Cloud Genii helps organisations improve the data structures, logic and information flow that underpin Salesforce performance.
When data is poorly structured, reporting weakens, automation becomes less reliable, and teams lose confidence in the platform.
This is not data cleanup for its own sake. It is about creating a Salesforce data foundation that supports reporting, segmentation, automation, AI readiness and long-term scale.
What is going wrong
Data problems rarely stay in one place. They weaken reporting, segmentation, automation, handoffs and adoption.
A reporting issue may actually be an object model issue. A segmentation issue may point to inconsistent source data. An automation issue may depend on fields no one owns.
Common symptoms include reports that no longer reconcile, fields that mean different things to different teams, duplicated data capture, weak object relationships, unclear ownership, poor campaign attribution and data structures that no longer match how the business operates.
Why it happens
Many data issues start as reasonable shortcuts: a field added quickly, a process changed without redesigning the object model, or reporting built around inconsistent inputs.
Over time, those decisions become the foundation for dashboards, automations, integrations and segmentation. The business keeps building on data structures that were never designed to carry that much weight.
Cloud Genii treats data architecture as a business reliability issue, not a cleanup exercise. The work starts by understanding how the business needs to see, manage and act on information, then aligning Salesforce structure to that reality.
What Cloud Genii does
Cloud Genii strengthens the structural foundations that make Salesforce more usable, maintainable and dependable across the business.
What we do
Review the current data model, object relationships, fields, ownership and reporting dependencies
Identify where weak structures are causing reporting, automation or segmentation issues
Design clearer data and process foundations for existing orgs or new implementations
Align data architecture with campaign, lead, opportunity, revenue and operational reporting needs
Create practical recommendations for cleanup, redesign, integration alignment or future platform readiness
Capabilities and structures involved
Relevant work may involve Salesforce data model design, standard and custom objects, object relationships, Lead, Account, Contact and Opportunity architecture, Campaigns and Campaign Members, field strategy, validation rules, duplicate management considerations, Reports and Dashboards, segmentation structures, Data 360 / Data Cloud readiness, integration patterns, API and data flow considerations, automation dependencies and governance configuration.
Clearer reporting confidence and fewer manual reconciliations
More reliable automation because the data foundation is clearer
Stronger segmentation and campaign execution
Cleaner ownership of fields, objects and business-critical data
Better readiness for AI, Agentforce, Marketing Cloud Next or Data Cloud work
A Salesforce data structure that is easier to govern and improve over time
Common signs data architecture needs attention
Data architecture work is usually needed when Salesforce contains a lot of information, but the business still cannot trust what that information means.
Reports do not reconcile across teams
Fields mean different things to different users or departments
Users capture the same information in more than one place
Automation depends on fields with unclear ownership
Campaign, lead or opportunity reporting is difficult to explain
Segmentation requires manual exports or spreadsheet workarounds
Data quality issues are blocking AI, Agentforce, Marketing Cloud Next or Data Cloud readiness
How data architecture improvement works
Cloud Genii does not start by moving data around. We first clarify what the data needs to support and where the current structure is creating friction.
Map the current data structure.Review the objects, fields, relationships, ownership patterns and reporting dependencies that shape how Salesforce is used.
Identify where trust breaks down.Find the points where reporting, automation, segmentation or handoffs are weakened by unclear or inconsistent data structures.
Clarify the future operating need.Define what the business needs Salesforce data to support across reporting, automation, marketing, revenue operations and future capability.
Design the right structural improvements.Shape the object model, field strategy, governance approach, integration logic or reporting foundation needed to support the business.
Create a practical roadmap.Separate quick cleanup from deeper redesign work, and define what should be handled now, later or as part of a wider Salesforce initiative.
Next step
If reporting, automation or marketing performance issues keep returning, the next step is often to review the data structure beneath them.
If the data issue is already known, Cloud Genii can help shape a focused data architecture improvement roadmap.
