\r\n Applying data analytics to understand better what drives Customer Experience (CX) is a hot topic, but one that might appear to be a daunting undertaking\r\n across these four issues:\r\n<\/p>\r\n
\r\n Let\u2019s create a starter kit for CX data analytics to begin to address these and other critical issues in this month\u2019s column, and add details in next\r\n month\u2019s column.\r\n<\/p>\r\n\r\n
\r\n What was it that Maria said in The Sound of Music? \u201cLet’s start at the very beginning; A very good place to start.\u201d It\u2019s important to figure out first what\r\n are your gnarly issues, the ones that keep you up at night and the ones that your execs keep asking, for which you don’t have clear answers.\r\n<\/p>\r\n
\r\nHere are some of these vexing questions that my clients have been asking, covered as well in my two books The Best Service is No Service<\/em> 1<\/sup> <\/em>and Your Customer Rules!2<\/sup>:<\/em>\r\n<\/p>\r\n \r\n As I\u2019ve suggested alongside each of these three questions, the next step is to inventory your data sources that might shed light on figuring out answers,\r\n or at least to decide where to begin your quest. Nothing magical here, something you\u2019ve probably done many times in other areas. A handy checklist helps,\r\n something like this for VOC data sources, selected from the 26 different VOC data sources that we often inventory, such as focus group logs, post-purchase\r\n surveys, customer service agent notes, and Tweets.\r\n<\/p>\r\n\r\n \r\n But if the data are not collected today, yet appear to be useful, you need to start asking, \u201cWhere could we get what we need?\u201d\r\n<\/p>\r\n \r\n You’re getting close to being able to address the second issue so let\u2019s take a peek at it now.\r\n<\/p>\r\n\r\n \r\n \u201cBig Data\u201d is often used very broadly to mean \u201clots of data\u201d or \u201clots of complex stuff\u201d, but let\u2019s pause to see what Gartner says about it \u2026\r\n<\/p>\r\n \r\n Big data<\/strong><\/a>\r\n is high-volume, high-velocity and\/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable\r\n enhanced insight, decision making, and process automation.3<\/sup>\r\n<\/p>\r\n \r\n As well as what Harvard Business Review<\/em> tells us about using Big Data:\r\n<\/p>\r\n \r\n So do you need \u201cBig Data\u201d? Most likely the answer is going to be \u201cyes,\u201d in different degrees based on your inventory and your ability to answer the three\r\n vexing questions that I posed at the start of this column. If your response to any of them is \u201cNot sure\u201d or \u201cDon\u2019t have many clues\u201d, then you\u2019re going to\r\n need the breadth and depth of \u201cBig Data\u201d and its ability to \u201cmash up\u201d current and new data sources in order to \u201cenhance insight\u201d and \u201cdecision making\u201d.\r\n<\/p>\r\n \r\n We will dig more deeply next month into Big Data, data scientists, and how to track progress. Stay tuned!\r\n<\/p>\r\n 1. The Best Service is No Service: How to Liberate Your Customers From Customer Service, Keep Them Happy, and Control Costs \r\n Bill Price & David Jaffe <\/em>(Wiley 2008). Based partly on my years as Amazon\u2019s 1st<\/sup> Worldwide VP of Customer Service, but also on \u201cBest\r\n Service\u201d providers around the world who have made it easier for their customers to do business with them, we proposed 7 Drivers that start with \u201cChallenge\r\n demand for service\u201d:\r\n<\/p>\r\n 2. Your Customer Rules! Delivering the Me2B Experiences That Today\u2019s Customers Demand<\/em>, Bill Price & David Jaffe <\/em>(Wiley 2015). Based on original research into 12 recognized CX leaders there are the 7 Customer Needs that produce\r\n a winning \u201cMe2B” culture, with a total of 39 sub-needs:\r\n<\/p>\r\n 3. http:\/\/www.gartner.com\/it-glossary\/big-data\/<\/a>\r\n accessed 19 October 2016\r\n<\/p>\r\n\r\n
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\u201cDo I need \u201cBig Data\u201d and, if so, what the heck is it?\u201d <\/h2>\r\n\r\n\r\n
\r\n Because of big data, managers can measure, and hence know, radically more about their businesses, and directly translate that knowledge into improved\r\n decision making and performance.4<\/sup>\r\n<\/blockquote>\r\n
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