ittybittyusability

Sounds great in theory, but what about reality?

Part Two (P1 click here) of the discovery process is focused on looking at (auditing) real-world implementation of product recommender systems in various products and services.

What is a comparative audit and why do we do it?

User experience professionals conduct comparative audits in order to understand the problem/solution space being investigated. We often look for and capture competitive experiences (if applicable) BUT equally as important we look outside the competitive landscape to gain a more holistic view and understanding of the space

What is a Product Recommender System or Engine?

Recommendation Systems collect user, product, and contextual data, both on- and off-site, in order to predict products or services to a specific user. It is a technology that uses machine learning and artificial intelligence (AI) to generate product suggestions and predictive offers, such as special deals and discounts, tailored to each customer.

What is the best strategy for a Product Recommender system to achieve personalized recommendations?

In order to be able to run, one needs to learn to crawl first, then walk. The same for “personalized” recommendations. The key word here is “personalized.” Just like a new user is “new” (you’re only a new user once), a personalized recommendation can only be achieved after establishing a well known profile of the customer via segmentation, implicit and explicit data, etc.