Data Cloud (Data 360) case study: online and offline retail activation
This Data Cloud (Data 360) case study shows how ForceFolks joined online and in-store customer records for a retailer. Data Cloud matched 91% of 12 million records and connected Commerce Cloud and Marketing Cloud. Audience generation and activation fell from 4 days to under 5 minutes.
Key takeaways
- ForceFolks connected online shopping and in-store transactions to a unified customer profile.
- The retailer activates audiences through Marketing Cloud using Data Cloud and Commerce Cloud data.
- Audience activation takes under 5 minutes, and data-engineering overhead fell by 40%.
- An enterprise architecture and delivery pod completed the rollout in 6 months.
Data Cloud (Data 360) case study: retail project details
| Attribute | Detail |
|---|---|
| Salesforce partner | ForceFolks |
| Industry | Retail & E-Commerce |
| Company size | Enterprise: $800M revenue, 3,200 employees |
| Salesforce products | Data Cloud, Marketing Cloud, Commerce Cloud |
| Services provided | Data Architecture, Customer 360 Consulting, Platform Integration |
| Systems integrated | Oracle NetSuite POS, Snowflake data warehouse, Google Analytics 4 |
| Delivery model | Enterprise Architecture & Managed Delivery Pod |
| Team | 2 Data Architects, 1 Marketing Cloud Solution Architect, 2 MuleSoft Developers, 1 BI Analyst |
| Timeline | 6 months, blueprint to launch |
How ForceFolks unified online and offline customer data
The retailer needed one customer profile across store purchases and online activity. ForceFolks built identity rules before connecting segments to campaigns. MuleSoft integration connected the POS, commerce and marketing systems.
[Commerce Cloud and POS data] → [Data Cloud identity matching] → [Customer segments] → [Marketing Cloud journeys]
- Streaming ingestion collects online behavior from Commerce Cloud and store transactions from Oracle NetSuite POS.
- Data Cloud receives each stream in Data Source Objects through streaming APIs and staging tables.
- Identity rules match email hashes, phone numbers and loyalty IDs into Unified Individual profiles.
- Calculated Insights compute lifetime value, purchase recency, frequency and value, and churn risk.
- Segment rules select customer groups and send them through real-time data actions.
- Marketing Cloud Journey Builder starts cross-channel campaigns within 5 minutes of a trigger.
Measured results
- Adoption: 100% of the core marketing team built segments in Data Cloud without SQL queries.
- Data fidelity: 91% identity-match rate across 12 million fragmented records.
- Cycle time: audience generation and activation cut from 4 days to under 5 minutes.
- Cost: data-engineering overhead down 40% through ready-made connectors.
- Time-to-value: $2.3M in retargeting opportunity identified within 90 days.
- Accuracy: 100% alignment in profile-mapping rules, checked by automated QA.
Retail Data Cloud implementation: project questions
How does Salesforce Data Cloud unify customer data from POS, commerce, and marketing?
ForceFolks loaded source data into Data Source Objects and matched email, phone and loyalty IDs into Unified Individual profiles. This retailer reached a 91% identity-match rate across 12 million records. Matching rules were specific to its data.
How long does a Data Cloud Customer 360 implementation take for an enterprise retailer?
This ForceFolks rollout took 6 months from blueprint to launch. It included online and in-store data, identity rules and campaign activation. After launch, audience generation and activation took under 5 minutes instead of 4 days.
Can Data Cloud activate audiences in real time through Marketing Cloud?
In this implementation, Data Cloud sent segments through real-time data actions to Marketing Cloud Journey Builder. The retailer's campaigns started within 5 minutes of a trigger. ForceFolks connected activation to the same identity rules used for the customer profiles.
Related services and case studies
Connect your retail data before adding more campaigns
Show ForceFolks your POS, commerce and marketing data sources. We can assess identity matching, segment rules and the path from a customer event to a campaign.