Happy 4 th everybody. To celebrate this occasion, we’re going to talk about one of America’s favorite pastimes…tweeting, and how it can help an even more American practice: entrepreneurship. (Hint: that’s you.)
Twitter recently surprised the business community by quietly opening up its analytics tools to all users without so much as making an announcement. This gives all users access to information about who is engaging with them and how. To access the features, users only need to visit the Twitter Ads Dashboard and click on the Analytics tab to use the new tools.
Now that the tools are fully available, how should you use them to maximize your marketing potential?
The hub for your analytics data comes from the timeline. After logging in to analytics.twitter.com, go to the menu bar and click Analytics>Timeline activity. This takes you to a series of metrics that are, thankfully, pretty minimalist and easy to interpret.
This is the first thing you’ll see, a timeline of @ mentions that will let you know how often people are mentioning your Twitter handle and when. This can be a quick and easy way to identify which actions are generating the most behavior on Twitter.
Be sure to think outside of tweets and blog posts alone. Conferences and events can contribute quite a bit to these as well. Add to that any online behavior, like comments or chat sessions. If you attract enough attention through any channel, it will lead people to your Twitter account.
Try to avoid confusing cause and effect here.
The second timeline shows you when people start following, or unfollowing, your account. This one tends to get more cluttered by bots than the mentions timeline, so it can be a less useful metric in some circumstances. This is most useful for finding spikes in your follower count. If you notice a spike in mentions that doesn’t create a spike in follows, it could be a bad sign.
This section is the most useful one for identifying the specific tweets that were most useful. At the top of this section, click on “Best” or “Good” to see the results sorted by engagement instead of recency. You’ll be able to identify which tweets picked up the most replies, retweets, and faves, which can help measure how well you’re connecting.
More interesting to us, though, is the fact that Twitter is also tracking the number of clicks each tweet is getting if it links elsewhere. This allows you to track clicks even if you aren’t using a shortener like bit.ly.
Unfortunately, Twitter isn’t currently tracking clicks as a primary metric. You can’t sort by clicks. Personally, we feel this is a big problem with the analytics system, since clicks are often a more useful metric than social activity. (Facebook likes, for example, rarely correlate well with conversions and other meaningful metrics.) In order to see your highest clicked tweets, at this point, you need to sort by “All” and eyeball it in order to find them.
To get to this section, you need to head back up to the menu bar and click on Analytics>Followers.
This screen starts with a graph displaying how your follower count has changed over time, and more importantly, gives you some information about them:
- Most Unique Interests – This tells you about the interests your followers have that separate your audience from other audiences. Essentially, this helps you discover your place in the market.
- Top Interests – This gives you the most popular interests of your followers, which is less useful for identifying niche interests, but useful for identifying what your audience cares about outside your niche.
- Location – For now, this just reports your Top Cities. So if Austin Texas isn’t showing up here, you’ve got a problem.
- Gender – Self explanatory.
- Your Followers Also Follow – This one is great for learning even more about your followers’ interests by looking at who else they follow. It’s also a great opportunity to discover people to network with for increased exposure.
As always, remember to tie this data back into your key metrics, and train yourself to ignore metrics that aren’t correlated with anything that matters. The biggest problem with any analytics package is the tendency to let it set the goals and do the thinking for you.
It’s up to you to decide what matters.