Companies today collect more data on customers and audiences than ever before. Not only focusing on what they buy, but also what they want. And, most importantly — why.
Just be sure to keep one thing in mind: not all data is created equal.
A recent survey by Gartner suggests that, on average, bad data costs organizations $13 million a year.1
So how do you tell good data from bad?
What is good data?
It’s simple, really. Good data is any data that helps you make better decisions. That calls for a strong underlying strategy. You need to set clear goals from the outset to make sure you’re collecting the right data, the right way.
Just as important, good data is actionable. It can help you identify emerging trends, tailor messages, better target customers and take advantage of opportunities.
In other words, good data is smart business.
What is bad data?
Data can fall short in more ways than one. When it’s incomplete, for starters. You can’t rewind the clock on data collection. So anything that isn’t intentionally tracked during a marketing campaign — such as conversions or sales — is essentially lost. What if you’re taking too narrow of an approach to data collection? Good data should give you a broad view of your customers, your business and your competition.
Inaccuracy is another common issue with data quality. It’s easy to understand why you want to capture, say, accurate revenue numbers. Yet inaccuracy can also apply to misunderstanding your customers or the market. How well do you know your target audiences? Are you interviewing the right market segments?
Or, data can be irrelevant. Maybe it’s outdated, making it harder for you to keep up with market trends. Or maybe you aren’t using data you’ve collected.