Today’s tech savvy customers expect relevant, contextual, engaging content that is personalized towards their interests. Engaging, immersive, and relevant experiences increase customer satisfaction and result in loyal customers and increased conversions.
With Blueshift’s Recommendation Studio, recommendations automatically adapt to each customer in real-time based on their current activity, past behaviors and purchases, their affinities, and the latest catalog data. This ensures that recommended content is always relevant and engages your customers, known and anonymous. Product, content, and offer recommendations can be easily coordinated across all channels like email, push, SMS, websites, mobile apps, and more, to deliver a consistent brand experience.
Blueshift provides a library of out-of-the-box industry-specific and commonly used recipes that customers have found success with. Simply select a recipe based on the intended audience, campaign, or any other use case and use it as is or tweak it for your specific requirements. Some common examples include campaigns for abandoned content, related items, users also browsed or bought, next-best-product, and so on.
You can test recommendation schemes by including different schemes in different messaging templates and running A/B tests to determine which recommendations are more effective. You can also use the email template click heat maps to get insights into how customers interact with various recommendations. With the Insights Recommended items report, you can measure which items are being recommended the most and which of those items users are engaging with.
Recommendations are included in certain Blueshift packages. Contact your Blueshift CSM to start using AI powered recommendations in your campaigns.
In order to include recommendations, you need to upload your item catalog to Blueshift and send user interactions with your catalog items via an event feed or API to Blueshift..
Blueshift’s recommendation engine can then easily recommend content from the catalogs based on the catalog metadata, customer data, and customer behaviors and serve that content dynamically within communications across channels.
If you have a data science team and have your own recommendations, you can upload them directly into Blueshift as recommendation feeds. You can then combine these external recommendations with our AI-powered recommendations to send the best performing combination of recommendations to your customers.
The recommendation scheme is configured in the Recommendation Studio and associated with a messaging template. When a campaign runs, it applies the recommendation steps for every user in the segment to deliver a unique and personalized message with items tailored to the individual user.
View Recommendation Schemes
You can view all the recommendation schemes by going to Recommendations in the left navigation.
Click the recommendation scheme to view and edit the details.
Add a Recommendation Scheme
Click +RECOMMENDATION > Photon Editor to add a recommendation scheme.
Note: You can also use the Classic Editor (Legacy Editor) to create a recommendation scheme. This editor will remain available for you to use until February 14, 2023.