The way products are displayed across 'Categories,' 'Collections' and 'Search results' influence what customers see and are likely to buy. In visual merchandising, online retailers rely on historical data and manually sort products based on their analysis of the same data. This analysis also tends to vary from person to person. This has a direct impact on the effectiveness of merchandising, visitor engagement on products and is time-consuming. Merchants spend time sorting products into a position across multiple listing pages, for e.g., a 'Winter Collection,’ a ‘Summer Collection,’ ‘An on-going sale,' etc.
The Solution: Intelligent product sorting with automation to meet growing demands in visual merchandising
Tagalys automates the process of visual merchandising by assigning a score to each product every day, based on the previous 30 days of visitor engagement data. This analysis combines engagement data from our own analytics with product catalog data, to give both new and old products a normalized score every day.
The T-score includes three components -‘Product Score, Tag Score, Date Score,’ which are based on visitor engagement data, and the merchant can influence the T Score using a 'Global Boost'
Enabling dynamic intelligent sorting across 'Categories,' 'Collections,' and 'Search' results to improve visitor engagement
The T-Score ensures that products - both old and new are given visibility based on their ranking, and this is done automatically without manual input that would otherwise have to be carried out every single day.
To learn about how the trending sort order can help your online store, set up a free onboarding session using link.