Retail and eCommerce Data to Intelligence Assessment on AWS

Retail and eCommerce organizations generate large volumes of data across digital storefronts, customer interactions, transactions, marketing campaigns, and supply chain operations. However, this data is often fragmented across platforms such as eCommerce systems, CRM, marketing tools, and analytics solutions—limiting its effectiveness in driving real-time decision-making. Without a unified and governed data foundation, retailers struggle to deliver consistent customer experiences, optimize product performance, and extract actionable insights from behavioral and transactional data. This results in lower conversion rates, inefficient marketing spend, poor inventory decisions, and missed revenue opportunities. Compass UOL helps retailers assess and modernize their data landscape on AWS by transforming fragmented data environments into scalable, analytics-ready platforms. This assessment evaluates current data sources, pipelines, governance models, and analytics capabilities to identify gaps and define a structured roadmap from raw data to actionable intelligence. Leveraging AWS-native data and analytics services, Compass UOL defines a reference architecture that enables unified customer data, real-time insights, and advanced analytics capabilities. This allows retailers to improve personalization, optimize product performance, and make data-driven decisions across the entire commerce lifecycle. Customers leave with a clear plan to unify their data, improve analytics maturity, and enable scalable intelligence that drives conversion, revenue growth, and operational efficiency.

Buyer Problem / Business Trigger

Fragmented customer and commerce data across multiple platforms Limited visibility into customer behavior, product performance, and campaign effectiveness Low conversion rates due to lack of personalization and real-time insights Inefficient decision-making in pricing, inventory, and marketing

Delivery Model

Discovery of data landscape and business priorities (conversion, personalization, operations) Assessment of data architecture, pipelines, and analytics capabilities Definition of AWS-native data and intelligence architecture Roadmap creation for data modernization and analytics enablement

Assessment / Engagement Scope

Inventory and evaluation of data sources (eCommerce, CRM, marketing, transactions, supply chain) Assessment of data ingestion, processing, and storage pipelines Review of data governance, quality, and consistency Evaluation of analytics, reporting, and personalization capabilities Identification of real-time analytics and AI/ML opportunities Design of AWS-native architecture (data lake, analytics, customer data platforms)

Expected Output / Deliverables

Data maturity and intelligence assessment report AWS reference architecture for retail data platforms Unified customer data and analytics model recommendations Prioritized use cases (personalization, product optimization, campaign analytics) Implementation roadmap for data modernization and analytics scaling

Customer Decision Questions This offer helps the customer answer:

How do we unify customer and commerce data to enable better decision-making? Which AWS architecture supports scalable analytics and real-time insights? Where can data-driven insights improve conversion rates and revenue?