3 Ways to Leverage Twitter Activity Analytics Today

3 Ways to Leverage Twitter Activity Analytics Today

In case you missed the great news today: Twitter opened Activity Analytics to the general public. This feature was originally launched for advertisers and verified accounts in July but many marketers do not fall into either category, making this a development of substantial value to the business community on Twitter.

There has been some speculation about why this is now available to the public but from our perspective at Shaping the Game it’s an obvious move. Individuals and organizations have been seeking ways to better understand the reach and impact of social activity for years—Even going so far as to pay third party services for any kind of visibility. Once vendors started inventing derivative, proprietary metrics, like ‘Klout’ and ‘Kred’, we realized it was only a matter of time before Twitter would provide more visibility.

As an individual user I am really grateful Twitter is moving towards transparency and open access because it aligns with my own values. As a shareholder I am even more excited because I believe this supports a strategy for success with the marketing community. However, as a marketer, the most important question is: How can we leverage this data?

Find your audience

Twitter Followers Location GraphicAfter logging into Activity Analytics navigate over to the second page, entitled ‘Followers’. There’s an excellent graphical representation in the middle column which helps understand where the account followers are in the world. We can think of a couple of great ways to leverage this information.

For example it might be valuable to compare this source of data against geography information contained within the analytics for the web property associated with this account. In our case, we’d be looking for the delta and overlap between my activity on Twitter and the activity on this blog, as well as my personal blog.

When comparing different sources of data it’s important not to get hung up on the specific. Instead, look for patterns in the aggregate data. If there are vast differences in the location of audiences across web and social, this is something worth following up on. Another great way to leverage this knowledge is more effective advertising buys, since it’s possible to geo-target most digital advertising.

Figure out what they like

Just to the left and right of the Location data there are reports which share the gender and interests of the account’s followers. The interest data is measured across all followers in the aggregate and broken up into three sub-categories:

  • Who else they follow
  • 5 most unique interests
  • Top 10 interests

Although it’s possible to extract deeply meaningful data on audience interests by conducting a more thorough analysis of the other accounts they follow, the second two bullets have done the heavy lifting for us. Based on this information it is possible to make smarter decisions about the mixture of content shared, to maintain the interest of the current audience.

Understand what works

Back on the Tweets page underneath the bar graphed metrics, the interface displays a new version of the account timeline. This view lists every tweet with columns for data on impressions, overall engagements, and engagement rate. Although the Twitter Activity Analytics overall experience is really impressive, it’s disappointing that it’s not possible to sort on the columns.

However, in the top right corner there’s a button to download the raw data so it can be opened in a spreadsheet. This is great news because doing so will open up all the data processing capabilities available in Excel. Before exiting the web interface, check out the sweet detail report. It’s possible to click on each tweet to view more specific information, including the distribution of impressions over time.

Once the raw data is opened in Excel it’s possible to sort and filter based on every data point. For example, allowing us to determine which tweets garner the highest engagement score. Viewed over time this knowledge will make it possible to craft content with a higher probability of success by looking for elements that worked in the past. One of our immediate observations is the engagement rate on tweets with images is typically two to three times higher.

What have you learned?

As always, we like to invite our audience at Shaping the Game to share their insights with us so we can all grow together as a community. What do you think about Twitter Activity Analytics? Do you think this information will help you make better marketing decisions? Or is this just more data noise? Please share in the comment section or join the conversation on Twitter by using #ShapingTheGame.



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