April 7th, 2017 | by

When sales intelligence data is inaccurate, incomplete, or outdated, the rabbit hole for a sales person can be very deep—and no one knows better than Steve W. Martin.

A lifelong sales trainer, Steve has consulted for and trained sales teams for hundreds of technology companies. “Contact data is a very important priority to my clients,” he says. Combing through social media for clues to contact information and calling wrong numbers consumes hours, and returns scant benefits: Burnout and high turnover are common among sales teams who have to question every phone number and email address.

What prompted his interest in DiscoverOrg’s data accuracy?

Testing data accuracy leads to surprising results“There are many different data sources,” Martin says. “The impetus for this study started from a conversation with one of my clients. We were discussing which contact data provider provides the best results for outreach campaigns.”

Martin, also a speaker and critically acclaimed author, was so intrigued by DiscoverOrg’s contractually guaranteed accuracy claim of 95% that he conducted a survey of our data and published the results: An Independent Study of DiscoverOrg Contact Data Accuracy.

The study was completely independent. DiscoverOrg had no foreknowledge that Martin was measuring their data accuracy and no influence over the sample data set used.

From a list of over 10,000 contacts, Mr. Martin randomly selected 100 records and personally researched each one. The following criteria were based on Martin’s focus on new client outreach via email and social media:

  • Name accuracy: Was the contact’s full name accurate, spelled correctly, and did it include an addressable nickname where applicable?
  • Company accuracy: Was the contact’s company current?
  • Title accuracy: Was the person’s title correct and did it specifically reflect their role in the organization?
  • LinkedIn URL accuracy: Was the person’s LinkedIn URL provided and was it correct.?
  • Seniority level accuracy: Was the seniority level designation accurate so that outreach campaigns could be targeted by hierarchical role within the company?
  • Email address accuracy: Was the email address valid and correct?
  • Twitter handle identity accuracy: Was the person’s twitter handle correct?

DiscoverOrg’s Sales Data Accuracy Put to the Test

With these variables in mind, here’s what Martin discovered with his random sampling of DiscoverOrg’s raw data.

Name accuracy of DiscoverOrgs contact data is 99%1.Name Accuracy

Contact name accuracy was 99%. This accuracy was based validating the contact’s full name, correct spelling, and addressable nicknames included (where applicable).

2. Company Accuracy

The contact company name accuracy was 98%.

3. Title Accuracy

The contact title accuracy was 96%.LinkedIn accuracy of DiscoverOrgs contact data is 97%

4. LinkedIn URL Accuracy

The accuracy of the LinkedIn URLs provided with each contact record was 97%. In addition, there were three records without a LinkedIn URL and it was confirmed that these contacts do not have LinkedIn profiles.

5. Seniority Level Accuracy

DiscoverOrg assigns a seniority level to each contact to group hierarchical roles such as “Vice President,” “Director,” and “Manager.” This helpful classification allows you to organize marketing campaigns by scope of responsibility. The seniority level was 100% accurate.Email accuracy of DiscoverOrgs contact data is 97%

6. Email Address Accuracy

Emails were sent to the sample data set addresses and the accuracy level was 97%. Three percent of emails bounced back with an “unknown email address” or “no such recipient” errors.

7. Twitter Handle Accuracy

While only 10% of the contacts had a twitter handle, the accuracy level was 100%.Twitter handle accuracy of DiscoverOrgs contact data was 100%


We contractually guarantee a 95% level of accuracy, so it was gratifying to see independent results support our claim. Even Martin himself was surprised by the results of the study.

A Good Data Believer

“I’ve heard from my clients over the years that certain contact data providers were better than others. In fact,” he says, “the accuracy of some providers is surprisingly low based on my observations. Conversely, the stories about DiscoverOrg set my expectations that the results would be quite good. But after quantifying the accuracy, I was even more impressed.”

So which data points does Martin think salespeople and marketers should give more weight to, that they’re not focusing on already?

“I think a key point is that marketing and sales have to select the data provider. There’s lots of options,” he adds, “and it’s easy to pick the wrong provider as everyone makes the same claims. Because contact data changes so quickly, a key deciding factor is the strategy and comprehensiveness the provider uses to update their contacts.”

The takeaway? A high level of data accuracy allows sales teams and marketers to do what they do best—solve problems for customers—and leave the research and verification to us.

Don’t take Steve W. Martin’s word for it. Dive into our data yourself and imagine what your sales team can do with sales intelligence like this (the sample is taken from HR and IT, two of DiscoverOrg’s many datasets). Then give us a call.

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Ben Loria
About the author

Ben Loria

Ben is the program manager for TiLT, DiscoverOrg's customer sales training program. He has a B.S. degree in Accounting and Business/Management, and lives in Portland, Oregon.