India Analytics Market, Competition, Forecast & Opportunities, 2029

The India analytics market is growing at a healthy CAGR rate of approximately 33.5% in the forecast period 2025-2029. The growth of analytics is being fuelled by several reasons including the expanding use of IoT devices and the rising adoption of AI solutions. The main issue with analytics is that as data sets get more varied, it becomes increasingly difficult to integrate them into an analytical platform. The acute shortage of experts in the field of analytics presents another challenge.

Analytics is an area of computer science that seeks for useful trends in data using arithmetic, statistics, and machine learning. Sifting through enormous data sets to find, understand, and share new insights and information is known as analytics or data analytics. It is particularly helpful in areas where a lot of data or information is recorded.

India Analytics Market: Drivers & Trends

High Growth Rate of Data:

Data has been expanding quickly over the last few years. By 2022, 10,96,58,793 million MB of data would be used in India, with a compound annual growth rate (CAGR) of almost 72.6%. The amount of data being produced comes from sensors (IOT) as well as more conventional sources like survey data and points of sale. Additionally, India adds up to 25 million new smartphone users every three months and has the highest mobile data usage rate in the world at 12 gigabytes (GB) per user per month. As a result, India is producing and consuming more data every day, which has a direct influence on the India analytics market.

Spurt of E-Commerce Companies:

The reason behind the booming ecommerce industry in India is crystal clear. It is being driven by a surge in internet penetration, the emergence of global players, a rise in smartphone usage, advancements in mobile technology, a burgeoning millennial consumer base, and the rise of digital payments. Although traditional ecommerce companies have played a significant role in raising awareness and initiating the ecommerce movement in India, the Indian ecommerce industry is evolving rapidly. Additionally, the Indian government’s Open Network for Digital Commerce (ONDC) initiative is poised to democratize the e-commerce industry, providing a level playing field for all sellers in terms of product, pricing, reach, and sales. However, to gain a competitive advantage in this new environment, sellers from across India will need to think differently. One of the ways to do this is to better understand their customers by leveraging consumer insights and data analytics.

Insights and analytics can equip small businesses with valuable information that can help them make informed decisions about their products, pricing, and marketing strategies. In the past, established players had a significant advantage in terms of access to resources and data. However, with the rise of analytics tools, small businesses, newly established brands, and first-time sellers can now access the same information as larger businesses, allowing them to compete on a more equal footing.

The use of analytics to better understand customers’ preferences and buying behaviour, enables sellers to tailor their marketing campaigns, product catalogues, and product offerings to meet those needs. For instance, consumer insights can help sellers gauge how their customers prefer to engage with their products. This may include information on what types of images or videos of products are most effective in driving conversions, what types of product descriptions are most compelling, or even what types of packaging or shipping options are most important to their customers.

This can help smaller sellers gain a competitive advantage, as they are often more nimble and able to quickly adapt to changing market conditions. Similarly, consumer insights can help businesses identify trends and opportunities in the market, allowing them to create new products or services that meet the needs and demands of their customers. This can be particularly important for smaller businesses, as they may not have the resources to experiment or conduct extensive market research.

Growing Applications of Analytics in Banking:

The Indian banking industry has recently adopted cutting-edge banking formats including payments and small financing banks. Through many programmes, like the Pradhan Mantri Jan Dhan Yojana and Post Payment Banks, India has recently focused on broadening the scope of its banking sector. These kinds of projects have significantly improved financial inclusion in India and propelled the nation's credit cycle, along with significant banking sector reforms including digital payments, neo-banking, the expansion of Indian NBFCs, and fintech. Banks are creating a work environment where data is the foundation of strategic planning and decision-making as a result. Data analytics in banking allows to contextualize and personalize their products and services to cater to their consumers better and have a straightforward customer-centric approach to grow the business. As a huge amount of data is generated, the need to extract useful information is imperative. Data analytics is therefore essential in improving the business. Data analytics initiatives can help financial institutions to offer clients a totally personalized service. By processing the information that users generate, their preferences, habits, and needs can be known to offer individual services. The market has put the customer and their data as the epicentre, as it must offer them personalized and unique services. In addition, companies can use all this information in processes where data analysis is needed to make decisions: from strategies to increase revenue, improve operational efficiency, respond more quickly to market trends, or gain a competitive advantage over rivals.

Below are some of the applications of analytics in banking are:

• Smart Account: With the help of data science functionalities and logistic regression analysis methods, financial institutes can offer the client a new value-added account concept of smart account. This allows banks to receive prediction of future expenses and other possible short or medium-term discoveries, analyse the consumer behaviour based on the expenses, automatic categorization of movements to consult by groups, compare expenses with anonymous clients of the same profile and product recommendations that meet the specific needs of the client.
• Efficient Consumer Analytics: Real-time data analytics aids in enhanced understanding of customers and effective personalization. Sophisticated machine learning (ML) algorithms and customer sentimentality analysis techniques can produce information about their behaviour, social media communication, their comments, opinions, and enhance personalization, thus getting more information about the user.

Businesses to Embrace Machine Learning for Enhanced Decision-Making:

In the upcoming years, machine learning will continue to be a major trend in the analytics industry. Businesses need to develop methods to derive insights and add value from the data they are collecting, and machine learning is the key to doing this. Businesses of all sizes may now readily integrate machine learning algorithms into their data analytics processes because of the growing availability of open-source tools and cloud-based platforms. Additionally, automated machine learning (AutoML) technologies are making machine learning more approachable by requiring little to no human involvement while enabling enterprises to quickly construct and deploy machine learning models. As a result, organisations seeking to obtain a competitive edge in the market have adopted machine learning at a significantly higher rate.

In conclusion, the use of analytics in India is quickly changing how companies run their operations. Businesses must invest in technology that will enable more efficient and effective decision-making if they want to stay competitive in the digital era.

Increasing Adoption of Databases across Industries:

Data is greatly increased by the expanding use of digital solutions across corporate sectors, including banking, healthcare, BFSI, retail, agriculture, and telecom/media. For instance, the use of artificial intelligence has significantly changed risk management, precision farming, and pest control in the agricultural sector.

Massive data volumes are produced by smart machinery, soil sensors, and GPS-equipped tractors. Huge data sets, including improved risk assessment, supply tracking, natural trends, optimal crops, and more, are analysed in agriculture using data analytics.

Businesses are using bots to automate and reform functional contexts in a similar way. The production of data by virtual assistants like Apple's Siri, Google Assistant, and Amazon Alexa is also staggering. Furthermore, network connection and smartphone technological advancements fuelled a nation increase in social media users.

Facebook, WhatsApp, YouTube, Instagram, Snapchat, and other social sites create enormous amounts of data. Therefore, it is projected that the industrial revolution would result in massive datasets due to enhanced technology in the sectors, the increased usage of smart apps, and developing social media platforms. Thus, it is anticipated that growing databases across sectors will drive the market.

India Analytics Market: Challenges

Growing Security Concerns:

Major security issues with the technology include fake data production and the requirement for real-time security, among other things, the privacy and security of consumer data. Some of the key issues that require attention are remote storage, inadequate identity administration, a lack of investment in system and network security, human error, linked devices, and Internet of Things (IoT) applications. For organisations, overcoming these difficulties is a significant undertaking. The market expansion would probably be hampered by the rising data loss or cyberattacks on stored customer data across businesses.

Market Segments

India analytics market is segmented into component, verticals, type, organization size, and region. Based on component, the market is segmented into services and software. Based on verticals, the market is segmented into BFSI, e-commerce, healthcare, IT & telecom, and others. Based on type, the market is segmented into business analytics, CRM analytics, supply chain analytics, risk analytics, and location analytics. Based on organization size, the market is segmented into large-sized companies, mid-sized companies, and startups. The market analysis also studies the regional segmentation to devise regional market segmentation, divided among north India, east India, west India, and south India.

Market Players

Major market players of India analytics market are Tata Consultancy Services, Wipro Limited, Infosys Technologies Private Limited, Capgemini Technology Services India Limited, Tech Mahindra Limited, Hexaware Technologies Ltd., Accenture India Private Limited, IBM India Private Limited, Microsoft Corporation India Pvt. Ltd., and Mu Sigma Inc.

Report Scope:

In this report, India analytics market has been segmented into following categories, in addition to the industry trends which have also been detailed below:

India Analytics Market, By Component:

• Services
• Software

India Analytics Market, By Verticals:

• BFSI
• E-Commerce
• Healthcare
• IT & Telecom
• Others

India Analytics Market, By Type:

• Business Analytics
• CRM Analytics
• Supply Chain Analytics
• Risk Analytics
• Location Analytics

India Analytics Market, By Organization Size:

• Large-Sized Companies
• Mid-Sized Companies
• Startups

India Analytics Market, By Region:

• South India
• North India
• West India
• East India

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in India analytics market.

Available Customizations:

India analytics market with the given market data, the publisher offers customizations according to a company’s specific needs.


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