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Data 360 and Agentforce: AI-Driven Decisions with Salesforce
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Published on
July 04, 2024
Reading time
6 Minuten
At a Glance
- Data 360 is the data foundation for Agentforce and brings together customer data from multiple sources into unified profiles.
- Agentforce acts autonomously and handles routine tasks in marketing, sales and service without team members needing to initiate every step.
- Without harmonised data, AI agents operate unreliably. Data 360 provides the context that enables precise action.
- Einstein AI remains active as the analytical foundation and provides lead scoring, opportunity insights and account insights within the Agentforce architecture.
- The added value comes from the interplay between Data 360 and Agentforce, transforming how organisations work across marketing, sales and service.
What is Salesforce Data 360?
Salesforce Data 360 is the data infrastructure at the core of the Salesforce platform. It consolidates customer data from various sources – for example, other Salesforce Clouds, external systems such as AWS, Google Cloud or Azure, or internal databases – into a single, unified customer profile.
What initially sounds like a classic data warehouse is conceptually different. Salesforce Data 360 uses a Unified Data Model (UDM) that semantically links records from different systems – recognising that “Schmidt, Thomas” in System A and “T. Schmidt” in System B may be the same person. It cleans up duplicate entries, inconsistent fields and outdated data points. The result is a complete, up-to-date 360-degree profile for each contact.
What Data 360 Delivers
- Connect data from Salesforce Clouds and external sources via native interfaces or MuleSoft connectors
- Harmonise records and automatically resolve inconsistencies
- Build unified customer profiles that update in real time
- Derive segments for marketing, sales and service directly from the data profile
- Provide these segments and profiles as a foundation for AI models and Agentforce agents
Data 360 is therefore not a standalone analytics tool. Instead, it is the shared foundation on which all other Salesforce products operate.
What Is Agentforce and How Has Salesforce AI Evolved?
Since 2024, Salesforce has fundamentally realigned its AI strategy. What was previously labelled “Einstein AI” (predictive analytics, lead scoring, automated recommendations) now sits within the broader Agentforce architecture.
Agentforce is the Salesforce platform for autonomous AI agents. Unlike traditional AI features, agents do not wait for team members to trigger a function. They monitor data, make decisions based on defined rules and language models, and execute actions autonomously – for example, creating a service ticket, following up with a lead, or triggering a campaign.
The AI Layer in Salesforce
- Einstein AI: The underlying AI layer for predictive models, NLP and image processing delivers scores, recommendations and insights directly into the Salesforce Clouds.
- Tableau (formerly Einstein Analytics): Visualisations and interactive dashboards enable data-driven decision-making.
- Agentforce: The autonomous agents are built on Einstein AI, Data 360 and the Salesforce Clouds, and act independently.
The Key Features of Einstein AI
- Predictive Analytics: Einstein analyses historical data to predict future trends and behaviour patterns, such as likelihood to purchase or churn risk.
- Lead Scoring and Opportunity Insights: Leads and active deals are automatically scored based on their likelihood of closing, enabling sales teams to allocate their capacity more effectively.
- Personalised recommendations: Based on customer behaviour and preferences, Einstein generates product or service recommendations directly within the workflow.
- Natural Language Processing (NLP): Einstein understands and processes text data, including customer enquiries via emails or conversation analyses, and derives actionable insights from them.
All of these functions are now part of the Agentforce architecture and provide the foundation for AI agents to make autonomous decisions.
Why Data 360 Is a Prerequisite for Agentforce
AI agents depend on the quality of the data they operate on. An agent designed to proactively contact customers needs to know which products they use. When did they last contact the service team? Are there any open complaints? And are they part of a customer segment with an increased risk of churn?
All this information sits in different systems, such as CRM, ERP, a support tool, or web analytics. Data 360 brings it together in a single, consistent profile that Agentforce can access in real time.
In Short: Data 360 provides the contextual insight that Agentforce draws on.
Without complete data profiles, agents would make decisions based on gaps too – with correspondingly unreliable outcomes. With Data 360 as the foundation, agents can act precisely, personally, and at the right moment.
Use Case: Data 360 and Agentforce for Marketing, Sales and Service
The Initial Situation
Let us consider a mid-sized company in the manufacturing industry, as found in countless examples across the DACH region. The company uses Salesforce for sales, service, and marketing, but operates with isolated data silos. The CRM holds transaction data, the ERP holds inventory and delivery data, and the marketing tool holds campaign histories. There is no unified customer view.
The Challenges
- The marketing team segments target audiences manually and based on outdated data.
- Sales prioritises leads based on gut feel, not on transparent criteria.
- The service team responds to issues rather than identifying them early.
The Solution
Data 360 harmonises data from CRM, ERP and marketing tools into unified customer profiles. Agentforce works on this basis and automatically takes care of routine tasks across all three areas.
Targeted Segmentation and Autonomous Campaign Management
Automated Segmentation Based on Real Behavioural Data
With Data 360, the Marketing Cloud analyses real customer behaviour – purchase history, responses to previous campaigns, service interactions and website engagement – and automatically creates segments. This replaces the manual maintenance of lists and filters.
An AI agent then takes over campaign orchestration. It identifies when a contact moves into a new segment, triggers the relevant communication, and adjusts timing and channel based on engagement data.
Tableau: Real-Time Monitoring of Campaign Performance
Tableau dashboards show the marketing team how individual campaigns perform – for example through click-through rates, conversion rates or revenue impact. Instead of weekly reports based on exports, the team works with a view that updates in real time.
The Impact: Greater relevance in customer engagement through up-to-date data, less manual segmentation effort and faster campaign optimisation based on measurable results.
The Advantages of Data 360
How Salesforce Data 360 can be used across departments together with Agentforce and other AI capabilities is outlined above. The overview below summarises the benefits you can expect:
– Current, behavioural data-driven segmentation instead of manual lists
– Autonomous campaign management using AI agents from Agentforce
– Real-time monitoring with Tableau dashboards
– Higher conversion rates through more precise audience targeting
– Competitive advantage through data-driven marketing based on robust analysis rather than gut instinct
– Transparent lead prioritisation with Einstein Lead Scoring
– Automated follow-up using Agentforce
– Early warning system for at-risk customer relationships through account insights
– More capacity for closing-critical activities
– Improved customer retention through proactive churn prevention measures
– Proactive customer engagement before issues escalate
– Full automation of standard enquiries
– Complete customer context for every service case
– Measurable service quality based on Tableau
– More efficient service processes by automating routine tasks and reducing processing times
Conclusion
The combination of Data 360 and Agentforce is changing how organisations work with Salesforce. Data 360 creates the unified customer view that has often been missing to date. Agentforce uses this view to handle routine tasks autonomously and involve team members in a targeted way where judgement and relationships matter.
Salesfive supports organisations in taking this step in a structured way – from data strategy through to Agentforce implementation. Get in touch with no obligation.
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