Refining data is tough. Here’s how to make it easier

Data RefineryWe’ve heard a lot of late about how data is the new oil. That’s largely because it is not only valuable, but the lifeblood of the economy. There’s another reason why the analogy is apt: like oil, data is often difficult to extract and expensive to refine.

Many companies are finding this out the hard way.

According to recent research we conducted, most marketers are caught in a conundrum. They realize that culling and synthesizing data is integral to taking a 360-degree single customer view. However, they also know that they’re over their heads when it comes to making sense of such data.

In our recent poll of 200 US and UK marketing professionals, some 82% said that they didn’t have the knowledge or resources to bring together a truly comprehensive view of the customer.

This schism between ideal and reality has prompted many marketers to give up on the single customer view, chalking it up as yet another marketing concept that’s great in theory but not applicable in the real world.

Digging deeper, we found that marketing departments often shy away from what they see as complex data analysis tasks.

Marketers said they spend up to 80% of their time analyzing and interpreting data, representing a huge opportunity cost. Though 99.5% of marketers said they are now attempting to parse consumer data, 1 in 5 say they don’t have the right tools to fully undertake this task.

About a third of marketers also spend more than half their time analyzing data. (One in 10 spend more than 80% of their time doing this.) Some 27% of marketers pass the data to the IT department, which creates a bottleneck and prevents the timely execution of marketing campaigns.

We aren’t the only ones to see this gap. Recent analysis found that marketers thought that overall their data rated 3 out of 5 on the quality scale, meaning it was “questionable.” In the study, 41% of marketers cited “inconsistent data across technologies” as their biggest obstacle to marketing ROI.

Of course, marketers are right that data is important. But they are wrong to assume that refining and extracting data should be a time- and resource-hogging activity. At this point, most marketers have realized that they can’t do it all and need solutions to handle the grunt work. By using tools to handle data analysis, marketers take an onerous task off the table, get access to better data and are free to pursue more creative applications of their craft.   

Platforms that combine powerful analytics, integrated campaign management, modeling, reporting and email communications can help marketers to rid themselves of a task that had been tying up time and resources.

The CMO’s job has grown infinitely more complex over the past few years as marketing came to encompass SEO, advertising, PR and graphic design. Technology is so pervasive that many marketers are expected to at least have some basic coding skills.

Unfortunately, as we’ve seen, data analysis and managing that data is harder than most marketers thought it would be. Marketers are either spending massive amounts of time just analyzing data or relying heavily on IT, outsourced agencies and data analysis firms.  Rather than shy away from complex data analysis tasks, marketers need to tackle their fear and understand that learning the right software and data analytics programs, in reality, is actually no harder than learning an email marketing tool or CRM platform.

The time has come when marketers need to take on a more agile approach. Using software solutions, such as a Customer Data Platform,  to automate data analysis is one way that marketers can keep their heads above water in this dynamic environment. For those that are currently drowning in data, it’s an option seriously worth considering.


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LIVE NEXT at: 11am EDT / 3pm GMT on November 2, 2017
 

Find out how to make better use of your data. Register to watch how to combine customer analytics and real-time, omnichannel customer journey tools to create personalized and contextual customer experiences in this BlueVenn Customer Data Platform software demonstration. In the session we’ll define how to:

  • Use predictive analytics to make real-time decisions that positively affect the customer journey
  • Improve targeting of campaigns using customer segmentation and RFV analysis
  • Use real-time personalization to better engage customers
  • Integrate online and offline channels into the BlueVenn Customer Data Platform to create a true Single Customer View 

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