Why CRM Users Don’t Trust the Data: Where to Start

By Stacey Segal, COO

Most CRM problems do not start with the software. They start with a question no one wants to say out loud:

“Do we actually trust what’s in here?”

Your CRM supports fundraising, reporting, segmentation, donor engagement, stewardship, and leadership decisions. When users do not trust the data, they start creating workarounds. They keep spreadsheets. They double-check everything. They ask someone else before making a decision. They stop using the system.

That is when a CRM becomes less useful, not because it cannot support the organization, but because confidence has broken down.

The good news is that rebuilding data trust does not require solving everything at once. It starts with practical, focused steps.

Start with the Data People Use Most

It is tempting to begin with the messiest corner of the database, or the data that's easiest to transform. That's not always the best place to start.

Instead, focus on the data your teams rely on every day.

For many organizations, that includes:

• Giving history

• Constituent names and contact information

• Communication preferences

• Relationship data

• Prospect assignments

• Key constituencies

• Campaign, fund, and appeal information

• Reporting fields used by leadership, etc.

These are the areas where small improvements can create immediate confidence and begin rebuilding trust. When users see that the information they depend on most is becoming more reliable, they use the system.

Define What Your Terms Mean

Data trust depends on shared meaning.

If one team defines “lapsed donor” differently from another team, both teams may be using the CRM correctly and still end up with conflicting results or "bad" reports.

That is why a glossary is often one of the simplest and most useful data governance tools an organization can create. It does not need to be complicated. A shared document or spreadsheet can be enough to start. And today, using AI is a great way to start this project.

At a minimum, define:

• The term

• The business meaning

• The system or data definition

• The source of truth

• The owner or decision-maker

For example, “major donor,” “household,” “lapsed donor,” “soft credit,” and “active prospect” may all sound obvious until they are used in reports, lists, or conversations.

Clarity prevents confusion later.

Fix the Workflow, Not Just the Field

Data quality issues are often treated like cleanup projects. Someone runs a list, fixes a few records, and everyone feels better, for a while.

Then the same problem returns.

That usually means the issue is not just the data. It is the workflow.

Ask questions like:

• Where is this information being entered?

• Who owns it?

• Is the field required at the right point in the process?

• Are users given clear choices?

• Are code tables consistent?

• Is there a validation rule or notification that could help?

• Is the team trained on what “good” looks like?

A cleanup project may fix the current problem. A better workflow helps prevent the same problem from coming back.

Use Notifications and Guardrails Thoughtfully

Not every data quality issue needs another training session.

Sometimes users need a reminder at the exact moment they are making a decision. In Blackbaud CRM, notifications can help reinforce important business rules, flag sensitive records, or remind users to take a specific action. This is also an area where AI can make a real impact. At BrightVine, we're building AI into our tools, like the BrightVine Data Link, and training it to recognize patterns, understand data rules, and alert users.

Notifications should be short, clear, and reserved for moments where context truly matters. If everything is urgent, nothing is urgent.

Used well, notifications help users make better decisions without slowing them down.

Create Ownership

Data trust improves when people know who is responsible for decisions.

That does not mean one person owns the entire CRM. It means specific data areas have clear business owners.

For example:

Gift processing owns gift entry standards. Prospect management owns prospect assignment rules. Alumni relations owns certain education and involvement data, Marketing owns communication preference processes, and Finance owns reconciliation.

Ownership does not have to be bureaucratic. It just needs to be clear enough that questions have somewhere to go.

Do Not Wait for a Perfect Data Governance Program

Many organizations delay data governance because they imagine it has to be a large formal initiative.

It does not.

Start with one high-value data area. Define the terms. Identify the owner. Review the workflow. Clean up the most visible issues. Document the decision. Repeat.

Slow and steady progress is still progress.

The Bottom Line

CRM trust is built through consistency.

Users need to know that the data means what they think it does, that important fields are maintained, and that the system supports how they work.

That does not happen through cleanup alone. It happens through definitions, ownership, thoughtful configuration, and practical governance.

When users trust the CRM, they use it. When they use it, the data gets better. And as the data improves, the organization can make smarter decisions with greater confidence.