Power Your Business with
Salesforce Data Cloud
Customer data is scattered across CRM, marketing, service, commerce, and external systems, limiting connected experiences across channels. Salesforce Data Cloud unifies customer interactions into a single, real-time profile that powers smarter decisions, personalised engagement, AI-driven experiences, and more consistent customer interactions across every touchpoint.
Results from Salesforce Projects
What is Salesforce Data Cloud?
Data Cloud is Salesforce’s real-time data platform that unifies customer data from multiple sources into a single, continuously updated customer profile. It connects data from CRM, marketing, service, commerce, and external systems, enabling teams to work from the same customer view while supporting personalised engagement, analytics, automation, and AI-driven experiences across the organisation.
Six services across
the full Data Cloud implementation
Data Source Integration
- Native Salesforce connectors for Sales, Service, and Marketing Cloud
- Zero-copy federation with Snowflake, Databricks, and Google Cloud
- Streaming APIs and batch ingestion from enterprise systems
- Data source monitoring for ingestion health and reliability
Identity Resolution Configuration
- Deterministic and probabilistic identity matching rules
- Source reconciliation for conflicting customer attributes
- Identity graph validation before production deployment
- Conflict resolution for household and company profiles
Segment Building
- Dynamic audience segments from unified customer profiles
- Calculated insights including LTV, churn, and engagement scores
- Suppression rules for converted and opted-out audiences
- Scheduled segment publishing for campaign activation
Data Activation Setup
- Marketing Cloud and Sales Cloud data activation
- Audience publishing to Google, Meta, and LinkedIn
- Salesforce Flow triggers from profile updates
- External activation through APIs and data connectors
Data Model Customisation
- Custom objects, attributes, and behavioural event definitions
- Relationship mapping across customers and business entities
- Consent and preference management configuration
- Data mapping documentation for governance and traceability
Reporting and Insight Configuration
- CRM Analytics dashboards built on unified customer profiles
- Cross-channel attribution across sales, marketing, and service
- Churn prediction and lifetime value reporting
- Data quality and segment performance monitoring
From data assessment to
activated unified profiles in four structured phases
Data Landscape Assessment and Architecture Planning - Phase 01
Data Model Build and Source Integration - Phase 02
Segment Build, Activation Configuration, and Testing - Phase 03
Production Go-Live and Ongoing Optimisation - Phase 04
Three common data problems,
and how Data Cloud resolves each one

THE PROBLEM
Unifying CRM and Marketing Data

HOW DATA CLOUD HELPS
Single Real-Time Profile Shared Teamwide

THE PROBLEM
Real-Time Personalisation

HOW DATA CLOUD HELPS
Always-Current Campaign Profiles

THE PROBLEM
Audience Segmentation for Campaigns

HOW DATA CLOUD HELPS
Automatically Activated Segments
Frequently Asked Questions
Data Cloud is Salesforce’s real-time customer data platform that unifies information from CRM, marketing, service, commerce, and external systems into a single, continuously updated customer profile for every team.
Data 360 is the latest evolution of Salesforce Data Cloud, adding AI-powered semantic modelling, enhanced zero-copy data access, Clean Rooms, and deeper Agentforce integration while retaining Data Cloud’s unified customer data foundation.
TechnoRUCS configures data integration, identity resolution, audience segmentation, activation across Salesforce clouds, custom data models, and reporting dashboards, tailoring every implementation to your data landscape and business objectives.
A typical Data Cloud implementation takes 8 to 14 weeks, depending on data sources, identity resolution complexity, integrations, and activation requirements. More complex multi-system environments generally require additional implementation and validation time.
Ready to Unify Your Customer Data with Data Cloud?