Customer 360 for Retail and Ecommerce
Rysun Labs · Operations & Productivity
Certification per AWS Marketplace.
Evidence tier Source Confirmed · 4 captures on record
What the publisher says
As described on AWS Marketplace.
Retail and ecommerce organizations sit on enormous volumes of customer data – and most of it is fragmented. Loyalty records that do not match ecommerce profiles. In-store purchase history disconnected from mobile behavior. CRM contacts that duplicate across regions.
**When customer data works against you**
Show the rest of the publisher’s description (12 more lines)
Fragmented customer data does not just create reporting problems – it actively undermines the programs built on top of it. Churn models that score on incomplete behavioral data. Personalization engines firing the wrong recommendations. Conversational AI tools that contradict themselves because they have no single source of truth to draw from.
**Rysun's Customer 360 platform on AWS** resolves customer identity across heterogeneous sources, builds a governed Golden Record, and enables the analytics, segmentation, and AI-ready data layer your organization needs to act on customer data in real time.
**A unified view of every customer**
Rysun delivers a unified, governed customer record – with the identity resolution, analytics, and AI-ready context layer that makes it actionable for churn prevention, personalization, CLV growth, and conversational customer service. The architecture and operating model are yours to own and extend after delivery.
- Unified customer identity resolved across online, in-store, loyalty, and third-party sources
- A governed Golden Record with full lineage – a single trusted version of every customer
- Predictive analytics for churn scoring, CLV modeling, and behavioral segmentation
- Personalization-ready customer data for cross-sell, upsell, and next-best-action recommendations
- AI-ready customer context layer powering conversational and agentic customer service on a single trusted profile
**Recommended AWS stack**
Amazon S3, AWS Glue, Amazon Redshift, AWS Lambda, Amazon OpenSearch Service for fuzzy and semantic matching, Amazon SageMaker AI for predictive analytics, Amazon Personalize for recommendations, Amazon Bedrock for conversational and agentic AI, Amazon QuickSight for dashboards.
Delivered in phases over 8-12 weeks. Scope, domain priorities, and source system coverage confirmed at engagement start.
Highlights
Highlighted by the publisher on AWS Marketplace.
Build a unified, governed Golden Record for every customer across retail and ecommerce channels – creating the trusted data foundation that analytics, AI, and operational teams can rely on.
Enable conversational AI assistants and agentic customer service workflows that draw on a single, real-time trusted customer profile – so every AI-driven interaction reflects accurate purchase history, loyalty status, preferences, and open issues.
Activate predictive churn scoring, lifetime value modeling, behavioral segmentation, and next-best-action recommendations – built on Amazon SageMaker AI and Amazon Personalize using your governed customer master data.
Agent build and provenance
See the full provenance
The layer-by-layer build, the evidence behind each claim, the risk basis and the cross-marketplace links are open to any account. Some rows are disclosed, some the source leaves Unknown; a free account shows you which.
Sources
Linked repositories
Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.
Evidence risk is the share of the build you cannot see before you deploy, not a security rating. Sign in to see the layer-by-layer basis for this band.