Case study · Retail
One customer, whether they shop online or in store
Retailers know their online customers and their loyalty members, but rarely as the same people. This is how we unified store, online and loyalty data in Dynamics 365 Customer Insights and use it for segments and journeys that reflect what customers actually buy.
Project overview
A customer data platform and journeys on Dynamics 365.
- Industry
- Retail
- Client
- Confidential
- Solution
- Customer data and marketing automation
- Platform
- Customer Insights
- Timeline
- 12–20 weeks
- Team
- 3–4 people
- Sources
- POS, eCommerce, loyalty
- Channels
- Email, SMS, app push
- Measurement
- Holdout groups
Expected business outcomes
What the client set out to achieve
Personalised journeys outperform batch campaigns, measured with holdout groups.
-
10–25%
Higher email revenue per send
Segments based on purchases and preferences replace one-size campaigns.
Target range, measured against a holdout group
-
One
Profile per customer
Store, online and loyalty identities unified by matching rules.
Match rate depends on how often customers identify in store
-
Weeks → days
To launch a new segment
Marketers build segments themselves instead of requesting data extracts.
Once data flows are established
Business challenges
How retail marketing worked before
Every channel has its own customer list.
Online
eCommerce customers in the shop platform.
Stores
Transactions recorded by till, often without a customer.
Loyalty
A separate loyalty database with its own IDs.
Campaigns
Batch emails to everyone, with little personalisation.
Results
Campaign success judged by opens and clicks, not incremental sales.
Proposed solution
What the Customer Insights build covers
Data unification first, journeys second, measurement throughout.
-
Data ingestion
POS, eCommerce and loyalty data loaded daily into Customer Insights.
-
Unified profiles
Matching rules combine identities into one profile per customer.
-
Segments and measures
Lifetime value, category affinity and recency segments marketers can build.
-
Journeys
Welcome, browse abandonment, replenishment and win-back journeys.
-
Consent
Preferences respected across every channel and journey.
-
Measurement
Holdout groups to measure incremental revenue.
Project requirements
What the client asked us for
The request was personalisation. It depends on unification: knowing that the loyalty member, the online shopper and the in-store buyer are the same person.
We measure with holdout groups from the start, so the business knows which journeys actually add revenue.
What the project had to deliver
- 01One profile per customer
- 02Segments marketers build themselves
- 03Journeys based on behaviour
- 04Honest measurement
Key challenges & considerations
What made it harder, and what we did
-
Store transactions without customer IDs
What we did
Store staff were given simple ways to capture a customer ID at the till, and unmatched sales were reported.
-
Different IDs in each system
What we did
Matching rules unified the different IDs into one profile and were checked against real customers.
-
Consent captured inconsistently
What we did
Consent was brought into one model, and unclear records were excluded from marketing.
-
Marketing teams used to batch campaigns
What we did
The team started with three automated journeys, each measured against a holdout group.
What we watched for
- Encourage customer ID capture in store
- Check matching with real examples
- Measure with holdout groups
- Start with three journeys, not thirty
Development process
Unify, segment, automate, measure
Each step delivers value before the next begins.
-
Data sources
POS, eCommerce and loyalty feeds connected and profiled.
-
Unification
Matching rules tuned and checked with sample customers.
-
Segments
Core segments and measures built with the marketing team.
-
Journeys
First journeys launched with holdout groups.
-
Scale
More journeys and channels added based on measured results.
Technology stack
Customer Insights end to end
Microsoft's customer data platform and journey orchestration.
Data
- Customer Insights – Data
- Data lake
- Matching rules
Journeys
- Customer Insights – Journeys
- SMS
- Push
Sources
- POS exports
- eCommerce platform
- Loyalty system
Reporting
- Power BI
- Holdout analysis
Quality assurance & deployment
Tested by the people who use it every day
A CRM succeeds when people choose to use it. Every process was tested with real users on real scenarios, and data migration was rehearsed until the record counts agreed.
- Scenario testing with users from each role
- Migration rehearsals, with record counts reconciled
- Integration tests for every connected system
- Security roles checked against real job roles
- Solutions moved between environments as managed releases
Deployment
- 01JourneysFirst journeys launched with holdout groups.
- 02ScaleMore journeys and channels added based on measured results.
- 03Phased go-liveOne team or region first, then the rest, each wave with training by role.
- 04Hypercare and warrantyDaily support through the first weeks, and six months of free bug fixing.
Final deliverables
Marketing that follows the customer
Marketers build segments from real behaviour across channels and launch journeys that respond to what customers do.
Holdout groups show which journeys add revenue, so budget moves to what works.
- Unified customer profiles
- Self-service segments
- Behaviour-triggered journeys
- Incremental revenue measurement
Handed over to the client
- 01Configured Dynamics 365Production and test environments
- 02Solutions and integrationsAs managed, documented releases
- 03Migrated dataWith record counts reconciled
- 04Training by roleWith short guides
- 05Six-month warrantyFree bug fixing after delivery
Success metrics
How success is measured
| Measure | Outcome | How it is measured |
|---|---|---|
| Higher email revenue per send | 10–25% | Target range, measured against a holdout group |
| Profile per customer | One | Match rate depends on how often customers identify in store |
| To launch a new segment | Weeks → days | Once data flows are established |
Verified reviews
What clients say about our Dynamics work
Verified reviews from our clients on the same kind of work, published on Clutch.
-
Custom Software Development
Web-Based Coupon App Development
The work produced by the team was of exceptional quality.
Verified review on Clutch (Jon Thies, opens in a new tab)
Jon Thies
CTO, Model Rocket Feb 2022 – Mar 2023
-
Custom Software Development
Mobile & Web Platform Development & Design
Silver Scintilla was responsive, respectful, and enjoyable to work with, quickly addressing any questions or requests.
Verified review on Clutch (DeShawn Brown, opens in a new tab)
DeShawn Brown
CEO & Founder, Lithios Jun 2021 – Nov 2022
-
Custom Software Development
Web-Based HRM System Development
Silver Scintilla provided the best solution with scalable functionality, personalized features, and robust security.
Verified review on Clutch (Suheb Khan, opens in a new tab)
Suheb Khan
Director, Collaborative Insight Technologies Jul 2020 – Jun 2022
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