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市場調查報告書
商品編碼
1755967
2032 年分類和空間最佳化市場預測:按解決方案、部署模式、應用和區域進行的全球分析Assortment and Space Optimization Market Forecasts to 2032 - Global Analysis By Solution, Deployment Mode, Application and By Geography |
根據 Stratistics MRC 的數據,全球分類和空間最佳化市場預計在 2025 年達到 23.6 億美元,預計到 2032 年將達到 53.5 億美元,預測期內的複合年成長率為 12.42%。
選擇理想的產品組合(商品組合)並將其有效地安排在可用的零售空間中(空間最佳化),以最佳化銷售額和客戶滿意度,這一策略流程被稱為「商品組合和空間最佳化」。決定在商店或線上銷售哪些產品、數量以及在何處擺放,需要考慮顧客需求、產品性能和可用空間。最終,該策略能夠幫助零售商提高存貨周轉、減少缺貨並改善購物體驗,進而盈利和營運效率。
數據主導零售規劃的需求不斷增加
零售商擴大使用進階分析來了解顧客的偏好和行為。這使他們能夠更好地根據目標市場定製商品組合,從而提高顧客滿意度和銷售額。最佳化的空間配置可以降低庫存成本並提高貨架效率。數據驅動的洞察還能使零售商快速回應季節和市場趨勢。這項策略提升了零售業的競爭優勢和營運效率。
部署成本高且整合複雜
由於技術、軟體和熟練員工所需的巨額支出,財務障礙隨之而來。這些解決方案必須與現有的IT基礎設施無縫整合,而整合的複雜性又進一步增加了難度。這種複雜性增加了實施時間,並增加了業務中斷的可能性。企業可能面臨人員配備、系統相容性和資料遷移方面的挑戰。這些因素共同降低了接受度,並阻礙了消費者的投資。
全通路零售的興起
技術、軟體和熟練員工所需的巨額支出造成了財務障礙。這些解決方案必須與現有的IT基礎設施無縫整合,這又增加了整合的複雜性。這種複雜性增加了業務中斷的可能性,並延長了實施時間。公司可能在員工培訓、系統相容性和資料遷移方面遇到困難。這些因素共同限制了採用率,阻礙了消費者投資,並阻礙了更廣泛的市場擴張。
資料隱私問題和監管壓力
由於遵守CCPA和GDPR等法規帶來的營運複雜性和成本增加,技術採用速度放緩。這些法律約束限制了資料分析的廣度和深度,從而降低了最佳化解決方案的準確性。許多組織也難以獲得客戶同意並維護資料安全,這可能會延遲計劃執行。此外,一些參與者由於擔心製裁和聲譽受損,不願充分利用先進的數據驅動技術。整體而言,資料隱私法是阻礙產業創新和繁榮發展的一大障礙。
COVID-19的影響
新冠疫情擾亂了全球零售營運、供應鏈和消費行為,對商品組合和空間最佳化市場產生了重大影響。零售商在管理庫存和根據需求突變調整商品組合方面面臨挑戰。門市關閉和客流量減少加速了對數據主導的空間最佳化工具的需求。在電子商務蓬勃發展的背景下,企業採用先進的分析和人工智慧主導的解決方案來改善貨架規劃和商品組合策略,確保在快速變化的零售環境中保持業務效率和客戶滿意度。
預測期內,分類最佳化部分預計將實現最大幅度成長
預計品類最佳化細分市場將在預測期內佔據最大市場佔有率,這得益於能夠為客戶帶來最大盈利的合理商品組合。該細分市場透過專注於高需求商品並最大程度減少無利可圖的庫存來提高存貨周轉。此外,該細分市場還透過根據當地偏好進行商品組合來提高客戶滿意度。品類最佳化中的高階數據分析和人工智慧主導的洞察有助於企業降低成本並提高銷售效率。整體而言,品類最佳化能夠更好地利用空間,從而提高零售環境中的收益和業務效率。
預計在預測期內,產品置入和商品行銷部分將以最高的複合年成長率成長。
產品擺放與商品行銷領域預計將在預測期內實現最高成長率,這得益於其能夠提升產品在零售空間的可見度和消費者參與度。有效的擺放策略能夠最大限度地提高零售商的貨架利用率,從而最佳化空間配置並改善庫存管理。商品行銷策略能夠影響購買行為,提高銷售額,並實現更精準的需求預測。這些方法還支援根據消費者偏好和季節性趨勢進行動態商品組合調整,有助於提高零售環境中的業務效率和盈利。
預計亞太地區將在預測期內佔據最大的市場佔有率,這得益於都市化加快、零售店面不斷擴大以及對即時庫存可視性需求的不斷成長。印度和東南亞等新興經濟體正在採用空間規劃技術,以應對零售空間有限和消費行為變化的問題。雲端基礎的商品分類工具因其擴充性和成本效益而日益普及。市場參與者正在與當地零售商合作,制定符合當地文化的最佳化策略,而智慧型手機的普及則推動著行動零售分析和店內決策效率的提升。
預計北美地區在預測期內的複合年成長率最高,這得益於其發達的零售基礎設施、日益普及的電商以及整個零售鏈中數據分析的廣泛應用。零售商正在利用人工智慧解決方案來最佳化貨架配置、加強庫存管理並提升客戶體驗。該地區的技術供應商數量眾多,數位轉型投資也持續成長。主要參與者正專注於整合機器學習和規劃工具,以根據當地消費者偏好調整產品組合,並最大化每平方英尺的盈利。
According to Stratistics MRC, the Global Assortment and Space Optimization Market is accounted for $2.36 billion in 2025 and is expected to reach $5.35 billion by 2032 growing at a CAGR of 12.42% during the forecast period. The strategic process of choosing the ideal product mix (assortment) and effectively arranging them in the available retail space (space optimisation) in order to optimise sales and customer happiness is known as "assortment and space optimisation." To decide which products to offer, in what number, and where to put them in-store or online, it entails examining customer demand, product performance, and available space. In the end, this strategy increases profitability and operational efficiency across a range of retail formats by assisting retailers in improving inventory turnover, decreasing stockouts, and improving the shopping experience.
Rising demand for data-driven retail planning
Advanced analytics are being used by retailers more and more to comprehend the preferences and behaviour of their customers. This makes it possible to create a precise product assortment that is suited to the target market, increasing customer happiness and sales. Allocating space optimally lowers inventory costs and increases shelf efficiency. Retailers may also swiftly adjust to seasonal shifts and market trends with the use of data-driven insights. All things considered, this strategy improves competitive advantage and operational efficiency in the retail industry.
High implementation cost and integration complexity
A financial barrier is created by the significant expenditure needed for technology, software, and qualified staff. Since these solutions must integrate seamlessly with the current IT infrastructure, integration complexity adds still another level of difficulty. Longer deployment durations and a greater likelihood of operational disruptions can result from this complexity. Businesses may have difficulties with personnel training, system compatibility, and data migration. These elements work together to limit acceptance and lower consumer willingness to invest, which impedes broad market expansion.
Emergence of omnichannel retailing
A financial barrier is created by the significant expenditure needed for technology, software, and qualified staff. Since these solutions must integrate seamlessly with the current IT infrastructure, integration complexity adds still another level of difficulty. Longer deployment durations and a greater likelihood of operational disruptions can result from this complexity. Businesses may have difficulties with personnel training, system compatibility, and data migration. These elements work together to limit acceptance and lower consumer willingness to invest, which impedes broad market expansion.
Data privacy concerns and regulatory pressures
Adoption of technology is slowed by the increased operational complexity and expenses associated with complying with regulations such as the CCPA and GDPR. The breadth and depth of data analytics are constrained by these legal constraints, which lowers the precision of optimisation solutions. Project execution may be delayed because organisations frequently struggle to secure client consent and maintain data security. Furthermore, some participants are deterred from utilising sophisticated data-driven technologies to their full potential due to concerns about sanctions and reputational harm. In general, privacy laws erect obstacles that impede this industry's ability to innovate and thrive.
Covid-19 Impact
The Covid-19 pandemic significantly impacted the Assortment and Space Optimization Market by disrupting global retail operations, supply chains, and consumer behavior. Retailers faced challenges in inventory management and adapting product assortments to sudden shifts in demand. Store closures and reduced foot traffic accelerated the need for data-driven space optimization tools. As e-commerce surged, businesses adopted advanced analytics and AI-driven solutions to improve shelf planning and assortment strategies, ensuring operational efficiency and customer satisfaction in a rapidly changing retail environment.
The assortment optimization segment is expected to be the largest during the forecast period
The assortment optimization segment is expected to account for the largest market share during the forecast period, due to the most profitable and relevant product mix for their customers. It enhances inventory turnover by focusing on high-demand items while minimizing underperforming stock. This segment also improves customer satisfaction through tailored assortments that meet local preferences. Advanced data analytics and AI-driven insights in assortment optimization help businesses reduce costs and increase sales efficiency. Overall, assortment optimization drives better space utilization, boosting both revenue and operational effectiveness in retail environments.
The product placement & merchandising segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the product placement & merchandising segment is predicted to witness the highest growth rate by enhancing product visibility and consumer engagement within retail spaces. Effective placement strategies help retailers maximize shelf utilization, leading to optimized space allocation and improved inventory management. Merchandising tactics influence buying behavior, driving higher sales and enabling better demand forecasting. These approaches also support dynamic assortment adjustments based on consumer preferences and seasonal trends. Consequently, they contribute to increased operational efficiency and profitability in retail environments.
During the forecast period, the Asia Pacific region is expected to hold the largest market share fuelled by rising urbanization, retail expansion, and increasing demand for real-time inventory visibility. Emerging economies like India and Southeast Asia are adopting space planning technologies to handle limited retail space and changing consumer behaviour. Cloud-based assortment tools are gaining popularity due to their scalability and cost-effectiveness. Market players are collaborating with local retailers to develop culturally tailored optimization strategies, while growing smartphone penetration enhances mobile retail analytics and in-store decision-making efficiency.
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, owing to the advanced retail infrastructure, strong e-commerce adoption, and widespread use of data analytics across retail chains. Retailers leverage AI-driven solutions to optimize shelf layouts, enhance inventory management, and improve customer experience. The region sees strong presence of tech vendors and consistent investment in digital transformation. Key players are focused on integrating machine learning with planogramming tools to tailor product assortment based on regional consumer preferences and maximize profitability per square foot.
Key players in the market
Some of the key players profiled in the Assortment and Space Optimization Market include Oracle Corporation, SAP SE, Blue Yonder Group Inc., RELEX Solutions, SymphonyAI, Accenture plc, McKinsey & Company Inc., Microsoft Corporation, Nielsen Holdings plc, Aptos LLC, Invent Analytics LLC, Tata Consultancy Services Limited (TCS), Antuit.ai, Trax Inc., ToolsGroup Inc., Solteq plc and DotActiv Ltd.
In March 2025, Oracle was recognized as a Leader in the 2025 IDC MarketScape for AI-driven Retail Assortment Planning Solutions. The report highlighted Oracle's AI-powered advanced SKU prioritization and assortment optimization capabilities, noting active results in cost savings and strong partnerships in developing new assortment optimization methods.
In June 2024, SAP acquired WalkMe, a digital adoption platform, for $1.5 billion. This acquisition aims to enhance user experience and adoption of SAP solutions, including those related to assortment and space optimization.
In March 2023, SAP partnered with Axfood, Sweden's second-largest food retailer, to develop an advanced assortment planning solution. This collaboration aimed to create a user-friendly system that integrates data from sales histories, forecasts, and customer insights, enhancing decision-making processes and reducing product wastage.