AI & 1:1 Recommendations

Companies at the cutting edge of customer engagement today are delivering 1:1 recommendations in many different forms, powered by Artificial Intelligence (AI) or Machine Learning. Today's digital marketer finally has access to data about customer behavior and preferences in real-time. However, synthesizing this data into recommendations is extremely hard. That's where AI powered systems come in.

RFP Questions for AI & 1:1 Recommendations

  1. Are unique recommendations available for every user? Is this a native capability or through a partnership/ additional integration?
  2. How are recommendations generated by your system?
  3. What forms of recommendations are available?
  4. Describe how recommendations can be deployed in email.
  5. Describe how recommendations can be deployed in mobile app push notifications.
  6. Describe how recommendations can be deployed on websites.
  7. What kind of latency can we expect for website recommendations?
  8. Can we import recommendations from our in-house team? If yes, describe how.
  9. Can we combine multiple types of recommendations into 1 email, with some recommendation blocks coming from our team? If yes, describe how.
  10. Does your solution offer a visual studio to preview recommendations and add filters?
  11. Does your solution offer predictive scoring on customer actions? What scores are available?
  12. What kind of analytics do you offer to understand the predictive scores?
  13. How often are scores updated?

Read Blueshift's responses to these questions

Updated 3 years ago

AI & 1:1 Recommendations


Suggested Edits are limited on API Reference Pages

You can only suggest edits to Markdown body content, but not to the API spec.


});