Real World Impact
/
Data Audit & Data Management
Exposes CRM duplication and reveals the underlying patterns causing it—so teams can fix the source, not just the symptoms.
Ask
Interpret
~ 1.5 mins
Plan
Review
~ 2 mins
Approve
Verify
~ 1 min
Execute
Compose
~ 4 mins
Present

Analyzed 162,380 contacts to identify duplicate records and pinpoint duplication patterns across key accounts and owners.

DATA SOURCE
Salesforce Logo
Salesforce
Hubspot Logo
HubSpot
CATEGORY
RevOps
COMPLEXITY
Advanced
ANALYSIS TIME
Manual:
~2.5 hrs
Petavue
~14 mins
See the Full Analysis in Action

Watch how Petavue builds and runs this workflow — validating fields, generating the plan, and producing insights in minutes.

The Petavue Workflow
Blue circle
Ask

Uncover the Right Questions

The request asked Petavue to identify duplicate contacts, quantify their volume, and detect patterns driving duplication—particularly within Key Accounts.Petavue first interprets the intent behind the question: understanding how duplication affects pipeline accuracy, account visibility, and ownership clarity across sales teams.

Can you find out how many dup contacts we got in salesforce, esp across key accounts? and not just count, I’d love to see if there’s a pattern (same email, diff accounts, diff owners etc).
Interpret
~ 1.5 mins
Plan

Craft the Plan

Petavue translates the request into a structured analytical plan.It selects the Salesforce Contacts table and identifies required fields, including email address, contact name, account ID, account tier (key vs. non-key), contact owner, and creation date.Petavue defines duplicate-detection logic—such as exact email matches, shared domains with differing names, and contacts linked to multiple accounts—and outlines how patterns will be grouped and compared.

Review
~ 2 mins
Approve

Confirm the Approach

Before execution, Petavue presents the plan in plain language for validation.It explains the duplicate-matching rules, how cross-account duplication will be identified, and how key-account records will be isolated—ensuring stakeholders agree on the methodology before any analysis runs.

Verify
~ 1 min
Execute

Ensure Accurate Execution

Petavue runs the validated analysis across the full Salesforce dataset.It detects duplicate clusters, validates matches at the row level, and categorizes duplication types (same email across accounts, same contact across owners, repeated imports).No sampling or heuristics are used—every flagged duplicate is traceable back to specific records.

Compose
~ 4 mins
Present

Surface the Insights

Petavue translates the results into actionable insights.It quantifies total duplicate volume, highlights how many duplicates affect key accounts, and surfaces dominant duplication patterns.Teams receive a ranked view of duplication severity—showing exactly which accounts, owners, and ingestion paths need attention.

The Outcome

Petavue analyzed 162,380 Salesforce contacts to identify duplicate records, with a focused audit on Key Accounts. Beyond counting duplicates, Petavue uncovered repeatable patterns—such as shared emails across multiple accounts, contacts owned by different reps, and inconsistent account linkage—revealing exactly how and why duplication was occurring. The result: a clear, defensible view of CRM duplication and where prevention efforts should focus.

Cross-Account Duplication

‍Identified high-impact duplicates where the same contact email exists across multiple key accounts.

Ownership Conflicts

‍Surfaced contacts owned by different reps, creating visibility and outreach conflicts.

Root Cause Patterns

‍Revealed duplication driven by manual entry, third-party imports, and missing deduplication rules.

FAQs

For any further questions, send us a message at support@petavue.com
How does Petavue define a duplicate contact?
Duplicates are identified using validated rules such as exact email matches, shared identifiers across accounts, and repeated contact records with different owners.
Are key accounts analyzed separately?
Yes. Petavue isolates key accounts to assess duplication risk where impact is highest.
Can this analysis detect partial or fuzzy matches?
Yes. Petavue can extend matching logic to include domain-level and name-based patterns if approved.
Does this replace Salesforce’s native duplicate rules?
No. It complements them by auditing existing data and exposing gaps in enforcement.
Can this help with cleanup workflows?
Yes. Petavue outputs exact record clusters so teams can merge, reassign, or enforce preventive rules.

GTM Teams are seeing real-life impact with Petavue