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Customer-focused analytics represent a key area of interest and investment for many organizations. One recent survey of US CFOs by Deloitte found that nearly 60% planned to invest in customer analytics and more than 38% planned to invest in marketing analytics in the next three years. But even as these organizations double down on their analytics investment, many executives are also raising questions about the reliability of the processes used to gather such information. This is in addition to growing concerns about how best to maintain the privacy of their customers while doing so.
According to a July 2016 report by KPMG, which looked at how marketers could “build more trust” into their analytics and data-gathering processes, one problem with current analytics methods is executives aren’t always confident in the results. When asked about the most trusted stage of their analytics-gathering process, 38% said it was the very first step, which was data sourcing. For every stage of the process after that, marketers said they had significant doubts. Only 21% of executives said they trusted their analysis or data modeling, while just 10% said they trusted how they were currently measuring the effectiveness of their analytics efforts.
Beyond simply finding the the most accurate way to gather and analyze marketing analytics data, many executives also express concern about their ability to use such data in an ethical way that respects customer privacy. This is emphasized by the wide ranging (and sometimes conflicting) methods marketers are using to safeguard customer data. When asked for KPMG’s study about various methods their organizations used to help ensure data analytics privacy and security, only two of 10 approaches listed were used by half or more of marketers.
As marketers are faced with an ever-growing range of data sources, and more insistent calls to act quickly on such information to make business decisions, finding ways to improve these gaps in current analytics efforts will be critical.
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