| Product Code: ETC4396885 | Publication Date: Jul 2023 | Updated Date: Aug 2025 | Product Type: Report | |
| Publisher: 6Wresearch | Author: Ravi Bhandari | No. of Pages: 85 | No. of Figures: 45 | No. of Tables: 25 |
The retail analytics market in India has been experiencing significant growth. Retailers are increasingly adopting data analytics to gain insights into consumer behavior, optimize inventory management, and enhance the overall shopping experience. With the growth of e-commerce and brick-and-mortar stores, retailers are leveraging analytics to make informed decisions, improve sales, and ensure customer satisfaction.
The India Retail Analytics market is witnessing robust growth, thanks to several key drivers. Firstly, the rapid digitalization of the retail industry in India has generated a vast amount of data. Retailers are increasingly realizing the potential of data analytics in optimizing operations, enhancing customer experiences, and boosting sales. Secondly, the competitive nature of the India retail landscape has driven retailers to seek data-driven insights to gain a competitive edge. Thirdly, the growth of e-commerce in the country has made it imperative for retailers to understand online consumer behavior, and retail analytics is crucial in this regard. Furthermore, the government`s push for `Digital India` and the increasing smartphone penetration among consumers have led to an exponential increase in data availability. The implementation of modern technologies like artificial intelligence and machine learning for predictive analytics has become a necessity for retailers. Lastly, the COVID-19 pandemic has accelerated the adoption of digital and contactless shopping, further emphasizing the need for robust retail analytics solutions. Thus, the India Retail Analytics market is poised for substantial growth as retailers harness the power of data analytics to stay competitive and meet changing consumer expectations.
Retailers in India struggle with data integration from various sources, especially in the fragmented retail landscape. Moreover, gaining actionable insights from analytics data and effectively using them to enhance customer experiences and operations is an ongoing challenge.
The COVID-19 pandemic had a significant impact on the retail analytics market in India. With the closure of physical stores and the surge in e-commerce, retailers turned to analytics to understand changing consumer behavior and make data-driven decisions. Retail analytics played a critical role in demand forecasting, inventory management, and optimizing online shopping experiences. As the retail industry continues to adapt to the post-pandemic landscape, the India retail analytics market is expected to remain relevant, with a focus on enhancing customer engagement and operational efficiency.
The India Retail Analytics market witnesses the active participation of key players who specialize in delivering data-driven insights for the retail industry. Notable companies like IBM Corporation, SAP SE, Oracle Corporation, and SAS Institute Inc. have been pivotal in providing advanced retail analytics solutions. These solutions enable retailers in India to optimize operations, enhance customer experiences, and make informed decisions, ultimately boosting their competitive edge in a dynamic market.
1 Executive Summary |
2 Introduction |
2.1 Key Highlights of the Report |
2.2 Report Description |
2.3 Market Scope & Segmentation |
2.4 Research Methodology |
2.5 Assumptions |
3 India Retail Analytics Market Overview |
3.1 India Country Macro Economic Indicators |
3.2 India Retail Analytics Market Revenues & Volume, 2021 & 2031F |
3.3 India Retail Analytics Market - Industry Life Cycle |
3.4 India Retail Analytics Market - Porter's Five Forces |
3.5 India Retail Analytics Market Revenues & Volume Share, By Application , 2021 & 2031F |
3.6 India Retail Analytics Market Revenues & Volume Share, By Business Function , 2021 & 2031F |
3.7 India Retail Analytics Market Revenues & Volume Share, By Component, 2021 & 2031F |
3.8 India Retail Analytics Market Revenues & Volume Share, By End User, 2021 & 2031F |
3.9 India Retail Analytics Market Revenues & Volume Share, By Organization Size, 2021 & 2031F |
4 India Retail Analytics Market Dynamics |
4.1 Impact Analysis |
4.2 Market Drivers |
4.2.1 Increasing adoption of technology in retail sector in India |
4.2.2 Growing demand for data-driven decision making in retail operations |
4.2.3 Rising need for personalized customer experiences in the retail industry |
4.3 Market Restraints |
4.3.1 Data privacy and security concerns hindering adoption of retail analytics solutions |
4.3.2 High initial investment and ongoing maintenance costs associated with implementing analytics tools in retail |
4.3.3 Lack of skilled professionals in the field of data analytics and retail domain |
5 India Retail Analytics Market Trends |
6 India Retail Analytics Market, By Types |
6.1 India Retail Analytics Market, By Application |
6.1.1 Overview and Analysis |
6.1.2 India Retail Analytics Market Revenues & Volume, By Application , 2021-2031F |
6.1.3 India Retail Analytics Market Revenues & Volume, By Merchandising analysis, 2021-2031F |
6.1.4 India Retail Analytics Market Revenues & Volume, By Pricing analysis, 2021-2031F |
6.1.5 India Retail Analytics Market Revenues & Volume, By Customer analytics, 2021-2031F |
6.1.6 India Retail Analytics Market Revenues & Volume, By Promotional analysis and planning, 2021-2031F |
6.1.7 India Retail Analytics Market Revenues & Volume, By Yield analysis, 2021-2031F |
6.1.8 India Retail Analytics Market Revenues & Volume, By Inventory analysis, 2021-2031F |
6.2 India Retail Analytics Market, By Business Function |
6.2.1 Overview and Analysis |
6.2.2 India Retail Analytics Market Revenues & Volume, By Finance, 2021-2031F |
6.2.3 India Retail Analytics Market Revenues & Volume, By Marketing and sales, 2021-2031F |
6.2.4 India Retail Analytics Market Revenues & Volume, By Human Resources, 2021-2031F |
6.2.5 India Retail Analytics Market Revenues & Volume, By Operations, 2021-2031F |
6.3 India Retail Analytics Market, By Component |
6.3.1 Overview and Analysis |
6.3.2 India Retail Analytics Market Revenues & Volume, By Solutions, 2021-2031F |
6.3.3 India Retail Analytics Market Revenues & Volume, By Services, 2021-2031F |
6.4 India Retail Analytics Market, By End User |
6.4.1 Overview and Analysis |
6.4.2 India Retail Analytics Market Revenues & Volume, By Offline, 2021-2031F |
6.4.3 India Retail Analytics Market Revenues & Volume, By Online, 2021-2031F |
6.5 India Retail Analytics Market, By Organization Size |
6.5.1 Overview and Analysis |
6.5.2 India Retail Analytics Market Revenues & Volume, By Large Enterprises, 2021-2031F |
6.5.3 India Retail Analytics Market Revenues & Volume, By Small and Medium-sized Enterprises (SMEs) , 2021-2031F |
7 India Retail Analytics Market Import-Export Trade Statistics |
7.1 India Retail Analytics Market Export to Major Countries |
7.2 India Retail Analytics Market Imports from Major Countries |
8 India Retail Analytics Market Key Performance Indicators |
8.1 Customer retention rate |
8.2 Average transaction value |
8.3 Return on investment (ROI) from analytics tools |
8.4 Customer satisfaction score |
8.5 Percentage increase in sales conversion rate |
9 India Retail Analytics Market - Opportunity Assessment |
9.1 India Retail Analytics Market Opportunity Assessment, By Application , 2021 & 2031F |
9.2 India Retail Analytics Market Opportunity Assessment, By Business Function , 2021 & 2031F |
9.3 India Retail Analytics Market Opportunity Assessment, By Component, 2021 & 2031F |
9.4 India Retail Analytics Market Opportunity Assessment, By End User, 2021 & 2031F |
9.5 India Retail Analytics Market Opportunity Assessment, By Organization Size, 2021 & 2031F |
10 India Retail Analytics Market - Competitive Landscape |
10.1 India Retail Analytics Market Revenue Share, By Companies, 2024 |
10.2 India Retail Analytics Market Competitive Benchmarking, By Operating and Technical Parameters |
11 Company Profiles |
12 Recommendations |
13 Disclaimer |
Export potential enables firms to identify high-growth global markets with greater confidence by combining advanced trade intelligence with a structured quantitative methodology. The framework analyzes emerging demand trends and country-level import patterns while integrating macroeconomic and trade datasets such as GDP and population forecasts, bilateral import–export flows, tariff structures, elasticity differentials between developed and developing economies, geographic distance, and import demand projections. Using weighted trade values from 2020–2024 as the base period to project country-to-country export potential for 2030, these inputs are operationalized through calculated drivers such as gravity model parameters, tariff impact factors, and projected GDP per-capita growth. Through an analysis of hidden potentials, demand hotspots, and market conditions that are most favorable to success, this method enables firms to focus on target countries, maximize returns, and global expansion with data, backed by accuracy.
By factoring in the projected importer demand gap that is currently unmet and could be potential opportunity, it identifies the potential for the Exporter (Country) among 190 countries, against the general trade analysis, which identifies the biggest importer or exporter.
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