Bad data doesn’t just clog your CRM, it quietly caps your revenue potential. Discover the hidden cost of dirty data, why it persists in scaling SaaS companies, and how a five-minute audit and the right habits can put you back on track.
You’re missing targets because your data is.
We speak to B2B SaaS leaders every week who’ve built strong teams, sharp playbooks, and solid forecasts. But when the numbers fall short, it’s rarely a strategy problem, it’s a data problem.
This is not the kind of data that shows up neatly in a dashboard. These are the easy-to-miss, human error data hygiene issues: Stakeholders aren’t linked to opportunities, deals are being pushed too fast through stages, deal values aren’t accurate, emails aren’t syncing to HubSpot or Salesforce. Very quickly, these discrepancies snowball into major issues.
Still, most companies treat it like background noise. Something for Sales to sort out later. This usually continues until a noticeable problem occurs, such as a key renewal gets missed or reps spend 30% of their week chasing leads that don’t exist anymore. At this point, bad data becomes a growth problem.
So, what’s the impact of bad data?
According to IBM, poor data quality costs the U.S. economy $3.1 trillion every year. In high-growth SaaS companies, that cost shows up in lost revenue, wasted rep time and inaccurate forecasts, and it compounds as the company scales.
Most revenue teams would say they’re data-driven. They check dashboards. Measure KPIs. Run QBRs. However, none of that matters if the underlying data is broken. Here’s why it usually is:
In B2B, up to 40% of CRM data becomes outdated each year. Stakeholders move roles, deal values shift, and opportunities progress or slip back. Even if your CRM looked clean last quarter, the data tied to your live opportunities may already be wrong, and that directly skews forecasts and coaching.
A rep forgets to link a stakeholder. Or skips a qualification step and moves a deal forward anyway. Or their email integration fails and no activity is captured. Small things, but they result in inaccurate data capture which impacts forecasting and buyer experience.
Marketing blames Sales. Sales blames Rev Ops. Everyone agrees it’s a problem, but no one is truly accountable and therefore not willing to fix these mistakes if they don’t feel responsible for them.
Let’s say your pipeline looks pretty good at first glance. Then you dig in and find:
And suddenly, the entire Go-To-Market motion feels broken, not because the strategy’s wrong, but because the inputs are flawed.
Take Ignite Reading. As the company scaled, their HubSpot CRM became cluttered with duplicates, uncategorised records, and inconsistent field completion. Nearly 20% of their company records had no clear owner, and cross-team reporting was unreliable. By auditing over 28,000 records, standardising inputs, and enforcing data hygiene across functions, they transformed HubSpot from a liability into a growth engine. Sales and marketing finally shared the same source of truth, reporting accuracy improved, and reps could spend their time on live opportunities instead of chasing errors.
The lesson here is that clean data doesn’t just save admin time. It restores confidence in the entire revenue process, from pipeline reviews to coaching to forecasting.
You don’t need to hire a whole data team. A quick audit can surface the gaps fast.
Ask yourself:
These are the small things that turn into big problems later if there’s no consistency.
This is exactly where Hive Perform fits in.
It doesn’t just track what happened, it shows what’s missing:
Instead of relying on memory, spreadsheets, or CRM workarounds, Hive makes the invisible visible, and because it pulls this information automatically, you can stop worrying about human error cluttering your CRM.
If you want to read more about good business practices and how Hive Perform can bring value to your company, check out one of our other blogs here: 👉 https://hiveperform.com/resource-hub