Cloudingo Setup Guide: Salesforce Deduplication Made Simple

Cloudingo is a cloud-based Salesforce deduplication tool known for its user-friendly interface and powerful automation capabilities. If DemandTools feels too complex, Cloudingo offers a more approachable alternative.

This guide covers everything you need to get started.

What Is Cloudingo?

Cloudingo is a Salesforce-native app that:

Identifies duplicate records across objects
Merges duplicates with customizable rules
Automates ongoing deduplication
Provides data import with duplicate prevention

Key differentiators:

Cloud-based (no desktop install)
Intuitive visual interface
Strong automation features
Real-time duplicate detection

Cloudingo vs DemandTools

Feature	Cloudingo	DemandTools
Interface	Cloud/web	Desktop app
Ease of use	Easier	More complex
Matching flexibility	Good	Excellent
Automation	Built-in	Scheduler add-on
Price	Lower entry	Higher
Learning curve	Shorter	Longer

Choose Cloudingo when:

You want a simpler UI
Cloud-native is important
Budget is constrained
You need quick wins

Choose DemandTools when:

You need maximum matching control
You’re doing complex data migrations
You have dedicated admin resources

Getting Started

Installation

Go to Salesforce AppExchange
Search “Cloudingo”
Click “Get It Now”
Install in Production or Sandbox
Assign permission sets to users

Initial Configuration

After installation:

Launch Cloudingo from the App Launcher
Connect your org (OAuth authentication)
Run initial analysis to see duplicate landscape
Configure matching filters based on your needs

Permissions Required

Cloudingo users need:

API access
Read/Modify on objects to deduplicate
Delete permissions (for merge operations)
Cloudingo permission set

Understanding Cloudingo Filters

Filters are Cloudingo’s matching rules. They define what constitutes a duplicate.

Pre-Built Filters

Cloudingo includes ready-to-use filters:

Standard Account Filter:

Account Name (fuzzy match)
Website (exact match)
Billing City (exact match)

Standard Contact Filter:

Email (exact match)
OR First Name + Last Name + Account (fuzzy)

Standard Lead Filter:

Email (exact match)
OR First Name + Last Name + Company (fuzzy)

Creating Custom Filters

Go to Filters → Create New Filter
Select object (Account, Contact, Lead, etc.)
Add matching conditions

Example: Contact Email Filter

Filter Name: Contact - Email Exact
Object: Contact

Matching Rules:
  Group 1:
    Field: Email
    Match Type: Exact

Example: Contact Multi-Field Filter

Filter Name: Contact - Name + Account
Object: Contact

Matching Rules:
  Group 1:
    Field: First Name
    Match Type: Fuzzy

    AND

    Field: Last Name
    Match Type: Fuzzy

    AND

    Field: Account Name
    Match Type: Fuzzy

Match Types Explained

Exact: Values must be identical (case-insensitive)

"john@acme.com" = "JOHN@ACME.COM" ✓
"john@acme.com" ≠ "jon@acme.com" ✗

Fuzzy: Allows similar values

"John Smith" ≈ "Jon Smith" ✓
"Acme Inc" ≈ "ACME" ✓

Phonetic: Sounds-alike matching

"Smith" ≈ "Smyth" ✓
"Jon" ≈ "John" ✓

Contains: Partial string matching

"Acme Corporation" contains "Acme" ✓

Running Deduplication Jobs

Manual Job Execution

Go to Jobs → New Job
Select filter (matching rule)
Configure options:
- Preview only vs. Execute
- Auto-merge vs. Manual review
- Master record selection rules
Click Run

Understanding Job Results

After running a job:

Job Results Summary:
─────────────────────────────────────────
Total Records Scanned:     10,000
Duplicate Groups Found:       450
Records in Duplicate Groups: 1,200
Records to Merge:             750

Duplicate Group: A set of records that match each other Master Record: The record that will survive the merge Victim Records: Records that will be merged into the master

Reviewing Duplicates

Before merging, review duplicate groups:

Click on a duplicate group
See side-by-side comparison
Verify they’re true duplicates
Adjust master selection if needed
Approve or reject the merge

Master Record Selection

Configure which record “wins”:

Selection Rules (in priority order):

Most recently modified
Most populated fields
Oldest created date
Manual selection

Field-Level Merge Rules:

Keep master value
Keep victim value
Keep most recent
Keep longest (text)
Keep highest (numbers)
Concatenate

Automation Setup

Cloudingo’s automation runs deduplication continuously.

Scheduling Automated Jobs

Go to Automation → Create Schedule
Configure:

Schedule Name: Daily Contact Deduplication
Filter: Contact - Email Exact
Frequency: Daily at 2:00 AM
Action: Auto-merge (high confidence matches)
Notification: Email on completion

Automation Modes

Preview Mode:

Identifies duplicates
Doesn’t merge
Sends report for review

Auto-Merge Mode:

Merges high-confidence matches automatically
Queues low-confidence for review
Best for ongoing maintenance

Alert Mode:

Notifies users when duplicates detected
Doesn’t merge automatically
Good for training period

Confidence Thresholds

Set thresholds for auto-merge:

High Confidence (Auto-merge):
  - Email exact match: 100%
  - All name fields exact: 95%

Medium Confidence (Review):
  - Name fuzzy + company fuzzy: 75-94%

Low Confidence (Flag only):
  - Partial matches: <75%

Data Import with Deduplication

Cloudingo can deduplicate during import—preventing new duplicates at the source.

Import Workflow

Go to Import → New Import
Upload CSV file
Map fields to Salesforce
Select deduplication filter
Choose action for duplicates:
- Skip (don’t import)
- Update (merge with existing)
- Create (import as new anyway)
Preview results
Execute import

Import Settings

Import Configuration:
─────────────────────────────────────────
File: trade_show_leads.csv
Object: Lead
Matching Filter: Lead - Email Exact

Duplicate Handling:
  If exact email match: Update existing record
  If fuzzy name match: Flag for review
  If no match: Create new record

Field Mapping:
  CSV Column      → Salesforce Field
  email           → Email
  first_name      → FirstName
  last_name       → LastName
  company         → Company
  phone           → Phone

Cross-Object Deduplication

Cloudingo supports Lead-to-Contact matching.

Setup

Create a cross-object filter:

Filter Name: Lead to Contact - Email
Source Object: Lead
Target Object: Contact

Matching Rules:
  Lead.Email = Contact.Email (Exact)

Run job with this filter
Results show Leads matching Contacts
Action: Convert Lead OR merge data

Lead Conversion via Cloudingo

When a Lead matches a Contact:

Cloudingo identifies the match
Options:
- Convert Lead to existing Contact
- Merge Lead data into Contact (without formal conversion)
- Flag for manual review

Best Practices

1. Start with Preview Mode

Always preview before executing:

Week 1: Run filters in preview mode
Week 2: Review results, adjust filters
Week 3: Execute on small batch (100 records)
Week 4: Full execution if results are good

2. Build Filters Incrementally

Start simple, add complexity:

Phase 1: Email exact match only
Phase 2: Add name + company fuzzy
Phase 3: Add phone matching
Phase 4: Cross-object matching

3. Document Your Configuration

Keep records of:

Filter definitions
Master selection rules
Automation schedules
Exception handling

4. Monitor Automation Results

Review automated job results weekly:

Check merge counts
Review flagged duplicates
Watch for false positives
Adjust thresholds as needed

5. Train Users

Even with automation:

Train users to check for duplicates
Show them how to handle alerts
Create a process for exceptions

Troubleshooting

Issue: Too Many False Positives

Causes:

Fuzzy matching too loose
Common names flagging incorrectly
Missing discriminating fields

Solutions:

Add more required fields to filter
Switch from fuzzy to exact on key fields
Add exclusion rules for common values

Issue: Duplicates Still Getting Through

Causes:

Filter not covering all scenarios
Automation not running frequently enough
Data entry bypassing checks

Solutions:

Add OR conditions to filters
Increase automation frequency
Enable real-time duplicate alerts

Issue: Merge Losing Data

Causes:

Master selection rules incorrect
Field-level merge rules not set
Related records not transferring

Solutions:

Review and adjust master selection
Configure field-level merge preferences
Check related object settings

Issue: Slow Performance

Causes:

Too many records in scope
Complex fuzzy matching
Running during peak hours

Solutions:

Add filters to reduce scope
Schedule during off-hours
Break into smaller batches

Pricing

Cloudingo pricing is based on Salesforce org size:

Tier	Records	Approximate Price
Starter	Up to 50K	$99/month
Professional	Up to 250K	$199/month
Enterprise	250K+	Custom

Includes:

Unlimited users
Unlimited jobs
All features

Integration with Other Tools

Cloudingo + Native Duplicate Rules

Use both together:

Salesforce Duplicate Rules: Real-time prevention
Cloudingo: Batch cleanup and automation

Cloudingo + Enrichment Tools

Workflow:

Clay or Breeze enriches records
Cloudingo deduplicates enriched data
Clean, enriched records flow to sales

Cloudingo + HubSpot

If syncing Salesforce ↔ HubSpot:

Deduplicate in Salesforce with Cloudingo
Sync clean data to HubSpot
Use HubSpot deduplication for HubSpot-native records

DemandTools Guide — Alternative for complex deduplication
Salesforce Duplicate Rules — Native duplicate prevention
Salesforce Matching Rules — Understanding match logic
The B2B Data Decay Problem — Why deduplication matters
HubSpot Duplicate Management — If using HubSpot too

What Is Cloudingo?

Cloudingo vs DemandTools

Getting Started

Installation

Initial Configuration

Permissions Required

Understanding Cloudingo Filters

Pre-Built Filters

Creating Custom Filters

Match Types Explained

Running Deduplication Jobs

Manual Job Execution

Understanding Job Results

Reviewing Duplicates

Master Record Selection

Automation Setup

Scheduling Automated Jobs

Automation Modes

Confidence Thresholds

Data Import with Deduplication

Import Workflow

Import Settings

Cross-Object Deduplication

Setup

Lead Conversion via Cloudingo

Best Practices

1. Start with Preview Mode

2. Build Filters Incrementally

3. Document Your Configuration

4. Monitor Automation Results

5. Train Users

Troubleshooting

Issue: Too Many False Positives

Issue: Duplicates Still Getting Through

Issue: Merge Losing Data

Issue: Slow Performance

Pricing

Integration with Other Tools

Cloudingo + Native Duplicate Rules

Cloudingo + Enrichment Tools

Cloudingo + HubSpot

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