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Dissecting data quality by understanding disparate sources

A great deal of the challenges that companies deal with as they delve into analytics concern data quality. As businesses work to better understand their client bases and make smarter decisions about marketing and sales, they need to know how reliable their information is. The last thing they want to do is shift their future tactics based on consumer insight that's riddled with errors.

In assessing the quality of their data, one of the key questions that companies need to ask is - where is our data coming from? More specifically - are people supplying information to their favorite brands directly, or alternatively, are businesses digging up information in other, more surreptitious ways?

According to Smart Data Collective, there are different types of data to consider. There's first-party, and there's other information that's coming through more indirect channels. Tracey Wallace, content marketing manager at Umbel, drew this key distinction.

Going straight to the source
The beauty of first-party data is that it comes directly from the original source. For example, if you run an e-commerce retail outlet and you engage with your customers using direct marketing emails, you can have one-on-one conversations that yield useful tidbits of information about real-life shoppers. There's no more reliable way to learn than that.

"For most companies, first-party data is an understood investment," Wallace explained. "It leverages the customer relationship to create a two-way line where the customer can offer up preferences via an on-site survey or simply through their on-site behaviors, and the company can respond through A/B testing, email campaigns and more."

If you have first-party data and you're not putting it to good use, you're pretty much leaving money on the table. There's valuable insight there, just waiting to be tapped into.

Examining other angles
Of course, if you don't have the benefit of productive firsthand interactions, you may have to rely on second- or third-hand data for improving your analytics efforts - in other words, data that comes via back channels or is bought from unreliable sources. According to Wallace, this is where data quality issues creep into the picture.

"Much of the concern in the big data industry regarding the origins of data is specifically talking about third-party data," she said.

Companies around the world are working hard to better understand the issue of data quality as it pertains to them. One of the most important questions for them to ask is - what's the source?

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