SALESFORCE MARKETING CLOUD | DATA 360
Salesforce Data Cloud
Strategic data unification within Marketing Cloud empowers immediate, intelligence-driven action. This foundational layer scales the Salesforce Agentforce strategy across the full customer lifecycle, guaranteeing accelerated revenue growth and maximised customer lifetime value.
What is Salesforce Data Cloud?
Data Cloud is an open and active, hyperscale customer data platform that powers the world’s first real-time CRM. Simply put – Data Cloud connects and harmonises your data to give you a complete view of your customers. Plus, with the combined powers of Data Cloud and Einstein, you can use AI to generate content, personalise experiences, and act on data faster.
“As B2B organizations strive to know which opportunities are best to pursue with extended sales cycles; how to retain accounts on a long-term basis; and align sales, marketing, and customer success to meet multi-persona requirements, CDPs are critical to your data-driven strategy.”
*SOURCE: IDC MarketScape | Worldwide Customer Data Platforms Focused on B2B Users 2024–2025 Vendor Assessment | Page 4
To discuss how Salesforce Data Cloud can impact your marketing automation and CX, contact us today.
Considerations* when analysing a CDP for your organisation
Account-Centricity & Enterprise Alignment
A B2B-focused CDP must be built on an account-centric data model, capable of handling the intricacies of B2B data structures. This includes managing hierarchies, scoring mechanisms, and multi-contact relationships at individual, group, opportunity, and account levels.
This granular view is essential for effective Account-Based Marketing (ABM) strategies. Furthermore, the CDP should offer a composable architecture, seamlessly integrating with existing enterprise systems. This modular approach facilitates bidirectional data flow, advanced query federation, and zero-copy ETL (Extract, transform, load), minimising data movement and maximising efficiency.
Streamlining sales and marketing collaboration requires robust lead scoring and qualification capabilities. A leading CDP will offer advanced scoring models, enabling sales teams to prioritise high-potential opportunities and tailor engagement strategies based on lead maturity.
Critically, the CDP should be able to enrich these profiles by incorporating unstructured and semi-structured data, such as support interactions, sentiment analysis, and Voice of Customer (VOC) feedback. This holistic view of the account fuels AI models, providing deeper insights and improving account management, acquisition, and retention.
Lead Scoring, Qualification, and Enrichment
Governance, Compliance, and Cross-Functional Integration
As AI-driven tools become more prevalent, robust governance and compliance standards are essential. The CDP must incorporate privacy, security, and data governance capabilities, ensuring adherence to data regulations and fostering trustworthy, transparent B2B engagements.
The value of a CDP is maximised when its unified data is leveraged across sales, marketing, customer success, and even product support. This cohesive approach supports initiatives like lead scoring, account insights, and proactive customer success measures, creating a unified customer experience.
Predictive AI enhances traditional B2B processes, including lead prioritisation, journey optimisation, and cross-channel orchestration. CMOs should ensure the chosen CDP’s AI capabilities are specifically tailored for the B2B context, enabling precise engagement that resonates with nuanced account needs. Furthermore, the emergence of Generative AI (GenAI) offers exciting possibilities.
A future-proof CDP will empower non-technical users with GenAI tools, providing accessible insights and data-driven recommendations. This democratises data access, enabling teams to explore data, create segments, and design customer journeys without requiring technical expertise, ultimately boosting productivity and data literacy across the organisation.
Predictive AI and Generative AI
B2B-Specific Tools and Proof of Concept
To accelerate implementation, CMOs should look for CDPs offering out-of-the-box templates, schemas, or playbooks tailored to B2B functions. These resources jump-start deployment by addressing common B2B scenarios, such as account engagement, renewal, and expansion strategies.
Finally, a crucial step in the selection process is demanding a thorough Proof of Concept (POC). This allows CMOs to validate the CDP’s performance against critical B2B scenarios and use cases, measuring outcomes against key objectives and ensuring tangible value and usability before making a final commitment.
By prioritising these considerations, CMOs can leverage CDPs to drive significant improvements in B2B growth, efficiency, and customer satisfaction.
*ACKNOWLEDGEMENT: Portions of the above suggestions for CDP considerations have been sourced from the IDC Worldwide Customer Data Platforms Focused on B2B Users 2024–2025 Vendor Assessment. We’ve added details to support the CMO and marketer in their CDP selection process.
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