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Marketing Analytics for Data-Rich Environments

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Industry practice has demonstrated that big data opportunities are enormous, but there is a need to (a) reconcile academic ‘big stats on small data’ with practitioner ‘small stats on big data’ and (b) combine deep learning methods with statistical modeling and theory-based models to establish causal effects. Privacy and security concerns will limit collection/retention of data. So there is a need to focus on the development of analytics for anonymized and minimized data and proactive development of methods for protection of customer privacy. ​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​

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Marketing Analytics for Data-Rich Environments

  1. 1. From: © M.Wedel & PK Kannan A Critical Examination of Marketing Analytics for Data- Rich Environments How the “big data” era started and its role in firms in the future. Michel Wedel & PK Kannan (2016)
  2. 2. From: © M.Wedel & PK Kannan© M.Wedel & PK Kannan The Era of Big Data  Data is assuming an ever more central role in organizations - Build and maintain customer relationships - Personalize products, services and the marketing mix - Automate marketing processes in real time  Big data may have been over hyped, but now: - Spawns data-driven decision culture in companies - Provides them with competitive advantages - Significantly impacts their financial performance  Has caused new forms of marketing to emerge - Recommendations, geo-fencing, search marketing, retargeting  Urgent demand for analytics capabilities - Not always clear which types of analytics work for which new problems and new data Michel Wedel & PK Kannan (2016)
  3. 3. From: © M.Wedel & PK Kannan© M.Wedel & PK Kannan 1900 202519501925 20001975 Social Location Search VideoClick-stream POS Scanning Scanner PanelTransaction Diary Panels Eye TrackingSurvey ANOVA, Regression Bayesian Decision Market Share Models MDS Conjoint MNL Latent Class HB Structural ORModels Data Big Data Analytics: A History of Data and Models 8 Digital data Rich Data Michel Wedel & PK Kannan (2016)
  4. 4. From: © M.Wedel & PK Kannan From: © M.Wedel & PK Kannan Segmen tation Trend Analytics Personalization Web Analytics Marketing Mix Recommendations Keyword Search Analytics Re Targeting Social Analytics Structured Internal Unstructured External Competitive Intelligence Path to Purchase Behavioral Profiling & Targeting Sentiment Analytics Attribution Analytics GPS & Mobile Analytics Online Review Analytics CRM Analytics Retail Analytics A/B Testing Diagnostic Breadth Advertising Analytics Evolution of Data-Rich Marketing Applications Michel Wedel and PK Kannan (2016)
  5. 5. From: © M.Wedel & PK Kannan© M.Wedel & PK Kannan Issues Impacting Data Rich Environments in the Near Future  Privacy and security concerns will limit collection/retention of data - Focus on the development of analytics for anonymized and minimized data - Proactive development of methods for protection of customer privacy  For marketing analytics to have its full impact for big data - Firms need to have a culture that recognizes the importance of data, analytics, and data-driven decision making - Have a governance structure that prevents silos and facilitates integrating data analytics into overall strategy (Big Data CoE + multidisciplinary teams)  Marketing analytics involves disparate domains - The next generation of marketing analysts need to learn how to integrate these fields in order to have sufficiently broad and deep knowledge Michel Wedel & PK Kannan (2016)

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