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I had an interesting conversation last night with a photographer friend who said he faced a dichotomy in his work: on the one hand, he doesn’t overly care about others’ opinions, and on the other hand, he feels as though he should shoot for views as the best way of seeing how his work is being valued as he doesn’t sell his photos.

To me, there’s no dichotomy here. We focus on things like views of a photo, followers, retweets, fans on a fan page, etc. because these are the measures and metrics we know about. This is the best we have to work with, for the most part, and so valuing them isn’t wrong or crass. In the absence of other, better metrics, we value what we know.

To alleviate my friend’s dichotomy, I suggested he consider other metrics that would more accurately gauge his work – in essence, expanding what he knows about his work and how people perceive it. Sales, of course, is one such measure. It’s easy to click follow or subscribe or friend someone, but it’s much more of a commitment to open your wallet and purchase the work of an artist. You have to be much more invested in it to put up some money.

If you’re in it for the love and not the money – which is perfectly okay and good – dig deeper into your analytics. Last night in my USF Advanced Social Media course, I talked a bit about using Google Analytics to measure inflows and outflows to social networks as a way of better gauging what people are doing with your stuff. Here’s two examples.

1. Measuring outflows. Using Google Analytics’ virtual pageviews, you can tell whether that giant Twitter badge on your blog is worth keeping around. Set up links using an arbitrary virtual pageview, and every time someone clicks out to a social site or platform from your blog or destination site, you’ll know. That giant “BE MAH FRIEND” badge may be taking up valuable real estate for little value. Add a virtual page view to high value links or affiliate links as a sanity check for your affiliate reporting, too.

Example code – no virtual page view:

<a href=”https://twitter.com/cspenn”>My twitter account</a>

Example code with virtual page view:

<a onclick=”javascript: pageTracker._trackPageview (‘/vpv-twitter-text-link’);” href=”https://twitter.com/cspenn”>My twitter account</a>

This will show up in your Google Analytics under Content. Filter for the virtual page name to see how popular it is. (/vpv-twitter-text-link in the example above, can be anything you want it to be, like /omg-im-linking-to-chris-brogan for example)

2. Measuring inflows. Nearly everyone on Twitter uses bit.ly or another URL shortener to make stuff easier to share. Go the extra step and use the Analytics URL Builder so that you can see traffic from individual social links you’ve shared – and how well they convert.

Take the link to your site, blog, or destination that you were going to share, feed it to the URL builder, append some useful data (did you share it on Twitter? Facebook? is it PPC? shared to a specific user? Customize as you like!), then feed the Google Analytics enhanced link to bit.ly.

Now, when you share that link, you’ll see exactly where your traffic is coming from and more importantly, you’ll see how your traffic does on your site. You can isolate, for example, how many people from an individual tweet bought something or downloaded an eBook. It’s laborious to do this with every single thing you share, but for high value stuff, this is the way to go.

For my photographer friend, every link he places to his photos (or embedded photo on his site) should have either an inflow or outflow, and if he had some engagement metric like a free eBook download, he’d begin to know more than just views about his photos. He could see how many people went from a tweet to his photo blog to subscribe to download, and if someday he chose to sell his photos, he’d need only add that to Google Analytics to deepen his understanding of his audience.

Try out these tools and see if you can make them work for you.

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In the absence of other metrics 1 In the absence of other metrics 2 In the absence of other metrics 3

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