Scoop Login
User Guide
Start typing to search…

CRM Writeback

Push calculated values back to your CRM automatically

CRM Writeback lets you push calculated values from Scoop back into your CRM system. Blend data from multiple sources, create sophisticated calculations, and automatically update your CRM with the results—enabling enriched customer records without manual data entry.

Why Use CRM Writeback?

Use CaseDescription
Customer Health ScoresCalculate scores from multiple data sources, write to CRM
Lead ScoringCombine behavioral data with firmographics for enriched leads
Territory AssignmentCalculate optimal territory and update account records
Lifecycle StageDetermine customer lifecycle position from activity data
Propensity ScoresCalculate purchase likelihood and push to sales records
Data EnrichmentAdd external data attributes to CRM records

How It Works

┌────────────────────────────────────────────────────────────┐
│ 1. EXTRACT                                                  │
│    CRM Data → Scoop Dataset (includes Record ID)           │
├────────────────────────────────────────────────────────────┤
│ 2. ENRICH                                                   │
│    Blend with other data sources                           │
│    Add calculated columns                                   │
│    Create derived metrics                                   │
├────────────────────────────────────────────────────────────┤
│ 3. WRITEBACK                                                │
│    Scoop → CRM (using Record ID)                           │
│    Automatic on each dataset processing                    │
└────────────────────────────────────────────────────────────┘

Supported CRMs

CRM Writeback is available for systems with API connections:

  • Salesforce
  • HubSpot
  • Microsoft Dynamics 365
  • Other CRMs with API connectors

See specific application documentation for connector details.

Setting Up CRM Writeback

Prerequisites

Before configuring writeback:

  1. API Connection — Establish API connection to your CRM
  2. Record ID — Extract records with their unique CRM Record ID
  3. Calculated Data — Create the values you want to write back

Step 1: Extract CRM Data with Record ID

When extracting from your CRM, include the Record ID column:

  • Salesforce: Id field
  • HubSpot: record_id or object-specific ID
  • Dynamics: accountid, contactid, etc.

Critical: The Record ID is required to update the correct records.

Step 2: Create Calculated Values

Option A: Calculated Columns

Option B: Blended Dataset

  • Combine CRM data with other sources
  • Preserve the Record ID through the blend
  • Always include Record ID in column selection

Step 3: Configure Writeback

Once your dataset has calculated values and Record IDs:

  1. Open the dataset menu
  2. Select Setup Application Writeback

Step 4: Map Fields

In the writeback configuration:

  1. Select the source table from your dataset
  2. Map Scoop columns to CRM fields
  3. Specify which column contains the Record ID

For each CRM field you want to update:

  • Select the Scoop column that contains the value
  • Verify data types are compatible

Step 5: Activate Writeback

Save your configuration. Now:

  • Each time the dataset processes, writeback runs automatically
  • Values are pushed to your CRM using the Record IDs
  • CRM records update with calculated values

Common Writeback Scenarios

Customer Health Score

Data Sources:

  • CRM: Account info, contract value
  • Support: Ticket volume, resolution time
  • Product: Usage metrics, feature adoption

Calculation:

Health Score = (Usage Score × 0.4) + (Support Score × 0.3) + (Engagement Score × 0.3)

Writeback:

  • Map Health_Score column → CRM Customer_Health__c field
  • Sales team sees scores directly in CRM

Lead Scoring

Data Sources:

  • CRM: Lead demographics, company size
  • Marketing: Email engagement, website visits
  • Third-party: Firmographic enrichment

Calculation:

Lead Score = Demographic Score + Behavioral Score + Fit Score

Writeback:

  • Map Lead_Score → CRM lead score field
  • Marketing automation triggers based on score

Cost to Serve

Data Sources:

  • CRM: Account and revenue data
  • Support: Tickets and time spent
  • Finance: Service costs allocated

Calculation:

Cost to Serve = Total Support Cost / Revenue

Writeback:

  • Map Cost_to_Serve → Account custom field
  • Account managers see profitability context

Best Practices

Data Quality

  • Validate calculations before enabling writeback
  • Test with a small subset first
  • Monitor for unexpected values

Record ID Handling

  • Never modify the Record ID column
  • Always include Record ID when blending
  • Verify Record IDs match CRM format

Field Mapping

  • Match data types (text to text, number to number)
  • Consider field length limits
  • Check for required field dependencies

Processing Schedule

  • Writeback runs each time dataset processes
  • Schedule during off-peak hours for large updates
  • Monitor CRM API limits

Troubleshooting

Records Not Updating

  • Verify Record ID column is correctly mapped
  • Check Record IDs exist in the CRM
  • Confirm API connection is active

Partial Updates

  • Check for null values in Scoop columns
  • Verify data type compatibility
  • Look for CRM validation rule failures

API Errors

  • Check CRM API rate limits
  • Verify user permissions for field updates
  • Review API connection status

Wrong Values Written

  • Review calculation logic
  • Check for data type conversions
  • Verify correct column is mapped

Monitoring Writeback

Track writeback success:

  • Check dataset processing logs
  • Monitor CRM field update timestamps
  • Verify sample records after processing

Security Considerations

  • Writeback uses your established API credentials
  • Only fields you map will be updated
  • Changes are logged in both Scoop and CRM
  • Consider which users can configure writeback

Related Topics

Updated 3 days ago