The short answer: CRM data is every piece of information your customer relationship management system holds about the people, companies, and deals your revenue team works. The data lives in four core record types (contacts, accounts, opportunities, activities) and dozens of fields per record. Below are concrete examples of each, plus the reports those records roll up into and the fields most likely to go bad.
If you want the abstract version (what CRM data is, why it matters, how it relates to hygiene), we have a separate page on CRM hygiene. This page is the worked examples version.
Example 1: A Sample Contact Record
A contact record holds the data about an individual person. Here is what a complete, well-formed B2B contact record looks like:
| Field | Example Value |
|---|---|
| First Name | Jordan |
| Last Name | Patel |
| Title | VP of Revenue Operations |
| [email protected] | |
| Mobile | +1 415 555 0182 |
| LinkedIn URL | linkedin.com/in/jordanpatel-revops |
| Account | Globex Corp (link to account record) |
| Country | United States |
| State | CA |
| Time Zone | America/Los_Angeles |
| Lead Source | Webinar: Q1 2026 RevOps Trends |
| Lifecycle Stage | Marketing Qualified Lead |
| Owner | Maria Schultz (AE, West) |
| Created Date | 2026-02-14 |
| Last Activity Date | 2026-05-28 |
| Email Opt-In | Yes (consent captured 2026-02-14) |
That record is what a clean contact looks like. The same record in a degraded database might have a blank title, an unsubscribed email, "VP Sales" in the title field instead of the standardized "Vice President, Sales," and a country field that says "USA" while the rest of the database uses "United States."
Example 2: A Sample Account Record
An account record holds the data about a company. Most B2B CRMs link multiple contacts to one account.
| Field | Example Value |
|---|---|
| Account Name | Globex Corp |
| Domain | globexcorp.com |
| Industry | Software (SaaS) |
| NAICS Code | 511210 (Software Publishers) |
| Employee Count | 620 |
| Annual Revenue | $78M (FY2025) |
| HQ Country | United States |
| HQ City | San Francisco, CA |
| Technology Stack | Salesforce, Outreach, Marketo, Snowflake, Gong |
| Account Tier | Tier 1 (named account) |
| Owner | Maria Schultz |
| Last Funding Round | Series C, $40M, 2024-09 |
| Parent Account | None |
| Customer Status | Active customer (since 2024-11) |
That is a clean account record. In a real CRM, the same account might exist three times under "Globex Corp," "Globex Corporation," and "Globex," each with different field values. Deduplication is the work of collapsing those into one trustworthy record.
Example 3: A Sample Opportunity Record
An opportunity (or deal) record holds the data about an active sales cycle.
| Field | Example Value |
|---|---|
| Opportunity Name | Globex Corp - RevOps Platform Expansion |
| Account | Globex Corp |
| Primary Contact | Jordan Patel |
| Stage | Negotiation |
| Amount | $182,000 ARR |
| Close Date | 2026-07-31 |
| Probability | 70% |
| Products | Platform Pro, Data Cloud add-on |
| Competitor | HubSpot Operations Hub |
| Owner | Maria Schultz |
| Created Date | 2026-04-02 |
| Days in Stage | 14 |
| Next Step | Procurement review call 2026-06-12 |
| Loss Reason | (blank, deal open) |
Opportunity records are where forecast accuracy lives or dies. A consistent stage definition across reps and a disciplined close-date practice are the two habits that make the forecast usable.
Example 4: A Sample Activity Record
Activity records hold the interactions: calls, emails, meetings, tasks. They are usually attached to a contact or opportunity record.
| Field | Example Value |
|---|---|
| Activity Type | Meeting |
| Subject | Discovery call - RevOps Platform |
| Date | 2026-05-28 |
| Duration | 45 minutes |
| Attendees | Jordan Patel (Globex), Maria Schultz (AE), Sam Lee (SE) |
| Related Opportunity | Globex Corp - RevOps Platform Expansion |
| Outcome | Technical evaluation set for week of 2026-06-09 |
| Notes | Confirmed budget cycle ends 2026-07-31. Decision criteria: SFDC native, EU data residency, integration with Snowflake. Procurement is required for any commit over $100K. |
Activity records are where the deal narrative lives. A new AE inheriting an account in 30 minutes is possible because the activity history tells the story without anyone explaining it.
CRM Reports Examples
Records on their own are not what makes a CRM useful. Reports are. Six reports show up at almost every B2B revenue team.
- Pipeline by stage. Open opportunity amount and count, grouped by stage. The funnel view of the team's workload.
- Forecast by owner or territory. Opportunity amount times probability, grouped by rep or region. The weighted-by-likelihood view of what is going to close this quarter.
- Activity by rep. Calls, emails, and meetings logged per rep over a period. Leading indicator of pipeline before pipeline shows up.
- Conversion rate by stage. Percentage of opportunities that progress from each stage to the next. Diagnoses where deals stall.
- Source attribution. Closed-won pipeline broken out by lead source (paid search, webinar, outbound, referral). Tells marketing where to invest more and less.
- Renewal forecast (for SaaS). ARR up for renewal in the next 90 days, with health score and CSM notes. CS team's working document.
Every one of those reports depends on consistent data underneath. Inconsistent stage definitions kill conversion-rate accuracy. Blank lead source kills attribution. Inconsistent close-date practices destroy the forecast. The reports look fine right up until someone tries to use them to make a decision.
Where Bad Data Hurts Most
Five fields go bad faster than the rest, and they account for most of the daily pain in a CRM that has been let drift.
| Field | Why It Matters |
|---|---|
| Email address | Bounces burn sender reputation; campaigns become guess-and-check. |
| Title | Drives lead scoring and routing; "VP Sales" vs "Vice President of Sales" splits the same role into two segments. |
| Industry | Drives ICP segmentation and territory definitions; inconsistent values produce wrong segments. |
| Employee count | Drives sizing rules and routing; blank or stale data sends enterprise prospects to SMB reps. |
| Lead source | Drives attribution and marketing budget; blank source makes the attribution report fiction. |
These are the fields that most justify a hygiene program. Fix them on a cadence and the downstream reporting works. Let them drift and the reports keep looking precise while encoding more guesses every quarter.
Common Questions
What is CRM data?
CRM data is every piece of information your CRM holds about the people, companies, and deals your revenue team works. The four core record types are contacts (individual people), accounts or companies (the organizations they work for), opportunities or deals (active sales cycles), and activities (calls, emails, meetings). Each record holds dozens of fields across identity, firmographic, behavioral, and operational categories.
What are some examples of CRM data?
Contact data: first name, last name, email, mobile, title, LinkedIn URL, account link. Account data: company name, domain, industry, employee count, revenue, technology stack, country. Opportunity data: amount, stage, close date, products, competitor, owner. Activity data: call notes, email opens, meeting summaries, task due dates. Together those records build the picture a CRM is meant to provide.
What are examples of CRM reports?
Common reports include pipeline by stage (a funnel view of open deals), forecast by territory or owner (weighted by probability), activity by rep (calls, emails, meetings logged), conversion rates between funnel stages, source attribution (which lead source produced the most closed-won), account health, and territory coverage. Most CRMs ship with templates for these and let you customize.
What fields should every CRM contact record have?
Required at minimum: first name, last name, email, account, owner, lifecycle stage, lead source, and created date. Recommended: title, mobile, LinkedIn URL, country, time zone, and last activity date. Industry-specific fields add to that list (NPI in healthcare, license number in real estate, ABN in Australia).
What kinds of CRM data go bad most often?
Email address is the single most volatile field; bounce rates of 15-25% are common on a database that has not been validated in a year. Title is next; people get promoted, switch roles, and re-title themselves at the same employer. Company size and revenue are usually wrong on accounts that grew through funding or shrunk through layoffs. Phone numbers churn slower but reassignment happens. Static fields (name, account creation date) stay reliable.
How do I know if my CRM data is good?
Run four checks. Duplicate rate (under 5% is healthy, over 10% is a problem). Email bounce rate (under 5% on a recent send is healthy). Fill rate on critical fields like industry, employee count, and title (over 70% is healthy). Percentage of records with activity in the last 90 days (depends on team size, but a sudden drop is a warning sign). Most CRMs let you build all four into a single dashboard tab.
Make Your CRM Records Look Like the Examples Above
Two paths forward:
Want a snapshot of your data first? Send a sample export. We will return a diagnostic: duplicate rate, bounce rate, format inconsistencies, and field completeness. Free, no commitment.
Ready to clean? Tell us your CRM, your data volume, and your biggest pain points. We will scope a project and turn it around in 24-48 hours.
Related: CRM Hygiene | What is CRM and Its Benefits | CRM Data Quality Checklist | The Cost of Bad CRM Data