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Scenario

A company collects customer feedback and preferences through various channels, such as post-purchase surveys (e.g., via Google Forms, results in Google Drive) or direct feedback. They want to use this information to dynamically tailor customer experiences. An Agentforce agent, powered by ACP, will ingest this data into Data Cloud, which then triggers personalized actions in Marketing Cloud, Service Cloud, and Slack based on updated customer segments and attributes.

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Actors

  • Marketing Operations Manager
  • Customer Service Manager
  • Agentforce Agent (powered by ACP)
  • Customer

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ACP Components Involved

  • Google Drive Connector (or specific Survey Tool Connector):
    • google_drive_read_sheet_rows (or survey_tool_get_new_responses): To fetch new survey responses.
  • Data Cloud Connector:
    • data_cloud_ingest_data_stream_event (or data_cloud_upsert_profile_attributes): To feed survey data into Data Cloud, updating customer profiles or triggering events.
    • data_cloud_monitor_segment_changes (or data_cloud_get_segment_membership_updates): To detect when customers enter or leave key segments.
  • Marketing Cloud Engagement (MCE) Connector:
    • mce_add_contact_to_journey (or mce_update_contact_in_data_extension): To enroll customers in specific Marketing Cloud journeys or update their data.
  • Salesforce Core Connector (Service Cloud):
    • salesforce_create_case: To automatically log a case for follow-up.
    • salesforce_create_task: To assign a task to a service agent.
  • Slack Connector:
    • slack_post_message_to_channel (or slack_post_message_to_user): To notify internal teams (e.g., service managers) about critical customer feedback.
(Tool names are illustrative and will depend on the final ACP connector implementation.)

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Workflow

The following diagrams illustrate the workflow. Participant aliases are: CustResp (Customer Response), SrcData (Source Data, e.g., GDrive/Survey), AFA (Agentforce Agent), DC (Data Cloud), MCE (Marketing Cloud Engagement), SvcCloud (Service Cloud), Slack (Internal Team), CSMgr (Customer Service Manager), MktgMgr (Marketing Ops Manager).

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Diagram 1: Data Ingestion and Processing

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Diagram 2: Event-Driven Orchestration

  1. Data Ingestion (Survey to Data Cloud):
    • The Agentforce agent periodically checks for new survey responses using the google_drive_read_sheet_rows tool (assuming survey results are collated in a Google Sheet).
    • For each new response, the agent extracts relevant data (e.g., customer identifier, satisfaction score, product interest, feedback text).
    • The agent uses data_cloud_ingest_data_stream_event to send this data to Data Cloud, which updates the corresponding unified customer profiles.
  2. Segment Updates & Event Triggering (Data Cloud):
    • Data Cloud processes the incoming data. Based on predefined rules and the new information:
      • Customers might be added to or removed from specific segments (e.g., “High-Value Interested in Product X,” “Low Satisfaction Score”).
      • Data Cloud might generate real-time events based on these changes.
  3. Agent Monitoring & Action Orchestration (ACP):
    • The Agentforce agent monitors Data Cloud for significant segment changes or specific events using data_cloud_monitor_segment_changes.
    • Scenario A: Customer expresses interest in a new product category.
      • Data Cloud adds the customer to the “Interested in Product X” segment.
      • The agent detects this change.
      • The agent uses mce_add_contact_to_journey to enroll the customer in a Marketing Cloud journey designed to nurture interest in Product X.
    • Scenario B: Customer provides a low satisfaction score.
      • Data Cloud adds the customer to the “Low Satisfaction Score” segment and/or flags their profile.
      • The agent detects this.
      • The agent uses salesforce_create_case to automatically open a high-priority case in Service Cloud, assigning it to a customer retention specialist. The case description includes the survey feedback.
      • The agent also uses slack_post_message_to_channel to notify the Customer Service Manager in a dedicated Slack channel about the urgent case.
  4. Closed-Loop Feedback (Optional):
    • Once a service case is resolved, the resolution details could be fed back into Data Cloud by an agent to further enrich the customer profile.

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Key Outcomes & Benefits

  • Proactive & Personalized Customer Engagement: Automatically triggers relevant marketing or service interactions based on real-time customer data and feedback.
  • Improved Customer Retention: Quickly identifies and addresses customer dissatisfaction by automating service recovery processes.
  • Increased Marketing ROI: Delivers more relevant marketing messages by dynamically segmenting and targeting customers based on their latest expressed interests.
  • Enhanced Data Utilization: Transforms raw survey/feedback data into actionable insights and automated workflows.
  • Streamlined Cross-Cloud Operations: Seamlessly connects data ingestion, data processing (Data Cloud), marketing execution (MCE), service management (Service Cloud), and internal communications (Slack).
  • Scalable Personalization: Enables personalized customer journeys at scale, which would be difficult to manage manually.
This use case demonstrates how ACP, with Data Cloud at its core, can create a highly responsive and intelligent system for orchestrating customer experiences across the entire Salesforce ecosystem and beyond.