Data Retention Policy Template. And Best Practices

If your company data is a closet, most businesses are storing everything like it might be useful “someday.” Old customer exports, email threads, backups from three laptops ago, and random spreadsheets named “FINAL_v7.”

That habit feels safe, until it isn’t. A breach, a lawsuit, a customer deletion request, or a compliance audit turns that closet into a liability.

This guide gives you a clear data retention policy template, plus best practices you can apply whether you run a SaaS, an ecommerce store, a marketing agency, or a local service business.

What a data retention policy is (and why it matters)

A data retention policy is a written set of rules that answers three questions:

• What data do we keep?
• How long do we keep it?
• How do we delete or destroy it when the time is up?

It matters because data has a “carrying cost.” Not just storage fees, but risk. The more you keep, the more you can lose, expose, or hand over in discovery.

A simple mental model helps: keeping data is like keeping receipts. You need some for taxes and warranties. Keeping every receipt since high school doesn’t make you safer, it makes the pile harder to manage when it counts.

For a deeper privacy-focused view (and an example template), see the IAPP’s data retention policy best practices and template.

Retention rules depend on your industry and data type

In the US, there isn’t one master “data retention law” for all businesses. Requirements change based on:

• Industry (healthcare, finance, public companies, education)
• Data type (payroll, tax records, card data, customer support tickets)
• State privacy laws (especially for personal data and deletion rights)
• Contracts (client agreements, DPAs, vendor terms)

That’s why a good policy is part legal, part operations, and part common sense. If you’re unsure, get legal guidance for your state and sector.

Common retention buckets to include (with practical examples)

Use categories that match how your team actually works. If your staff can’t classify data quickly, the policy won’t stick.

Data category	Examples	Typical retention approach (high-level)	End-of-life action
Financial and tax	invoices, tax filings, audit records	keep for legally required periods and audit needs	archive, then securely delete
HR and payroll	payroll, performance notes, hiring files	keep per employment and tax rules, then minimize	securely delete, restrict access early
Customer and prospect data	CRM records, support tickets	keep while active, shorten when inactive	delete, anonymize, or aggregate
Product and app data	logs, analytics events	keep short, rotate often	auto-delete, aggregate metrics
Security and access logs	auth logs, admin actions	keep long enough for investigations	archive with strict access
Payment data	cardholder data, transaction refs	keep as little as possible	delete quickly, tokenize

If you want a compliance-oriented walkthrough and another sample format, Drata’s guide is a helpful reference: What is a data retention policy? Best practices + template.

Data retention policy template (copy, paste, and customize)

Use the structure below as your baseline. Keep it short enough that people will read it, but specific enough that they’ll follow it.

1) Policy name, owner, and effective date

Policy: Data Retention Policy
Company: [Company Name]
Effective date: [YYYY-MM-DD]
Policy owner: [Role, e.g., Head of Operations or Security Lead]
Review cadence: [Every 12 months, or sooner if laws change]

2) Purpose

We retain company data only as long as needed for business operations, legal obligations, dispute resolution, and security. We reduce or remove data that no longer serves a defined purpose to lower privacy and security risk.

3) Scope

This policy applies to data created, received, stored, processed, or transmitted by:

• Employees and contractors
• Company-owned devices and accounts
• Cloud tools (CRM, email, help desk, file storage)
• Production systems, logs, backups, and archives

Data types covered: customer, prospect, employee, vendor, financial, operational, analytics, and security data.

4) Definitions (keep these plain)

Retention period: how long data is kept before deletion or destruction.
Archive: long-term storage with restricted access and monitoring.
Secure deletion: deletion methods intended to prevent recovery (for example, cryptographic erase for cloud storage, secure wipe for devices, shredding for paper).
Legal hold: a pause on deletion because of litigation, investigation, or audit.

5) Retention schedule (your “source of truth”)

Fill this table with what you actually store. Start with 10 to 15 rows, then expand later.

Data type	System owner	Retention period	Storage location	Disposal method	Notes
Customer account data	[Team/Role]	[e.g., life of account + 24 months]	[SaaS DB/CRM]	delete or anonymize	honor deletion requests when applicable
Support tickets	[Team/Role]	[e.g., 36 months]	[Help desk]	delete	keep longer for regulated clients only
Access logs	[Team/Role]	[e.g., 12 months]	[SIEM/log tool]	auto-delete	restrict access, monitor exports
Backups	[Team/Role]	[e.g., 30 to 90 days]	[Backup tool]	rotation	document exceptions for incidents
Payroll records	[Team/Role]	[e.g., per applicable law]	[HRIS]	delete	confirm state and federal rules

Tip: write retention periods as numbers (months/years), not vague phrases like “as needed.”

6) Storage and access rules

• Data is classified as Public, Internal, Confidential, or Restricted.
• Restricted data (PII, payment-related, health data) must be encrypted at rest and in transit where supported.
• Access is role-based. Admin access is limited, logged, and reviewed.
• Exports (CSV, PDF downloads) must be tracked or restricted for sensitive datasets.

7) Deletion and destruction process

• Deletion occurs via automated workflows where possible (time-based rules).
• Secure deletion must cover primary systems and known copies (exports, shared drives).
• Backups follow the documented backup retention window; exceptions require approval by [Policy Owner].
• Paper records are shredded using a trusted shredding process.

8) Legal holds and exceptions

When a legal hold is issued by [Legal/Compliance], deletion for relevant records stops immediately. Holds are documented, time-stamped, and lifted in writing.

9) Training, audits, and enforcement

• New team members are trained within [30] days.
• Quarterly checks confirm: retention rules, deletion jobs, access controls, and exception tickets.
• Violations may lead to access removal and corrective action.

For another practical set of examples and pitfalls to avoid, Secureframe’s guide is a good companion: Creating a data retention policy: examples, best practices, and template.

Best practices that prevent “we thought it was deleted” moments

Most retention failures happen in the gaps, not the policy doc. Focus here:

Start with a data inventory. If you don’t know where data lives, you can’t retain or delete it with confidence.

Tie each dataset to a purpose. If nobody can explain why it exists, it’s a deletion candidate.

Treat backups as their own system. Deleting in the app doesn’t delete last week’s backup.

Automate retention where possible. Manual calendars and reminders break fast, especially in small teams.

Design for least access. Many breaches spread because too many people can export too much data.

Write down your “legal hold” trigger. Lawsuits and disputes are when teams panic and freeze all deletion, sometimes too late.

How to choose retention periods without guessing

Use this quick checklist:

• Legal minimums: What must you keep, and for how long, in your industry and state?
• Business needs: How long do refunds, chargebacks, and support escalations typically take?
• Security needs: How far back do you need logs to investigate incidents?
• Privacy expectations: Would a reasonable customer expect you to still have this data?
• Operational cost: Does keeping it add risk without real value?

When in doubt, choose the shortest period that still meets legal and operational needs, then document the reason.

Conclusion

A strong retention program isn’t about hoarding data “just in case.” It’s about keeping what you need, protecting it well, and letting go of the rest on purpose.

Use the data retention policy template above, fill in your real systems, assign an owner, and automate deletion wherever you can. Your future self, especially during an audit or incident, will thank you.