t.co/H43Kls1h. At that point, we make a call back to Twitter and grab your superfan’s handle and insert it into the Authors variable in Adobe SocialAnalytics. Every move your superfan’s follower makes is associated with your superfan. Over time, you’ll be able to see who is driving valuable interactions from Twitter and you can bring those superfans into your advocacy marketing program. Incidentally, you will also be able to isolate these influencers from a reporting perspective in order to keep an eye on them.
Here is an illustration of how the process would work when @Bryankorourke tweets a link to the webinar I recorded with Tiffany Chang Black of Facebook on monetizing the Like button (see what I did there?).
In the above example we would be able to see not only how many of Bryan’s followers clicked through, but also how many (and which) segments of the webinar they watched as well as how many of them downloaded the companion whitepaper. Now THAT is true influence!
So let’s take a look at a sample report that would be available once the socialAuthors plugin was deployed. This is a perfect report to include in a Social ROI dashboard.
Hopefully you have found this useful and are excited to expand your social media analytics strategy! I would love to hear what you think about this post as well as additional topics of interest. You can always find me on Twitter @chicagoml. Thanks for reading!