Why are store specific planograms better than cluster specific?

Planograms have been a proven method of managing product displays in stores for decades.

Creating planograms using the conventional systems usually means defining a specific space of a certain category as a set of shelves with specific dimensions and then more or less manually filling this space with products.

This means that the more space variants we have, the more manual work is involved in managing the planograms. 

In addition, if we want to optimize the number of faces of each product within one space variant based on the sales of a particular store, or even add some products and remove others, we would have to manually manage almost as many planograms for each category as we have stores.

Since managing thousands of separate planograms means an unacceptable amount of human resource costs in the conventional systems, the method of creating cluster specific planograms was developed.

Cluster specific planograms

Cluster specific planograms are the way to manage product displays in hundreds of stores of large retailers.

The idea is to divide stores into clusters based on size and demographics, such as in the following table:

For the combination of cluster and category, a space is then defined and a planogram is drawn, which is sent to all stores of the corresponding cluster.

This approach works quite well for unified store networks where cluster numbers are relatively small, but can quickly get out of hand in non-unified networks.

In our example, where we divided the stores by size and location, we ended up with 12 clusters. If we also added, for example, a division by average customer purchasing power – low, medium, high – we would have gotten to a hard-to-manage 36 clusters.

Moreover, when creating cluster-specific planograms, there is no capacity to deal with different dimensions of sales equipment within the same cluster, so stores often receive a planogram that does not exactly match the dimensions and have to improvise.

Store specific planograms

Store specific planograms in Quant enhance the concept of sharing the same planogram within a cluster by automatically generating optimized store specific planogram for each store.

Quant's artificial intelligence takes a planogram template created by a user for a given cluster and tailors it to the exact space of each store based on product sales of that store.

Optimization takes into account many other aspects besides available space:

• sales history,
• demand forecast,
• logistical parameters such as the number of days we have to hold the capacity allocated to the product within the display,
• events and promotions,
• product priorities,
• availability of products at a given store,
• …

If necessary, Quant is able to determine that a product on the planogram is not available at a particular store and automatically select the most similar available replacement for it that is not already on the planogram.

Thanks to automatic optimization, not so detailed clustering is needed. In fact, the only necessary separation criteria are the space variants within a given category.  

If we have 2 beverage fixtures with 6 shelves in some stores and 3 fixtures with 5 shelves in others, we need to create 2 planogram variants for these two space variants. Artificial intelligence and automatic optimization in Quant will take care of the rest.

Key benefits of store specific planograms

• The allocation of space according to local demand and the frequency of deliveries significantly reduces the workload on the store staff in terms of replenishing shelves from the handy store. 
• Fast-moving goods are allocated adequate space, improving availability by 1–3% and minimising the risk of outages. This results in up to 5% higher overall sales.
• Slow-moving goods do not build up overstocks just to meet the planogram, reducing the total value of inventory often by more than 5%.

Quant's Planogram Software module has been able to automatically generate store specific planograms from templates for almost 20 years. We are constantly improving our algorithms based on user feedback. Hundreds of thousands of store specific planograms are created every month in Quant and then implemented in stores in more than 30 countries.