Dynamic content adaptation
Customers want to receive content that fits their preferences in real time. In this way, a woman browsing for accessories will be displayed handbags and a man looking for shoes will see different content - matching their respective preferences.
Personalized address of existing customers
Identify regular customers and reward them for their loyalty directly. Addressing users personally with their name following their login also conveys that the shop knows and appreciates the user.
Personalized address of unknown users
It is also possible to address unknown users in a personalized way. For example, the traffic channel reveals a lot about the user: is he price-sensitive or brand-affine? The bargain hunter can be referred to a current sale, the product specialist coming from a partner site receives in-depth information about the product.
Targeted motivation for returning visitors
Returning visitors, if addressed specifically, have a great potential. A prominent display of the "forgotten" shopping cart from the previous visit or the last viewed items is worthwhile. This way, the offers are within direct view despite shop hopping.
Personalization: The Technical Basis
The technical basis for forecasting the interests of new and existing customers in real time and displaying the right content at the right time at the right place are complex, self-learning algorithms. They analyze user data in real time (e.g. traffic channel, purchase history, place of residence or local weather). This allows web shops to offer a shopping experience that is tailor-made for the user.
TESTING FOR PERFECT PERSONALIZATION
In order to be able to estimate which measures really appeal to users, (dynamic) A/B- & multivariate tests should be applied. They allow valid statements on the success of a particular campaign. Learn more about A/B-testing now
