Data Subject Requests Checklist for Solo SaaS Founders

Customers occasionally ask for a copy of their data, a correction, or full deletion. Payment processors, enterprise buyers, and privacy laws (GDPR, CCPA/CPRA, and others) make these requests routine rather than rare. A solo founder who improvises each time spends hours hunting through databases, logs, and third-party tools while risking an incomplete or late response.

This is a practical operating checklist, not legal advice. Requirements differ by jurisdiction, the type of data you hold, and whether you act as a controller or processor. When volume grows or regulated data appears, involve a qualified professional.

What these requests typically cover

Most frameworks give individuals some combination of:

Access: confirmation of what you hold and a copy in a portable format.
Correction: the right to fix inaccurate personal data.
Deletion (or erasure): removal of personal data, subject to legal exceptions.
Restriction or objection: limiting certain processing in specific cases.

You usually have a defined response window (commonly around 30 days under GDPR, with possible extensions). The exact clock, exceptions, and format expectations vary. Treat every request as something you must log, verify, and complete or formally decline with a reason.

Preparation: systems that make requests tractable

Build the capability before the first request arrives.

Inventory what you actually store

List every place personal data can live:

Primary database (users, profiles, activity).
Authentication provider (Auth0, Clerk, Firebase Auth, etc.).
Billing system (Stripe customer objects, invoices).
Email and support tools (transactional email, helpdesk tickets, chat logs).
Analytics and product analytics.
Error monitoring and logs (Sentry, log aggregators).
File storage (avatars, exports, attachments).
Any AI or vector stores if you embed customer content.
Backups and cold storage.

Note retention periods and whether data is truly deleted or only soft-deleted. Soft deletes that leave data recoverable for months still count as holding the data for many privacy purposes.

Decide identity verification

You must confirm the requester is the account owner (or has authority). Common approaches:

Require the request from the registered email address and confirm via a one-time link or code.
For higher-risk accounts, ask for additional proof that matches information already on file.
Reject or delay requests that arrive from a different email without verification.

Document the method so every request is handled the same way.

Prepare export and deletion scripts

Even a simple SQL query or admin script that dumps a user’s rows to JSON is better than manual screenshots. For deletion, write a script that:

Removes or anonymizes personal data in the primary store.
Triggers deletion in third-party systems where APIs exist (or notes the manual steps).
Records what was done and when.

Test the scripts on a staging account. Deletion is harder to reverse than export.

Response process

Follow a consistent sequence for every request.

Log the request — Date received, channel (email, form, support ticket), what was asked (access, deletion, correction), and the account identifier.
Acknowledge promptly — A short reply that you received it and will respond within the applicable window. Include a reference number if useful.
Verify identity — Complete your verification step before releasing or deleting data.
Scope the work — Identify which systems hold relevant data. Check for legal holds or exceptions (ongoing contract obligations, tax records, fraud investigation).
Fulfill or partially fulfill — Export in a structured, machine-readable format (JSON or CSV is usually acceptable). For deletion, execute the script and confirm third-party cleanup. For corrections, update the records and note the change.
Document exceptions — If you retain something (for example, invoice data required for tax law), state the reason and the legal basis clearly.
Respond with the outcome — Provide the export or confirm deletion/correction. Include a brief note on any residual data and why it remains. Offer a contact for follow-up.
Close the log — Record completion date, actions taken, and any residual data.

Keep the language plain. Avoid promising absolute erasure of every backup if your systems cannot achieve that instantly; describe the realistic timeline and residual risk.

Practical implementation notes for small stacks

Stripe and similar — Customer objects and payment methods can be deleted or anonymized via API or dashboard. Invoices often must be retained for accounting. Export the customer record before deleting if the user also asked for access.
Email providers — Most allow suppression or deletion of contacts. Transactional logs may have shorter retention by default; check the provider’s settings.
Analytics — Prefer tools that let you delete or exclude a user ID. If the tool only offers IP anonymization or short retention, document that limitation.
Logs and error trackers — Many retain data for 30–90 days by default. Search for the user identifier and delete or redact where the product allows it. For pure log files you control, a targeted purge or short retention policy reduces the surface.
Backups — Full-system backups are the hardest. A common practical approach is to note that data will age out of backups according to your retention schedule (for example, 30 or 90 days) and will not be restored in a way that reintroduces the deleted records. State this explicitly in the response.
AI features — If you store prompts, completions, or embeddings that contain personal data, include those stores in the inventory and deletion path.

A lightweight spreadsheet or even a dedicated folder of markdown files can serve as the request log while volume is low. When requests become weekly, move the log into your support tool or a simple internal table.

Checklist before you consider the process ready

Written inventory of every system that can hold personal data, with retention notes.
Documented identity-verification step for requests.
Working export script or query that produces a portable file for a test user.
Working deletion or anonymization script covering the primary database.
List of third-party tools and the manual or API steps required for each.
Standard acknowledgment and final-response email templates.
Request log template (date, type, verification, actions, completion, residual data).
Note in your Privacy Policy that describes how users can submit requests and what to expect.
Tested the full path on a staging account, including one residual-data case (for example, an invoice).

Common pitfalls

Treating deletion as “set a deleted_at flag” while the data remains fully queryable and in backups indefinitely.
Releasing an export without verifying the requester, then discovering the email was compromised.
Forgetting support tickets, chat transcripts, or uploaded files that contain the user’s personal data.
Promising “complete and immediate deletion from all systems including backups” when that is operationally impossible.
Responding only by email without logging the request, so you cannot prove timeliness or completeness later.
Ignoring requests that arrive through a contact form or social channel instead of the preferred email.

When the simple process is no longer enough

Revisit the setup when:

You start receiving more than a handful of requests per month.
Enterprise customers ask for a formal process or DPA language covering subject requests.
You process special-category data or sell into jurisdictions with stricter rules.
A request involves data you received from another controller (processor scenario).

At that point, a short consultation with counsel familiar with your main markets usually costs less than an incomplete response or a regulatory inquiry.

Handling data subject requests well is mostly preparation and consistent execution. Inventory the systems, script the common actions, log every request, and respond in plain language. That is usually sufficient for a solo micro-SaaS until the volume or the stakes rise.