One of the biggest surprises companies turn up when they start digging into their HubSpot data is the sheer volume of bad and inaccurate data in the average database. When you collect data, you do so with the best intentions. It’s not that hard for a prospect—or your team—to enter their information correctly, right? Wrong. Any data collection program that requires manual human input is going to experience data entry errors.
But dirty data in your HubSpot marketing database can result from many sources:
manual entry errors
data that’s been entered in the wrong field
Improperly formatted data
duplicate data
errors during import or export
versioning mistakes
misspellings, typos and other errors
integration issues that break the sync
A contact or company record with any of these issues is problematic for your marketing and sales teams.
No matter where your bad data comes from, it can significantly united states telephone area codes water down the success of your marketing campaigns. A contact record with issues is inherently less valuable to your organization than one that is clean. This is why HubSpot data quality is so critical. Let’s take a look at the three biggest reasons all companies should consider instituting data integrity and quality assurance programs.
3 Ways Bad HubSpot Data Quality Hurts Your Marketing
There are many ways that bad data can harm your marketing and sales campaigns. Sometimes this impact will be specific to your own campaigns. But there are some common ways low-quality data impacts campaigns—resulting in those billion-dollar losses we detailed above.
1. Low-Quality Data Makes Lead Scoring Difficult
Lead scoring is at the center of some of the most successful B2B marketing campaigns. Knowing where to focus your attention and being able to identify what stage of the buying process individual leads are in, is critical for optimization. However, 79% of B2B marketers have not established lead scoring within their marketing operations.
Lead scoring relies heavily on your ability to collect accurate data from prospects. You need to collect enough data to gain a complete picture of each prospect to score them accurately. You can’t use what you don’t collect. But it’s critical to make sure that you don’t sacrifice data quality in your HubSpot databases in your effort to scale the data you collect.
Duplicate HubSpot records can make lead scoring difficult. Sometimes, the same lead will get scored twice and receive two completely different scores. Then, when a salesperson is assigned that lead, their approach will be dictated by which record they were assigned. Beyond that, the wrong record might receive updates. This can make it difficult to track and identify relevant companies in your HubSpot database—resulting in lost sales.
Errors in your data mean errors in the scores that you assign to leads and accounts. What if a company’s estimated annual revenue was incorrectly entered? If the amount listed in the Hubspot database was substantially lower than the company’s revenue, all associated leads would have incorrect scores, due to the lower revenue opportunity.
It’s impossible to quantify the cost of missing out on these leads without a full data quality audit. Even then, you can’t maintain data quality with
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