If you’ve asked this before…
“How can we get more visitors to our website?”
… You’re certainly not alone, as increasing traffic is often the number one problem faced by marketers today.
The bad news? Saying “get more traffic” is easier said than done. You could write guest posts, optimize for SEO traffic, or drive visitors through social media. The options are endless. This article focuses on the latter, though.
In this post, I’ll share the seven most powerful lessons we learned from running social media experiments to increase our social media referral traffic by 200%.
Ready to dive in?
1. Giveaways 2x shares per blog post
When we A/B tested a blog post on body language, we split it between two variations:
Version A had a giveaway at the endVersion B did not
The result? Version A doubled the amount of shares. In other words, instead of 1,100 shares, we got 2,200. Here is the simple CTA we used at the end for version A:
We kept running these tests and seeing the same results — insert a giveaway, 2x the shares on the article. The compounding effect on traffic for this experiment was monumental for us.
2. Inserting Click-to-Tweet throughout articles would boost shares
In the below spreadsheet, we analyzed articles that used Click to Tweet (CTT) links versus articles that did not:
Seems obvious, but it was refreshing to see data that backed up our hypothesis.
At a glance, you might be thinking, “Awesome! I’m going to add CTT links to every article now!” … but I’d recommend testing everything. This might work with our audience but could have a profoundly different impact on your audience.
Our philosophy for CTT was if it doesn’t feel natural, don’t force it. The most common CTT links we used were quotes or interesting statistics.
3. Twitter was our “most valuable” share source
Just because you’re getting more shares, doesn’t mean you’re getting more traffic.
For example, after someone (let’s call him John) Tweeted our article, the goal was for someone else to click the link that John Tweeted. If someone new did NOT click that link, someone new did NOT visit our blog. If that happens, John’s Tweet isn’t delivering any return, because we’re getting zero new visitors to our content.
Thus, the more people that click a link after it’s shared, more “valuable” the share becomes. Make sense?
In other words, that means:
For every share we get on Twitter, 2 people clicked that link they saw in their Twitter newsfeedFor every share we get on Facebook, 1.5 people clicked that link they saw in their Facebook newsfeedFor every share we get on LinkedIn, 0.75 people clicked that link they saw in their LinkedIn newsfeed
For example, if we got 1,000 shares on Twitter and 1,000 shares on LinkedIn for the exact same article … we could expect 2,000 visits from Twitter (1,000 shares * 2 views per share), but only 750 visits from LinkedIn (1,000 shares * 0.75 new views per share). Despite them, both have 1,000 shares.
That means getting shares on Twitter is more valuable than getting shares on LinkedIn, even though LinkedIn has the highest number of shares. Interesting, right?
This opened our eyes to not only track the total number of shares but also keeping in mind our most valuable share source.
4. Visualizing our “share retention” over time
In this experiment, we sought to understand the rate that shares decrease over time per article.
5. Influencer sharing articles results in significant shares spike
Next thing we know we’re getting thousands of new people reading that blog post, discovering Sidekick.
Yes, seems obvious. Get an influencer to share your article and you’ll get more shares. Duh. But since this happened, we started reverse-engineering our writing, constantly asking ourselves, “What influencer would share this article?” then working backwards to make sure it appealed to them.
Over to you
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These results were powerful for our audience, but your audience will be different. Make sure you treat this as inspiration to run experiments, not prescription. It’s always important to remember that different customers react differently and what works for one company may not work for another.
Thanks for reading! And I’d love to hear your thoughts on these experiments or any of your own in the comments below.