Get space optimized to local demand
A growing number of SKUs to choose from, limited shelf space, heterogeneous store characteristics, and the increasingly fragmented customer demand. All of these factors put pressure on retailers to satisfy the local demand.
Consumers have become more specific and more demanding as far as the products they want to consume, their qualities and prices. Consumers exhibit brand recall and top-of-mind instead of merely reaching out for the lowest price or what their local stores happen to stock. Success can no longer be achieved from mere value chain efficiency. Size class-based or cluster assortments aren’t enough to keep shoppers loyal.
Retailers can satisfy the local demand by finding an assortment for each store that is optimal from the point of view of demand in its trading area. An efficient space means fewer missed sales opportunities, less capital tied to over-stocking your products, and improved customer satisfaction.
Unikie’s Space Optimization leverages Artificial Intelligence, Machine Learning, and state-of-the-art predictive analytics to find the optimal space to each individual location.
Retail Chain Optimized space through AI & store digitalization
Using predictive analytics and AI, the solution provided the best assortment scenarios, visualized in the Digital Twin of the store. The optimized space delivered total sales growth of 13.62%, units sold grew by 5.37% leading to margin uplift of 13.71%.
Demand-driven space optimization guides you to carry products that people want to buy
Demand-driven retailing forecasts each location’s demand potential guiding you to manage space.
That’s the demand side, the full potential of each location to which the optimization engine is optimizing each assortment: Delisting long-tail SKUs, identifying and listing new SKUs that shoppers want, optimizing macro space for both shoppers’ convenience and the optimal category allocation.
Retailers applying demand-driven space optimization can enjoy over 20% improved profits, simultaneously gaining significant time-saving in every step of the process from planning to store implementation.
Increase your margins with demand-driven space optimization
Store space sets the boundaries for assortment. With macro space data, factual category space data, your tactics and business rules, you gain the capability to efficiently manage your stores.
Leveraging AI, ML and predictive analytics, we at Unikie ensure you will meet your local, store specific, shopper demand according to your strategy. You do not need to react to the market – you’ll start to drive it.
The benefits of moving from manual processes to data-driven, coherent and transparent workflow will empower everyone in your team to focus on more value-added things.
Assortment
In the short term, you can achieve sales and/or margin uplift by optimizing assortment to local demand. In the long term, you will implement new processes and tools that minimize the time needed to assortment work, freeing up time for innovative category development.
Space
In the long term, macro-level space planning will optimize your store space to further maximize sales and customer satisfaction.
Procurement
In the short term, you will be optimizing Net Working Capital via narrowing the long tail of SKUs. In the long term, you will gain a better view of the store coverage, and the utilization of customer demand improves your negotiation power.
How Hyperpersonalization Empowers Traditional Retailers in 2025
With AI, traditional retailers can now match and exceed those expectations — optimizing assortments, tailoring offers in real-time, and driving the market instead of reacting to it.
Frequently Asked Questions
Demand-driven space optimization focuses on the demand potential by trading area, guiding the optimization towards localized spaces and assortments according to retailer’s tactics and business rules.
Traditionally, retail chains have focused on the supply side, aiming to increase value chain efficiency whilst maintaining low, steady margins. Supply-driven retail analytics has its root in logistics analytics, aiming to optimize the flow-of-goods based on historical averages.
Demand-driven retail analytics, on the other hand, focuses on the demand side, the shoppers by trading area, aiming to optimize space to meet the full local demand potential.
Space optimization is a state-of-the-art service to optimize your store space.
It offers an End-to-End process that takes you all the way from sales predictions to executing your space scenarios in stores.
A Modular process is designed to manage and execute at an individual store level as well as clusters and chains of stores.
Space optimization leverages data from different data sources. The data typically includes a store, shelf, module, loyalty card, shopper, POS, product, etc. information which will be synchronized and enriched for the data model.
Space optimization leverages Machine Learning, state-of-the-art AI mathematical optimization model and predictive analytics – ensuring you meet your local, store specific shopper demand according to your strategy. You do not need to react to the market – you’ll start to drive it.
It enables you to optimize your store-specific spaces based on each store’s local demand. Secondly, it enables you to combine optimized store-specific assortment with each store’s true shelf space and optimize the space for each SKU based on your space management tactics and rules.
A mix of commercially available and open source technologies has been used. The process is currently run on either Microsoft Azure or AWS platforms. For optimization, IBM Decision Optimization (CPLEX) is utilized, providing advanced capabilities for solving complex decision problems.
