U.S. Retail And Supply Chain Analytics Competitive & Commercial Benchmarking Analysis

Table of Contents

Chapter 1 Methodology and Scope
                   1.1 Market Definitions
                   1.2 Objectives of The Study
                       1.2.1 Objective - 1
                       1.2.2 Objective - 2
                       1.2.3 Objective - 3
                   1.3 Research Methodology
                       1.3.1 Primary Research
                       1.3.1 Secondary Research
                       1.3.1 GVR Internal Database
                   1.4 List of Secondary Sources
                   1.5 List of Abbreviations
Chapter 2 U.S. Market-Leading Analytics Practices
                   2.1.Practices benchmarking framework (U.S.-specific)
                       2.1.1.Demand forecasting aligned to U.S. seasonal trends (e.g., flu season, back-to-school)
                       2.1.2.Retail media effectiveness tracking across major U.S. media platforms
                       2.1.3.FDA-driven recall alert integration
                       2.1.4.Supply chain risk intelligence tied to U.S. disruptions (e.g., extreme weather, inflation)
                   2.2.Vendor Scoring Matrix
                       2.2.1.Circana and top 4-5 vendors ranked (1-5 scale) on delivery of best-in-class practices
                       2.2.2.Commentary on innovation, data latency, customer satisfaction (U.S. use cases)
Chapter 3 U.S. Commercial Terms Benchmarking
                   3.1. Pricing Models Comparison
                       3.1.1.Fixed annual vs. usage-based pricing (e.g., based on # of stores, categories, modules)
                       3.1.2.Tiered licensing by user type (analyst, manager, vendor partner access)
                       3.1.3.Cost-per-module or per analytic service line
                   3.2.Service Level Agreements (SLAs)
                       3.2.1.Typical U.S. data refresh rates (e.g., real-time, daily, weekly)
                       3.2.2.Support availability (U.S. hours vs. offshore)
                       3.2.3.System uptime & incident response benchmarks
                   3.3.Exit & Portability Clauses
                       3.3.1.Norms around contract termination, data extraction rights, and wind-down periods
                       3.3.2.Common limitations or penalties on early exits in U.S. contracts
Chapter 4. U.S. Retail Pharmacy Case Practices
                   4.1.Case references from
                       4.1.1.CVS Health
                       4.1.2.Walgreens Boots Alliance
                       4.1.3.Rite Aid
                       4.1.4.Kroger Health
                       4.1.5.Albertsons Companies
                   4.2.Key Contractual Terms in the U.S. Retail Pharmacy Sector
                       4.2.1.Duration, auto-renewal practices, exclusivity clauses
                       4.2.2.Analytics tools bundled into JBP (Joint Business Planning) with vendors
                       4.2.3.Modularity and expansion clauses over time
Chapter 5. U.S. Pricing & Revenue-Sharing Models
                   5.1.Pricing Approaches Used in the U.S
                       5.1.1.Flat-fee models (per client, per year)
                       5.1.2.Usage-based billing (by transaction, SKU, or promotion)
                       5.1.3.Outcome-based pricing (e.g., based on lift in conversion, sales, or margin)
                   5.2.Revenue-Sharing Practices
                       5.2.1.Case Scenarios: where vendors share uplift in revenue, margin, or cost savings
                       5.2.2.Case Scenario: where joint monetization is applied (e.g., retail media, co-owned insights)
Chapter 6 U.S. Competitive Landscape — Vendor Benchmarking
                   6.1 Company Market Position Analysis, 2024
                   6.2 Comparison Matrix on the Following Dimensions
                       6.2.1 Core analytics offerings for U.S. retail & pharmacy clients
                       6.2.2 Data types supported (shopper panels, POS integration, loyalty card, syndicated data)
                       6.2.3 Tech stack: dashboard UI, predictive engines, cloud deployment, APIs
                       6.2.4 U.S. client base segmentation (pharmacy, grocery, mass retail)
                       6.2.5 Compliance & data security
                   6.3 Profiles of Notable 10+ U.S.-Focused Vendors
                       6.3.1 NielsenIQ
                           6.3.1.1 Overview of services/modules offered
                           6.3.1.2 Industry verticals served
                           6.3.1.3 Core differentiators and innovation (AI/ML usage)
                       6.3.2 SymphonyAI Retail CPG
                           6.3.2.1 Overview of services/modules offered
                           6.3.2.2 Industry verticals served
                           6.3.2.3 Core differentiators and innovation (AI/ML usage)
                       6.3.3 Numerator
                           6.3.3.1 Overview of services/modules offered
                           6.3.3.2 Industry verticals served
                           6.3.3.3 Core differentiators and innovation (AI/ML usage)
                       6.3.4 Retail Solutions Inc. (RSI, now part of IRI)
                           6.3.4.1 Overview of services/modules offered
                           6.3.4.2 Industry verticals served
                           6.3.4.3 Core differentiators and innovation (AI/ML usage)
                       6.3.5 84.51° (Kroger-owned; offers analytics to other retailers in some cases)
                           6.3.5.1 Overview of services/modules offered
                           6.3.5.2 Industry verticals served
                           6.3.5.3 Core differentiators and innovation (AI/ML usage)
                       6.3.6 Dunnhumby
                           6.3.6.1 Overview of services/modules offered
                           6.3.6.2 Industry verticals served
                           6.3.6.3 Core differentiators and innovation (AI/ML usage)
                       6.3.7 SPINS LLC
                           6.3.7.1 Overview of services/modules offered
                           6.3.7.2 Industry verticals served
                           6.3.7.3 Core differentiators and innovation (AI/ML usage)
                       6.3.8 Inmar Inc.
                           6.3.8.1 Overview of services/modules offered
                           6.3.8.2 Industry verticals served
                           6.3.8.3 Core differentiators and innovation (AI/ML usage)
                       6.3.9 C3 AI
                           6.3.9.1 Overview of services/modules offered
                           6.3.9.2 Industry verticals served
                           6.3.9.3 Core differentiators and innovation (AI/ML usage)
                       6.3.10 Profitero, Inc.
                           6.3.10.1 Overview of services/modules offered
                           6.3.10.2 Industry verticals served
                           6.3.10.3 Core differentiators and innovation (AI/ML usage)
                       6.3.11 Circana
                           6.3.11.1 Overview of services/modules offered
                           6.3.11.2 Industry verticals served
                           6.3.11.3 Core differentiators and innovation (AI/ML usage)