The global customer analytics in e-commerce market was valued at US$ 11 billion in 2022, growing at a CAGR of 15%. The market is expected to grow at US$ 12 billion in 2023 and reach a value of US$ 48.6 billion in 2033. Customer analytics in e-commerce will witness increased market demand due to enhanced data collection and consumer understanding and retention in the market.
The market is supported by:
The online interaction of businesses today generates huge data volumes every second. Customers are enjoying numerous benefits as a result of numerous e-commerce businesses making life simpler and more convenient to the users in the market. All of the products provided by the retailer, such as food, appliances, furniture, and apparel, are delivered right to the buyer's door, ensuring convenience with every purchase.
A better experience is increasingly attracting customers to spend additional funds, enabling e-commerce entities to generate significant revenue growth by providing individualized experiences in the market. The key to e-commerce business success, it is crucial to learn customer preferences. The e-commerce customer analytics solution assists businesses in growing and better understanding their customers.
Retailers are increasingly turning to e-commerce for their products. Customer analytics is becoming increasingly important for online retailers in order to make better business decisions. Increasing sales can be achieved by leveraging customer analytics in e-commerce companies. E-retailers can gain valuable insights into their customers' behavior by using customer analytics. These insights can then be used by companies to improve the way they do business in the future.
Using advanced analytics, and artificial intelligence, e-commerce marketers are making the most of their marketing efforts with the help of their data science and business intelligence teams. E-commerce analytics help businesses to better understand potential customers, forecast their behavior, and cater to their needs in real time, allowing companies to deliver products and services that match customers' expectations.
Through cross-selling, targeted advertising, and better product recommendations, online merchants can enhance their customer experiences. Growing demand for In-app purchases and demand for professional services to grow market for customer analytics in e-commerce businesses.
For instance, Sellerboard developed a set of analytics tools to help e-commerce sellers optimize their operations and inventory levels. Sellerboard gives e-commerce sellers a comprehensive view of their business metrics and costs in real time for a nominal fee. For e-commerce sellers, Sellerboard can be an invaluable tool with its dashboards, PPC automation, stock management, and review request feature.
India is experiencing a dramatic rise in e-commerce and digitally influenced spending due to the low data, smartphone, and internet costs, and the emergence of new online shopping channels. It is estimated that 260 million to 280 million digitally influenced shoppers and 210 million to 230 million online shoppers existed in 2021. Online stores are expected to multiply 2.5 times over the next decade, and online shoppers are expected to spend almost six times as much on the web.
According to a study, by 2030, 54% of online shoppers will reside in rural areas, and they will account for 24% of online retail sales. In addition to younger adults, rural affluent are also one of the major sources of growth in this sector, along with young professionals.
Online shoppers in North America spend an average of $3,500 per year. Deliveries are being beefed up by retailers across the continent with the help of distribution centers focused on e-commerce, e-distribution, and car delivery.
Data Points | Key Statistics |
---|---|
Estimated Base Year Value (2022) | US$ 11 billion |
Expected Market Value (2023) | US$ 12 billion |
Anticipated Forecast Value (2033) | US$ 48.6 billion |
Projected Growth Rate (2023 to 2033) | 15% CAGR |
Customer analytics in e-commerce refers to accumulation of data pointers that are analyzed to figure out what are the existing customers and prospects interacting with, together with generating insights on why and how the interaction is being done.
Interpretation of this data helps e-commerce businesses understand what exactly resonates among different consumer segments. Marketing initiatives of every e-commerce business has some sort of customer analytics associated with them.
Customer analytics in e-commerce generate actionable insights pertaining to number of pages viewed daily, number of users clicking on featured homepage offers, users bounced versus user stayed, average time spent on website and webpages, among other metrics. These metrics suggest continuously changing consumer sentiments. These metrics can be further studied to derive actionable insights and ensure informed business and operational decisions.
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High demand for customer analytics in e-commerce technology is being recorded on a global scale. This demand may be attributed to high penetration of Internet and the booming e-commerce industry. Large volumes of unstructured online or offline customer visitation data is accumulated using customer analytics in e-commerce.
Enterprises operating in retail and e-commerce industry are procuring Big Data analytics solutions, like Hadoop, to interpret the accumulated data for further reporting and generation of actionable insights. The insights are used to improve webpages interface and user experience.
Market players are offering customer analytics in e-commerce arena to be used conjointly with conventional market evaluation resources. This factor is expected to propel the adoption of customer analytics in e-commerce industry over the forecast period.
However, customer analytics in e-commerce is still in a nascent stage and is yet to emerge into the mainstream. Due to this factor, performance related expectations vary from end-user to end-user.
The only option to deduce if a customer analytics solution complements operational needs is via trial and error. Businesses operating in the e-commerce industry are unable to harness actionable insights, and this in turn affects their customer experience metrics and decision making. This factor is estimated to restrict the growth of global customer analytics in e-commerce market over the forecast period.
Some of the key players participating in the global customer analytics in e-commerce market are
The global customer analytics in e-commerce market is projected to be a fragmented market. This fragmentation of the global customer analytics in e-commerce market may be attributed to the high presence of analytical solution and service providers in regional and local markets.
Market in North America is expected to hold the largest share of the global customer analytics in e-commerce market. Advancements in DevOps and Big Data analytics is projected to fuel the demand for customer analytics in e-commerce.
Additionally, these regional markets showcase extensive sales footprint of key players, like IBM, Oracle and Dell, and key procurers like, Amazon.com, thus propelling the adoption of customer analytics in e-commerce industry. Market in Southeast Asia Pacific region is estimated to record the fastest growth in the global customer analytics in e-commerce market.
The Customer Analytics in e-commerce market report is a compilation of first-hand information, qualitative and quantitative assessment by industry analysts, and inputs from industry experts and industry participants across the value chain.
The report provides in-depth analysis of parent market trends, macro-economic indicators, and governing factors, along with market attractiveness as per segment. The market report also maps the qualitative impact of various market factors on market segments and geographies.
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The global customer analytics in e-commerce market can been segmented on the basis of component applications, and region.
1. Executive Summary 2. Industry Introduction, including Taxonomy and Market Definition 3. Market Trends and Success Factors, including Macro-economic Factors, Market Dynamics, and Recent Industry Developments 4. Global Market Demand Analysis and Forecast, including Historical Analysis and Future Projections 5. Pricing Analysis 6. Global Market Analysis and Forecast 6.1. By Component 6.2. By Application 7. Global Market Analysis and Forecast, By Component 7.1. Solutions 7.1.1. Standalone Analytics Tools 7.1.2. Integrated Analytics Platforms 7.2. Services 7.2.1. Professional Services 7.2.2. Managed Services 8. Global Market Analysis and Forecast, By Application 8.1. Customer Retention 8.2. User Engagement 8.3. In-app Purchases 8.4. Others 9. Global Market Analysis and Forecast, By Region 9.1. North America 9.2. Latin America 9.3. Europe 9.4. East Asia 9.5. South Asia & Pacific 9.6. Middle East and Africa 10. North America Sales Analysis and Forecast, by Key Segments and Countries 11. Latin America Sales Analysis and Forecast, by Key Segments and Countries 12. Europe Sales Analysis and Forecast, by Key Segments and Countries 13. East Asia Sales Analysis and Forecast, by Key Segments and Countries 14. South Asia & Pacific Sales Analysis and Forecast, by Key Segments and Countries 15. Middle East and Africa Sales Analysis and Forecast, by Key Segments and Countries 16. Sales Forecast By Component and By Application for 30 Countries 17. Competition Outlook, including Market Structure Analysis, Company Share Analysis by Key Players, and Competition Dashboard 18. Company Profile 18.1. IBM 18.2. Hitachi ID Systems 18.3. Dell 18.4. Happiest Minds 18.5. Oracle Corporation 18.6. CA Technologies 18.7. ATOS 18.8. Centrify Corporation 18.9. Microsoft Corporation 18.10. Ust Global 18.11. Empowerid 18.12. Onelogin and Trustwave
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