How we enable BENT to prevent out-of-stock and overstock situations


BENT is a mid-size fashion retailer in Belgium. It has a growing presence, combining about twenty brick-and-mortar stores with its webshop. The latter has gained true momentum these past few years and has urged the retailer to further push efforts. The team was eager to step up the adoption of new technologies to continue on its path.

An end-of-season price markdown challenge

Each store keeps around 10.500 different types of shoes. Predicting the right amount of inventory needed per store, as for any sales forecast, is always challenging. Moreover, managing inventory has always been a time-intensive and cumbersome process for any retailer.

It has, however, become more important than ever to ensure that a sufficient number of items are in store when a sales opportunity presents itself. The potential customer, anxious for a fresh pair of shoes, has become less forgiving. Provided with the ability to shop online or check where to find these shoes close by, such a sale opportunity can be lost in the blink of an eye.

Yet, hoarding and piling up inventory has never been the right answer to ensure a customer walks out of the store happy and satisfied. The challenge is, therefore, twofold and equally entails safeguarding excessive inventory from piling up in one or more stores due to differences in sales.


How AI-driven recommendations can help

We provided the team at BENT with a customized inventory redistribution optimization solution running an adapted algorithm. The tool safeguards an ideal range of stock across 300.000 items and suggests what inventory should be moved and where.

When the solution recommends a shift, a single push of a button suffices to transfer the order directly into the ERP tool, activating the inventory transfer in due time.

Moreover, the application enables the team at BENT to predict further fluctuations and automate certain actions accordingly.


Hubspot blog photo - BENT  (800 x 419 px)


How successful is it?

Stores encountered fewer out-of-stock situations, growing the number of in-store sales (5%-10% increase in revenue). Shops piled up lesser stock, lowering the impact of unsold items on financials. 

But, more importantly, the time required to count stock and ensure the redistribution of items was substantially reduced, enabling the team to focus on more high-value tasks.


Download the full case

Learn more about how Only for Men was able to work more efficiently and effectively, using AI-driven price markdowns. Download the client case here.