I love data. I’ve spent the last 5 years of my career dedicated to doing research on huge datasets of hundreds of thousands and millions of rows to reach best practice conclusions. And those conclusions are great for experimentation with specific brands and audiences.
But the real power comes when you begin analyzing your own, individual sets of data so you can find out what kinds of content, timing, and behaviors work best for your specific audience.
Enter RetweetLab.com! Using this free tool, you can analyze any Twitter account -- including your account or a competitor's account -- to unearth the data you need to get more retweets. The tool works by allowing you to compare your current behaviors (the small graphs in the text) with the behaviors that are correlated with your account getting more retweets. Here's how you can use this new, free tool to analyze and improve your own Twitter presence.
How to Use RetweetLab to Analyze Your Twitter Marketing
Let's start with something we're all familiar with -- the Twitter hashtag. Ever wonder how important it is to spreading your Twitter content? RetweetLab can help you understand that.
The graph above details the effect of hashtags on retweets for my account, @DanZarrella. You’ll notice that the vast majority (93.4%) of my tweets do not contain a hashtag; but those tweets that do contain a hashtag tend to get more retweets. I may want to think about experimenting with more hashtags in light of this data, right?
Time of day, especially in the cluttered Twitter stream, can have a huge impact on your effectiveness, too. Take a look at what the hour of day breakdown shows us, this time from an example using the @HubSpot account:
We see that our account sends the most tweets at 2 p.m., but that tweets at that time seem to get fewer retweets than the rest of the day. Based on this, maybe we should experiment with more tweets in the morning, rather than afternoon -- as you can see, around 8 a.m. we do quite well with retweets, and even much later in the night, around 10 p.m.
This is actually a somewhat predictable insight. They send most of their tweets during the early afternoon, peaking at 2PM, but they tend to get the most retweets around 9AM. Perhaps because this is when people are thinking about coffee?
Let's move on to another way to slice and dice your Twitter data -- seeing the impact of asking a question on the retweets you receive:
Using RetweetLab to analyze @Mashable, we find that the vast majority of their tweets (92%) are not questions. However, tweets that are questions seem to get more retweets than those that are not. We can analyze this with Twitter content that's a quotation, too:
The graph above takes data from the @Guardian Twitter account, and ask you can see, most of their tweets don't contain quotes. But the ones that do contain quotes tend to get more retweets. You know what to do, @Guardian.
Any readers out there who have read some of my Twitter data before know that I'm a believer in directly asking people to retweet if you want more retweets. This is a type of Twitter call-to-action (CTA), and just like any other part of your marketing, it's important to measure whether your CTA is working. Retweetlab allows you to analyze the effect of calls-to-action like “please retweet” on your tweets. Take a look at one example:
The average length of their tweets, in characters, is 103.38, and from the small orange graph we can see that their tweets tend toward being on the longer side of the scale. But the sprocket on the blue line graph shows us that they get the most retweets for shorter tweets. Perhaps they should test more succinct messages to help their content spread further.
Try out RetweetLab for yourself, and tell me what insights you’ve found that may change how you tweet in the comments.