The Forrester Wave™: Customer Analytics Service Providers, Q2 2023

Customer Analytics Service Providers Vendor Product Comparisons 2023

Key features and pros and cons of top Customer Analytics Service Providers products:

Fractal Analytics - Leaders

Pros:

Fuses analytics, engineering, and design to deliver value with emphasis on design and engineering over analytics
Successfully productized analytical offerings allowing for SaaS subscription-based pricing
Excels at customer genomics platform for personalization and AIDE platform for uncovering digital friction
Strong decision optimization and insights activation capabilities
Dedicated funding for R&D in generative AI and neuroscience

Cons:

Does not own proprietary data, approaches customer data enrichment through partnerships
Reference customers less satisfied with lack of formal data literacy training

Quantium - Leaders

Pros:

Strong collaborative approach to innovation with successful joint ventures
Successfully productized analytical assets like Q.Checkout with SaaS subscription revenue
Excellent talent development, consistently top employer in Australia
Demonstrates ability to forge privacy-preserving data partnerships between clients
Excels at business consulting with deep industry expertise in retail, CPG, financial services, health, and telecommunications
Strong commitment to ESG principles with ethics panel reviewing all projects

Cons:

Lags in customer experience and contextual marketing due to lack of NLP accelerator
Expanding global delivery model

Tiger Analytics - Leaders

Pros:

Open IP philosophy with proprietary 'Lego block' accelerators for building custom solutions
Strong 'follow the sun' delivery model leveraging onshore, near-shore, and offshore resources
Differentiated verticalized customer data models using graph and relational representations
Excels at personalization through journey intelligence and activation platform
Quick adoption of emerging analytical techniques including reinforcement learning and computer vision
Strong engagement success with value capture methodology and proprietary project management tools
High client reference satisfaction across all capabilities

Cons:

Standard vision of 'delivering actionable insights' not differentiated

Tredence - Leaders

Pros:

Vision to enable CX transformation across customer-facing and operational domains
Superior customer data management through Customer Cosmos with 10 verticalized and 40+ domain-specific models
Leverages Atom.AI platform to develop new verticalized accelerators using cutting edge techniques
Strong partner ecosystem with top accolades from Microsoft and Databricks
Excels at personalization and retention use cases
Strong vertical and domain specific consulting services
Perfect score on likelihood to recommend from reference customers

Cons:

Reference customers identified areas for improvement in change management tools and services

Blend360 - Contenders

Pros:

Strong strategic consulting demonstrating ability to unite disparate client functions
Helped clients adjust employee incentives to align with long-term goals like lifetime value
Perfect marks on 'likeliness to recommend' from reference customers

Cons:

Takes 'it's everyone's job' approach to innovation without dedicated team and budget
Lacks breadth and depth of partnerships compared to established competitors
Approaches MLOps in ad hoc fashion
Does not emphasize responsible AI practices such as fairness and explainability
Working on expanding global delivery model, was 100% US based recently

Evalueserve - Strong Performers

Pros:

Excels at insights delivery with cross-functional insights collaboration through MagnifAI platform
Strong analytical control tower for prioritizing, implementing, and measuring analytics impact
Strong data literacy training through Evalueserve University for clients and internal resources
Strong functional expertise demonstrated in control tower capabilities
All reference customers extremely likely to recommend

Cons:

Customer data models primarily limited to B2B industries and marketing use cases
Doesn't exhibit same aptitude for emerging techniques like reinforcement learning
Takes ad hoc approach to MLOps
Standard vision of partnering 'from ideation to impact'

EXL - Strong Performers

Pros:

Built thriving customer analytics business on BPO roots in financial services, healthcare, retail, and entertainment
Over 300 senior industry subject matter experts to lead engagements
Flexible and innovative pricing models including outcome-based pricing
Strong accelerators for acquisition and retention
Solid responsible AI practices with AI governing board with project veto power
Uses best-in-class tools for explainability and fairness
Client references extremely happy with responsible AI practice

Cons:

Vision to help clients become 'data led' is anachronistic
Verticalization doesn't extend to customer data models which use generic accelerators
Puts less emphasis on CX use cases

Material - Challengers

Pros:

Focus on behavioral science and design
Offers formal training program to develop existing talent
Competitive insights delivery capabilities using design expertise to embed insights into employee workflows

Cons:

Does not have formalized approach to innovation
Limited partner ecosystem
Only employs about 60 data scientists
Does not offer verticalized customer data models
No proprietary customer data assets for enrichment
Does not possess strong capabilities in emerging analytical techniques like reinforcement learning
Gaps across customer insights lifecycle

Merkle - Contenders

Pros:

Shines at customer acquisition
Proprietary DataSource asset with 3,000 attributes covering 98% of US households
Able to merge attitudinal segments with behavioral ones for acquisition
Clear ability to implement marketing campaigns
Thrives on measuring impact with proprietary tools and frameworks

Cons:

Employs over 3,000 data scientists but lacks formalized analytics training for employee development
Recent innovations like data clean rooms are primarily marketing focused rather than CX focused
Lacks industry-specific accelerators for customer retention
Lags at insights activation due to inability to develop insights-infused apps
Emphasis on customer acquisition rather than full CX

TTEC - Strong Performers

Pros:

Strong approach to talent strategy with almost 1,000 analytics-related courses through TTEC Talent Training Platform
Truly global delivery model with massive pool of resources spanning six continents
Differentiates with data annotation and training services
Can deliver insights directly through TTEC Engage's sales and service representatives
Engages in outcomes-based pricing more than other vendors
Strong MLOps capability in humanify insights platform that can validate third-party models

Cons:

Vision that 'conversations are the currency of customer satisfaction' may resonate more with CX leaders than marketers
Lacks verticalized analytical accelerators for customer acquisition and retention
Reference customers lukewarm on decision optimization capabilities

ZS - Strong Performers

Pros:

Excels at personalization through Personalize.AI leveraging multiple models
Successfully deployed personalization for wide range of clients from airlines to QSRs
Quick to adopt emerging techniques, leveraging generative AI to deliver personalized emails
Offers SaaS solutions with differentiated pricing model
29 delivery centers provide global coverage
Full-fledged MLOps platform tracking drift, utilization, cost, and model health metrics
Client references very satisfied with capabilities

Cons:

Vision to decrease time to value is undifferentiated from other vendors
Could improve talent strategy, lags in formalized employee development programs
Does not offer proprietary data for enrichment
Offers no formal training in data literacy

FAQs

Q: Which vendors are Leaders in 2023?

A: Fractal Analytics, Quantium, Tiger Analytics, Tredence

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

A: Leaders in the Forrester Wave demonstrate strong current offerings and robust strategies. They excel across the evaluation criteria including customer data management, customer analytics techniques and applications, insights to action, business consulting, and engagement success. Leaders also show strong vision, innovation, partner ecosystems, pricing flexibility, talent strategy, and global delivery capabilities.

Q: How do I interpret a Forrester Wave?

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

Report:

Top Vendor Products for Customer Analytics Service Providers in 2023

Customer Analytics Service Providers Vendor Product Comparisons 2023

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FAQs

Q: Which vendors are Leaders in 2023?

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

Q: How do I interpret a Forrester Wave?

Reference