There is a good way and a bad way of looking at click data.
The bad way: You posted something yesterday. It got 150 clicks.
The good way: Over the past 7 days, your posts received 1,402 clicks, for an average of 112 clicks per post and 1.39 clicks per follower. Clicks were up over a week prior. An increase in posting frequency drove the uptick in clicks, as your clicks per post remained flat.
See the difference? On a day-to-day basis, social media marketers get drawn into the “How did my individual piece of content perform?” trap. Unfortunately, looking this deep into the weeds doesn’t really tell us anything actionable. Raw performance data is necessary, but we need to see it in context (and often in aggregate) in order to identify trends and take action.
There are three primary data points we use to evaluate interest, and one bonus data point for those of you who really want to compare yourselves against other companies. These data points must be used in conjunction to get a full picture of your traffic.
Clicks are, well, clicks. You publish links to Twitter, Facebook, and linkedIn. You use a URL shortener. You get reports on clicks, broken down by social network, social property, and post, and grouped by campaign.
If you don’t, you should be — link shortening and click tracking is the most fundamental tool in your social media marketing toolkit.
Check out bit.ly for a handy free URl shortener or – ahem! – check out Argyle Social for an integrated, business-class offering.
Clicks data becomes most useful when viewed in trends. A month-on-month increase of 20% is excellent, whereas a 20% decrease over the same time period is less than ideal. However, be careful when ascribing too much to this number. We’ll need some additional data to explain any trends we see.
A raw clicks count doesn’t tell us much of anything. If we take clicks and divide by the number of posts made during the time period, we can start explaining the trends we see. Let’s say in month 1 we get 1,000 clicks and make 50 posts, for a total of 20 clicks per post. Imagine the following situations that could arise in month 2:
Both results are good—you generated 25% more clicks than the prior month. But the first scenario is clearly better. Not only are you getting more total clicks, you’re also getting more clicks on every post that you make. This indicates that whatever you’re doing seems to resonate with your audience!
When looking to increase clicks, you have two primary levers: you can post more often, and you can post better content. Posting more often will only get you so far, so make sure you’re laser-focused on the clicks per post you’re generating.
The same logic works if you’ve had a particularly bad month:
In both situations your clicks went down by 25%. As before, the first scenario is clearly better. Your clicks per post have stayed consistent; the decrease in clicks is just because you’ve made fewer posts. That’s easy enough to fix.
We can also normalize clicks by the number of followers in a given period. This is especially useful if you’re going through a period of high growth in your fan base.
Continuing with the example above, let’s say in month 1 we get 1,000 clicks and have 800 followers for a total of 1.25 clicks per follower. Imagine the following situations that could arise in month 2:
Both results are good, but the first scenario is clearly better. While it’s hard to make a definitive judgment about what’s going on, it seems like the 150 new fans added in the second scenario weren’t as interested in the content you were sharing, thereby driving down the average click rate.
The ultimate way of normalizing clicks is both by fan base and by post count. A simple example: if you generated 1,500 clicks on 50 posts and 1,500 fans, your response rate is 1,500 / 50 / 1,500 = 2%. What this means is that 2 out of every 100 fans click on every link you post.
We’ve found that this metric is the most easily understandable way to look at the level of interest your fans are showing in your content. While results will obviously vary, we try to aim for response rates of 1-3%. Anything higher than 3% is gravy, while anything under 1% needs work.
Trust us on this one. If you don’t already know your average response rate, throw together a quick spreadsheet and figure it out. You’ll be fascinated by how much you learn by the end of the exercise.