Personalization Glossary

At PSYKHE, we're obsessed with the why: Why do we like the things we like? Why does one person like a pair of shoes, a sofa, a travel destination, or a song, while someone else does not? Understanding all the factors that drive individual taste, including personality and psychographic data, enables us to create the world's most sophisticated recommendation engine. After all, you can't personalize without personality. Shaping a stellar recommendation strategy is a big job, so to help you grasp what a complete AI personalization blueprint for your business entails, we've collated definitions related to personalization here.

Recommendation Strategy

When a retailer begins to attempt to implement greater personalization on their platform, a solid product recommendation strategy is crucial in order to create a recommendation engine that can maximize marketing ROI. In order to help your system make the best algorithmic decisions possible so that the right products are recommended to the right user or consumer, the most effective type of recommendation strategy for each context needs to be considered. Generally, the more data the better, but which product data, such as color, product type, style, and so on, and which user data, segments, age, demographics, operating device, or psychological data, is most important to each context, will be critical to consider.

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