Service
Cloud23 implements Salesforce Data Cloud to unify customer data from core systems, channels and CRM into real-time profiles that power personalisation, analytics and AI.
Salesforce Data Cloud is Salesforce's customer data platform. It ingests data from CRM, core systems, data warehouses and digital channels, resolves identities into unified customer profiles, and activates those profiles in real time across Salesforce applications, marketing, analytics and AI. Cloud23 designs and implements Data Cloud for organisations that need a single, trustworthy view of the customer to actually drive action, not sit in a report.
The case is sharpest in financial services, where customer data is scattered across core banking, card systems, policy administration and digital channels. Data Cloud's zero-copy connections to warehouses such as Snowflake and BigQuery mean unification does not require yet another copy of the data, and the resulting profiles become the grounding layer for Einstein and Agentforce, because AI in the enterprise is only as good as the data beneath it.
We implement Data Cloud use-case first. Rather than a boil-the-ocean data programme, each phase is anchored to a specific outcome, such as next-best-action in the contact centre or real-time segmentation, so value lands early and the data model grows with evidence behind it.
What you get
Prioritised use cases with the data sources, profiles and activations each one requires, sequenced into a fundable roadmap.
Source mapping, harmonisation approach and identity resolution rules that determine how records from different systems become one customer.
Data streams, harmonised data model, unified profiles and zero-copy connections built, tested and documented.
The derived measures and audience segments your first use cases need, built to be reused rather than rebuilt per campaign.
Unified profiles surfaced where work happens: agent consoles, journeys, analytics and AI grounding, with measurement wired in.
Ownership, stewardship and quality monitoring so profiles stay trustworthy after the project team moves on.
How we work
Identify and prioritise the decisions and moments a unified profile should improve, and define how success will be measured.
Assess candidate sources for quality, availability and identifiers, and map them to the target data model.
Design ingestion, harmonisation, identity resolution and zero-copy patterns against your existing data estate.
Build data streams, unified profiles, calculated insights and segments iteratively, validating match rates and data quality as you go.
Deliver the first use case end to end and measure it, proving the platform with a result rather than a diagram.
Establish governance and monitoring, then extend to further sources and use cases on the strength of the first.
When it fits
In practice
FAQ
A warehouse stores and analyses data; Data Cloud is built to activate it. Data Cloud resolves identities into unified customer profiles and pushes them into live systems, such as agent consoles, marketing journeys and AI agents, in real time. The two are complementary: zero-copy connections let Data Cloud work directly against warehouse data instead of replacing it.
Identity resolution is the process of recognising that records from different systems, such as a core banking client, a card holder and a web visitor, are the same person, using deterministic and probabilistic match rules. The output is a unified profile per customer. Match-rule design is one of the most consequential decisions in an implementation, which is why we validate match rates with real data early.
Not strictly: Agentforce agents can work from CRM data alone. But an agent is only as informed as the data it can see, and Data Cloud gives agents unified profiles and signals from beyond the CRM. Organisations with fragmented customer data usually find Data Cloud is what makes their AI use cases credible.
Data Cloud is consumption-based: usage is metered in credits consumed by ingestion, processing, queries and activations, rather than per user. That makes early architecture decisions commercially significant, since inefficient pipelines burn credits. Cloud23 models expected consumption during design so costs are understood before they occur.
It depends on the number of sources and the state of your data, but the use-case-led approach means a first, well-scoped use case with a small number of sources can typically be live within a few months. The mistake to avoid is spending a year unifying everything before activating anything.
Keep exploring
Data & AI
Cloud23 designs, builds and operates Salesforce Agentforce agents and enterprise AI solutions that do real work in service, sales and operations, grounded in your data and governed by explicit guardrails.
Explore serviceData & AI
Cloud23 provides data and analytics services for Salesforce-centred organisations — data strategy, single-customer-view architecture, Data Cloud implementation, dashboards and the data foundations that AI initiatives depend on.
Explore serviceIntegration
Cloud23 designs and builds enterprise integration on MuleSoft, using API-led architecture to connect Salesforce with core banking, payments, identity and legacy systems for regulated businesses across Africa and beyond.
Explore serviceSalesforce
Cloud23 designs and implements Salesforce Financial Services Cloud for banks, insurers and wealth managers across Africa and beyond, from digital onboarding journeys to a single view of the client.
Explore serviceA short conversation with our team is the fastest way to understand whether this is the right engagement for you, and what it would involve.