Detecting Retail Out of Stock Issues-Case Study

This case study examines the challenge of detecting retail inventory issues. The presentation covers the detection technology, a background on how it was used in an actual project, and a discussion of lessons learned.
Retail out of stock
retail out of stock stock out

Our client is a retailer of personal care products like daily-use cosmetics and oral hygiene. Majority of the client’s inventory can be broadly classified into the following product categories: 

  • Shampoos, 
  • Face creams
  • Body lotions 
  • Soaps

The focal point of their business approach is to provide exceptional customer service, coupled with high-quality products and technical support.


Our client wanted to upgrade their shopping experience and improve the efficiency of their operations by incorporating the latest technologies. But the company faced difficulties in integrating advanced tools and technologies into their operations. A long-standing issue that they wanted to overcome was the inefficient detection of out-of-stock products. The client was not able to find a fitting resolution to their problem and as a result approached for feasible vision-based solutions.


  1. Lack of inventory control and visibility
  2. Consumer demands were not matched due to understocking
  3. They could not monitor out-of-stock products and fix inventory issues on time
  4. Ultimately our client lost sales because out of stock products and inaccurate inventory keeping

What made them choose

When we started working with our client, the first step was to audit the data used to predict out-of-stock products. After a careful examination of data, we identified several outliers. In addition to that, we also examined their SOPs and operational practices to sum up our reports and draw a conclusive outline. We then reviewed the gaps and explored possible solutions with our clients before ultimately deploying our out-of-stock solutions.

An Outstanding AI-Solution

Analysis of Shelf Models-Retail Out of Stock accuracy
Analysis of Shelf Models
Analysis of Object Models-Retail Out of Stock accuracy
Analysis of Object Models
  1. Visionify’s out-of-stock solutions enabled clients to monitor out-of-stock products on its entire portfolio of 40+ categories with the help of integrated cameras on aisles and shelves. 
  2. After deployment, the client was able to determine what product categories and SKUs had highest out-of-stock rates and how much money was lost due to it.
  3. Our model identified that the category of Shampoo products had the highest stock outage, topping the charts at 29%.
  4. With the help of our solution, the client was able to predict consumer demands and subsequently negotiate better inventory and supply terms with vendors. 
  5. Our client was able to enrich their customer experience and build long-lasting relationships with them.
  6. The company was able to increase sales and improve its bottom line.

How does our client feel?

Our client is delighted with the solution and the results we have provided. Our approach was highly praised by the client, especially the fact that our team was able to deliver on time with the promised budget. 


Out of Stock Sales Results
Analysis of Classification Mode
  • Our solution enabled the client to decrease the Out-of-Stock (OOS) rates. significantly 
  • The company has significantly improved its bottom line across product categories.
  • They can now assess inventory levels and find best categories to focus on by tracking sales data and consumer demand forecasts.
  • With better product availability and a deeper understanding of consumer patterns, they have increased their sales percentage for every category.