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Marketing Analytics Market size was valued at USD 5.3 billion in 2023 and is anticipated to register a CAGR of over 16% between 2024 and 2032. The growing demand for data-driven marketing is significantly propelling the market expansion. Businesses are increasingly reliant on data to understand customer behavior, preferences, and market trends. Many companies are strengthening their portfolios by forming partnerships with key market players.
For instance, in June 2024, CleverTap, the all-in-one engagement platform, announced its partnership with RentoMojo, an online rental solution. Through this collaboration, RentoMojo aims to enhance its customer engagement strategies, drive substantial revenue growth, and streamline its marketing efforts.
Report Attribute | Details |
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Base Year: | 2023 |
Market Size in 2023: | USD 5.3 Billion |
Forecast Period: | 2024 to 2032 |
Forecast Period 2024 to 2032 CAGR: | 16% |
2032 Value Projection: | USD 20.1 Billion |
Historical Data for: | 2021 - 2023 |
No. of Pages: | 220 |
Tables, Charts & Figures: | 285 |
Segments covered: | Application, Deployment Model, Organization Size, and End User |
Growth Drivers: |
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Pitfalls & Challenges: |
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In addition, Artificial Intelligence (AI) plays a crucial role in driving the marketing analytics market growth. The demand for AI-driven analytics solutions has been growing as businesses seek to optimize marketing strategies, boost customer engagement, and achieve higher ROI, thus driving the market growth. For instance, in May 2024, Salesforce expanded its Einstein Copilot capabilities by introducing new features for marketers and merchants. This solution is Salesforce’s trusted and reliable conversational AI assistant and helps different-sized businesses with day-to-day marketing and merchandising tasks along with its existing functionalities for sales and service.
The high cost of marketing analytics solutions presents notable challenges, especially for small & medium enterprises (SME). These businesses often face budget constraints, limiting their access to sophisticated analytics tools. High-cost software licenses, implementation, and maintenance expenses make it difficult for SME to invest in comprehensive analytics solutions. The financial barrier prevents smaller companies from fully leveraging the benefits of advanced data analytics, hindering their ability to compete effectively in the market.