Creating one connected view of every retail customer
A unified customer data platform that connected point of sale, loyalty, ecommerce, mobile, customer service and marketing data into a governed customer 360 view, giving teams a consistent understanding of customers across channels and enabling faster segmentation and personalized engagement.
Customer information existed across the retail estate, but teams did not have one trusted customer view.
Store transactions, loyalty profiles, ecommerce activity, mobile behavior and service interactions were managed in different systems. Business teams could see individual pieces of customer behavior, but connecting those signals required manual work and repeated data reconciliation.
What we found
- Customer identifiers differed across POS, loyalty, ecommerce and service systems.
- The same customer could appear as multiple records across channels.
- Customer attributes and transaction history were not consistently connected.
- Marketing teams depended on manual extracts to build campaign audiences.
- Analytics teams spent time joining and reconciling customer data before analysis.
- Customer service teams had limited context about recent purchases and interactions.
- Customer segmentation was refreshed periodically rather than from a continuously updated view.
What the business needed
- A single governed customer identity across physical and digital channels.
- A trusted customer profile combining behavior, value, preferences and interactions.
- Near real time availability of important customer events where required.
- Reusable customer segments for marketing, analytics and service.
- Faster audience creation without repeated data preparation.
- Common customer metrics and definitions across business functions.
- A foundation for recommendation, retention and next best action use cases.
We created a governed customer data foundation that connected identity, behavior and value across channels.
The solution focused on resolving customer identity first, then building reusable customer attributes and segments that could be consumed by analytics, marketing and service teams.
Customer 360 data platform
The platform created a consolidated customer profile from multiple retail sources and made it available through governed analytics and downstream business processes.
- Ingested POS, loyalty, ecommerce, mobile, CRM, customer service and campaign data.
- Designed customer identity resolution rules using deterministic and probabilistic matching where appropriate.
- Created a golden customer record with stable identifiers and mastered customer attributes.
- Built reusable customer features covering purchase frequency, recency, monetary value, category affinity, channel preference and engagement.
- Created standardized customer segments for high value, at risk, active, new and dormant customers.
- Exposed governed customer data through Power BI and downstream marketing and service processes.
- Implemented access controls, data quality checks and privacy controls around sensitive customer information.
Customer signals were connected through a governed data layer and exposed as reusable customer intelligence
The architecture supports batch and near real time data patterns depending on the business requirement and source system capability.
A six stage approach to create a trusted customer view and make it usable across the organization
The implementation prioritized the highest value customer data sources and business processes before expanding the customer model.
Profile
Assess customer sources, identifiers, data quality, ownership and existing customer reports.
Unify
Connect customer records and define the enterprise customer identifier and source hierarchy.
Resolve
Apply identity matching rules and create the trusted customer profile.
Enrich
Build behavioral attributes, value measures, preferences and reusable customer features.
Activate
Expose customer intelligence to analytics, marketing, personalization and service teams.
Improve
Monitor quality, match rates, adoption and business response and continuously refine the model.
The customer data model reduced manual reconciliation and made customer intelligence available much faster.
Faster customer insight generation
Reusable customer datasets and standardized features reduced the time required to prepare customer analysis.
Lower reconciliation effort
Identity resolution and common customer identifiers reduced repeated matching and joining work across teams.
Faster campaign audience creation
Marketing teams could use governed customer segments instead of preparing audiences from multiple source extracts.
Improvement in segment response
More relevant customer segments supported better targeted customer engagement.
Faster customer service context
Service teams could access a broader customer history without collecting information from separate systems.
Customer identity match target
A standardized matching process established a measurable quality target for the consolidated customer identity.
Customer data became an enterprise capability instead of a collection of channel specific records.
The customer 360 foundation gave business teams a consistent view of customer behavior and created a reusable base for future analytics and AI use cases.
One Customer View
Store, digital, loyalty and service interactions could be understood against a common customer identity.
Faster Customer Analytics
Reusable customer features and segments reduced repeated data preparation for analytics teams.
Better Customer Activation
Marketing and customer teams could work with more timely and relevant customer segments.
Foundation for Personalization
The customer model created the data foundation needed for recommendations, next best action and retention use cases.
Build a customer view that every team can trust.
From customer identity resolution and data engineering to customer segmentation, analytics and activation, a governed Customer 360 foundation can connect retail channels and create a stronger base for personalization.
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