Retail Blinks Series: Optimize Your Brand’s Range

Optimize Your Brand’s Range

Manufacturers often miss growth opportunities with their retailer through this one factor:

Their Brand’s Range.
Shelf space has always been considered a key driver of sales and brand awareness – at least against competing brands.


With major Shopper behavior changes during the last 12 months, the importance of space productivity has been increasing drastically.

Retailers are reacting and adapting their own range quickly, based on shoppers’ spending changes.

So here is the dilemma:

Shall a Brand maintain a long assortment tail with high risk of decreasing my brand’s effectiveness and finally seeing my low selling SKUs – and space – cut by the retailer?
be proactive in cutting low selling SKUs to provide more space to my better selling SKUs?

Consider the cost of maintaining low selling SKUs on a shelf: Delivery, Returns, Activation costs…

On the other hand, being proactive on my Brand’s Range delivers huge benefits:

• Additional space justified by additional sales
• Increased availability
• More flexibility to launch and try new items‍

On Hypertrade Data Collaboration Platform, we use 2 simple metrics that must be checked monthly.

1. The average number of SKU sold by day by branch of the category [sub-category] of the retailer (A) and the same for the Brand (B).

2. A comparison between the Brand’s share of SKU (A) and its share of sales (B).

In both cases, when (A) > (B) it is usually a sign that range optimisation or activation is required. What decision will you take?


Retail shorts is a series of practical practice sharing Hypertrades could learn, capture, implement and monitor across the diversity of our Clients.

We hope it helps!

Hypertrade is a Retail Data Collaboration Platform that provides tech, data and continuous retail expert support to turn your teams into Champions.

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With 30 years of retail expertise, Hypertrade supports retail players in implementing category management solutions & methodologies across the entire value chain, with data science and collaboration.

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