Spotlight

Report:

The Forrester Wave™: Customer Analytics Technologies, Q2 2024

How does Forrester define the Customer Analytics Technologies market in 2024?

Customer analytics technologies help insights professionals extract value from customer data through advanced analytics including segmentation, propensity modeling, churn analysis, engagement analysis, journey analysis, lifetime value analysis, and recommendation analysis. The market is characterized by the integration of generative AI capabilities, though buyers should prioritize robust underlying analytics over AI window dressing. Key differentiators include the ability to treat unstructured data as a first-class citizen, verticalized data models and analytics, and optimization of customer-level decisions beyond just delivering insights.

Key Facts for The Forrester Wave™: Customer Analytics Technologies, Q2 2024 in 2024

How did the Customer Analytics Technologies market evolve in 2024?

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 Technologies 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 covers a comprehensive evaluation of 11 customer analytics technology providers across 34 criteria. It evaluates vendors' current offerings (including data sources, customer profiles, segmentation, propensity modeling, churn analysis, engagement analysis, customer journey analysis, decisioning, optimization, and responsible AI), strategy (vision, innovation, roadmap, partner ecosystem, adoption, pricing), and market presence (revenue and number of customers). The evaluation focuses on providers that offer extensive out-of-the-box customer analytics capabilities for business users such as CX professionals, marketers, and digital product leaders.

Q: Who should use this research?

A: This research should be used by insights professionals, customer experience professionals, marketers, and digital business leaders who are evaluating and selecting customer analytics technology vendors. It helps buyers understand which providers excel at treating unstructured data as first-class citizens, offer verticalized data and analytical models, and optimize customer-level decisions. The research is particularly valuable for organizations that want to move beyond GenAI window dressing to find vendors with robust underlying analytics capabilities, and for those seeking to bridge the 'insights to action gap' in their customer analytics initiatives.

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

A: To be included in this evaluation, vendors must offer a comprehensive customer analytics solution for business users with extensive capabilities out of the box, including churn analysis, behavioral segmentation, and customer lifetime value analysis. They must serve business users such as CX professionals, marketers, and digital product leaders. Additionally, vendors must have earned at least $100 million from customer analytics engagements in their last fiscal year, provide services across at least three vertical industries, and demonstrate significant interest from Forrester clients.

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

A:

  • Revenue below $100 million from customer analytics engagements
  • Solutions primarily designed for data scientists rather than business users
  • Lack of comprehensive out-of-the-box analytical capabilities (missing core analyses like churn, segmentation, or lifetime value)
  • Limited vertical industry breadth (fewer than three verticals served)
  • Insufficient Forrester client interest or market presence
  • Solutions that are primarily customer data platforms without deep analytical capabilities
  • Point solutions focused on single analytics use cases rather than comprehensive platforms

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

A:

  • Prioritize vendors with differentiated analytical techniques under the hood rather than being beguiled by generative AI window dressing
  • Look for providers that treat unstructured data as a first-class citizen with strong NLP and data processing capabilities
  • Select vendors who excel at verticalized data models and analytical techniques specific to your industry to accelerate time to value
  • Prioritize vendors that provide decision-making guidance or optimization capabilities, not just propensity scores and insights
  • Evaluate the vendor's ability to integrate with your existing marketing and operational systems
  • Consider the vendor's approach to user adoption, training resources, and community support
  • Assess pricing transparency and flexibility, including outcome-based models where appropriate
  • Evaluate responsible AI capabilities including model monitoring, explainability, and fairness controls

Q: How has the Customer Analytics Technologies market evolved in 2024?

A:

  • Generative AI is being integrated across customer analytics technologies, though often as interface enhancements rather than transformational analytical capabilities
  • Unstructured data (especially natural language from conversational customer interactions) is becoming increasingly important and needs to be integrated with structured customer data
  • Verticalization of data models and analytical techniques is accelerating time to value and enabling industry-specific best practices
  • The 'insights to action gap' is being addressed through decision optimization, prescriptive recommendations, and reinforcement learning approaches
  • Real-time decisioning and next-best-experience capabilities are becoming critical differentiators
  • Responsible AI capabilities including fairness evaluation, explainability, and model monitoring are gaining importance

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

A: Current Offering evaluates the strength of each vendor's existing product capabilities across 24 criteria including data management, analytical models, decisioning, usability, and responsible AI features. Strategy evaluates forward-looking elements across 8 criteria including the vendor's vision for the market, innovation track record, product roadmap, partner ecosystem strength, adoption approach, pricing models, community engagement, and supporting services. Current Offering focuses on 'what the product can do today' while Strategy focuses on 'where the vendor is heading and how they support customers.'

Reference

View Leaders
View Vendor Movements