Tip Sheets

Data Hygiene Checklist

Issue link: https://read.uberflip.com/i/1175480

Contents of this Issue


Page 0 of 2

WARNING: The impact of bad data F R O M M E A N TO C L E A N I N 8 ST E P S Remember the movie Gremlins ? If you're under the age of 35, it's probably before your time. But it's a cautionary tale that marketers of every age should know, because the story of how those furry balls of cuteness turning to scary, fanged mischief-makers is the story of how good marketing data goes very, very bad. While your database may seem like a tame and well-behaved beast on the surface, you need to pay attention and follow the rules to avoid losing control and ending up with a monster on your hands. CHECKLIST SHARE NOW: Bad data is bad for business Unlike Gremlins, which enjoyed their heyday in the 1980s, the impact of bad data continues to grow with each passing year. Experian's 2015 data quality benchmarking report (gated content) highlights the importance of the issue and the prevalence of bad data everywhere. According to the report, 99 percent of organizations believe data is essential for marketing success, yet few organizations feel confident about data quality. In fact, the vast majority of US respondents (92 percent) suspect their customer and prospect data might be inaccurate in some way. And it's not just a bad email here and a misspelled name there: it's a big issue. In 2014, US organizations suspected that approximately one quarter of their data (25 percent) was inaccurate, and in the span of just one year, that number rose to nearly one third (32 percent). Those data issues directly impact revenues. More than four out of five organizations believe inaccurate and incomplete customer or prospect data results in wasted resources, reduced productivity and wasted marketing and communications spend. SHARE THIS! 99% say data is essential to marketing success 92% suspect their data is inaccurate 83% say inaccurate data impacts revenue

Articles in this issue

Links on this page

view archives of Tip Sheets - Data Hygiene Checklist