If you are a marketing, order fulfillment or data manager, there are some things you don’t want to be greeted with when you come to work in the morning – and a surprising number of them revolve around issues with your contact data. For example:
- You’ve sent someone’s sensitive personal information to a similar but incorrect address that was fat-fingered during data entry, and it’s become a news story.
- 20% of your marketing budget was spent on direct mail pieces to people with names like “Mickey Mouse” and “SpongeBob SquarePants” who faked out your lead magnets to get free bonuses.
- You shipped several high-ticket items to a fraudster using fake contact information.
- You are facing a court order for violations of the Telephone Consumer Protection Act (TCPA), for unsolicited telemarketing to wireless phones that once belonged to your contacts but have now changed hands.
According to Gartner, the cost of bad data to US businesses is roughly $15 billion per year as of 2018, and UK site MyCustomer notes that bad customer data alone costs UK businesses 5.9% of annual revenue. But those are just aggregate numbers that often don’t mean anything to the average business. Here, let’s look at some of the real ground-level consequences of bad contact data.
According to this source, the average company spends $180,000 per year simply on direct mail that is misdelivered due to inaccurate data. Your cost per converted lead is directly impacted by the quality of your data, in a chain that runs through areas such as direct mail costs, list maintenance, human intervention, and the yield and ROI of your campaigns.
Misdelivered packages. Service failures. Customer service issues. Problems like these are what, down in the trenches, create negative brand reputations that no amount of advertising or marketing can overcome – particularly in an era of social media, where your failings are always on display. Conversely, when people can count on you for quality in all of their interactions with you, it builds consumer trust and a good word-of-mouth reputation.
This is one area where the cost of bad contact data becomes very real and tangible, as newer data privacy regulations have introduced serious penalties for compliance violations. For example, the European Union’s GDPR regulation includes potential fines of up to 4% of annual revenue, while the TCPA regulation mentioned above includes penalties of up to $1500 per individual violation, resulting in numerous multi-million dollar judgments against consumer firms nationwide. As a result, compliance issues alone have become a major reason for an increasing focus on data quality.
Pay now or pay later
One way to look at the impact of data quality on your business is what we call the “1-10-100” rule:
- Catching bad data at the time of data entry may cost one cent per entry
- Correcting bad data at the time of use may cost ten cents
- Managing the consequences of using bad data may cost a dollar – or more
Scaling this to an organizational level, a proactive approach to data hygiene is far and away the most cost-effective way to avoid the negative financial and reputational consequences of bad contact data.
This means having processes that encompass all of your contact data touch points, including marketing, shipping, customer service and more. In particular, it means ensuring clean contact data at both the time of data entry and the time of deployment, since data decays at a substantial rate every year.
Today this also means automating the process of contact data quality, by integrating tools such as address validation, email validation, lead and order validation directly into your marketing automation or CRM environment.
Want to learn more? Visit our solutions pages online, or download our free white paper Hitting the Data Trifecta: Three Secrets of Achieving Data Quality Excellence.