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Customer Outcome Analytics Director
Pearson
Chandler, AZ, United States
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Description
At Pearson, we’re committed to a world that’s always learning and to our talented team who makes it all possible. From bringing lectures vividly to life to turning textbooks into laptop lessons, we are always re-examining the way people learn best, whether it’s one child in our own backyard or an education community across the globe. We are bold thinkers and standout innovators who motivate each other to explore new frontiers in an environment that supports and inspires us to always be better. By pushing the boundaries of technology — and each other to surpass these boundaries — we create seeds of learning that become the catalyst for the world’s innovations, personal and global, large and small.
Customer Outcome Analytics Director
• Outcome Focus Insight (OFI) -- The position will develop/implement the OFI program by designing surveys, collecting data, and providing insightful analyses to the appropriate stakeholders. As part of the OFI team, this position will be deeply involved in managing the collection of CES, CSAT, NPS and other related metrics, and refining it on an ongoing basis. Preferably, this individual should have previously been involved in a VoC program. The ideal candidate would be proficient in collecting and analyzing information to tell a compelling story from the customer’s viewpoint.
This individual should be an effective questionnaire designer and have a strong background in market research to be able to make sound decisions about when, where, and how often we gather feedback from our customers – all within the context of a VoC program.
Responsibilities
•Create and maintain research roadmap.
•Design and program questionnaires for multiple consumer touchpoints.
•Collaborate with stakeholders to gather requests and requirements and then make informed decisions about what should be included in surveys.
•Responsible for maintenance and insights from our VoC tool.
•Provide subject matter expertise on the NPS, CES and other CSAT metrics.
•Lead the data gathering and analysis of information.
•Identify key issues or drivers in the data to tell a comprehensive story as it relates to broader initiatives.
•Create and manage key dashboards – tracking and explaining CES, CSAT, NPS and customer experience ratings scores, customer feedback/sentiments, key drivers and other relevant KPIs.
•Perform correlation analysis (e.g. factor analysis, text / data mining, decision trees, discriminate analysis, logistic regression, clustering, etc.) as necessary.
•Familiarity with statistical modeling would be a plus.
•Provide research and analytical support to the Consumer Insights team on similar projects.
•Build and maintain customer journey maps based on customer segmentation and vision to value acceleration approaches.
Qualifications and Experience:
•Bachelor's Degree in Business, Marketing, Market Research or relevant background
•At least 5 years in a corporate market research or VoC role preferably in a B2B industry or subscription based business.
•Alternatively, at least 5 years in a customer experience or loyalty marketing agency or consulting role.
•Understanding of quantitative and qualitative market research techniques, and ability to determine optimal research approach to meet given objectives.
•Experience in measuring/tracking Net Promoter® methodology, customer effort and customer satisfaction, including managing the CES, CSAT and NPS surveys, optimizing response rates, reporting, and analyzing survey results.
•Advanced in PowerPoint, Excel, and Word and experience with data reporting/analysis, data visualization and text analytics tools.
•Strong analytical background with proven track record for structuring/solving problems, drawing conclusions and formulating recommendations.
•Ability to plan, organize and prioritize multiple simultaneous assignments real-time, as well as manage to time constraints.
•4+ years leading a virtual team
•General knowledge of a variety of statistical techniques is preferred but not required (e.g. clustering, factor analysis, logistic regression, decision trees, discriminate analysis, etc).