Small habits, big improvements.

Data quality isn’t glamorous. It’s not the bit anyone puts in a job description. But it’s the foundation underneath everything else your charity does — fundraising, communications, finance, service delivery, reporting, you name it.

This module helps your team understand what data quality actually means (spoiler: it’s not perfection), spot the most common issues, and build tiny habits that prevent problems before they start.

Simple habits → cleaner CRM → happier teams → better decisions.

Lesson 5.1 — What Data Quality Really Means

A calm, human definition your whole team can get behind.

Most people hear “data quality” and think of long spreadsheets, complicated metrics or someone in the corner shouting about validation rules. But everyday data quality is much simpler and much more human.

At its core, good data quality means having information that is accurate, complete enough to do the job, and stored where people expect to find it.

That’s it.

Not perfect. Not pristine. Just fit for purpose.

The six dimensions of data quality (CRAFT version)

We can keep this friendly:

When people understand these six ideas, they start spotting issues naturally — and fixing them becomes routine instead of a chore.

Why everyday data quality matters for charities

Three reasons make this especially important in our sector:

1. Better supporter experience

When details are wrong, messages go to the wrong place, donors get duplicate letters, or someone receives an appeal right after opting out.

Small mistakes affect trust.

2. Better fundraising decisions

Clean data → stronger insights → better campaigns → more income.

It’s not rocket science — it’s hygiene.

3. Less stress for teams

When data is tidy and predictable, everything gets easier:

Selections, reporting, thanking, forecasting, dashboards, and even handovers.

Good data quality is a shared responsibility

It’s not just the “database person” who updates records. Every team member contributes to data quality when they:

• capture the right information
• update details promptly
• follow naming conventions
• avoid creating new spreadsheets if the CRM can do the job
• store files in the right place

Every small action helps.

This is about culture, not policing.

Where the CRAFT Forge comes in

The Data Quality Checker app – available in CRAFT Forge – gives you a quick, MOT-style view of:

• duplicates
• missing fields
• invalid formats
• casing issues
• unusual titles
• out-of-date information

It’s a simple way to build awareness and kick-start conversations.

Lesson 5.2 — Common Issues: Casing, Titles, Postcodes & Duplicates

Four tiny problems that quietly create big headaches — and how to fix them.

Most data problems in charities aren’t dramatic. They’re small, almost invisible habits that accumulate over time: a title entered the wrong way, a postcode missing one letter, or a duplicate record created because someone was in a rush.

This lesson highlights the four issues we see most often — and explains how to spot them, prevent them, and fix them quickly.

1. Casing

(“mr smith” vs “Mr Smith”)

Inconsistent casing looks minor, but it signals wider problems: messy exports, untidy mail merges, and supporter communications that feel unprofessional.

What it looks like

• all-caps (“JOANNA MCDONALD”)
• all lower-case (“joanna mcdonald”)
• mixed, inconsistent patterns

Why it matters

• Printed letters look sloppy
• Emails risk triggering spam filters
• People feel undervalued when their name appears wrong

Quick win

Adopt one simple rule: Names are in “Proper Case” across every system.

Where the Forge app helps

The Data Quality Checker highlights casing inconsistencies automatically so you can tidy them in one go.

2. Titles

(Mr, Mrs, Ms, Dr, Mx… and the “creative” versions)

Titles cause more trouble than anyone expects. Supporters use different conventions; staff enter them inconsistently; legacy imports contain surprises like “Lady”, “Rev”, “Mrr”, or “Unknown”.

What it looks like

• Misspellings (“Mrr”, “MsS”, “Mr.” vs “Mr”)
• Outdated or misgendered titles
• Inconsistent punctuation
• Titles stored differently in different forms

Why it matters

• Titles affect segmentation, stewardship and respect
• Incorrect titles can cause distress or embarrassment
• Inconsistent titles break personalisation in thank-you letters and emails

Quick win

Agree a simple allowed-title list across the organisation.
Everything else: flag for review.

Where the Forge app helps

It flags unusual or invalid titles so you can correct them before they cause issues.

3. Postcodes

This is one of the quickest data wins charities can make.

Postcodes unlock everything: wealth screening, gift aid validation, segmentation, mapping, route planning, socioeconomic insight… and yet, they are often wrong.

What it looks like

• Missing final character
• Wrong spacing
• Lowercase letters
• Entire postcode missing
• Invalid formats (“ZZ1 2XX”)

Why it matters

• Gift Aid claims fail
• Addresses fail to validate
• Mailings cost more and return more
• Insight and dashboards become unreliable

Quick win

Validate postcodes at the point of entry — either through your CRM’s validation tools or a simple lookup before saving.

Where the Forge app helps

The Data Quality Checker flags invalid, incomplete and unusual postcodes instantly.

4. Duplicates

One person = one record. Always.

Duplicates are the single most expensive and time-consuming data problem charities face. They affect everything—reporting, supporter care, fundraising accuracy, stewardship, and even GDPR compliance.

What duplicates look like

• Same name, different email
• Same supporter, different spelling
• Separate event and donation records
• Legacy imports splitting one person across many rows

Why duplicates matter

• Donors receive multiple appeals → feels impersonal
• Reporting becomes wildly inaccurate
• Income forecasting breaks
• GDPR rights (access, deletion, restriction) become harder to fulfil

Quick win

Before creating a new record, always search three ways:

• Name
• Email
• Postcode

If the CRM offers duplicate detection: turn it on.

Where the Forge app helps

The duplicate check gives you a clear, MOT-style score and highlights the most likely matches.

Pulling It All Together

Casing, titles, postcodes and duplicates may seem small individually, but together they have a huge impact.

Fixing them doesn’t require a big project or a migration — just small, shared habits:

• slow down for five seconds
• check before creating a new record
• stick to agreed formats
• use the right tools (like the Forge app)
• tidy as you go

Small consistency → big clarity.

Lesson 5.3 — Quick Win: One 5-Minute Data Fix You Can Try Today (practical action)

A small habit that builds confidence, reduces errors, and improves your data instantly.

Big data clean-ups are overwhelming. Five-minute fixes aren’t — and they create the same momentum with far less friction. When people see a small improvement that took almost no time, they’re much more likely to keep going.

This lesson gives your team one simple action that improves data instantly, builds confidence, and reinforces the good habits we’ve been talking about.

You’re not aiming for perfection. You’re aiming for progress.

Your 5-Minute Fix: Correct 10 Records with Simple, High-Impact Issues

Pick one of the four common issues from the last lesson:

• inconsistent casing
• unusual or invalid titles
• missing or malformed postcodes
• obvious duplicates

Then follow this short, calm process.

Why This Tiny Fix Matters

Five-minute tidy-ups deliver:

1. Cleaner supporter experience

Correct names, correct titles, accurate addresses — these things matter to people.

2. Fewer mistakes later

A record fixed today prevents three problems next month.

3. A culture of shared responsibility

When everyone contributes small improvements, the CRM stays clean without relying on one overstretched “database person”.

4. Momentum

Teams start thinking: “What else could I tidy while I’m here?”

And that’s when behaviour changes.

Optional Extension (for teams or power users)

If time allows, try a “data tidy sprint”:

• 5 minutes per person
• 10 records each
• 6 people = 60 fixes in half an hour

Small actions → real impact.

Wrap-Up

Everyday data quality isn’t about big overhauls. It’s the sum of tiny, consistent choices.

This module has shown your team that:

• data quality is achievable
• it’s shared
• it’s valuable
• and it can start with just five minutes