OPTIMIZE BUYING
Initial Buy Optimization
Create a collection that sells, matching a buyer's experience and feel for fashion with AI-driven item recommendations. Discover relationships between different products and product groups, understand what sizes to combine, and start creating channel-specific assortment.
![Hero - Initial Buy Optimization Hero - Initial Buy Optimization](https://www.crunch.fashion/hubfs/Platform%20Pictures/Hero%20-%20Initial%20Buy%20Optimization.jpg)
Our platform is used by fashion industry leaders such as
![g-star-raw](https://www.crunch.fashion/hubfs/g-star-raw.png)
![scotch-soda-logo](https://www.crunch.fashion/hubfs/Client%20Logo/scotch-soda-logo.png)
![Torfs 254](https://www.crunch.fashion/hubfs/Client%20Logo/Torfs%20254.png)
![Vandevelde 254](https://www.crunch.fashion/hubfs/Client%20Logo/Vandevelde%20254.png)
Why?
Why do fashion retail teams need AI-driven item recommendations?
Fashion retailers often struggle with item fail rates of up to 60%. Understanding what item will sell well is complex and uncertain. By extracting patterns from datasets such as data on previous items sold, trends and current sales, AI-driven tooling can help decide on what items to combine to create a winning collection.
![Group 17 Group 17](https://www.crunch.fashion/hubfs/Group%2017.png)