We are excited to introduce a new feature that is set to redefine the way you create and deliver recommendations to your users. Say hello to "Item context from analytics" a powerful addition to our recommendation engine that opens up a world of possibilities for personalization and customization.
This addition empowers you to effortlessly specify which elements should serve as context for a particular campaign without the hassle of altering your website or delving into complex jinjava scripting. Instead, you can harness the power of our analytics to do the heavy lifting for you.
Why Item Context Matters
Understanding users' preferences and behaviors is key to delivering recommendations that truly resonate with them. Item Context takes personalization to the next level by allowing you to add context to different types of recommendations. This means even more tailored product suggestions, ultimately leading to higher user engagement and conversion rates.
How It Works
The process couldn't be simpler. In the Additional Settings of Synerise Recommendations, you can now enable a toggle for Item Context from Analytics. This empowers you to enrich your recommendations with the specific product context you've defined – whether by aggregate or expression.
Item Context enhances your workflow by eliminating the need to include product context in complex campaign configurations. Now, you can seamlessly add context directly from each recommendation you create without having to modify campaign code.
Now, let's explore a few real-world scenarios to showcase the potential of this new feature.
Enhancing Cross-Sell and Upsell: Boost your cross-selling and upselling efforts by taking into account the context of a user's current shopping cart or wish list. For example, if a user has added a camera to the shopping cart, the Item Context feature allows you to recommend complementary accessories such as lenses, tripods or camera bags. You can display this recommendation on your website or mobile app, send it via email, or use mobile push notifications. You have the flexibility to choose the communication channel and method that suits you best!
Dynamic Content Personalization: Tailor your content recommendations based on the context of the user's browsing history or previous content interactions. This ensures that the content you recommend aligns with their interests at that specific moment. For example, if users are looking for fitness apparel or sportswear, Item Context can be used to suggest workout accessories such as fitness trackers, yoga mats or running shoes, creating a complete fitness kit tailored to their preferences. Keep in mind that you can put the recommendation wherever you like, and you don't need to write any code for it. The context assignment is handled through analytics in the recommendation configuration. This means it's entirely code-free!
Other possible general scenarios
Recommending products similar to last viewed, last purchased or most frequently purchased product.
Suggest products that complement recent purchases, recent views, products in a shopping cart, or products on a wish list.
Looking for more inspiration?
Check out our use case which shows a sample scenario for using item context in Similar Recommendations.