The Global Retail Analytics Market size was valued at USD 6.35 billion in 2022 and is projected to reach USD 34.52 billion by 2031, with a CAGR of 20.7 % during the forecast period 2023–2031.
Retail analytics collects analytical data regarding inventory levels, supply chain movements, consumer demand, sales, and other factors. This information can be utilized for various purposes, including maintaining procurement levels and making vital marketing decisions. Retailers can effectively utilize these insights to enhance their operations in various ways, including optimizing store layout and design, enhancing pricing strategy, enhancing promotional campaigns, iterating product displays, driving personalized product recommendations, and developing comprehensive customer personas. Moreover, retail analytics data can give organizations valuable customer information, allowing merchants to better comprehend and address their demands. Tools for retail business analytics help anticipate future sales and demand. Increased emphasis on business intelligence (BI) and analytics and the adoption of cutting-edge technologies for retail analytics solutions are projected to expand and intensify competition. Global leaders in retail analytics are developing innovative technologies and deploying retail business intelligence to capitalize on profitable income prospects.
The retail industry is becoming more data-rich as more businesses go digital, establishing many more data-capture opportunities. According to Google's Zero Moment Of Truth (ZMOT) research, 70% of consumers research online before purchasing in-store. Retail analytics gives insights into the business and processes of the organization along with detailed insights on consumers with scope and need for improvement. This field goes beyond superficial data analysis, using techniques such as data discovery and data mining to filter datasets to produce actionable insights that can be applied in the short term. Moreover, companies use retail analytics to create better snapshots of target customers. By harnessing data from retail analytics, companies can identify the ideal customers from a diverse range by age, gender, buying pattern, preference, and location.
| Report Metric | Details |
|---|---|
| Base Year | 2017 |
| Study Period | 2016-2026 |
| Forecast Period | 2023-2031 |
| CAGR | 20.7% |
| Market Size | USD 34.52 billion by 2031 |
| Fastest Growing Market | Asia Pacific |
| Largest Market | North America |
| Report Coverage | Revenue Forecast, Competitive Landscape, Growth Factors, Environment & Regulatory Landscape and Trends |
| Geographies Covered |
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As digital acceleration gets momentum, the global retail and consumer products community is shifting faster than anyone could have anticipated. Enterprises and users have begun to understand that digital transformation requires a data-driven approach to every area of their businesses to gain a competitive edge. For instance, digital transformation for a retailer could involve giving real-time best offers when customers are in physical locations or optimizing inventory to create a better online and in-store experience. By providing customers with the services and products they require, digital transformation in retail may increase customer loyalty and satisfaction. Emerging technologies that blur the boundaries between the digital and physical worlds define the fourth industrial revolution (Industry 4.0). Access to data, coupled with strong analytics tools such as scenario analysis, predictive learning algorithms, and visualization, is revolutionizing the performance of businesses. Companies may now collect massive data sets in real time from their physical facilities and assets, perform complex analytics to produce fresh insights, and make more successful decisions. The digital revolution is revolutionizing product design, development, and delivery to clients. It has significant ramifications for the retail supply chain.
For instance, Retail analytics optimizes the supply chain, uses existing data to increase conversion, and customizes shopping experiences with predictive modeling and micro-targeting/pricing. Therefore, technological advancements such as artificial intelligence augmented reality, and machine learning in retail analytics are expected to bolster the growth of the retail analytics market throughout the forecast period. Furthermore, other prime factors positively impacting the retail analytics market include the utilization of social media, an increase in online shopping, and the rising use of smartphones. Social media allows retailers to better understand consumer preferences by tracking consumer behavior and predicting and anticipating future behavior. As per data from the e-commerce vendor Custora, 90% of consumers try to reach out to brands on social media. Therefore, the prolific use of social media is a key driving factor for the retail analytics market. In addition, the latest trend in the retail analytics market is to personalize the customer experience by predicting demand and footfall with the help of retail analytics.
Large retail businesses employ technology for everyday tasks such as billing and payments, preventing shrinkage, maintaining stock records, and supply chain management. Solutions such as retail analytics are utilized to gain insights pertaining to sales, inventory, customers, and other critical factors in the decision-making process; CRM tools increase customer relationship management, and ERP solutions facilitate other operations. While huge corporations capitalize on these technologies, the unorganized retail sector must contend with limited availability, feasibility, and uptake. Unorganized retailers are under pressure from deep-pocketed offline, modern trade outlets, and the e-commerce bandwagon; however, despite their desire to employ technology to advance, they are frequently constrained by budgetary constraints. Hidden expenses associated with maintaining old obsolete systems might quickly become prohibitive, leaving little funds for innovation or digital transformation. Especially in rural and isolated places, the high cost of capital and the difficulty of obtaining capital funding have severely inhibited the expansion and improvement of such retail companies.
Organizations are establishing analytics capabilities to inform business solutions to various concerns and plan for the future. Companies will need to utilize robust data and analytic skills to foresee and respond to altering baselines during and after the implementation of adverse situations. The retail sector is becoming increasingly competitive, and optimizing corporate procedures while meeting customer expectations has become essential. At all phases of the retail process, data analytics is being incorporated; it helps to keep track of all developing items, anticipate sales, and predict future demand. Customers' heat maps can also optimize the positioning of offers and products. Using analytics, it is possible to swiftly and effectively identify clients interested in particular products based on their prior purchases. This assists retailers in developing tailored marketing efforts.
On the basis of geography, the retail analytics market has been segmented into North America, Europe, Asia Pacific, and LAMEA.
North America is projected to hold the largest market share in the retail analytics market during the forecast period due to the high implementation rate of retail analytics in the region. Retail analytics solution deployment is high in North America for sophisticated systems and the availability of high working capital at the disposal of several retailers in the region. The United States is one of the most powerful marketplaces because it is an early adoption of technology, with large corporations investing extensively in various technologies to remain competitive. Numerous major corporations are expanding their investments in the creation of innovative smart stores, which are also anticipated to stimulate market growth in this region. For example, Amazon has begun developing Amazon Go convenience and food stores throughout the United States.
The Asia-Pacific market accounted for the second-largest revenue share in 2021 due to the region's concentration of developed and developing economies. Significant opportunities exist for retail shop expansion and technological advancement due to increasing digitalization and the penetration of e-commerce in fast-growing countries such as India and China. Furthermore, by increasing the use of Wi-Fi products that provide real-time analytics of customer activity, Asia Pacific retailers are customizing the measures to provide the best appropriate products to the customers. China, India, and Japan are focusing on data management to facilitate data-driven business decisions and enhance retail operations. Moreover, key firms' increasing deployment of smart shops in this region drives revenue development in the retail analytics market. Ikea, a Swedish furniture and home goods manufacturer, wants to dominate India's leading cities by developing a few large four to five small-format stores in each city to reach more customers in densely populated areas.
In 2021, the Europe market represented the third-largest revenue share. Rising collaboration and the introduction of new goods by major European corporations drive market expansion. For instance, on 18 December 2022, dunnhumby, the world's leading retail data science company, launched Dunnhumby Sphere, an all-in-one customer-first retail media platform. dunnhumby Sphere is an end-to-end retail media platform that helps unify audience targeting, scheduling, forecasting, and measurement across several retail media platforms. This platform enables retailers to establish and expand their retail media capabilities and scale and maximize revenue from retail media. At the same time, advertising partners benefit from enhanced collaboration and the capacity to plan, book, measure, and pay for campaigns across online and in-store channels.
The LAMEA region is anticipated to grow at a significant rate in the retail analytics market, owing to the region’s growing retail industry and increasing urbanization. According to the Dubai Chamber of Commerce and Industry, UAE’S retail sector is projected to expand at a CAGR of 4.9%, which is expected to further create opportunities for the retail analytics market in the LAMEA region.
The retail analytics market can be segmented by component, application, business function, and end user.
The global retail analytics market is segmented by component type into solutions and services. In 2021, the solution segment had the largest revenue share. A retail analytics solution aims to provide merchants with data on sales, inventory, customers, and other crucial elements they must consider when making choices. The discipline integrates numerous granular categories to generate a comprehensive view of a retailer's health and sales and development and reinforcing potential. This segment's revenue growth is driven by the growing demand for retail analytics, which helps businesses make better decisions, manage their organizations more efficiently, and deliver superior customer service.
In 2021, the services segment contributed a moderate proportion of total income. With customer behavior data, retail analytics services provide scalability, cost-effectiveness, and better-targeted marketing and communications. This segment's revenue growth is driven by the ability to convert foot traffic into sales, boost digital and social marketing skills by sending customized electronic mailers based on customers' purchasing behaviors, and provide intelligent business analytics.
The global retail analytics market is segmented by application type into merchandising analysis, price analysis, customer analytics, promotional analysis and planning, yield analysis, and inventory analysis, among others. In 2021, the inventory analysis category had the biggest revenue share. Many external factors influence why people purchase particular things. There may be a huge demand for HDMI cables as a result of aggressive TV advertising. Customers may stock up on essential household items in preparation for a winter storm. Predictive retail analytics can help businesses optimize their supplies in advance and plan promotions to capitalize on external occurrences. As a result, retail analytics are becoming increasingly popular.
In 2021, the pricing analysis segment contributed a moderate proportion of total revenue. Pricing has a significant impact on a product's rate of sale. Increasingly, businesses are utilizing retail analytics to comprehend how pricing influences mobility, putting them in a good position to prevent out-of-stock and giving them confidence in the ROI on price reductions, hence supporting the revenue growth of this market.
The global retail analytics market is segmented by organization size into large enterprises and small and medium-sized enterprises (SMEs). Large enterprises had the biggest revenue share in 2021 due to their increased emphasis on enhancing consumer contact through retail analytics. Due to their solid financial condition, large businesses may invest in cutting-edge technology, such as retail analytics. In addition, volatile market conditions, severe competition, and market disruption caused by COVID-19 prompted big companies to adopt retail analytics to minimize losses and improve revenues, driving this category's revenue growth.
In 2021, the Small and Medium-Sized Enterprises (SMEs) market segment stood for a small revenue share. SMEs are becoming more aware of the possibilities of analytics; as a result, they are rushing to apply retail analytics to remain competitive and improve business operations. This is due to the increasing adoption of cloud-based deployment and the availability of low-cost software, both of which drive the revenue growth of this market.
Based on business function, the retail analytics market can be segmented into finance, sales, marketing, supply chain, store operations, and others. The store operation segment is projected to hold a significant market share as the number of organizations in the retail sector has been increasing.
