3 New Ways to Look at Channel Attribution with Social Magnet – Part 3: Clicks Per Person

I’ve written about some new ways to measure channel attribution with Social Magnet a couple times previously, covering Monthly Reach and Monthly Productivity. This time, instead of measuring what you can attribute to each channel, I’m going to look at how to use Social Magnet to measure the relative direct response value of audience members within each channel. The metric I’m focusing on is Clicks per Person, or the number of clicks each audience member contributes to your direct response initiatives over a given time, in each channel.

The value of this information is that it allows you to determine the relative value of an email subscriber versus a Facebook Fan or a Twitter Follower (and soon a LinkedIn Group Member). You may have seen studies that say that a Facebook fan is worth $X or an email subscriber is worth $Y. That sort of industry wide data is useless, even directionally. Not only are the calculations based on inputs that may have no bearing on your own business, but the way organizations use their audiences in each channel varies so dramatically that benchmarking is rendered all but irrelevant. The only way to know the value of your own audience is to measure it yourself, which is what Social Magnet allows you to do.

Here’s how to do it:

Start with a Comparative Report like the one shown in Part 2, here. From this you’ll need the number of messages and clicks for each channel over a period of time. Start with a month – it’s long enough for you to work through a complete cycle of communications in each channel, but not so long that your audience size will vary dramatically enough to skew your results.

From here, you just need to divide the number of clicks per channel by the audience size in each channel. Social Magnet provides reporting on your audience size for many of its click-rate calculations, so that data is readily available. You’ll want an average audience size for the date range you’re looking at, which may be different from the size when at the end of the range. For example, if you started the month with 1000 Facebook Fans and ended with 1200, use 1100 as your audience size for calculations. If your social activity was weighted towards the end of the month when you had a larger audience, you can shift that number accordingly, to 1120 or 1150. (There is a Six Sigma accurate way to do the calculation but it requires taking the actual audience at the date of each message, and the number of clicks from each message. Social Magnet has this data, but the extra work isn’t normally justified as the changes to the data are insignificant.)

Here’s what it might look like in a spreadsheet:

In this example, we see that Email is generating .08 clicks per person per month. Facebook and LinkedIn are slightly higher, with Twitter followers clicking on average over 6 times more often per month as email subscribers. Look in the far left hand column for the explanation – frequency. Twitter allows for a much higher frequency than the marketer in this example is using for email. It doesn’t mean that email is not effective. Rather, if you’re sending a once-weekly newsletter like in this example, you have a significant opportunity to drive incremental engagement through social channels.

We see also in this example that Twitter is an especially productive channel, not just because of the added frequency, but also because the clicks per message are higher than the other social channels. We can deduce that this brand enjoys more success through Twitter than other channels, and the metrics here suggest that more Twitter followers would be more profitable to this brand than more Facebook fans. So audience development initiatives (sweepstakes, cross-promotion, contests, advertising) might pay off higher in Twitter than Facebook.

What would your data look like in this table? This marketer is seeing a 2% click-through on email. With a  3% click-through the Clicks/Person would jump to .12, rivaling Facebook. Increasing the email frequency also directly affects Clicks/Person.

Even though this only measures clicks, and not what happens once traffic from each of these channels reaches your website (which we’re working on, by the way), I think it’s enormously informative when it comes to resource allocation. Every channel does count, and moving the needle on any of the key metrics – frequency, click-rate or audience size – can have an immediate impact on results. Most of us don’t have the luxury of doing everything we possibly can in each channel, so analyses like this make resource allocation a little more strategic, and help drive more ROI from whatever time we have to invest.

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