Want to save this article for later?
You’re attending a baby shower, bought diapers off Amazon, and suddenly you’re flooded with emails recommending baby products? It’s an instant engagement failure because you don’t have children and you have no real interest in purchasing baby food (although there are rave reviews on the banana flavor).
This is the limitation of segmenting users simply by purchase behavior.
Customer actions such as purchasing, browsing products, adding products to a cart or adding items to a wishlist don’t necessarily mean the user prefers one category over another.
The challenge for marketers is persistent: marketers can’t determine a set of users with a propensity or affinity towards one thing over all others. The available means to segment users are based on the actions users take and often won’t indicate what users predominantly like. As a result, marketers are unable to establish an effective match between products and each user’s likes/needs based on what they care about the most.
At present, marketers have the ability to segment users based on behavior – the actions they perform in an app. Most of the options segment users based on what they did or didn’t do instead of what they like or dislike.
What if there was a way for marketers to segment users on relative importance or frequency or weightage of an action over all other actions that a user has taken?
Owing to these ingrained limitations, marketers end up spamming customers with messages that aren’t relevant and are less effective in driving conversions or revenues.
Psychographic Segmentation is the latest feature in CleverTap. It’s a Machine Learning-powered functionality that automatically tells you what your users are most interested in.
For instance: you can determine the dominant content film category preferred by top customers of your streaming app, and the time of day they prefer to watch it. This will allow you to engage with these users with recommendations in their preferred category, just before their preferred viewing time.
This helps you optimize your campaigns to ensure that you are reaching users in the right context at the right time with a message that they really care about. It is an accurate and a more intuitive way of understanding how your users like to spend time on your app.
Another use case: sending contextual messages to users who prefer to make purchases on a specific day of the week or time of day.
There are many other ways to use customer interest as a precursor to your marketing campaigns, and we cover some more below.
The best thing about sending contextual messages?
Early tests have determined that Psychographic Segmentation can improve conversions up to 5x versus sending non-contextual messages.
Every single one of your users is unique. Knowing what each user is most interested in helps marketers identify user habits, lifestyles, or even personality traits, thus engaging them in a more focused manner.
Using psychographic segmentation, you can:
Let’s look at a few examples of how you could use Psychographic Segmentation to target specific users no matter what category your app is in.
With ever increasing data points on customer behavior, it is only a matter of how marketers use them to create a more personalized experience for customers.
At CleverTap, we are leading the charge by building features that let you use the power of Machine Learning to run intelligent campaigns and derive data-backed insights.
All CleverTap users now have access to Psychographic Segmentation. If you’re not a user yet, sign up now and give it a try. For anything else, we encourage you to use the comments section below to share your thoughts.