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Data Quality- Why 52% is Not Accurate Enough

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52% is not accurate enough

“To bring value, you must be better than a coin flip.” – My Father.

 

Delivering Value

My father was not only a brilliant man but an inspiration, and his quote has impacted what I have done and what I will continue to do both professionally and personally. When I co-founded Webbula over 11 years ago, our intention from day one was embracing and continuously breeding data quality. 

Early in my career, I learned that data could profoundly impact how organizations in any vertical could use it as drivers for better experiences. For the last 15 years, organizations have been obsessed with feeding the machine with more data than correct data. Despite good intentions, overabundance adds a level of complexity to maintaining its accuracy and quality. Furthermore, it compounds issues with companies that try to monetize and distribute it. 

As a technologist and business owner, I am continually thinking about bringing value to our clients and redefining why data quality and accuracy are essential. 

Delivering value MUST be better than 52%.

Data Quality Matters Now and Forever

It is not hard to garner support at any organizational level that excellent data quality is ideal for business in the digital transformation era. The support for focusing on data quality is as strong as ever, but when it comes to figuring out who is responsible and who will fund the activities is when things get a little dicey. However, the challenge is for organizations to think not only about today but the many tomorrows on ownership of data quality.

We live in a hypercritical and hypersensitive world where brands are punished publicly for not doing enough or doing too much. Over-Personalizing an experience could brand the organization as invasive and creepy. Not using any data to individualize the experience can lead people to feel like just another number and increase the likelihood of finding a competitor that “gets them.” This is why data quality, its use, and accuracy matters more than ever. There is also growing pressure from thought leaders and research that says customers demand it but offer little substance to strike that balance.

So as organizations continue to scale for greater relevancy across channels, they must have a scalable and consistent strategy in their data quality practices. It starts with auditing the data, followed by employing a vendor whose accuracy of appending that data is best of breed. 

The Case for Accuracy

A few weeks ago, I received a forwarded email from a colleague who commented, “here is where an append went wrong.” The email was from a Presidential Candidate who was using the wrong information to contact her. The email assumed she was a male due to first name personalization (Mark vs. Beth), had a deep affiliation to their political side of the aisle, and desired to donate time and money to elect the candidate. Every single data point used in that email was incorrect, which means that whatever source of information that the vendor used to append that data was amazingly flawed. While we snickered about this over a call, it got me wondering how inaccuracy of something so simple such as gender can quickly derail the true message of any email and the brand damage that can be inflicted.

As marketers, we probably all have stories around mistakes made when using data, but as a brand, we can learn from our mistakes, and it starts with the data vendors. To do this, you have to know what to ask the vendor to guide you in making the right decision. Here are a few suggestions:

  1. Was the data sourced from offline or online channels?
  2. Are your audiences sourced from “known” data signals
  3. How do you verify the quality of data, and can you prove it?

These three questions are simply a guidepost, and if interested, we would be happy to provide you further guidance on questions to ask, even if you don’t use Webbula in the end.

Accuracy Must Be Measured

We also feel independent and unbiased data quality measurement is crucial to what we do. That’s why we chose Truthset, a data intelligence company, to validate the accuracy and compliance of our consumer data.  Just recently, we were honored to learn that we ranked first in 28 key demographic categories by Truthset analysis. This is something that we are incredibly proud of and, most importantly, will benefit our customers and the individuals on the other end of becoming more personalized and relevant to their audience. 

Dad, we bring value every day to the industry, and the coin we flip is way above 52% because of our determination to continuously improve.

 

Meet the Author

Headshot of Douglas Egeth

Douglas Egeth

As the Chief Operating Officer for Webbula, Douglas is responsible for developing new technology applications, supervising Webbula’s data flow process and overseeing day-to-day operations. His 15+ year technology career has been diverse with prominent organizations in the technology, financial, healthcare, entertainment and telecom sectors, as well as with several governmental agencies. Before joining the Webbula team, Douglas was a part of the ground floor crew at Colotraq where he grew the company into the largest neutral B2B telecom broker in the world. He graduated Summa Cum Laude from Seton Hall University with dual degrees in Business Administration and Decision Sciences.