Big Data – It’s Quality Not Quantity that Counts


“Big Data” as we know it has become the most used buzzword in digital marketing. There’s no doubt in the volume and accessibility of data which have both dramatically increased. However, instead of simplifying the marketing decision making process, the data can actually complicate it by forcing marketer to dig through piles of information.

In a recent study by the web data monitoring company Cannote, 44% of advertisers said that there was “too much information to effectively measure for business.” So how are marketers suppose to find quality data available?

Well, here are a few tips for marketers to obtain value from collecting data working towards actionable insights for future campaigns.

Create a Clear Cut Data Strategy

Marketers need to determine what they would want to achieve by collecting and analyzing data. Would they want to learn more about the customers buying habits? Do they want venture into new customer segments? Or are they working towards generating sales? Each of these goals will influence how the data is collected, organized and used. So, by having a data strategy marketer’s can then determine a clearer understanding of what they’re going to do with the data and if it’s actually valuable to them.

Focus on Data that’s “Smart” Rather Than “Big”

Although the long term goal for many marketers should be based on creating leverage using Big Data, the initial strategy should be based on collecting that is considered to be “smart” data instead of going for “big” data sets. Sure having all of the data resources available for leverage would be great, but it’s simply not a realistic approach for many brands.

Finding a Good Technology Partner

Although there’s a plethora of data that might be scary, the good news is that we now have the sophisticated technology that can help digital marketer’s manage and collect “smart” data. Audience or data management platforms (AMP/DMP) can actually work well with a marketer’s sorting quality, proprietary data, actionable insights and massive volumes of data that is available. Again the focus here is made on data quality, not quantity and overtime modeling based on third party overlays can be better used when analyzing such massive volumes of data.

Combining these approaches with the latest audience and data management techniques will enhance the performance of the marketing process. In fact, small investments in the quality of audience and data management can actually deliver greater value to marketers instead of analyzing massive volumes of unusable data.

And as the old saying goes, at times less may actually turn out to be more.

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