Personalization Glossary

A/B testing? Recommendation models? The personalization engine space uses several acronyms that may seem daunting, so we're here to help. You can find definitions to the most common e-commerce customer experience optimization terms here!

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Individualization

Every shopper is a unique individual. Every shopper is their segment.

Shoppers, products, product attributes, and actions have to be mapped at an individual level to create a unique Style Profile for every shopper. This can be used across channels to create a unique journey for every shopper.

This is 1:1 personalization.

Every eCommerce site has 3 components: shoppers, products, and actions the shoppers take.

Let us take the case of 10 shoppers on the same eCommerce site which sells 30 dresses. For every product, there are around 10 actions each shopper can take, which are click to view (to view the product description page), buy now, add to cart, add to wishlist, change the size, change color, click on a similar item (from the items similar to this widget), click on a frequently bought with item, back (the back button on the browser), close (closing the tab), etc.

10 shoppers can each take any of 10 actions on each of the 30 items. This means 3000 possibilities can happen.

Typically, eCommerce sites attempt to bucket shoppers who take similar actions into a segment, For example, if 3 out of the 10 shoppers added dress #8 to the cart, they will be put in one segment. Further, the eCommerce retailer will retarget these shoppers with ads across all channels with images of dress #8 and dresses visually similar to it. Sounds logical, right?

But what if I told you that dress #8 was a knee-length, turquoise blue dress with a scoop neck and shopper #1 had clicked on every knee-length dress on the site, shopper #2 had clicked on dresses in different shades of blue, and shopper #3 had clicked on scoop neck dresses? This means that 3 different shoppers liked the same dress for 3 completely unrelated reasons.

If the eCommerce retailer captured the affinities of each of the shoppers, they would have sent shopper #1 knee-length dresses, shopper #2 blue dresses, and shopper #3 scoop neck dresses. This affinity could have been captured if every click of the shopper was tracked.

Retail personalization, powered by AI delivers a unique experience to every shopper optimized for greater engagement and higher conversion. Every shopper sees a distinct version of the eCommerce site which is dynamically personalized right from the first click. This experience is then delivered at scale to every single shopper across all touchpoints and channels.

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