Case Study

Architecting a customer data foundation for multi-product lead aggregation and consent management

Cloud Genii helped a South African insurance services organisation create a stronger person-level foundation for Marketing Cloud audiences, consent handling and multi-channel communication readiness.

Client: South African insurance services organisationIndustry: Financial services / Insurance / Customer data and marketing operationsService: Customer data foundation and consent managementPlatform: Salesforce Marketing Cloud

TL;DR

Cloud Genii helped strengthen the customer data foundation behind a high-volume Salesforce Marketing Cloud environment.

The work focused on person-level aggregation, audience hygiene, opt-in and opt-out state management, and the practical problem of fragmented customer identifiers across multiple product journeys.

Instead of treating email, SMS, WhatsApp, quote and newsletter data as separate operational silos, Cloud Genii helped create a controlled foundation for audience and consent decisions.

A dependable base for segmentation, suppression, journey eligibility, reporting and future Marketing Cloud evolution.

Person-level foundation

Customer and quote activity organised into a usable audience base.

Consent control

Email, SMS and WhatsApp preference states aligned clearly.

Audience hygiene

Stale and duplicate audience issues reduced through controlled logic.

Future readiness

A stronger base for segmentation, reporting and Marketing Cloud Next planning.

The situation

The client’s marketing operation depended on customer and quote data flowing into Salesforce Marketing Cloud from several product-led journeys. A single person could interact with the business more than once, across different products and at different times, creating multiple operational records that were useful for campaign execution but harder to reconcile into a dependable customer view.

At the same time, the business needed to respect channel preferences across email, SMS and WhatsApp. The practical challenge was not simply sending messages. It was knowing which record represented the person, what the latest usable information was, and whether that person could be contacted through each channel.

What was getting in the way

Customer identity was fragmented across quote activity, newsletter audiences, subscription records and channel-specific data sources.
The quote process generated operational identifiers that were useful for journeys and handoff, but did not automatically create a clean, long-term customer view for marketing purposes.
The newsletter audience had become a static and degrading data set because it was not continuously enriched with fresh demographic and behavioural information.
Consent and preference handling had to work across multiple channels rather than being treated as separate lists with separate logic.
Marketing teams needed a dependable person-level foundation that could support segmentation, journey eligibility, suppression and future optimisation without rebuilding logic in every campaign.

What Cloud Genii changed

Designed a person-level aggregation approach that consolidated opted-in journey records, historical newsletter records and subscription-related sources into a usable Marketing Cloud audience structure.

Structured logic to prioritise usable customer attributes from newer or better records, reducing reliance on stale or incomplete contact data.

Brought channel preferences into the customer view by aligning email, SMS and WhatsApp opt-in or opt-out states with the audience records used for communication.

Supported subscriber reactivation where a valid fresh opt-in existed, helping the business distinguish between historic suppression and newly provided consent.

Improved audience hygiene by deduplicating contact records where possible and preparing sendable audiences from a controlled person-level base.

Connected the aggregation process to the broader Marketing Cloud operating model so journey, newsletter, WhatsApp and reporting processes had a stronger data foundation.

Salesforce capabilities involved

Salesforce Marketing CloudAutomation StudioData ExtensionsSQL Query ActivitiesPerson-level audience aggregationNewsletter audience dataQuote and lead data structuresEmail opt-in and suppression logicSMS preference handlingWhatsApp preference handlingAll Subscribers status managementDeduplication logicAudience hygieneConsent-state managementSegmentation readinessMarketing Cloud Next readiness

What changed

  • A clearer base for deciding who should receive communication and through which channel.
  • Improved ability to consolidate customer details across quote-led and newsletter-led data sources.
  • Stronger preference-state management across email, SMS and WhatsApp.
  • Reduced risk of outdated audience data driving communication decisions.
  • Better readiness for future segmentation, reporting, journey orchestration and Marketing Cloud Next or Data Cloud evolution.
  • A defensible consent and audience-management model for a high-volume, multi-product marketing environment.

What this shows

This case study shows Cloud Genii’s belief that marketing automation only scales when the data foundation is strong enough to support it. The visible campaign is rarely the real problem. The real work is often below the surface: identity, consent, audience structure, data freshness and operational control. By improving those foundations, Cloud Genii helped create a trustworthy base for customer engagement across channels.

Need a stronger customer data and consent foundation?

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