Successful Retail Store Spaces In 5 Steps

Successful Retail Store Spaces In 5 Steps
March 17, 2021 Omnibus

Floor space management or organization of product categories decisively impacts buyers’ decision-making within the physical stores.

Well-organized store layout provides not only easier store navigation but also increases shopping basket size.

Without any exaggeration, we might call floor space management the key variable of retail success and overall store profitability.

One little reservation has to be added. Precautionary: Space management isn’t an isolated activity. It’s a part of the retail system and thus intrinsically connected to other retail variables. Fundamentally speaking: The sales start and end with something of value for the customers. No shoppers, no sales. If consumers don’t trust retailer’s brand or price / quality perception is low or assortment sucks, retailer can make space management miracles without any real effects. But considering you’re at least average on other variables, space management has decisive effects on store performance.

For years, I’ve been developing store formats, and preparing store layouts for retailers of different formats and branches (from pop-up bookstore to national grocery hypermarkets). That gave me the opportunity to study in-store customer behaviour, make actionable insights based on data, and also to work with different project teams – from interior designers & architects to data scientists. All the while, I’ve been gathering feedback, making A/B testing and trying to improve the process. Thus, I’ve developed a method named #levers for successful store spaces.

Recent proof of #levers came through the remodeling of a supermarket that brought significant improvements in all key performance indicators: 18% more sales, 31% less inventory, higher stock turnover, not to mention increased profitability of sales space.

An essential part of the #levers is also a process of preparing quality – user-friendly and tactically enhanced – store layouts. Here is how.


First, you have to firmly grasp the whole assortment = offer you provide (or plan to provide) in your retail space.

This is not a physical but a conceptual grasping. Just make sure that you have all the products listed and possibly classified into categories.

The main tool for such an overview is called Customer Decision Tree (CDT).

It joins similar products and services into categories, then sorts them into a hierarchy based on customers’ buying habits, wants, and needs.

Let’s take coffee as an example.

Category: COFFEE

Under the umbrella, we put everything shoppers associate as coffee.

Of course, for micro-planning we make further segmentations on the sub-category level: ground coffee, instant coffee, decaf, beans, cappuccino, craft, organic etc. For the explanation purposes, let’s just add there might be more levels of sub-categories. Say, price-level: premium, main-stream, low-budget. All this is a category management stuff.

But as here we are into store layouts (macroplanning), let’s move a level up the ladder.


Here coffee is joined together with tea, hot chocolate, and milky drinks. The product categories that solve the similar need to a shopper.

One level up is …


We can put it in one or another section for now, but the final decision depends on the store channel or store strategy.

One further level up is …


The departments in supermarkets are usually larger groups. Beside packaged food, there might be departments like non-food, seasonal products, fresh food, deli, household etc.

So, the hierarchy bottom-up goes like this:

SKU ⇒ brand ⇒ ground coffee ⇒ coffee ⇒ hot drinks ⇒ food for breakfast ⇒ packaged food ⇒ food

Sample of a Customer Decision Tree (c) Omnibus 2021. You can see how each category gets 2 values – % of sales and % of space


After the tree is built and all the categories are well placed within the hierarchy, it’s time to add the data.

  1. Sales data

Margin, ROI, sales revenue, volume, trend are the usual indicators. If possible, start with the data on an SKU (article) level, then group it into sub-categories and category levels. Then you can move further up the tree.

For grocery, the top levels might be Fresh Food, Packaged Food, Non-Food, and Services.

  1. Space data

Now you have to join all the elements of the tree with shelf space (m) or store area (m2) information. According to sales data, you will calculate proportional % shelf space. We can call it space-to-sales or space-to-movement. From our experience, we usually start with an average value between volume and value sold.

In general: if category X has 10% sales share and category Y 5% -> then category X should have twice as much space as category Y.


With the CDT clearly established and the basic statistical analysis behind us, it’s time to power up the space recommendations with the proper tactics.

Basically, we want to leverage predictable patterns of customer behaviour for reaching our strategic retail goals.

#levers provide a whole set of tactical tools, rules, and methods based on shopper insights you can apply. Our product #leverages defines 10 key tactics that help you impact store KPIs. More information is available via our free web-based #levers demo. At this place, we’ll just describe some factors that should be considered for setting proper tactical decisions.


Let’s say category Y represents organic products in a grocery store. As such, it might be strategically important as organic associates health, quality, value, etc. In that case, we will assign the above proportional share of space to that category.


Each product category should have the proper role designed. This is always made in relation to the overall retail strategy.

If coffee is your destination category in which you’d like to differentiate from competitors, then you should probably have a wide or/and deep assortment of coffee products, underpinned with more than average shelf space. Of course, expanding on one side means shrinking on the other. Some other categories’ space should be sacrificed. A bit like rolling Rubik cube, yes. When you make a move all the other positions also change.


For each category, you should consider whether the shoppers’ buying decisions are more of an intent-driven or impulse nature.

Impulse categories are the ones where “a consumer experiences a sudden, often powerful and persistent urge to buy something immediately” (Rook, 1987).  Might be salty snacks, carbonated soft drinks, but also shoes (notorious fact: a collection of Imelda Marcos consisted of 3000 pairs of shoes, pure impulse!).

In general, impulse categories are shelf space elastic. By extending the shelf space by 10% you increase sales of the category above 10%.

On the other hand, you might see that motivation for buying other categories is more intent-driven (planned). Often these categories are spatial inelastic not so responsive to shelf space.

Based on the division of products on unplanned (impulse) and planned (intent-driven) we can define a good tactical plan for space organizations. It should:

– decrease the unnecessary space for inelastic categories and increase the space for upward elastic categories

– decrease the unnecessary space for intent-driven categories and increase the space for impulse categories.

Finding the right balance between extending space for elastic categories and shrinking space for inelastic is more and more possible by using A/B tests in a real environment. Proper use significantly impacts the shopping basket and overall sales.


It’s also very important to discern seasonality patterns. Some categories – like candles or toys or chocolate boxes – make most of the sales during one or two particular months within the year. It doesn’t make sense to assign the shelf space according to yearly levels of sales. It’s much smarter to assign lower shelf presence during regular months and extend the space drastically during the seasonal months (by using flexible temporary displays for example).

With tactically boosted CDT, you are ready for the next step.


The result of a good sales to space model are recommended levels of shelf space for each category in CDT. Now let’s grab all the categories and move them into a floor plan.

But what kind of special tool allows this drawing of the space floor plan?

Actually, all retail space management software / solution packages provide modules for this. The author of this article is familiar with the following: JDA, Symphony (former Intactix, Aldata), Nielsen Spaceman, Planorama, DotActiv, and Iantech’s Prisma. Depends on your preferences, budget, people onboard.

While the specialized software solutions provide advanced analytical tools, even plain old Excel works for some retailers. As Chinese leaders say: it doesn’t matter what color the cat is as long as the cat catches mice! That’s also the motto for our sales to space mathematical model #leverages.

First, you might lay out the space for the higher hierarchical levels from CDT.

For groceries, you might start with Packaged Food, Fresh Food, and Non-Food departments then spread the space accordingly to lower hierarchical elements.

When we do this, we encounter another important space lever: relative position of a category regarding main traffic flow heavily influences the success of the sales.

Intent-driven or planned categories, generally not very responsive to shelf space (low space elasticity), are not very responsive to store traffic.

On the other hand, moving the carbonated soft drinks section (heavy impulse category) on the main aisle with a full frontal access might triple the category shopping basket share.

For better results, you should use different shopper insights. From past observational data to more specialized in-store shopping behaviour research like our unique shopping paths research where we traced paths of shopping carts.


With the well-organized and tactically enhanced store layout, you’re ready to make an action plan, prepare a timetable, and implement.

Don’t forget to measure, learn and improve. After all, this is your pilot store. The one that will soon spread the gains over the whole chain of your stores.


We can help retailers from different branches in every step of the process summarized above.

From preparing a solid Consumer Decision Tree to providing floor space analysis for actionable improvements.

Our product #levers is a synthesis of years of experience, knowledge gathering, best practices, and also constantly observing shoppers and gaining practical feedback from store managers and others. It provides a method and mathematical model which heavily leans on CDT and shopper insights. It is open to adding parameters and comparing the data from different viewpoints.

Moreover: #levers is a process that structures the roadmap thet gets your team from concept to store remodeling.

If you’d like to learn more, you can join our May and June 2021 45-minute online webinar where we will demonstrate the model on a case. Sessions are free but you might gain unique insights for your purposes. Book your space soon as we’ll limit the number of visitors to provide a better experience.

How do you book a free webinar? Just use our contact form and put JOIN FREE WEBINAR as a subject. After that, we’ll provide you with the details together with free pdf material.

Of course, if you need to transform your retail space or need to improve on a particular space management issue, you might enroll in our workshops. We lead you through the process – from organizing input data to creating and positioning new space initiatives – and help you and your team build a pilot store step-by-step.



Hey. Would you like to learn more and put the knowledge at work in your own project?

From January to March 2023 I have time slots available for individual online courses. Entrance available up to 31.12.2022.

It’s individual, full of personal feedback, and we’ll develop a learning plan suitable for your own needs.

(Maybe you own a little store, or want to develop own skills or skills of your team members, or even get into independent consultant business)

If you’d like to join, don’t hesitate and contact me up to 31.12.2022 by filling this simple form.



  1. Rizka Firdhayanti 7 months ago

    thanks for information

    • Author
      Omnibus 2 months ago

      Hi Rizka. Thank you. Always good to get a feedback!

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