Hyper-personalization is an extension of traditional personalization techniques used in marketing. For example, using a customer’s name in an email or sending a coupon on their birthday. While traditional personalization only used limited customer data, hyper-personalization is based on a wide variety of provided and collected data.
This data often includes demographic, geographic, purchase history, search history, and real-time behavioral information. This data is combined to form individual customer profiles. Marketers can use these profiles to customize product recommendations, time engagement attempts, and adapt service to customer expectations.
In this article, you’ll learn how hyper-personalization works, how big data factors in, and how you can leverage big data and hyper-personalization.
When creating a hyper-personalization framework, you should follow these steps:
Collect your data—you need to consistently collect a wide variety of data on as many of your users as possible. The more data you have on an individual, the easier it is to create personalized content for them. You can collect this data from a variety of sources, including personal profiles and histories, website analytics, and third-party data collection agencies.
Segment your customers—while hyper-personalization doesn’t use segmentation as traditional methods do, it can still be helpful. Segmentation enables you to better visualize your various markets ...
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