Spotlight

Report:

The Forrester Wave™: Customer Analytics Services, Q2 2025

How does Forrester define the Customer Analytics Services market in 2025?

Customer analytics services providers help businesses transform complex customer data into actionable insights to drive growth and competitive advantage. In an evolving landscape where customer expectations change as rapidly as technology, businesses face pressure to deliver seamless, personalized experiences with rapid response times. While commoditization of basic customer analytics (churn models, propensity models, lifetime value, segmentation) has accelerated, vendor differentiation now depends on the depth of insights facilitated by advanced technologies like graph databases and vector embeddings for richer contextual understanding. Leading providers distinguish themselves by turning insight into impact through advanced decision optimization, real-time feedback mechanisms, and explainable AI to drive smarter, faster outcomes.

Key Facts for The Forrester Wave™: Customer Analytics Services, Q2 2025 in 2025

How did the Customer Analytics Services market evolve in 2025?

What product features are required to be included in this year's evaluation?

What are the common features of top products in the Customer Analytics Services space?

No common features specified.

Scope Exclusions

Inclusion Criteria

Vendors must, among other requirements:

Offering Strengths — Relative Weighting

Strategy Strength — Relative Weighting

FAQs

Q: What does this research cover?

A: This research evaluates 10 customer analytics services providers across their current offering capabilities and strategic vision. The evaluation focuses on providers that specialize in advanced customer analytics services such as churn analysis, behavioral segmentation, and customer lifetime value analysis. Vendors were assessed on criteria including data sources and types, customer data models, personalization, analytics capabilities, insights delivery and activation, decision optimization, vertical and functional expertise, and strategic elements like vision, innovation, partnerships, pricing flexibility, and global delivery.

Q: Who should use this research?

A: This research should be used by enterprises seeking to select a customer analytics services provider. It is intended as a starting point for evaluation, helping buyers understand how different vendors compare across capabilities and strategy. Companies should use this to identify providers that align with their specific needs—whether that's end-to-end CX transformation, personalization excellence, industry-specific expertise, AI-powered automation, or particular vertical specialization. The interactive comparison tool allows clients to weight criteria based on their own priorities.

Q: What are the mandatory features of vendors included in this market?

A: Vendors must specialize in customer analytics with services including churn analysis, behavioral segmentation, and customer lifetime value analysis. They must generate at least $40 million in annual revenue from customer analytics services representing at least 50% of total revenue. Vendors must serve clients across diverse verticals and maintain strong mindshare among Forrester's enterprise clients through frequent mentions in inquiries, advisories, and competitive assessments.

Q: What are some reasons for not being included in this report?

A:

  • Insufficient focus on customer analytics services as core business
  • Revenue from customer analytics below $40 million annually
  • Customer analytics services representing less than 50% of total revenue
  • Limited vertical breadth in customer base
  • Lack of mindshare among Forrester enterprise clients
  • Declined to participate in evaluation process
  • Shift in business focus away from customer analytics (e.g., TTEC focusing on call center technology)
  • Does not meet inclusion criteria for significant focus on customer analytics services (e.g., Material)

Q: What should buyers consider when evaluating products in this market?

A:

  • Depth of insights beyond commoditized analytics capabilities
  • Ability to process diverse data types (text, image, video, audio, document) for contextual understanding
  • Advanced decision optimization and real-time feedback mechanisms
  • Explainable AI capabilities for transparency
  • Vertical and industry-specific expertise relevant to your sector
  • Functional competencies aligned with your use cases
  • Innovation roadmap including generative AI and agentic AI capabilities
  • ModelOps maturity for model lifecycle management
  • Insights activation and implementation capabilities, not just analysis
  • Pricing flexibility including outcome-based and joint venture models
  • Global delivery capabilities and support coverage
  • Change management and adoption enablement services
  • Partner ecosystem strength with major technology platforms
  • AI responsibility and governance frameworks
  • Customer data model sophistication and customization
  • Speed to value through accelerators and pre-built solutions

Q: How has the Customer Analytics Services market evolved in 2025?

A:

  • Rapidly evolving customer expectations driven by technology adoption
  • Relentless race to integrate latest AI capabilities in competitive landscape
  • Commoditization of traditional customer analytics (churn models, propensity models, lifetime value, segmentation)
  • Shift from insight generation to insight-to-impact transformation
  • Adoption of advanced technologies including graph databases and vector embeddings for richer contextual understanding
  • Integration of diverse data types (text, image, video, audio, document) for deeper insights
  • Focus on advanced decision optimization and real-time feedback mechanisms
  • Emphasis on explainable AI for transparency and trust
  • Movement toward agentic AI and AI-powered automation
  • Growing importance of responsible AI and bias detection/mitigation

Q: What differentiates Strength of Offering vs. Strength of Strategy?

A: Strength of Offering evaluates current capabilities including data sources, customer data models, analytics competencies across the customer lifecycle (acquisition, retention, personalization, CX), emerging analytics like genAI, ModelOps, insights delivery and activation, decision optimization, AI responsibility, vertical and functional expertise, measurement, project management, change management, and training. Strength of Strategy assesses forward-looking elements including vision for market evolution, innovation focus (particularly in agentic AI and genAI), partner ecosystem depth, pricing models and transparency, talent development and retention strategies, and global delivery capabilities.

Reference

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