Creating a data quality checklist: regular maintenance and validation

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Without a system, data quality degrades over time. New pages launch without tracking. Filters get misconfigured. Conversion goals change. Settings drift. Your analytics starts clean but slowly becomes corrupted by neglect.

A data quality checklist prevents this. Regular maintenance catches problems before they become expensive.

Why maintenance matters

Prevents accumulation of small errors

One missing tracking tag isn't catastrophic. Two isn't either. But after a year, you've missed tracking on 20 pages. That's significant. Regular checks catch errors early.

Catches configuration drift

Someone makes a change they forgot to document. Someone else disables a filter thinking it's outdated. Settings drift from the intended configuration. Checks prevent this drift.

Maintains historical comparability

Year-over-year comparisons only work if configuration is consistent. Regular checks ensure you're measuring the same things year after year.

Monthly checklist

Compare key metrics to last month

Pull traffic, conversions, and revenue for this month vs. last month. Are changes explainable by business activity (campaigns, seasonality)? Or do they signal tracking problems?

Check for unexplained spikes or drops

Traffic up 30% with no campaign launch? Conversions down 20% without site changes? Investigate. Unexplained changes often indicate tracking errors.

Verify bot filtering is enabled

Check that bot filtering is still on. Check that known bot filters haven't been disabled. Confirm settings match last month.

Scan for new referral spam

Review referral sources. Any new domains that look suspicious? Add them to the blocklist.

Check conversion goal reporting

Are all conversion goals firing? Do conversion counts match your payment processor (approximately)? Large gaps suggest tracking is broken.

Verify internal traffic is excluded

If you filter internal traffic, spot-check that it's working. Generate test traffic from your office and confirm it doesn't appear in reports.

Quarterly checklist

Full configuration audit

Review all active filters. Why does each exist? Is it still needed? Disable any filters that have become unnecessary.

Verify tracking on all pages

Spot-check your site. Pick 10 random pages and verify tracking code is present. Check page source directly.

Compare analytics to payment processor

Pull conversion counts from both systems for the quarter. Calculate variance. Document the expected difference.

Review and update documentation

Update the document describing your analytics setup. Document any changes made since last quarter. Ensure new team members could understand the setup.

Audit conversion goal definitions

Are all goals still accurate? Have any changed? Update definitions if needed. Document why each goal exists.

Check for new data quality issues

Have you launched new features? New traffic sources? Verify tracking is in place. Test each new channel.

Annual checklist

Complete setup audit

Do everything in the quarterly checklist, but more thoroughly. Review every setting. Check every page. Audit every conversion.

Year-over-year comparison

Compare this year to last year. Are metrics comparable? If configuration changed, note how comparison is affected.

Identify systemic improvements

What tracking problems did you fix this year? What could you improve next year? Plan improvements based on this year's learnings.

Team training

Train your team on data quality. How to spot problems. How to report issues. How to avoid introducing errors.

Tool review

Are you using the right tools? Should you upgrade? Add new tools? Review tooling annually to stay current.

Creating your checklist

Customize for your business

These checklists are templates. Customize for your specific setup. Add checks specific to your data sources. Remove irrelevant items.

Make it a calendar event

Set recurring calendar reminders. Monthly checklist first Friday of the month. Quarterly checklist first day of each quarter. Annual checklist December 1st.

Assign responsibility

Assign someone to own the checklist. This person runs the checks, documents findings, and reports results to the team.

Document results

Keep records of what you checked and what you found. Over time, this creates a history of data quality and helps you spot trends.

Frequently asked questions

Can I automate the data quality checklist?

What if I find a problem during a checklist?

How long does a full checklist take?

What should I do if I'm too busy for monthly checklists?

Should I involve other team members in the checklist?

Can a checklist prevent all data quality issues?