Report:

A: This research evaluates 11 customer analytics service providers across 29 criteria grouped into three categories: Current Offering (customer data management, analytics techniques and applications, insights to action, business consulting, engagement success), Strategy (vision, innovation, partner ecosystem, pricing flexibility, talent strategy, global delivery), and Market Presence (revenue, customers, projects). The evaluation helps identify providers that can operationalize analytical models in industry-specific ways and deliver value beyond just building models.

A: Customer experience (CX) professionals should use this research to select the right customer analytics service provider for their needs. It helps evaluate providers based on their ability to incorporate multidisciplinary capabilities (data science, behavioral science, design, engineering), offer relevant vertical/horizontal accelerators, and apply emerging technologies like generative AI to real enterprise use cases. The accompanying Excel-based comparison tool allows readers to customize criteria weightings based on their specific requirements.

A: All vendors included in this evaluation must: 1) Specialize in customer analytics, providing advanced services such as churn analysis, behavioral segmentation, and customer lifetime value analysis; 2) Generate at least $40 million in revenue from customer analytics engagements in their last fiscal year; 3) Serve clients across at least three different vertical industries; and 4) Have significant interest and mindshare from Forrester's client base.

A:

• Insufficient revenue from customer analytics engagements (less than $40 million annually)
• Limited vertical breadth (serving fewer than three industries)
• Primary focus on other services rather than customer analytics specialization
• Lack of advanced customer analytics capabilities (churn analysis, behavioral segmentation, lifetime value analysis)
• Insufficient Forrester client interest or mindshare
• Declined to participate in the evaluation
• Only partial participation in the evaluation process
• Did not meet materials submission deadline of April 7, 2023

A:

• Look for providers that incorporate data science, behavioral science, design, and engineering - not just data scientists
• Prioritize vendors with well-developed accelerators for your specific industry and use case
• Seek providers with live generative AI use cases at enterprise scale, not just pilots
• Evaluate the provider's ability to operationalize models and bridge the insights-to-action gap
• Consider vertical expertise and domain-specific customer data models relevant to your business
• Assess the vendor's innovation approach and investment in emerging analytical techniques
• Review talent development programs and employee satisfaction scores
• Examine global delivery capabilities and coverage in your operating regions
• Evaluate pricing flexibility including SaaS subscription models and outcomes-based pricing
• Consider the vendor's partner ecosystem and integrations with your existing technology stack
• Assess data literacy training and change management capabilities
• Review responsible AI practices including explainability, fairness, and governance

A:

• Model building is commoditized - every vendor can build great models, but operationalizing them is the key differentiator
• Success requires embedding insights into employee or customer experiences in ways that change behavior
• Multi-disciplinary approach combining data science, behavioral science, design, and engineering is essential
• Industry- and domain-specific accelerators are de rigueur to demonstrate expertise and accelerate time to value
• Generative AI adoption at enterprise scale is emerging, with use cases across the customer insights lifecycle
• Vertical and horizontal specialization through market-tested accelerators has become standard
• Shift from data scientist armies to balanced teams including engineers, designers, and consultants
• Privacy-preserving data partnerships and responsible AI practices are gaining importance

A: Strength of Offering (Current Offering) evaluates vendors' position on the vertical axis and measures the capabilities and features they deliver today, including customer data management, analytics techniques and applications, insights to action capabilities, business consulting, and engagement success. Strength of Strategy evaluates vendors' position on the horizontal axis and assesses their strategic direction and execution, including vision, innovation approach, partner ecosystem, pricing flexibility, talent development, and global delivery model.