7 docs tagged with "Personalization"

In this recipe, we are feeding product data along with customer segment data to an LLM (in this case OpenAI) in order to generate customized product descriptions. The scenario is that we have customers with different priorities viewing the same products. Serving up the same product description to every customer may, however, turn some of them off. If we can appeal directly to a particular customer segment, spin the product information in such a way that it becomes attractive to them, we can increase conversions.

In the Conscia DX Engine, you can use Context Field Enrichment to set a Context Field that supports date comparisons in Experience Rules. For example, an insurance company may want to present personalized content if the visiting customer’s insurance policy expires within some number of days from the present moment. The following recipe is a model for how to use Context Fields and Experience Rules to make data comparisons to determine content selection.

Splitting Traffic with Multiple Data Sources

Connecting content in your headless CMS with customer data in your CDP

You can implement a solution based on this recipe that explains how to create a personalized email message using user data from a Customer Relationship Manamagement System (CRM) or Customer Data Platform (CDP) and content from the Kontent.ai Content Management System (CMS) and using Twilio to send an email message.

In this tutorial, you will learn how to connect Conscia with a headless CMS to orchestrate personalized experiences for your users. We will use Contentstack as an example, but all headless CMSs work in exactly the same way.

In this recipe, we are merging together data for a full-page article view, where a visitor can read a blog post and then find related articles to read next. These related articles are being supplied by Algolia Recommend's Related Products model. This same recipe can be used for featuring related products in an online storefront using any kind of machine learning model.