Navigating Sustainable, Profitable Growth in a Rapidly Changing World
The global assortment and space optimisation (ASO) market is expected to be driven by the need to make effective product assortment decisions, especially under constraints such as limited shelf space or budgetary limitations. Growth in cloud computing, big data and artificial intelligence (AI) offers merchants the chance and the capability to timely carry out assortment and optimisation better aligned to customer needs and behaviours, increasing merchants’ chances of earning better profits. Advanced solutions offer deeper insights into consumer behaviour, purchase decisions, and changes in the market. Such solutions are likely to stimulate the market. North America, Europe and Asia are expected to be key markets.
Over the last few decades, assortment and space optimisation (ASO) has evolved to become a heavily data-driven analytical process from a simple intuitive exercise. Indeed, analytical and business processes have also evolved with time; the change brought about by technological developments (in terms of their impact on business operations) and their increasing adoption have led to more data-driven decision making for assortment and space optimisation (ASO).
Several major players have adopted assortment and space optimisation (ASO) solutions to offer better experiences to shoppers and maximize profits. For example, in 2021, Kantar launched Richmix eAssort to enhance ecommerce growth. RichMix, an assortment optimisation tool used transferable demand curves to determine the incremental impact of altering items and facings in a retailer’s mix to maximize growth. The solution used machine learning-based predictive modelling to draw a granular view products and tactics likely to witness greatest growth in the ecommerce environment. The launch sought to strengthen the company’s portfolio in the assortment and space optimisation SaaS market.
In 2018, Oracle Retail introduced a new Oracle Retail Assortment and Item Planning Cloud Service for fashion and soft line retailers. The service provided a framework of best practices for retailers while equipping business analysts with advanced analytics and data science that enhanced the accuracy of assortment and item planning; it offered retailers a rich visual, end-to-end workflow to define and execute local market assortments.
In 2021, Makro Brazil and Colombia implemented AI powered Assortment Optimisation from Symphony RetailAI. Employing machine learning and AI, Symphony RetailAI’s assortment optimisation solution analysed consumer data, identified buying preferences, product and brand loyalty, and change in demand. The solution was expected to help in offering more personalized shopping experiences to shoppers.
In 2017, DIA selected Symphony GOLD Store and Category Space Optimisation solutions to be able to better manage shelf space across its locations and different formats throughout Spain, Portugal, Brazil, Argentina and China.
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Key Findings of the Report:
- Growing number of SKUs and decreasing spaces have led to greater adoption of effective assortment and space optimisation (ASO). This trend is expected to help market growth.
- Advancements in cloud computing, big data and AI are expected to contribute to market growth.
- North America, Europe and Asia are projected to be key markets.
Market Analysis by Component, Deployment, Enterprise Size and Region:
- By component, the market is segmented into solutions and services.
- By deployment, the market is classified into on-premises and cloud.
- By enterprise size, the market is divided into large enterprises, and small and medium sized enterprises.
- By region, the market is segmented into North America, Europe, Asia Pacific, Latin America, and Middle East and Africa.
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Report Summary
| REPORT FEATURES | DETAILS |
| Base Year | 2025 |
| Historical Period | 2019-2025 |
| Forecast Period | 2026-2035 |
| Scope of the Report |
Historical and Forecast Trends, Industry Drivers and Constraints, Historical and Forecast Market Analysis by Segment:
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| Breakup by Component |
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