The Forrester Wave™: Customer Analytics Services, Q2 2025

Customer Analytics Services Vendor Product Comparisons 2025

Key features and pros and cons of top Customer Analytics Services products:

Fractal - Leaders

Pros:

Neuroscience-based approach to customer insights combining Customer Genomics platform with behavioral research
Superior next best experience capabilities using multimodal generative AI
Microstimuli strategy addressing shrinking consumer attention spans
Strong partnerships with AI leaders like OpenAI and NVIDIA
High hiring standards (only 0.6% of applicants) and investment in training programs
Up to 15% of business from outcome-based engagements

Cons:

Lacks proprietary data, relies on partnerships for data processing
Only one reference customer responded to Forrester's outreach for this evaluation
Most business engagements are project-based rather than outcome-based

Tredence - Leaders

Pros:

ATOM.AI platform with accelerator tools, proprietary data models, and prebuilt web applications
Unique Foundry and Factory delivery model accelerates time to value
Focus on end-to-end CX transformation and last-mile adoption
Investment in adjacent activation capabilities like composable architectures
Strong vertical support for retail, CPG, travel and hospitality
Databricks' 2024 Retail and CPG Partner of the Year
All reference customers praised data science and thought leadership expertise

Cons:

Some customers mentioned communication gaps, though resolved with new leadership

ZS - Leaders

Pros:

Personalize.AI platform with dynamic microsegments and genAI-powered 'text-to-journey' analytics
Integrated testing and model observability directly in platform
Variety of customer data models customizable for domain and industry needs
Superior pricing flexibility including joint ventures (20% of customer analytics revenue)
Global delivery with 35 offices providing 24/7 support
Max.AI agentic platform for accelerating AI adoption
75% of analytics projects use accelerators and models

Cons:

Does not have proprietary customer data, relies on partners

Blend360 - Strong Performers

Pros:

'Fewer, bigger, better' strategy with 54% four-year CAGR
90% of insights engagements include direct implementation and managed services
Strong focus on automation and AI-powered solutions for real-time decision-making
15-20% of annual revenue from generative and agentic AI solutions
Codeveloping innovative solutions with longstanding clients
Reference customers cited competencies in data engineering, data science, and change management
One customer referred to Blend as 'indispensable'

Cons:

Limited project management capacity with just over 20 project managers for a midsized company
Customers hoped for improvements in product management
Relatively young company (founded 2017) compared to competitors

C5i - Strong Performers

Pros:

Incorporates various unstructured data types (text, video) through genAI accelerators like TXTSense and VideoSense
Discovery platform with intuitive UX for insights delivery and cross-functional collaboration
Decision engine using advanced approaches like reinforcement learning and multiarmed bandit methods
75% success rate in advancing genAI proofs of concept to full-scale implementation
15% of employees empowered to advance vertically or move into new roles annually
Customers praised ability to streamline insights delivery

Cons:

80% of delivery centers in India, which may expose clients to delays or delivery challenges
Currently expanding to get 'closer to the customer' with nearshore centers
Some customers desired faster response times and nearshore delivery availability

Merkle - Strong Performers

Pros:

Robust proprietary consumer data used in 60% of client engagements
Tech integration capabilities combining user attributes and feedback for segmentation
GenCX platform supporting self-service analysis through natural language querying
Strong connections with agency strategists enhancing execution ability
Codeveloping proprietary accelerators with tech leaders like Snowflake
Customers prefer Merkle over larger consultancies for superior person-level data knowledge
Customers found Merkle proactive in relationships

Cons:

Only 25% of analytics staff focus on vertical-specific analytics (lower than peers)
Some customers hope for improvements in ModelOps implementation
Shifting focus from upper-funnel metrics to 'total experience economy'

Tiger Analytics - Strong Performers

Pros:

'Lego blocks' approach using open IP foundational accelerators to enhance time to value
Excels in ModelOps from onboarding to remediation
Simplified consumption channels enabling users to add models directly into applications
Microsoft Partner of the Year Award for Business Transformation in 2024
Goal to surpass $1 billion in revenue in next five years
Offerings tailored to various industries and functions

Cons:

Did not provide reference customers for this evaluation
One customer mentioned customer data models were too generic for their use cases
Innovation centers around open IP instead of proprietary solutions

Blend360 - Contenders

Pros:

Exceptional vertical specialization with over 1,300 experts including 300+ senior professionals
Vertical-specific solutions like EXL Paymentor, Fan360, and integrated insurance LLM
Global AI governance policy and framework with rigorous bias detection using IBM's AI Fairness 360
Over 50 delivery centers across global markets
Strategic partnerships including NVIDIA
Reference customers highlighted deep industry expertise and flexible pricing

Cons:

Decision optimization could improve with higher focus on models and simulations rather than frameworks
All reference customers rely on EXL as staff augmentation
Partnerships not as extensive as some peers

Evalueserve - Contenders

Pros:

IntelliLens platform integrating six functions for audience building, campaign tracking, and social listening
Over 80% of customer analytics clients use platform assets to accelerate time to value
4,500+ domain experts and consulting frameworks
Global delivery hubs in Chile, China, India, Romania, and US with 'follow the sun' model
Clients praised depth of industry knowledge, domain expertise, and output quality
Strong functional competencies

Cons:

Lags peers in innovation focus areas such as agentic AI
Emphasizes emerging technologies far less than others in evaluation
One reference noted gap in communication skills and executive communication abilities
Specializes in B2B2X but partnerships less extensive than some peers

EXL - Contenders

Pros:

Exceptional vertical specialization with over 1,300 experts including 300+ senior professionals
Vertical-specific solutions like EXL Paymentor, Fan360, and integrated insurance LLM
Global AI governance policy and framework with rigorous bias detection using IBM's AI Fairness 360
Over 50 delivery centers across global markets
Strategic partnerships including NVIDIA
Reference customers highlighted deep industry expertise and flexible pricing

Cons:

Decision optimization could improve with higher focus on models and simulations rather than frameworks
All reference customers rely on EXL as staff augmentation
Partnerships not as extensive as some peers

LatentView Analytics - Contenders

Pros:

Impressive array of platform-agnostic vertical and domain-specific accelerators
MARKEE solution streamlining campaign analytics with Databricks stack and Mosaic AI
Smart Innovation leveraging AI simulation testing and concept generation for CPG
Listed as one of Unilever's 12 best-in-class partners for DataLab Ecosystem
90% repeat business rate with top accounts retained for over a decade
Elite Databricks partner with recognition for AI Penpal accelerator
References positive about email analytics and marketing expertise

Cons:

Vertical and function-centric approach does not extend to customer data models (prefers custom development)
One reference mentioned service gaps and desire for more available resources
Prioritizes client value over emerging AI trends
Acquisition of Decision Point Analytics still expanding onsite and nearshore support

FAQs

Q: Which vendors are Leaders in 2025?

A: Fractal, Tredence, ZS

Q: What does "Leader" mean in Forrester Wave terms?

A: Leaders demonstrate superior current offerings and strong strategic vision. They excel in turning insights into impact through advanced decision optimization, real-time feedback mechanisms, and explainable AI capabilities. Leaders distinguish themselves through the depth of insights, facilitated by advances in technologies such as graph databases and vector embeddings, and their ability to drive measurable business outcomes.

Q: How do I interpret a Forrester Wave?

A: https://www.forrester.com/policies/forrester-wave-methodology/

Report:

Top Vendor Products for Customer Analytics Services in 2025

Customer Analytics Services Vendor Product Comparisons 2025

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FAQs

Q: Which vendors are Leaders in 2025?

Q: What does "Leader" mean in Forrester Wave terms?

Q: How do I interpret a Forrester Wave?

Reference