- super flexible data model based on category level
- no additional software needed (perfectly fits as an interface to different solutions)
- works with or without planograms
- further improvement with machine learning provided
- possible upgrade for specific strategies
- smart store planning to leverage on elastic categories
- combine past data with the creative future prediction for incremental value
- includes findings from in-store customer research to increase shopping basket
- be “good enough” on unelastic categories & differentiate boldly on elastic categories that support your point of sale strategy
- emphasize strategically important destination categories
- let space create a remarkable retail environment
- choose one of the different tactical scenarios that are right for your retail goals
CASE #1 STUDY
In 2019, our retail partner wanted to stop the slight but lasting downfall of the grocery store in a highly competitive environment of one of the major Slovenian cities.
For the remodeling of a grocery store (1.700 square meters), we analyzed the situation based on Smart Store Layout model & methodology. Together with the partner’s project team, we set bold initial hypotheses which served as an input to Smart Store Layout model algorithm. On the basis of Smart Store Layout recommendations, a new store layout was prepared. Shelf space decreased, clear shopping paths have been established, easier store navigation introduced & the categories laid out in a thoroughly different way.
One year and one corona later we can firmly claim that most of the model suggestions were correct. Over-stocked & slow-moving categories have been very effectively substituted with growing and more impulse-purchase based categories.
The reduced shelf space resulted in an overall stock decrease of 8% and profitability increased of 5%! Space profitability increased by 20%. In some top categories, we reduced the stock level to 1/3 of the former level without any negative impact on overall sales. The space freed has been leveraged for growing, high-margin categories. The model is also very useful for targeting particular destination categories: healthy and organic products increased by more than 25% (above comparable stores).
Through the next cycle of iteration, we already tapped into the new potential for higher profitability, better customer satisfaction, and even faster stock turnover.
In the midst of the first corona wave, another supermarket was remodelled according to the model. Despite all the outside turbulences, the “Case #2” gave even better results than the first one. Now, with half year of results behind us, we have a very solid case in hands. If interested, send us an email note and we’ll send you a free 2-page document with “Case #2” description.
In-built scenarios help get initial space recommendations quickly. Later, we can adjust and fine-tune “volumes” of parameters for specific situation.
Workshop environment helps us leverage your team capabilities, powerful analytics and knowledge from the past projects.
Together, it blends in a unique product that leads to the space optimization and innovation model fitting your own retail strategy!
Either play with the model on your own or try our step-by-step workshop environment. It’s your retail game!
Quickstart with analysis and get first space recommendations. Then develop your concept and remodel your store against it. Yes, it will work!
We can provide either elementary support or full concept development with Auto Cads.
Some additional features included
GETTING STARTED IS EASY
Book an initial
FREE 30-MINUTE DISCUSSION DATE
in which we’ll discuss your needs and define the situation.
After the discussion, you’ll get our proposal with a timeline.
— STORIES MEET AND VIOLATE THE LISTENERS EXPECTATIONS Remember a good crime story, maybe a detective…
Our shopping missions are based on shopping goals. For the grocery stores, some regular shopping mission…
Kako iz poplave današnjih podatkov izvleči uvide, ki kažejo vzorce vedenja kupcev na povsem nov način? Dobavitelj, ki bo k podatkovnim uvidom sistematično pristopil, bo ustvaril veliko konkurenčno prednost. Poleg tega bo izstopil iz rutinskega plačevanja prispevkov in skupaj s trgovcem ustvaril novo vrednost.
Dobavitelji lahko s projekti dodane vrednosti uspešno okrepijo vezi s trgovci. Ključno je prepoznavanje težav trgovcev (pain points) in generiranje podatkovnih uvidov, ki pomagajo razrešiti problem.