CLV 및 이탈 예측 AI 시장 : 점유율 분석, 업계 동향과 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the cLV and Churn Prediction AI market size is projected to be USD 2.32 billion in 2025, USD 2.72 billion in 2026, and reach USD 6.06 billion by 2031, growing at a CAGR of 17.38% from 2026 to 2031.

This report is Segmented by Component (Software and Services), Deployment Mode (Cloud, On-Premise, and Hybrid), Enterprise Size (Large Enterprises and Small and Medium Enterprises), End-User Industry (Retail and E-Commerce, BFSI, Telecommunications, Healthcare, and Other End-User Industries), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global CLV And Churn Prediction AI Market Trends and Insights

Growing Adoption of Predictive Analytics Tools Across Retail and BFSI

Retailers and banks are embedding real-time propensity scoring into revenue operations because generative AI has flooded digital storefronts with high-engagement shoppers who postpone purchases. During the 2024 holiday season, generative-AI referrals to United States retailers surged 1,300%, yet conversion rates trailed traditional channels by 9%. Financial institutions mirror this urgency; a wealth-management firm with USD 18 billion in assets cut churn by 15% and saved USD 7.5 million annually after deploying an AI-driven retention model. Platforms processing billions of daily interactions, such as Klaviyo, now enable midsize brands to lift gross merchandise value 62% within a year by pushing predictive insights back into storefront workflows. Asia-Pacific's private consumption is on track to reach USD 36 trillion by 2035, with 39% of consumers already using generative AI for shopping, expanding the addressable base for predictive tools.

Rising Need to Reduce Customer Acquisition Costs Through Retention Strategies

Digital advertising saturation and shifting search behaviors have inflated customer acquisition costs, making retention the fastest route to profitable growth. Sales, marketing, and service use cases account for nearly 40% of the USD 4.4 trillion long-term AI opportunity, yet fewer than half of executives report a revenue lift of more than 1% from generative AI so far. No-code agents such as Pecan's Predictive AI Agent let planners build production-grade churn models in minutes, reducing manual forecasting time by 60%. Telecom research shows that explainable ensembles can slash churn by up to 25% and reduce retention marketing costs by 45% by prioritizing high-risk, short-tenure customers. Retailers balancing personalization with supply resilience also saw a 37% increase in customer lifetime value, though stockouts rose 29%, reinforcing the need for predictive models to align with operational constraints.

Data Silos and Poor Data Quality Limiting Model Accuracy

Nearly one-third of enterprises cite data quality as a top AI challenge, with only 43% reporting a consistent data structure across their systems. This inconsistency in data structure poses significant hurdles for organizations aiming to implement AI effectively. The healthcare sector serves as a prime example of this challenge. Companies like ClosedLoop must process a wide range of data types, including electronic health records, unstructured clinical notes, insurance claims, lab results, and social determinants of health, before they can generate explainable, actionable predictions. To address these data-related challenges, 60% of firms are planning to hire new providers specializing in data organization and multidisciplinary talent. This strategic move is expected to increase the average spending on outsourced services by 7%, reflecting the growing importance of data management in AI adoption.

Other drivers and restraints analyzed in the detailed report include:

1. Proliferation of Cloud-Native Customer Data Platforms Enabling Real-Time Churn Scoring
2. Increasing Integration of AI in Customer Success Workflows Among SaaS Enterprises
3. Shortage of Skilled Data Scientists Constraining Implementation in SMEs

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Services captured a smaller base than Software in 2025, yet they are forecast to expand at an 18.91% CAGR between 2026 and 2031 as buyers outsource data harmonization, model validation, and EU AI Act conformity checks. Enterprises expect to increase spending on outsourced data services by 7%, and 60% will engage new partners for data organization and access to multidisciplinary talent. Totango's Unison offering bundles professional services with custom models that analyze calls, emails, and tickets months before renewal, illustrating how specialized expertise underpins adoption. The shift extends across financial services and healthcare, where explainability and bias audits demand that domain regulators recognize.

Software is projected to maintain a 67.98% share of the Customer Lifetime Value (CLV) and Churn Prediction AI market in 2025, driven by the ability of agentic platforms to lower technical barriers for users. For instance, Pecan's Predictive AI Agent significantly reduces the time required for model deployment, compressing it to just minutes. Similarly, ChurnZero's credit-based AI marketplace enables businesses to scale operations without adding headcount. However, as governance costs continue to rise, hybrid engagement models are gaining traction. These models involve vendors offering a combination of software licenses and managed services, which is gradually narrowing the gap between revenue generated from pure software sales and fee-based implementation services.

Cloud held 71.78% of the CLV and Churn Prediction AI market share in 2025, driven by the adoption of warehouse-native data platforms and the scalability of elastic GPU capacity. However, hybrid deployments are projected to grow at a robust CAGR of 22.54%, as enterprises in Europe and the Middle East navigate the dual challenges of meeting transparency mandates while adhering to data-residency regulations. A recent Lenovo survey of 800 decision-makers found that 58% prefer hybrid AI solutions. The primary reasons cited for this preference were enhanced privacy controls and the ability to customize solutions to meet specific organizational needs. Teradata AI Factory brings NVIDIA's AI stack on-premises for banks and hospitals that need deterministic costs and GDPR compliance.

Public cloud continues to play a critical role in supporting burst training and enabling ecosystem integrations, such as Klaviyo's real-time synchronization with Shopify. However, rising egress costs and concerns about inference latency are driving organizations to move recurrent scoring workloads closer to customer data. While on-premises solutions maintain a niche presence in defense and public-sector applications, they are increasingly integrating with managed update streams. This trend is gradually blurring the traditional lines between deployment models and expanding the CLV and Churn Prediction AI market size across diverse infrastructure frameworks.

Geography Analysis

North America remained the largest contributor to the CLV and Churn Prediction AI market in 2025, as SaaS ecosystems mainstreamed AI across sales, service, and marketing. Examples include Gainsight embedding insights inside Slack and Zendesk, adding autonomous agents through the Forethought deal. The region benefits from deep venture funding, a robust SaaS ecosystem, and an abundance of technical talent, which collectively cement its leadership position. However, rising API costs have sparked debates over ownership and control of customer data, posing a challenge to the market's growth trajectory.

Europe and the Middle East are advancing rapidly, driven by a preference for hybrid deployment models and the need to meet compliance deadlines. A regional survey revealed that 46% of AI pilots successfully transitioned to production, with companies reporting an anticipated return of USD 2.78 for every USD 1 invested in AI initiatives. Despite this progress, only 27% of organizations in the region have implemented comprehensive governance frameworks. As a result, partners that specialize in data integration, bias audits, and documentation capture are gaining significant mindshare and competitive advantage in the market.

Asia-Pacific is forecast to record a 22.42% CAGR, outpacing every other region. The region's private consumption is expected to grow significantly, with affluent consumers generating three times the spending growth in 2025 and accounting for 75% of new spending. Cross-border e-commerce and tourism are growing at a faster pace than domestic markets, adding complexities such as travel frequency and foreign-exchange variables to lifetime-value models. Local brands in key markets like China, India, Indonesia, and Thailand are leveraging AI to iterate and innovate faster than multinational competitors. This dynamic reflects an innovation loop that is accelerating demand for churn prediction tools and driving the overall growth of the market in the region.

1. Gainsight, Inc.
2. Qualtrics International Inc.
3. Zendesk, Inc.
4. Totango Inc.
5. ChurnZero Inc.
6. Pecan AI Ltd.
7. Baremetrics Inc.
8. Optimove Ltd.
9. Blushift Labs, Inc.
10. Klaviyo, Inc.
11. HubSpot, Inc.
12. ChurnKey, Inc.
13. MoEngage, Inc.
14. NGDATA NV
15. Amperity, Inc.
16. BlueConic, Inc.
17. Custora, Inc.
18. Twilio Inc.
19. Alteryx, Inc.
20. Express Analytics LLC

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Growing Adoption of Predictive Analytics Tools Across Retail and BFSI
  • 4.2.2 Rising Need to Reduce Customer Acquisition Costs Through Retention Strategies
  • 4.2.3 Proliferation of Cloud-Native Customer Data Platforms Enabling Real-Time Churn Scoring
  • 4.2.4 Increasing Integration of AI in Customer Success Workflows Among SaaS Enterprises
  • 4.2.5 Emergence of Federated Learning Frameworks Addressing Data-Privacy Barriers in Cross-Industry CLV Modeling
  • 4.2.6 Demand for Explainable AI to Meet Upcoming EU AI Act Requirements Driving Platform Upgrades
• 4.3 Market Restraints
  • 4.3.1 Data Silos and Poor Data Quality Limiting Model Accuracy
  • 4.3.2 Shortage of Skilled Data Scientists Constraining Implementation in SMEs
  • 4.3.3 Rising API Access Fees from Third-Party Data Vendors Inflating Total Cost of Ownership
  • 4.3.4 Model Performance Degradation from Rapidly Shifting Customer Behavior Post-Generative AI Adoption
• 4.4 Impact of Macroeconomic Factors on the Market
• 4.5 Industry Value Chain Analysis
• 4.6 Regulatory Landscape
• 4.7 Technological Outlook
• 4.8 Porter's Five Forces Analysis
  • 4.8.1 Bargaining Power of Suppliers
  • 4.8.2 Bargaining Power of Buyers
  • 4.8.3 Threat of New Entrants
  • 4.8.4 Threat of Substitutes
  • 4.8.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Component
  • 5.1.1 Software
  • 5.1.2 Services
• 5.2 By Deployment Mode
  • 5.2.1 Cloud
  • 5.2.2 On-Premise
  • 5.2.3 Hybrid
• 5.3 By Enterprise Size
  • 5.3.1 Large Enterprises
  • 5.3.2 Small and Medium Enterprises
• 5.4 By End-User Industry
  • 5.4.1 Retail and E-commerce
  • 5.4.2 BFSI
  • 5.4.3 Telecommunications
  • 5.4.4 Healthcare
  • 5.4.5 Other End-User Indutries
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
    • 5.5.1.3 Mexico
  • 5.5.2 South America
    • 5.5.2.1 Brazil
    • 5.5.2.2 Argentina
    • 5.5.2.3 Rest of South America
  • 5.5.3 Europe
    • 5.5.3.1 United Kingdom
    • 5.5.3.2 Germany
    • 5.5.3.3 France
    • 5.5.3.4 Italy
    • 5.5.3.5 Spain
    • 5.5.3.6 Rest of Europe
  • 5.5.4 Asia-Pacific
    • 5.5.4.1 China
    • 5.5.4.2 Japan
    • 5.5.4.3 India
    • 5.5.4.4 South Korea
    • 5.5.4.5 Rest of Asia-Pacific
  • 5.5.5 Middle East and Africa
    • 5.5.5.1 Middle East
      • 5.5.5.1.1 United Arab Emirates
      • 5.5.5.1.2 Saudi Arabia
      • 5.5.5.1.3 Rest of Middle East
    • 5.5.5.2 Africa
      • 5.5.5.2.1 South Africa
      • 5.5.5.2.2 Egypt
      • 5.5.5.2.3 Rest of Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.4.1 Gainsight, Inc.
  • 6.4.2 Qualtrics International Inc.
  • 6.4.3 Zendesk, Inc.
  • 6.4.4 Totango Inc.
  • 6.4.5 ChurnZero Inc.
  • 6.4.6 Pecan AI Ltd.
  • 6.4.7 Baremetrics Inc.
  • 6.4.8 Optimove Ltd.
  • 6.4.9 Blushift Labs, Inc.
  • 6.4.10 Klaviyo, Inc.
  • 6.4.11 HubSpot, Inc.
  • 6.4.12 ChurnKey, Inc.
  • 6.4.13 MoEngage, Inc.
  • 6.4.14 NGDATA NV
  • 6.4.15 Amperity, Inc.
  • 6.4.16 BlueConic, Inc.
  • 6.4.17 Custora, Inc.
  • 6.4.18 Twilio Inc.
  • 6.4.19 Alteryx, Inc.
  • 6.4.20 Express Analytics LLC

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment