Sales Trainer Steve W. Martin recently ran an independent study of DiscoverOrg contact data quality which found that the vendor lives up to its high quality data claims and SLA.  According to Martin, “DiscoverOrg had no foreknowledge that I was measuring their data accuracy and no influence over the sample data set I used.”

Martin randomly selected 100 contacts from a file of 10,000 and conducted the study himself.  He evaluated seven fields and found very high data quality levels:

• Full Name Accuracy was 99%, including spelling.
• Contact Company name was 98%
• Title Accuracy was 96%
• LinkedIn URL accuracy was 97%.  The three contacts that lacked LinkedIn URLs confirmed that they did not have LinkedIn profiles.
• Seniority Level accuracy was 100%
• 97% of the emails were deliverable with only a 3% bounce rate.  As contacts decay at a 2% rate per month, 97% is at the upper end of expectations.
• Twitter Handles were correct 100% of the time, but only 10% of the contacts had the field populated.

With the exception of Twitter handles where there is likely a significant underpopulation of the field, the dataset lived up to its 95% SLA and data quality claims.  It should be noted that Martin did not evaluate DiscoverOrg’s technographics, org chart relationships, responsibility data, or event alerts.  These are other areas where their editorial data distinguishes the firm.

“This study confirms what I have personally heard from a wide cross-section of the technology companies I work with,” said Martin.  “DiscoverOrg provides highly accurate contact data. In addition, this study was based on a small subset of the data that DiscoverOrg provides. Of primary importance to my clients are the detailed IT organization charts, the identification of the different technologies installed, recent trigger events such as personnel changes, and the direct phone numbers of contacts.”

These types of studies are often expensive to conduct and difficult to construct when comparing vendors.  I performed similar studies as internal benchmarks when I worked at OneSource (now D&B Hoovers) and for clients since becoming a consultant and no vendors approach this level of data quality (Note: I have never evaluated RainKing which utilizes similar data collection methods).  What is clear is that the smaller universe, editorially-crafted DiscoverOrg file of 60,000 companies and 1 1/2 million contacts clearly has higher contact data quality than other vendors (again, excluding RainKing).  When discussing DiscoverOrg and RainKing with clients, I describe them as using traditional artisanal research methods which entail focusing on a smaller universe of companies and contacts at these companies.  This approach makes for a strong fit for firms employing an ABM approach to target large accounts, but may be insufficient for more transactional marketing approaches which are more sales development and demand generation focused.  Both cost and lack of coverage of SMBs would be issues at those firms.

“Bad data is costly and can be the single point of failure in an otherwise successful campaign,” says the firm on their website.  “We don’t just pay lip-service to the quality of our data. We contractually guarantee it. We know that success in every sales and marketing effort begins with highly accurate, verified data that your team can trust.”

What is clear is that this quality-centric approach to gathering data has proven successful.  Both RainKing and DiscoverOrg have high growth rates and regular Inc. 5000 membership.  DiscoverOrg closed last year with $71 million in annualized recurring revenue so is almost assured of making the Inc. list for the seventh year in a row.

Martin published his results online as a PDF.