Talk:Planogram

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Proposed new section: Data representation

Hello, I'd like to propose a new section on how planograms are represented as data, to sit after "Placement methods". A draft with full citations is in my sandbox: User:J Finsbury/sandbox.

Rationale: the article describes what a planogram specifies but says nothing about how one is recorded or exchanged, how product data feeds it, or how compliance is verified. The draft covers those in about 200 words. Sources are peer-reviewed operations research and computer-vision papers (Hübner et al. 2021, European Journal of Operational Research; Tonioni & Di Stefano 2017, ICIAP; Laitala & Ruotsalainen 2023; Ou et al. 2025) plus two GS1 standards; no commercial software is named. Happy for anyone to use all, part or none of it, or to edit freely.

Proposed text, to be inserted as a new section immediately after "Placement methods" (identical to the sandbox):

Proposed section: Data representation

A planogram specifies where each product sits on a fixture and how many facings it has. It is produced in space-planning software and may be shared in a variety of formats, such as an image of the intended layout or a text file listing the products in order on each shelf. The plan records the fixtures and the shelves within them, with their widths, heights and depths. For each product it records its site on the shelf: the space allocated to it, the number of facings, how many units are stacked and how many stand behind each facing, together with rules such as minimum or maximum quantities set by the retailer. The product's own dimensions and images are held separately as master data, and the dimensions determine how many units fit that site. Standards such as GS1's define how height, width and depth are measured from a product's "default front", which may differ from how it is sited on the shelf, and how product images for space planning are captured, cropped and named. Approaches to automated analysis include representing a planogram as a graph in which each node is a facing and edges link neighbouring facings.

Plans are revised periodically, typically when the assortment changes or the space given to a category changes. Research on shelf planning has found that practice often relies on planners' experience and trial and error, and that fixture dimensions are frequently set by hand even where commercial software is used.

Checking compliance between the planned and actual shelf by computer vision, comparing photographs of the fixture with the planogram to find missing or wrongly sited products, is increasingly possible; one such system has been deployed across more than 7,000 stores of a single convenience chain.

References

J Finsbury (talk) 16:50, 6 September 2026 (UTC)

I've retagged this with the correct template, {{edit COI}}, per your userpage's declaration. AlphaBetaDeltaLambda(αβδλ)^talk 17:23, 6 September 2026 (UTC)

Thanks for fixing that, and apologies for the wrong template J Finsbury (talk) 17:44, 6 September 2026 (UTC)

Added to the article on 11 September, a week after posting, with no objections. Happy for anyone to review, edit or revert. J Finsbury (talk) 17:18, 11 September 2026 (UTC)

Proposed new section: History

I'd like to propose a short History section, to sit after "Overview". Full text with citations is in my sandbox: User:J Finsbury/sandbox.

It covers the research lineage (empirical studies from the 1960s, decision models from the 1970s), the first dictionary attestation of the word, and the arrival of PC-based planogram software by the early 1990s. Two historical software packages are named because the cited source names them; no current products are mentioned. Sources: Bianchi-Aguiar et al. 2021 (European Journal of Operational Research), Drèze et al. 1994 (Journal of Retailing), Merriam-Webster. Happy for anyone to edit or use part of it.

Proposed text, to be inserted as a new section immediately after "Overview" (identical to the sandbox):

Proposed section: History

Shelf space has been described as the retailer's scarcest resource since at least 1961. The first empirical studies of how shelf space affects sales date from the 1960s, and controlled experiments in supermarkets in the late 1960s and early 1970s found an average space elasticity of about 0.2, so that doubling a product's facings raised its sales by roughly a fifth. These findings were first applied in mathematical decision models in the early 1970s, and the number of published optimisation studies roughly doubled after 2000. A 2014 meta-analysis of 1,268 estimates put the average space elasticity at 17%.

Merriam-Webster dates the first known use of the word planogram to 1986. By the early 1990s, numerous personal-computer shelf-management systems were available to retailers, including Apollo from Information Resources and Spaceman from Nielsen; although they offered optimisation features, retailers used them mainly for "planogram accounting", reducing the time spent manually arranging shelves. Successor packages remain in use, and the research literature continues to note a gap between commercial software, which relies mainly on data processing with limited use of mathematical optimisation, and academic models.

References

J Finsbury (talk) 17:27, 11 September 2026 (UTC)

Added to the article today, a week after posting, with no objections. The opening was reworded slightly for readability and one sentence on space elasticity was left out, to go in "Placement methods" instead. Happy for anyone to review, edit or discuss. J Finsbury (talk) 12:28, 18 September 2026 (UTC)

Proposed replacement for "Placement methods"

I'd like to propose replacing the "Placement methods" section (both the "Visual" and "Commercial" subsections) with a section titled "Shelf space planning". The current section rests on a vendor blog and a Prezi presentation, both tagged since September, and contains an unsourced 15–30 cm figure. The replacement covers the same ground (position, facings, blocks, commercial placement) and adds what the current text omits: stock availability, merchandising rules, supplier agreements, and how plans are produced in practice.

Twelve sources: operations research reviews (Bianchi-Aguiar et al. 2021 and Hübner et al. 2021, European Journal of Operational Research), marketing science (Drèze et al. 1994; Chandon et al. 2009, Journal of Marketing; Eisend 2014, Journal of Retailing), Gruen and Corsten's industry study of out-of-stocks and their Harvard Business Review summary, two Federal Trade Commission documents on slotting and category captains, a Center for Science in the Public Interest report, a doctoral thesis and an Interfaces practice paper. No commercial software is named. Happy for anyone to edit or use part of it.

Proposed text, to replace "Placement methods" in full:

Proposed section: Shelf space planning

A planogram is the output of shelf space planning, the stage of category management that follows the choice of assortment and precedes decisions about replenishment. Retailers usually fix how much space a category receives within the store first, then plan the products within it. For each product the planner, generally called a merchandiser, decides how much space it receives and in how many facings, which shelf it sits on, where on the shelf it goes, what stands beside it and which way it faces. The fixtures themselves are typically treated as fixed, since retailers rarely alter shelving when reallocating products.

Demand

Experiments since the 1960s have shown that a product sells more when given more facings, with diminishing returns; a meta-analysis of 1,268 estimates put the average space elasticity at 17%. Position matters at least as much. One field study found that average sales rose by 39% between the worst and best shelf height, by 15% between the worst and best horizontal position, and by 59% when both were combined, and another found products on the top shelf 17% more likely to be noticed and 20% more likely to be chosen than those on the bottom. Products between roughly eye and knee level are the most likely to be seen, and horizontal position has a weaker effect than height. Arranging related products in families and rectangular blocks increases attention, although excessive visual complexity reduces it. Only about 30% of purchase decisions are settled before a shopper enters the store, which is why placement carries this weight.

Availability

The number of facings and the units held behind each facing together determine how much stock the shelf holds, and therefore how often it must be refilled and how likely it is to run empty. Running out is costly. Out-of-stock rates for fast-moving consumer goods have stayed at around 8% since at least the mid-1990s; when a product is missing, fewer than half of shoppers buy a substitute and nearly a third go to another store, retailers lose around 4% of sales as a result, and and about three quarters of stock-outs are caused by practices within the store, such as ordering errors and shelves not being refilled from the backroom, rather than by upstream supply problems. Planners therefore set minimum quantities and safety stock for each product, and may give a product more facings than its sales alone would justify so that enough stock is held between deliveries; perishables carry upper limits instead, to limit how long stock sits on the shelf. One study concluded that once enough stock is held to avoid running out, position affects sales more than additional facings do.

Rules and agreements

Demand and availability are balanced against merchandising rules and commercial commitments. Rules keep products of the same brand or type together in blocks, fix the order in which they appear, and place heavy or bulky items on lower shelves. Minimum facings may be set for newly listed products so that they have a chance to establish themselves, and maximums for strong sellers to leave room for the rest of the range. Suppliers also shape the plan. Retailers may commit to shelf shares in supply agreements, charge slotting fees for placing new products, and appoint a leading supplier as category captain to advise on, and sometimes draft, the planogram for a category, a practice that has drawn scrutiny from competition regulators. Secondary placements, such as gondola ends, are often planned separately from the main fixture.

Practice

Because fixture widths can differ between stores, retailers may plan a template for a cluster of similar stores and derive store-specific versions from it. Mathematical models that weigh these factors have existed since the 1970s, but planning in practice still relies heavily on planners' experience and trial and error, and commercial software is used mainly to draw, adjust and replicate plans rather than to optimise them. Research has turned to tailoring plans to individual stores with differing demand, and to applying predictive analytics to the forecasts that feed them.

References

J Finsbury (talk) 18:03, 18 September 2026 (UTC)