Your most flexible module
The use cases for this module are endless. Depending on your strategy, the module can boost certain brands and categories, and you can choose how much they should be weighed. You can also choose which similar or cross-selling products should be shown depending on the event type.
For frequent shoppers, the module can be set to show favorite products that they “might have forgotten.”
The module also has a split-testing function, so you can test which settings perform the best.
Importantly, you can control all settings yourself – without help from Raptor’s data scientist team.
Check out this module’s many other, groundbreaking benefits:
- The module makes personal recommendations based on both CookieID and UserId (1st party data)
- You can choose which products to use as backfilling for different event types
- The module can both boost and suppress products. This way, the module can be set to not show product in certain contexts (which you define yourself).
- You can choose which similar or cross-selling products should be shown depending on event type.
- You decide whether the module should boost certain brands/categories, and how much they should be weighed.
- For frequent customers, the module can be set to show favorite products that they “might have forgotten.”
- The module has a built-in split-test function, so you can test several settings in the same module
Always one step ahead of the user journey
As a brand-new feature, the module also suppresses certain data points as the customer journey moves forward.
In other words, the algorithm can be instructed to stop showing certain products – and start showing something else. This is an especially useful feature for when the visitor has made their first conversion and can be nudged to make a second one.
Let’s look at both ways to use it:
More data points than ever before
Real-time Personal Recommendations is our most intelligent and flexible module yet. The algorithm takes data points from every step of the customer journey into account. It not only calculates the customer’s interests and intent. Uniquely, it can accurately predict what your customer needs next.
The module considers more data points than ever, including:
- Collaborative data from other users
- Online and offline purchases
- Products searched for
- Products looked at
- Search data
- Basket data
- Visit data
… and many other data sources to help show the most relevant recommendations for the user.
How do I use it – and where do I find it?
The new, updated module is available for both web and e-mail recommendations if you are already a user of Web Personalization and E-mail Personalization by Raptor.
The module comes at no further expense and can be found in the control panel by looking for Real-time Personal Recommendations (or the technical name “GetUserItemRecommendationsWeb”).
There are several places you can put the module:
- Front page
- Login page
- Basket page
For the highest conversions, we recommend placing it as a sidebar that follows your customer throughout their visit. This way, the module constantly calculates the best possible recommendations and shows them in real time.