BlastPoint’s CEO & Co-Founder, Alison Alvarez, talks about the importance of customer data validation. Alvarez, who has over a decade of experience working with customer data in multiple sectors, discusses validating cell phone numbers and how bad data can predict bad results.
Bad data can take lots of different forms. Sometimes it’s benign and easily fixable like when the name of a town is misspelled. It’s potentially much more harmful, however, when customers intentionally provide fake information to avoid being contacted. Like when “Mickey Mouse” lives at “123 Fake Street.”
Why should you care?
Companies worry about the validity of different types of data depending on their circumstances. Customers generally give accurate physical addresses to utility providers, for example, because they need something to be hooked up. But the phone numbers they provide are sometimes less accurate, and this is critical when utilities need to inform customers about problems with their electricity or water supplies.
In industries where companies don’t interact with a customer’s dwelling, however, things can become more complicated. Financial services companies, for example, need good data to adhere to “Know Your Customer” laws, as they face liability if they work with anyone prohibited from having an account. While they have become very adept at verifying new customers, they still sometimes have issues with legacy data regarding long-time customers, which can be at odds with compliance.
Geocoding can help identify bad data
The easiest way to tell when an address is fake, is when it doesn’t resolve to a geocode. While “123 Main Street,” for example, exists in a lot of places, it will fail if the zip code isn’t accurate. Sometimes, it might just be that the customer lives in a new neighborhood that hasn’t yet been added to the full geocode resolution. But sometimes the wrong address is provided on purpose.
Geocoding cell phones
Outside of addresses, cell phone numbers are the most valuable piece of information that a utility has about its customers. One reason is that people are up to 8x more likely to respond to a text message than to an email. Another is that people tend to hold onto their numbers when they move from place to place. If they leave an unpaid bill behind, therefore, the utility still has a way to connect with them. It also has a unique identifier to track them over time.
“It’s a very valuable piece of information that companies should be working hard to validate,” says Alison Alvarez, BlastPoint’s CEO. “ They should also be focused on ways to ensure people are incentivized to provide that piece of data.”
BlastPoint can assess the validity of your data
BlastPoint often does upfront data quality assessments for our clients, to determine how reliable it is. Duplicate email addresses, phone numbers, or similar things are red flags. One client, for example, employed a social worker who would complete the paperwork for customers when they needed help but provide his own email address. There were over 100 people, therefore, who had the same email address, and the system initially recognized each of them as being valid before BlastPoint’s software discovered the problem.
“You can assess the quality of your data by where it fails,” says Alvarez, “and we know if it fails with emails, phone numbers, street addresses, or something else.”
“Garbage in, garbage out,” Alvarez continues. “If our clients request it, we also provide them with a report on their data validity, so they can understand exactly what is going on as well.”
The cost of bad data
When a customer’s records aren’t solid, this often means that person is in a bad place and could potentially signal a pending write off or a high debt balance.
“BlastPoint’s software can link bad data to particular negative outcomes,” says Alvarez. “So we know the cost of bad data and the ROI of fixing it. This is unique for every footprint and regulatory obligation, and we can evaluate the web of costs that come with each particular outcome.”
Besides being more likely to result in write offs, customers with bad data also often have higher debt rates. This means that a company will lose the time value of money even if the debt is eventually paid off and face increased cash flow uncertainties.
Bad data isn’t just a clerical annoyance. It’s a potential red flag for deeper issues that impact everything from the effectiveness of customer engagement to a company’s bottom line. Validating customer data is, therefore, a critical first step in operationalizing that data.