Every sales leader eventually discovers the same painful truth: your Salesforce reports are only as good as the data behind them. Duplicated leads inflate pipeline, confuse ownership, and trigger clashing sequences from marketing and SDRs. Ops teams try to keep up with manual exports, VLOOKUPs, and weekend cleanup projects, but duplicates creep back in faster than humans can chase them.
A Salesforce duplicate report gives you visibility, but on its own it’s still a snapshot. The real leverage comes when you treat deduplication as a continuous system: Salesforce rules and reports to define what “duplicate” means, Google Sheets as a flexible workspace to review edge cases, and an AI computer agent to do the grunt work. By delegating the click‑heavy tasks to an agent, you preserve human judgment for the 10% of records that actually need it while keeping your CRM clean every single day.
Below are three levels of sophistication: manual, no‑code automation, and AI‑agent driven. You can start with the basics and layer automation as your volume grows.
App Launcher and search for Duplicate Rules and Matching Rules.Duplicate Record Sets.New Report and search for the type Duplicate Record Sets.Record Type = Lead and date filters.Official docs: https://help.salesforce.com/s/articleView?id=sf.managing_duplicates_overview.htm
Pros: Native, secure, respects existing rules.
Cons: Static, still requires a lot of manual reviewing and merging.
Reports → New Report.Leads (or Contacts, Accounts).Email, Phone, or Account Name.RowCount > 1 to surface groups with duplicates (or use a bucket field or custom filter logic to isolate them).Potential Lead Duplicates.Docs (Reports): https://help.salesforce.com/s/articleView?id=sf.reports_builder_edit.htm
Pros: Flexible, no admin access needed.
Cons: Easy to miss fuzzy duplicates and cross‑object duplicates.
File → Import or upload to Drive.Data → Remove duplicates to quickly remove exact matches on Email or other fields. Docs: https://support.google.com/docs/answer/13971709=COUNTIF(A:A, A2) to flag values that appear more than once.Pros: Transparent and very flexible for one‑off audits.
Cons: Extremely time‑consuming at scale; error‑prone when re‑keying changes.
View Duplicates (if enabled by your admin).Docs: https://help.salesforce.com/s/articleView?id=sf.duplicate_rules_merging.htm
Pros: Safe, governed merge process.
Cons: Record‑by‑record; doesn’t give overview of the problem.
You can avoid constant CSV exports by using a live connector.
Options include:
Example with Salesforce Connector for Sheets:
Extensions → Add-ons → Get add-ons and search for Salesforce.Extensions → Salesforce Connector.Reference: https://support.google.com/docs/answer/9071123 (using connectors and add-ons)
Now your duplicate‑checking sheet updates automatically without manual exports.
Once the data flows into Sheets, you can create a reusable “dedupe workbook”:
Raw_Salesforce for imported data.Dedupe_View tab that references raw data with formulas such as:=UNIQUE(Raw_Salesforce!B:B) to get unique emails.=COUNTIF(Raw_Salesforce!B:B, B2) to count how many times each email appears.Is_Duplicate with a formula like =IF(COUNTIF(Raw_Salesforce!B:B, B2)>1, "Yes", "No").Is_Duplicate = Yes to get a working list.Keep_Record_Id column where your team chooses the winning Salesforce Id.Pros: Reusable, teams can collaborate in real time.
Cons: Still needs humans to push changes back into Salesforce.
To avoid manual updates:
Approved_Merges).Update Record or Merge actions, using the Keep_Record_Id and Duplicate_Record_Id fields.Docs (Salesforce + automation platforms) are typically found under each tool’s help center, e.g., https://help.salesforce.com and https://support.google.com/docs for Sheets.
Pros: Removes repetitive updates, ideal for RevOps and agencies running periodic cleanups.
Cons: Logic is brittle; if your rules change, you must rebuild workflows.
Now imagine your “dedupe analyst” is an AI computer agent that can:
Simular Pro is designed to behave like a power user across your desktop, browser, and cloud apps.
A Simular AI agent can:
Duplicate Record Sets and Potential Lead Duplicates reports.Human_Review tab.Pros: End‑to‑end automation, uses your existing UI and tools, no API development.
Cons: Requires initial design of the workflow and clear written rules.
Instead of a quarterly cleanup, you can:
CreatedDate = YESTERDAY, run duplicate checks for new records only.Because Simular agents are production‑grade and every action is logged, RevOps and agencies can treat them like reliable junior analysts—only faster and tireless.
Simular emphasizes transparent execution: you see every step the agent takes. When business logic changes (e.g., SDR territories, priority accounts), you update the workflow description once and the agent’s behavior updates without rebuilding brittle no‑code flows.
This is how you go from “cleaning duplicates when it hurts” to a continuous, agent‑driven hygiene system that quietly protects your Salesforce and keeps every Google Sheets dashboard honest.
Start by enabling Salesforce’s native duplicate management. In Setup, review your Matching Rules (for Leads, Contacts, Accounts) and ensure they reflect how your business defines a duplicate—email exact match, fuzzy company name, same phone, etc. Then create Duplicate Rules that either block or allow duplicates while reporting them.
Next, go to the Reports tab and create a new report using the type `Duplicate Record Sets`. Add filters, such as `Record Type = Lead` or specific owners, and display columns like `Duplicate Rule`, `Record Count`, and `Created Date`. Run the report to see clusters of records Salesforce has flagged. For a broader view, also build standard Leads/Contacts reports grouped by Email or Account Name and use row count filters to identify likely duplicates.
Finally, export these reports to CSV or Google Sheets to review edge cases. This combination gives you both a rule‑driven view (Duplicate Record Sets) and a more exploratory view (grouped reports).
First, export your Salesforce duplicate reports (Duplicate Record Sets, or grouped Leads/Contacts reports) as CSV and open them in Google Sheets, or use a connector to sync the data directly into a `Raw_Salesforce` tab. Once the data is in Sheets, add helper columns to make patterns obvious.
For example, if column B is Email, add a column `Duplicate_Count` with `=COUNTIF(B:B,B2)` and another column `Is_Duplicate` with `=IF(COUNTIF(B:B,B2)>1,"Yes","No")`. Turn on filters and quickly show only rows where `Is_Duplicate` is `Yes`. Use conditional formatting to highlight high‑risk clusters, such as duplicates owned by different sales reps.
You can also create a pivot table summarizing duplicates by owner, region, or source campaign. This gives sales and marketing leaders an immediate sense of where data quality is breaking down, letting them prioritize cleanup work and tighten upstream lead capture.
Safe merging starts with defining a clear “survivor” rule. Decide which record should win: the one with open Opportunities, the most recent activity, the most complete data, or a specific record type. Document this rule so sales, marketing, and RevOps are aligned. In Salesforce, when you click `View Duplicates` from a Lead, Contact, or Account, use this rule to choose your master record.
Before merging, scan critical fields: email, phone, account, lifecycle stage, and owner. If ownership or lifecycle is different across duplicates, confirm with stakeholders before merging. For bulk cleanups, export candidate duplicates to Google Sheets, mark a `Keep_Record_Id` and `Archive_Record_Id`, and only then start merging, using either Salesforce’s UI or an integration tool.
Always test your process on a small batch, confirm reports and automations (like marketing journeys or sequences) behave correctly afterward, and only then scale up. That’s the difference between a tidy CRM and an accidental data disaster.
Preventing new duplicates is a mix of configuration, training, and automation. In Salesforce Setup, strengthen your Matching Rules so they reflect real‑world duplication patterns—e.g., catching leads where emails differ slightly but domains and names are similar. Then configure Duplicate Rules to either alert or block users and integrations when they try to create a likely duplicate record.
Next, tighten your lead capture flows. Ensure web forms, imports, and marketing automation all respect Salesforce’s duplicate checks. Train sales and marketing teams to search before they create a new record, and to use existing accounts or contacts whenever possible. Regularly review Duplicate Record Set reports to see which sources and users are generating the most issues.
Finally, schedule periodic audits using Google Sheets and, ideally, an AI computer agent that runs duplicate reports automatically. This creates a feedback loop: when you find new patterns of duplicates, you can refine your rules before the problem grows.
An AI agent like Simular behaves like a tireless RevOps assistant who lives inside your browser and desktop. You design the playbook once: log in to Salesforce, run specific duplicate reports, export or sync data into a Google Sheets dedupe workbook, apply your business rules for choosing the surviving record, then perform merges or updates back in Salesforce.
Because Simular Pro can handle thousands to millions of steps reliably, it can execute this playbook every night or even multiple times per day. It can skip records that violate edge‑case rules (e.g., conflicting owners, different regions) and send them to a `Human_Review` tab while safely auto‑merging straightforward duplicates. All actions are transparent: you can inspect exactly which clicks, fields, and decisions the agent made.
The result is continuous CRM hygiene without adding headcount. Sales, agencies, and business owners keep their focus on strategy and revenue, while the agent quietly keeps Salesforce clean in the background.