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Retail Analytics Market worth $25.0 billion by 2029 – Exclusive Report by MarketsandMarkets™

The study finds that partnerships for innovation, a rising emphasis on sustainability and ethical analytics, supply chain optimisation, in-store analytics, and a focus on data privacy and security will all be critical.

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Adoption of real-time capabilities and sophisticated analytics, such as artificial intelligence, for omnichannel integration and improved customer experiences is what the Retail Analytics Market will look like in the future. Partnerships for innovation, a rising emphasis on sustainability and ethical analytics, supply chain optimisation, in-store analytics, and a focus on data privacy and security will all be critical.

The Retail Analytics Market is projected to grow from USD 8.5 billion in 2024 to USD 25.0 billion by 2029, at a compound annual growth rate (CAGR) of 24.0% during the forecast period, according to a new report by MarketsandMarkets™. The Retail Analytics Market is expected to grow significantly during the forecast period, owing to various business drivers like the increasing increasing adoption of omni-channel retail strategies, exponential growth of e-commerce platforms, and proliferation of data generated through diverse channels is also responsible for driving the market’s growth.

Browse in-depth TOC on “Retail Analytics Market“

300 – Tables
75 – Figures
310 – Pages

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Scope of the Report

By Software by analytics type, the predictive analytics segment to register for the largest market size during the forecast period.

By software by analytics type, the predictive analytics segment is expected to register the largest market size during the forecast period. Predictive analytics software can help forecast sales volumes, identify demand fluctuations, and predict customer preferences, enabling retailers to optimize pricing strategies, allocate resources efficiently, and tailor marketing campaigns to target specific customer segments. Recent advancements in predictive analytics technology, including the integration of AI and machine learning algorithms, have further enhanced the capabilities of predictive analytics software, enabling retailers to gain deeper insights, make more accurate predictions, and drive greater business value.

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By services, managed services to register for the highest CAGR during the forecast period.

The managed segment of the Retail Analytics Market is growing rapidly. Managed service providers (MSPs) offer tailored solutions that cater to the unique needs and challenges of retailers, delivering insights that drive operational efficiency, enhance customer engagement, and drive revenue growth. MSPs employ skilled professionals with expertise in data analysis, machine learning, and retail industry trends, enabling retailers to harness the full potential of their data assets. Additionally, managed services provide scalability and flexibility, allowing retailers to adapt to changing business requirements and market dynamics without the need for significant investments in infrastructure or personnel.

By region, Asia Pacific accounted for the highest growth rate during the forecast period.

Asia Pacific is witnessing significant growth in the Retail Analytics Market. The surging popularity of e-commerce, with regions like China and India leading the charge, is a major growth driver. Retailers are increasingly reliant on data to understand online consumer behaviour, optimize pricing and promotions, and personalize marketing efforts. Additionally, the growing adoption of the Internet of Things (IoT) in stores is generating vast amounts of data on customer traffic, product interaction, and inventory levels.

Top Key Companies in Retail Analytics Market:

Some major players in the Retail Analytics Market include Microsoft (US), IBM (US), SAP (Germany), Oracle (US), Salesforce (US), MicroStrategy (US), SAS Institute (US), AWS (US), Qlik (US), Teradata (US), WNS (India), HCL (India), Lightspeed Commerce (Canada), RetailNext (US), Manthan Systems (India), Fit Analytics (Germany), Trax (Singapore), ThoughtSpot (US), RELEX Solutions (Finland), Tredence (US), Creatio (US), Solvoyo (US), datapine (Germany), Sisense (US), EDITED (UK), Retail Zipline (US), ThinkINside (Italy), Dor Technologies (US), Triple Whale (Israel), Flame Analytics (Spain), Alloy.ai Technologies (US), Conjura (UK), Kyvos Insights (US), Pygmalios (Slovakia), and SymphonyAI (US).

Recent Developments:

• In February 2024, IBM announced the availability of the popular open-source Mixtral-8x7B large language model (LLM), developed by Mistral AI, on its Watsonx AI and data platform, as it continues to expand capabilities to help clients innovate with IBM’s own foundation models and those from a range of open-source providers.
• In January 2024, IBM announced its collaboration with SAP to develop solutions to help clients in the consumer-packaged goods and retail industries enhance their supply chain, finance operations, sales and services using generative AI.
• In January 2024, Salesforce announced the availability of Einstein 1 Studio, a set of low-code tools that enables Salesforce admins and developers to customize Einstein Copilot and seamlessly embed AI across any app for every customer and employee experience.
• In November 2023, MicroStrategy announced the availability of MicroStrategy ONE in the AWS Marketplace. By bringing together MicroStrategy’s powerful generative artificial intelligence (AI) capabilities for business intelligence (BI) and the scalability and reliability of Amazon Web Services (AWS), customers can now access a ready solution for deploying trusted AI at scale for analytics.
• In September 2023, Oracle showcased new AI-powered capabilities within Oracle Analytics Cloud. Leveraging the Oracle Cloud Infrastructure (OCI) Generative AI service, the new capabilities assist analytics self-service users to conduct sophisticated analysis and make better business decisions without having to wait for data scientists or IT teams more quickly and efficiently.

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Retail Analytics Market Advantages:

• Retailers can better fulfil customer demand by optimising pricing, promotions, inventory management, and product assortment with the use of retail analytics, which offers insights into customer behaviour, preferences, and trends.
• Retail analytics enables merchants to enhance the overall shopping experience, personalise marketing campaigns, and make customised product recommendations by evaluating customer data from many touchpoints. This increases customer happiness and loyalty.
• Retail analytics forecasts demand, identifies slow-moving commodities, and optimises replenishment procedures to help merchants maximise inventory levels, minimise stockouts and overstock situations, and increase supply chain efficiency.
• Through the automation of manual operations, the streamlining of procedures, and the identification of opportunities for cost reduction and performance improvement throughout the retail value chain, from procurement to distribution, retail analytics solutions increase operational efficiency.
• By helping companies to anticipate market trends, spot new business possibilities, and respond swiftly to shifting customer tastes and shifting market dynamics, retail analytics gives merchants a competitive edge that boosts sales and market share.
• Through the analysis of trends and abnormalities in transaction data, as well as the mitigation of fraud-related risks and revenue loss, retail analytics assists retailers in detecting fraudulent activity, including fraudulent transactions and refunds.
• Retail analytics gives businesses the ability to better allocate marketing expenditures, maximise marketing return on investment, and enhance the efficacy of customer acquisition and retention strategies by evaluating the success of marketing campaigns and promotions.
• Retailers may foresee future trends, take proactive business decisions, and seize market opportunities by using predictive analytics tools to forecast sales, demand, and customer behaviour.

Report Objectives

• To define, describe, and predict the Retail Analytics Market by offering (software and services), business function, application, end user, and region
• To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
• To analyze the micro markets with respect to individual growth trends, prospects, and their contribution to the total market
• To analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the Retail Analytics Market
• To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
• To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
• To profile key players and comprehensively analyze their market rankings and core competencies.
• To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the Retail Analytics Market
• To analyze the impact of recession across all the regions across the Retail Analytics Market

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