How Poor Quality B2B Data Costs Millions In Lost Opportunity and How To Avoid It

How Poor Quality B2B Data Costs Millions In Lost Opportunity and How To Avoid It

Last year, Gartner shared a startling statistic. “Every year, poor data quality costs organizations an average of $12.9 million.”

We can expect bad data’s impact to only worsen for companies. Poor data quality loses you access to opportunities, ruins strategic planning, and wastes your time and energy.

Business trends in the past decade focused heavily on having access to data. For the first time, businesses could have in-depth details found, logged, and analyzed about their prospects, customers, and own work processes. But once the data floodgates were opened, data and metrics were collected constantly without concern for accuracy and usefulness. 

Let’s review how poor quality B2B data impacts your business, why bad data is so common, and what you can do about it.

How Does Poor Data Quality Cost You Millions Annually?

Poor data quality hurts you in the big picture and while doing daily activities.

First, disorganized data culture stops everyone from being on the same page and causes mistakes. 

Does your company have different definitions for a “prospect” vs. a “lead”? Does everyone know those differences or are some using those terms interchangeably? When a contact has a phone number listed in the database, is that number the company HQ phone line, their office desk number, or their cell phone number? If those three options are listed, are you sure everyone and every integrated app know and understand those differences?

Second, if your data is being mismanaged, you’re unable to make intelligent decisions.

Let’s say you have data saying your anti-competitor campaign from last year made the most revenue, so you decide to invest more this year, going after even more competitors. But, if customers weren’t accurately tagged with the outreach campaigns they experienced before buying, you could be investing heavily in marketing that won’t make an impact.

Third, poor data slows down the daily work of everyone. 

Let’s look at a sales rep’s experience. If they send an email to a prospect, but the wrong title or name was connected to the email address, they’ve lost that prospect. It doesn’t matter how good the messaging is – the prospect will immediately see they were called by the wrong name or title and disregard the email. 

How about if the rep hops on the dialer? Every wrong, out-of-date, or mislabeled number means leaving voicemails, talking to the wrong people, or listening to the phone ring forever. The rep’s time has been wasted. 

Lost time leads to lost chances for closing deals. Campaigns with the wrong targets waste marketing spend. And, any number of mistakes can be made from your product team misunderstanding how to build new features to customer success reps hitting metrics that don’t contribute to continued revenue. 

Why is Data Health Frequently Poor?

For data to be valuable, it needs to fulfill several objectives and be:

  • Accurate
  • Consistent
  • Accessible
  • Timely
  • Complete

According to Talend’s 2022 State of Data survey, companies are struggling in all five separate areas. And, it only takes errors in one section to cause revenue loss. 

Let’s consider timely data. In the above example of deciding to launch a competitor-focused campaign, maybe your company does track and collect all the necessary data to have made a better decision. But, the data isn’t put together and shared until someone has already been a customer for at least six months (maybe the data collection and evaluation is part of your customer success plan). All your decisions are now based on data at a minimum of six months old. 

So, your data collection process could take too long, could introduce too many human errors, could be siloed and inaccessible, or could not follow an inconsistent gathering process. But, the biggest problem is data accuracy. Data decay happens over time; mistakes in the gathering process, human error, and app sync issues all make your database untrustworthy.

Avoiding Revenue Loss with a B2B Data Partner

What can you do instead of being stuck with constant lost opportunities? The first option is to evaluate your entire data process and find all the areas that need fixing. However, you’re now paying for a massive amount of expensive data management in-house.

You’ll likely save time and money by having a B2B Data Partner like SalesIntel. Your partner will already have an entire data collection and verification process in place and can help with everything from providing data on new contacts and companies to enriching or cleaning data you already have.

A data partner can’t magically solve every data problem you might have. You’ll have to make data accessible and collect data on customer touchpoints and deals on your own. 

But, a B2B data partner can immediately ensure you’re contacting the right people and not wasting your time. A provider like SalesIntel integrates with the tools you use, such as Salesforce and, so you’re not adding another data silo. 

SalesIntel has a human verification and research team to reverify data every 90 days. The database is easy to filter and search for relevant prospects. Using our Chrome extension, Rev Driver, our data is also available to see while on LinkedIn or company websites. If SalesIntel is missing the data you need, we have a Research On Demand team to find what you need.

So to summarize, SalesIntel is:

  • Accurate because of 90-day human re-verification of data.
  • Consistent because all the data is organized the same way and is mapped to your database fields as needed.
  • Accessible because SalesIntel can be integrated with your CRM and sales/marketing tools and is available online with Rev Driver.
  • Timely because the database is instantly available for use.
  • Complete because our Research on Demand team can find and verify any additional data you need.

Using a data partner like SalesIntel, you immediately achieve the objectives needed for data to be healthy, useful, and continuously improving revenue. 

You have the accurate data you need when and where you need it. No more wasting time dialing the wrong numbers. No more sending emails to people who left the company last quarter. And, no more being misinformed about your prospects.

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