Space-to-sales and share-of-shelf analysis

The problem, in the words we usually hear

"We think we're under-spaced, but all we have is a feeling." "The buyer asked why we should get more facings and we didn't have a clear answer." "We have the sales data and the planogram, but they live in different files and nobody has put them together."

A request for more facings is much easier to discuss when both sides are looking at the same numbers. Without them, the conversation tends to rest on opinion. With them, it rests on a shared description of the shelf that either party can check.

What is measured

The analysis looks at a small number of well-understood measures, calculated per item and rolled up by brand or segment:

• Facings: how many units face the shopper on the shelf
• Linear space: the shelf width each item or brand occupies
• Velocity: units sold over the period in the data supplied
• Velocity per facing: sales rate divided by facings, a simple way to compare how hard each facing is working
• Share of shelf: each brand's portion of the section's linear space or facings
• Share of sales: each brand's portion of the section's sales in the same data

Comparing share of shelf with share of sales shows where space and sales are in line and where they diverge. A brand whose share of sales is well above its share of shelf may be under-spaced; one whose share of shelf is well above its share of sales may have more space than its sales support. Those are observations, not conclusions: assortment roles, margin, promotions, out-of-stocks and new-item launches can all explain a gap.

How the work runs in an engagement

Inputs usually include the item list, dimensions, current facings (or a set we build from photos), and velocity data by item for a defined period. Velocity must come from real point-of-sale or syndicated data that you supply; Planogrammer does not estimate it, and items without data are shown as having no data rather than filled in.

Planogrammer is not self-serve software. GOODS consultants build the sets inside a consulting engagement, so the inputs go to a person who asks follow-up questions rather than a form that silently accepts whatever it is given.

We match each velocity row to an item in the set, flag anything that does not match cleanly, and then run the measures on the current set. If you have a proposed set, we run the same measures on it so both can be compared.

What the deliverable looks like

The analytics overlay puts share of shelf and velocity directly onto the 3D render, and a heat map can colour each item's planned space by its sales rate. That makes it easy to see where high- and low-velocity items sit on the shelf, not just what the totals are.

Alongside the visuals you get the underlying table, so every number on the image can be traced back to an input. The written summary lists observations such as where share of shelf and share of sales diverge, which items have unusually high or low velocity per facing, and how a proposed set would change those measures. It does not forecast sales or promise a result from any change.

Related work

Space-to-sales views are most often used alongside a buyer presentation or a reset proposal, where facing counts are the question being decided. They are also the natural bridge into a wider analytics project for brands that want to go further.