Data Quality How-To: Two Steps to Ensure Accuracy

Data Quality How-To: Two Steps to Ensure Accuracy

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We all want quality data, quality insights, or benchmarks. Everybody knows that data is the most important thing for any company, and many companies are prepared to spend a fortune in order to get their hands on quality data that will help them grow and increase sales. However, with more and more providers entering the market, it’s become increasingly important to due diligence on a vendor before buying data from them.

When a company is looking for data vendors, their main questions are:

While it's clearly very important to ask these types of questions before making a purchase from a data provider, it's also a good idea for companies to measure the quality of the data they've purchased in order to ensure the success of their marketing campaigns. Many companies today are too trusting when it comes to data vendors, and are willing to pay the full amount for a data list when they haven't done any validation tests on the data acquired.

Some reasons why companies fail to validate a purchased data list:

So to fix this issue with failed data validation, we’ve written a short guide on how any company who buys a contact list from a vendor, can make sure that their data is of the highest possible quality.

Data Quality Guide

There are two types of data quality validation. There is a “Pre-Purchase Checklist” which verifies a company and its data before committing to purchasing, and there is the the second stage - “Post Purchase Checklist” which verifies the data purchased using validation techniques.

FYI: The guide below contains technical steps and strategies, which require an experienced manager to apply, or outside help from a marketing or data specialist.

Pre-Purchase Checklist

Before deciding to buy a list, a company should go through this checklist so they can eliminate any vendor who fails to meet these standards:

By going through this pre-purchase checklist, any company will be able to filter subpar data vendors and avoid purchasing poor data.  This will ultimately mean less outdated, incorrect or incomplete data being transferred to your CRM, and gives you a good start in ensuring a successful marketing campaign.

Post-Purchase Checklist

We've gone over the pre-purchase checklist to help weed out potentially untrustworthy providers, but it's also important to verify the data after a purchase is made. If you find that the data you bought isn't good quality, and you wish to seek a refund from the vendor, you'll need to provide evidence that it's not up to the standard they promised.

With this in mind, let's take a look at examples of platforms that can validate your purchased data for free, and how to carry out the process.

Facebook Audience:

  1. Upload the data CSV to Facebook Custom Audience: Download the data you received from your vendor, make sure that the full name, company name, email address and phone number are in the CSV.

  2. After 15 days visit Facebook Audience Insights: After you’ve uploaded the data to Facebook Audiences, Facebook will provide you with the match rate in real-time, although you won't have access to data insights such as gender, job title, or industry of the uploaded list. After 15 days, you may access the Facebook Audience Insights, choose the list your uploaded, and Facebook will provide you insights on your audience by segmenting by gender, job title, industry, etc.

  3. Validate Facebook enrichment data with your purchased data: After you've checked what insights Facebook has for your audience, you can now manually validate what Facebook insights has compared to your purchased data. For example: if 40% of your audience from the vendor are in the telecoms industry, and Facebook Audience also shows that 25% of audience is in the telecoms industry, it shows that your audience is valid and it’s accurate.

LInkedIn Audience

  1. Upload the data CSV to LinkedIn Matched Audience: Download the data you received from your vendor, make sure that the full name, company name, email address, and phone number are in the CSV.

  2. After 15 days visit LinkedIn Matched Audience: Visit the LinkedIn Matched Audience tab and you’ll find out what percentage of your vendor data audience was matched. For example you may see a 40% match rate - which means that LinkedIn Audience contains 40% of your vendor audience.

  3. Validate match rate:  If the match rate is over 30%, we can assume the data was valid and your vendor has provided quality data. But we should not stop at 30%; the higher the match rate, the higher quality the data is.

After 15 Days visit Facebook Audience Insights

TowerData Audience:

  1. Upload the data CSV to TowerData: Download the data you received from your vendor, make sure that the full name, company name, email address and phone number are in the CSV.

  2. Validate data:  TowerData is able to validate data accuracy in real-time. By uploading the list, Towerdata will show how many of the contacts are in your target.

It’s important to validate your data using at least two tools so that you can be sure the data purchased data corresponds to your criteria. There are other platforms and tools which will allow you to match and validate databases such as PIPL, Acxiom, LiveRamp, Google Adwords, Adroll, MarinSoftare, and TheTradeDesk.

If you find that your match rate is below 10%, or the demographic data from the platform doesn’t correspond to your criteria, schedule a call with your vendor, explain how you validated the data and ask them to replace it or refund the full amount.  


In conclusion, buying company contact data can be a very useful asset in a company’s growth and expansion, but we should always verify data accuracy. As more data is discovered, and collated, we should implement a data workflow validation in our companies which will reduce conflicts.  

This guide was more focused on traditional data and how to verify it, but in the next post, we will provide a guide on how to verify 1st, 2nd, 3rd party data.