If you are sitting on 50,000 contacts in HubSpot and think that is a strength, think again. In most B2B companies, 40-60% of the CRM data is junk. It is duplicates, old addresses, incorrect company names and "test test" from an onboarding nobody remembers. Poor data quality costs more than you think. Not only in missed deals, but in bad decisions and wasted hours. This can be fixed, but not through a one-off project.

Why HubSpot data turns to junk over time

A CRM is like a warehouse. It starts out organised, but after a few years you find shelves with mislabelled boxes and expired products. HubSpot is no exception. When the sales team, marketing and customer service all enter data without shared rules, the result is a mess that is hard to get an overview of.

Add to that the fact that most companies change strategy, staff and tools from time to time. Every time a change happens, old fields are left behind, automations that are no longer used keep creating new records, and integration flows fill the database with irrelevant contacts. The consequence is that you make decisions on shaky ground.

When data turns to junk over time, you notice it first in small things: wrong names in email sends, salespeople calling the same prospect twice, reports that do not add up. But beneath the surface the problems are much bigger. You no longer know which data is correct, and that means every analysis you make risks being misleading.

The three biggest data problems in Nordic B2B companies

#1: Duplicates. And no, it is not just about the same contact happening to exist twice. It may well be the same company under different names, or the same person registered with several email addresses. Duplicates make you overestimate your pipeline and underestimate your churn.

#2: Outdated data. People change jobs, companies go bankrupt and domains stop working. If you do not have a process for continuously updating and removing old records, you are building reports on a reality that no longer exists.

#3: Faulty fields. A CRM can quickly become a patchwork of fields created for campaigns, projects or specific customers. When those fields are no longer used, they remain anyway and often get filled with incorrect or incomplete information. That makes automations stop working as they should and makes segmentation skewed.

All three problems are symptoms of the same root cause: data quality has not received the same strategic focus as campaigns, content or sales training. It is seen as an IT problem, not a business issue.

Stena Recycling's 90-day data cleanup

We saw this clearly when we worked with Stena Recycling. They had 47,000 contacts in HubSpot. In a first analysis, only 8,000 were actually usable. The rest were duplicates, misspelled company names, old email addresses and internal test records from the 2019 onboarding. The solution was a 90-day data cleanup. We did not start by cleaning everything, but focused on business-critical data. Which contacts contributed to the business? Which companies were in active processes? By prioritising correctly, we quickly raised data quality in the pipeline and in reports, without the whole organisation having to pause.

In parallel we built rules and automations so that new data did not fall into the same traps. We set standards for how fields should be filled in, automatic checks for email format and company association, and workflows that flagged duplicates before they could cause problems. The result was clear: sales reported fewer incorrect leads, marketing could segment correctly and management got reports that actually reflected reality. No magic here, only methodical work and an understanding that data quality is an ongoing process.

Automatic rules that keep your data clean going forward

Cleaning data once gives a short-term improvement. HubSpot has features to detect duplicates, validate fields and automatically update information through integrations. But the tool is only half the solution. The other half is defining which rules are business-critical for you.

It is about setting a standard for how contacts and companies should be registered, integrating data sources that keep your records up to date, and giving teams clear guidelines for how to handle new information.

When data quality becomes part of your culture, you no longer have to spend time "cleaning up" before every campaign or report. You get a CRM that is a reliable source for decisions, and you reduce the risk of missing deals because of incorrect or outdated information.

FAQ

How do you clean HubSpot data?
Start with business-critical data, and use automatic rules to find duplicates and keep outdated information updated continuously.

CRM data quality: where should you start?
Identify which fields and records directly affect the business, and clean them first before you take on the whole database.

How do you avoid duplicates in HubSpot?
Use HubSpot's built-in features to detect and merge records, and set up guidelines for how new contacts should be registered.

What is data hygiene in CRM?
It is the process of keeping data correct, up to date and usable through continuous checking and updating.

Takeaway

• Poor data quality is not just a technical problem, it is a business risk. By prioritising business-critical data and building in automatic checks, you get a CRM that actually supports your growth.

Take a look at our page on HubSpot CRM & customer journey setup to see how structured data can change the way you work.