How much is bad data quality costing you?
Like many modern businesses, you probably rely heavily on your data. But unless your data is of the highest quality, it’s costing your business in many ways – some of which may not be immediately apparent.
Join me, and take a look at the cost of bad data quality, starting with the obvious…
Lost revenue
I’m betting that at some point you send emails. Whether you’re nurturing your potential and new customers, launching a new line, or simply sending a monthly newsletter, it has to get to the right recipient. Having even a small percentage of bad email addresses means you’re losing money.
If you’ve spent $1,500 dollars on an email campaign to 5,000 recipients and 5% of your emails can’t reach the right recipient, that’s 250 people that don’t get the chance to spend money with you and you’ve wasted $75 the minute you hit ‘send’.
I know $75 may not sound much but trust me, it gets much worse. Let’s say your average sale is $500 and your conversion rate is 10%. You’ve just lost 25 sales, for a total cost of $12,575.
And it’s not just email that’s affected.
Direct mail can fall victim to bad data with the same outcome, but it usually costs you even more money than with email. In a report published in 2015, the US Postal Service (USPS) estimated that in 2013 approximately 6.8 billion pieces of mail could not be delivered as addressed.
If your business is one of those that still sends out catalogues, you’re losing even more. If you spend $7,500 getting your catalogue designed, and another $3,500 getting 5,000 copies printed and mailed, you’ve spent $11,000. If 5% of those catalogues can’t be delivered that’s $550 wasted right off the bat. Assuming the same conversion rate and average sale, you’ve lost $13,050.
In other words, sending an email AND a catalog to 5,000 customers every month for a year is going to cost you $306,600!
DataMatch contains email list cleaner software which will suggest correct entries for incorrect email addresses, automating a highly manual process, checking syntax gTLDS (.com, .org, etc) and ccTLDS (.uk, .au,.ca, etc.)
There’s more than just a monetary cost. Bad data can badly damage your reputation.
Damaged reputation
One of the effects of bad data for companies that send out a lot of email is a low sender reputation. Contrary to common belief, this problem doesn’t just occur when your emails trigger spam alerts.
If an email address has a misspelling or other error, it can be marked as undeliverable and bounced back to you. And too many undeliverable emails can result in a bad sender reputation with your email provider. When that happens, it can lower – or even prevent – the deliverability of future emails, even when you use the correct email address and have followed opt-in best practices. Your emails start hitting the spam folder and even that, depending on the email software the recipient is using, can compound the issue.
The damage caused in this scenario by poor data quality on your reputation can remain for months or years affecting your email marketing campaigns.
Lost customers
If you’re fortunate enough to have a large and loyal customer base, it can take just one slip to lose someone.
All the time, effort and money spent on building out your sales funnel is wasted if you don’t have quality contact information, or other important details.
Imagine you’re nurturing a prospect along the way to a $50,000 contract. If they leave the company you lose contact with them, that contract is lost. But if your data is accurate and up to date you’re fine. You’ve already identified their replacement and it’s a much simpler task to switch to a new contact than to start from scratch.
Fines and lawsuits
Many organizations are in industries that are subject to regulations, such as FINRA and HIPAA. Under these regulations, you can be fined for even an accidental breach of regulations.
The Health Insurance Portability and Accountability Act of 1996 (or HIPAA, for short) strictly regulates what information you can and cannot share, and with whom. Under HIPAA, a single violation which is due to willful neglect and is not corrected (read: uncorrected bad quality data) can cost $50,000. And if there is more than one, those fines can add up to $1.5 million dollars.
Even if you’re not in an industry that is regulated, you can be fined for calling individuals who are on the National Do Not Call Registry. It’s not enough to rely on the individual making the call to check external databases. That information should be on the contact’s record where it can be seen easily when carrying out telemarketing campaigns to keep you safely within federal regulations.
The solution
Whichever way you look at it, bad quality data is costing your business money. But it doesn’t need to.
There are many solutions and companies that can help you improve the quality of your data, but they come with a cost. And it’s not just the purchase or subscription costs. Whichever solution you use, it’s going to take time. And time is money.
The quickest – and best – way to identify and correct bad quality data is DataMatch Enterprise.
DataMatch Enterprise includes multiple proprietary and standard algorithms for detecting phonetic, fuzzy, miskeyed, and abbreviated variations, resolving data quality issues. The suite consists of scalable configurations for deduplication & record linking, suppression, enhancement, extraction, and standardization of business and customer data.
The DataMatch Enterprise suite can be used to find and link customer data, consolidate data across multiple sources, and remove deceased and unwanted records – quickly and easily improving your marketing and mailing performance. Even better, with the DataMatch Enterprise suite, you can automate daily maintenance functions with our API.
DataMatch Enterprise is no slouch either. In independent tests, DataMatch Enterprise out-performed IBM and SAS when it comes to matching accuracy and speed. With the ability to support up to 100 million records, it’s big enough to handle the most rigorous demands of clients such as General Electric (GE), Hewlett Packard, Deloitte and the state of California.
