Onsite personalization refers to the targeted and interest-based approach of users on a website or in a webshop. Personalization is an important tool in online marketing to ensure that users are always shown the most appropriate content. Onsite personalization dynamically adapts the website to the user’s behavior. The next step is to increase the length of time users stay on the site, reduce the bounce rate, improve user loyalty and user engagement, and increase overall sales and conversions.
Various actions are available for onsite personalization:
- Dynamische Contentanpassung
A common feature of personalization is the dynamic adaptation of website content to the interests of the user. Elements can be dynamically displayed or even hidden. This could be the complete exchange of the homepage teasers or the display of certain promotional products of the category or brand under consideration.
- Personalized approach of existing customers
A simple and proven method of personalization is the personalized approach to users. This involves using the name of the logged-in user to address him/her after logging on to the website. For example “Hello Laura, nice to have you back! You currently have 3 products in your shopping cart. Get an exclusive 10% discount when completing your purchase.”
- Personalized approach of unknown users
Without knowing much about the user beforehand, personalization can take place with the first click on the page. Based on the traffic channel through which the user reaches the site, target groups (or personas) can be formed and individually addressed with various measures. A possible buyer group could be bargain hunters, who access the shop from price comparison sites: This type of user is most likely to be attracted by a reference to a reduced-price offer.
- Personalized approach of returning customers
For returning visitors, the most recently viewed products can be displayed. Many users compare different shops before making a purchase – if they return to the site, they can quickly find their desired item again. It is also possible to display the previously abandoned shopping cart.
- Personalisierte Empfehlungen
Recommendations can be generated based on the interests of the users in comparison with the surfing behavior of other users. Dividing the users into (dynamic) segments can be helpful here.
An important component of a successful personalization strategy is to test the success of the various measures. In this context, both simple A/B-Tests and more detailed multivariate tests can be used.
The technical basis for a personalized approach to both new and existing customers is provided by complex, self-learning algorithms. They analyze user data in real-time (e.g. the click-in channel, purchase history, place of residence or local weather) in order to then provide users with content tailored to their needs.