Post-COVID Businesses Will Stop Treating Bad Data Like Sour Milk

“Customer data has an expiration date, just like milk in the fridge. Without regular intervention, customer data degrades at 2 percent each month and 25 percent over the course of a year.”

Misspellings, incorrect addresses, outdated telephone numbers: these are just a few ways that data either starts bad, or eventually decays in accuracy. To combat this for business post-COVID, Ray Melissa, CEO at data firm Melissa, said, “Data cleansing and verification services — including address autocompletion, real-time email verification, HLR mobile lookup and others — provide data quality for easy onboarding and cleansing existing customer records. This is very important, with studies revealing that it costs five times as much to acquire a new customer as it does to retain an existing one.”

The following is an excerpt from How 35 Execs Are Powering The Great Digital Shift Of 2020 (And Beyond), contributed by Ray Melissa, CEO at data firm Melissa.

With the economy starting to ramp up again as the lockdown eases, it’s time for businesses to reimagine best practices to drive growth. Taking better care of customer data is one area that will result in immediate returns.

Customer data has an expiration date, just like milk in the fridge. Without regular intervention, customer data degrades at 2 percent each month and 25 percent over the course of a year.

This is exacerbated by more consumers providing contact data via their mobile devices. Inputting data on a small screen increases the risk of mistyping. In fact, approximately 20 percent of addresses entered online contain errors such as spelling mistakes, wrong house numbers and inaccurate postal codes.

But you don’t have to throw out “bad” customer data like you would spoiled milk.

Issues with incorrect data, such as customer names, addresses, email addresses or telephone numbers, can be easily fixed. Industry-leading data cleansing and verification services — including address autocompletion, real-time email verification, HLR mobile lookup and others — provide data quality for easy onboarding and cleansing existing customer records. This is very important, with studies revealing that it costs five times as much to acquire a new customer as it does to retain an existing one.

Usually, “bad” customer data just needs a little cleaning to help the business reengage and sell to a customer. And in these challenging times, nobody can afford to discard customer data.

It’s also important to fill in any gaps and enrich customer data with location and demographic intelligence as part of the ID verification process. This helps to deliver a 360-degree single customer view (SCV) — something that can aid future marketing and sales efforts.

As businesses look to reopen and rethink how they do business, it’s time to move away from considering customer data as “bad” in today’s economic environment. Instead, all data should be recognized as being valuable, as it may hold the key to driving growth.

All it takes is a best-practice approach with customer data quality to ensure that data is “good” and that its value is maximized to drive growth and profitability.