“Capture lost sales & improve customer experience.”
By applying patented machine learning, CB4’s software leverages POS data to detect in-store operational issues affecting items with high local demand, helping employees capture lost sales. This results in better customer experience, higher sales, fewer expenses, time-consuming store walks, and more tim to focus on the highest ROI tasks.
Every retail chain experiences operational issues that affect in-store sales. No matter how sophisticated the operations & IT teams, or how motivated the selling floor staff is, products are misplaced, promotions are not always executed, and top selling items are left in the stockroom. This is where CB4 comes in.
CB4’s technology is based on proprietary data-compression algorithms that can automatically capture the local demand patterns at each store, regardless of their affecting factors. Detected patterns are not bound by assumptions on how stores are segmented or clustered, or how various internal and external factors affect the demand behavior locally.
CB4’s algorithms automatically detect similar demand patterns among products and stores, regardless of whether those products were purchased together by the same customer (‘basket analysis’) in specific stores. The algorithms automatically identify the related ‘fuzzy-clustered’ patterns and define an exact sales benchmark for target products at each store. It then generates recommendations based on anomalies and unmet opportunities that are detected for specific products in specific stores.
On CB4’S algorithm:
It is CB4’s mission to provide their customers with the most advance machine learning, and pattern recognition solutions in the industry. With an emphasis on solutions. This means insights translated into actions and ROI measured in a straightforward way.
The team strives to build revolutionary yet simple solutions that empower retail teams with prescriptive analytics, powered by AI and machine learning. CB4’s solutions, allow retailers to better understand and serve their customers.