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Framework to Quantify Customer Experience
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</div> <div class="card publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">Framework to Quantify Customer Experience</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anant%20Sharma">Anant Sharma</a>, <a href="https://publications.waset.org/abstracts/search?q=Ashwin%20Rajan"> Ashwin Rajan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Customer experience is measured today based on defining a set of metrics and KPIs, setting up thresholds and defining triggers across those thresholds. While this is an effective way of measuring against a Key Performance Indicator ( referred to as KPI in the rest of the paper ), this approach cannot capture the various nuances that make up the overall customer experience. Customers consume a product or service at various levels, which is not reflected in metrics like Customer Satisfaction or Net Promoter Score, but also across other measurements like recurring revenue, frequency of service usage, e-learning and depth of usage. Here we explore an alternative method of measuring customer experience by flipping the traditional views. Rather than rolling customers up to a metric, we roll up metrics to hierarchies and then measure customer experience. This method allows any team to quantify customer experience across multiple touchpoints in a customer鈥檚 journey. We make use of various data sources which contain information for metrics like CXSAT, NPS, Renewals, and depths of service usage collected across a customer lifecycle. This data can be mined systematically to get linkages between different data points like geographies, business groups, products and time. Additional views can be generated by blending synthetic contexts into the data to show trends and top/bottom types of reports. We have created a framework that allows us to measure customer experience using the above logic. <iframe src="https://publications.waset.org/abstracts/152386.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analytics" title="analytics">analytics</a>, <a href="https://publications.waset.org/abstracts/search?q=customers%20experience" title=" customers experience"> customers experience</a>, <a href="https://publications.waset.org/abstracts/search?q=BI" title=" BI"> BI</a>, <a href="https://publications.waset.org/abstracts/search?q=business%20operations" title=" business operations"> business operations</a>, <a href="https://publications.waset.org/abstracts/search?q=KPIs" title=" KPIs"> KPIs</a>, <a href="https://publications.waset.org/abstracts/search?q=metrics" title=" metrics"> metrics</a> </p> <a 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