Overseas List Scrubbing - Any recommendations?

searcher profile

March 03, 2022

by a searcher from Southern Methodist University - Edwin L. Cox School of Business in Dallas, TX, USA

Hi Seachers - question for everyone.

On the proprietary sourcing side, I have been using a vendor I found on Guru.com and paying $0.25/row for data scrubbing. While the work is good, it is not great. A scrubber is needed as the lists I am buying from DataAxle are pretty sub-par when it comes to sales range, employee counts, and email addresses.

What are the best vendors you have found for scrubbing?

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commentor profile
Reply by a professional
from University of Nebraska in Papillion, NE, USA
Hey everyone, Sales volume is tricky as it's based on industry code and employee size. We have to model this based on this information on a privately held company is not available for us to get. We call verify our data and each record we have listed in the database. We confirm type of business and if they're open or not. We do not ask them sales volume as the person answering typically doesn't know this, but they do know how many people are in the office. Both are those are then used to create a sales volume for this location If you would like to set up a meeting with me to learn more about how we acquire the data and what end results you're seeing with this data provider I would love the feedback. My email is redacted and I would love to speak.
commentor profile
Reply by a searcher
in Houston, TX, USA
The source of the issue lies in the data provided by vendors providing the data. You can scrub the data but it may be in vain if the data you are starting with isn't robust to begin with.

Consider this issue about data doesn't apply to DataAxle only, it applies to all vendors. DataAxle is great at what it does, and other data products are great at what they do. In my experience no platform or product provides reliable and accurate data on both decision makers AND their businesses. I'm not aware of any vendors that provide reliable and accurate revenue data but usually you find ways of reverse engineering revenue data if it's a must have e.g. revenue = # of employees X average revenue per employee by industry
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