Inconsistent definitions and incomplete data skew your dashboards. Create a glossary of key business terms that everyone follows, and set up CRM data standards with a dashboard to track compliance. 76% of organisations report that less than half their CRM data is accurate (Validity, 2024).
How to Build Meaningful CRM Dashboards: 2 Simple Strategies
If you've ever doubted the accuracy of your reports, you're not alone. According to Validity's 2024 CRM Data Management study, 76% of organisations say less than half of their CRM data is accurate and complete (Validity, 2024). Dashboards and reports sit at the heart of every data-driven business decision-but are yours telling the story you need to hear?
This article covers two straightforward ways to improve the quality of your dashboard reporting: defining clear sales stages and setting data standards.
TL;DR
Inconsistent definitions and incomplete data skew your dashboards. Create a glossary of key business terms that everyone follows, and set up CRM data standards with a dashboard to track compliance. 76% of organisations report that less than half their CRM data is accurate (Validity, 2024).
The problem: inconsistent data, misleading dashboards
Inconsistent data, undefined processes, and misaligned reporting practices can all lead to incomplete or misleading dashboards. An audit might sound like a pain, but consider how much better your decision-making could be with the right information.
Strategy 1: Define clear sales stages
One major issue behind inaccurate reporting is inconsistent definitions. What constitutes a lead, an opportunity, or a closed deal? If one salesperson's idea of a "qualified lead" differs from another's, your data becomes fragmented.
Create a glossary of key business terms that everyone follows. Ensure these definitions are easily accessible and part of your onboarding and training processes. When everyone's aligned, your dashboards will reflect a more accurate picture of your pipeline, marketing efforts, and overall business health.
Strategy 2: Double-check your data
Even with the best processes, human behaviour can lead to gaps in your data. Salespeople may occasionally skip recording a meeting or leave incomplete fields, which distorts the bigger picture.
Set up data standards within your CRM, such as requiring key fields like email addresses. Create a dashboard where you can track records that don't meet the agreed standards. To further engage your team, add a dashboard highlighting which users are most diligent in maintaining data quality.
Frequently asked questions
Why are my CRM dashboards inaccurate?
Common causes include inconsistent definitions of leads and opportunities across the team, incomplete data entry, and fields that aren't required. Defining standards and holding the team accountable improves accuracy.
How do you define a qualified lead in a CRM?
A qualified lead should have clear, agreed criteria-such as budget, authority, need, and timeline (BANT)-that everyone on the sales team uses. Document this in a glossary and train new team members on the same definitions.
What data should be required in a CRM?
At minimum, require contact details (email, phone), company name, and stage/status. Depending on your process, you may also require next steps, opportunity value, or expected close date. Avoid requiring too many fields, as that can reduce adoption.
Next steps
Need help taking your dashboards to the next level? We're here to guide you. Book a call with one of our experts or take our free CRM Scorecard for a 5-minute assessment and personalised recommendations.
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