Use behavioural data in email to create segments without asking for preferences.
A few years ago I heard a tale of a record label that used behavioural data inside email to segment their audience. This particular label had a whole load of subscribers who were just plain old boring no-data-given-and-had-no-conversation-with, subscribers.
The label had been sending emails that had content about all of their artists. But to make more of their list, they wanted to get in depth and be more specific with each of the artists.
The usual way to do this is to do a survey, or create a preference center where people would click a button and show their interest in something. But this isn’t a great way of getting action. Let’s admit it – surveys are boring and nobody wants to fill one out unless they’re getting something for it.
So they devised a plan to find out what subscribers wanted to hear about, and how to take them on a journey without asking for more specific information.
Using Clicks To Infer Preferences
The best way they could think of to understand true preferences was to watch people. Not in some sort of creepy ‘behind the bushes’ watching – but the way marketers do it. They stalked them using data. Specifically they tracked subscriber click behaviour.
Firstly they sent out emails that were general in nature – lots of artists in a single email. Depending on what a subscriber clicked on, they then used that data to infer that the artist the subscriber clicked on was the artist the subscriber was interested in. Makes sense.
Taking that data, each artist was then assigned a segment of people who had clicked on information about them.
Getting Deeper with Preferences
Getting deeper in, they would then send more specific news to each artist’s segment. The subscriber would only receive information about that particular artist and be encouraged to take an action – be it downloading a song, buying tickets, or something else that further showed their interest in the artist.
This was repeated several times.
Each time an email requesting action was sent, the list of subscribers in each segment would be segmented.
Those who showed most interest in a particular artist would then be filtered out to a smaller, yet more active group. From here, the label would invite the most active subscribers to be a part of their street teams. Street teams were a select group of people who had the most amount of buy-in.
The label had created a group of subscribers that much more highly motivated to share the artist’s latest news, promote events and gigs, and generally be ambassadors of that particular artist.
A rare success
The promise of big data seems to be that you can do anything you want with it. While this is possible it seems only some of the largest organisations have the resources to use these vast amounts of data to their best extent.
But for many others using data in simple ways and thinking in more creative fashion about existing can help push forward your lists, grow your engagement, and get those successes you’re after.