Customer Analytics

Start Date: 08/16/2020

Course Type: Common Course

Course Link: https://www.coursera.org/learn/wharton-customer-analytics

About Course

Data about our browsing and buying patterns are everywhere. From credit card transactions and online shopping carts, to customer loyalty programs and user-generated ratings/reviews, there is a staggering amount of data that can be used to describe our past buying behaviors, predict future ones, and prescribe new ways to influence future purchasing decisions. In this course, four of Wharton’s top marketing professors will provide an overview of key areas of customer analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their application to real-world business practices including Amazon, Google, and Starbucks to name a few. This course provides an overview of the field of analytics so that you can make informed business decisions. It is an introduction to the theory of customer analytics, and is not intended to prepare learners to perform customer analytics. Course Learning Outcomes: After completing the course learners will be able to... Describe the major methods of customer data collection used by companies and understand how this data can inform business decisions Describe the main tools used to predict customer behavior and identify the appropriate uses for each tool Communicate key ideas about customer analytics and how the field informs business decisions Communicate the history of customer analytics and latest best practices at top firms

Course Syllabus

What is Customer Analytics? How is this course structured? What will I learn in this course? What will I learn in the Business Analytics Specialization? These short videos will give you an overview of this course and the specialization; the substantive lectures begin in Week 2.

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Course Introduction

Customer Analytics Capstone Project In this Customer Analytics capstone project course, you’ll combine the skills you’ve learned about customer analytics, you’ve set up your own analytics system, and you’ll use it to create some actionable data points for marketing strategy. You’ll also apply what you’ve learned about customer analytics to a real business challenge you create. You’ll use what you’ve learned about customer analytics to create some data points for marketing strategy, and you’ll also apply what you’ve learned about customer analytics to create some data points for marketing strategy. You’ll also apply what you’ve learned about customer analytics to create some data points for marketing strategy. You’ll also apply what you’ve learned about customer analytics to create some data points for marketing strategy. You’ll also apply what you’ve learned about customer analytics to create some data points for marketing strategy. You’ll also apply what you’ve learned about customer analytics to create some data points for marketing strategy. You’ll also apply what you’ve learned about customer analytics to create some data points for marketing strategy. You’ll also apply what you’ve learned about customer analytics to create some data points for marketing strategy. You’ll also apply what you’ve learned about customer analytics to create some data

Course Tag

Predictive Analytics Customer Analytics Regression Analysis Marketing Performance Measurement And Management

Related Wiki Topic

Article Example
Customer analytics Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. Marketing provides services in order to satisfy customers. With that in mind, the productive system is considered from its beginning at the production level, to the end of the cycle at the consumer. Customer analytics plays an important role in the prediction of customer behavior.
Customer analytics Forecasting buying habits and lifestyle preferences is a process of data mining and analysis. This information consists of many aspects like credit card purchases, magazine subscriptions, loyalty card membership, surveys, and voter registration. Using these categories, consumer profiles can be created for any organization’s most profitable customers. When many of these potential customers are aggregated in a single area it indicates a fertile location for the business to situate. Using a drive time analysis, it is also possible to predict how far a given customer will drive to a particular location. Combining these sources of information, a dollar value can be placed on each household within a trade area detailing the likelihood that household will be worth to a company. Through customer analytics, companies can make decisions based on facts and objective data.
Customer analytics There are two types of categories of data mining. Predictive models use previous customer interactions to predict future events while segmentation techniques are used to place customers with similar behaviors and attributes into distinct groups. This grouping can help marketers to optimize their campaign management and targeting processes.
Concentrix Includes Voice of the Customer Analytics (VOCA) for unstructured content analysis, performance scorecards, call centre analytics, call volume forecasting, operational analytics, agent optimization; IVR analytics; web analytics customer life time value, revenue enhancement, and other analytics capabilities..
Analytics Analysis techniques frequently used in marketing include marketing mix modeling, pricing and promotion analyses, sales force optimization and customer analytics e.g.: segmentation. Web analytics and optimization of web sites and online campaigns now frequently work hand in hand with the more traditional marketing analysis techniques. A focus on digital media has slightly changed the vocabulary so that "marketing mix modeling" is commonly referred to as "attribution modeling" in the digital or marketing mix modeling context.
Kissmetrics Kissmetrics is a customer analytics platform based out of San Francisco, California that was founded by Neil Patel and Hiten Shah.
Tealeaf Tealeaf is now a key component of IBM's customer analytics portfolio which also includes heritage Coremetrics web analytics technologies. In late 2014 IBM introduced a SaaS-based version of Tealeaf as a complement to its on premise deployment model. In June 2016 IBM optionally integrated the SaaS-based version of Tealeaf into its IBM Customer Experience Analytics offering, combining it with web analytics and multi-channel journey analytics.
Symphony EYC Symphony EYC is a customer analytics, retail and distribution improvement company. Symphony EYC was created in December 2012 with the merger of Aldata and EYC under existing parent company Symphony Technology Group, founded by Romesh Wadhwani. Symphony EYC's customer engagement analytics service complements the retail and distribution optimization capabilities of Symphony GOLD.
INETCO Systems Limited INETCO Systems Limited is a software company based in Vancouver, British Columbia, Canada. It develops business transaction monitoring, customer analytics and data forwarding technology for the banking, payment processing and retail industries.
INETCO Systems Limited In 2015, INETCO won "Best Data Solution" at the Fintech Innovation Awards for the INETCO Insight solution. In January 2015 the Company also launched the INETCO Analytics self-serve customer analytics solution for Card Operations, Fraud Management, ATM, POS, Digital Banking, Branch and Omnichannel Banking environments. In April 2015, INETCO was chosen to present INETCO Analytics at FinovateSpring 2015.
Canopy Labs Canopy Labs is a customer analytics company headquartered in Toronto, Ontario, Canada with offices in San Francisco. It was founded in 2012 and offers SaaS marketing analytics for businesses and organizations. The company is an alumnus of the Y Combinator accelerator program.
Peter Fader Peter Fader is the Frances and Pei-Yuan Chia Professor of Marketing at the Wharton School of the University of Pennsylvania. He is also the academic Co-Director of the Wharton Customer Analytics Initiative, an academic research center focused on the development and application of customer analytic methods.
Fractal Analytics Fractal Analytics is based on Artificial Intelligence and Machine Learning techniques. Their products include Customer Genomics; Trial Run, a cloud-based business platform; text mining suite: dCrypt; and Centralized Analytics Environment (CAE), a collaborative workbench built on the KNIME Server.
Indicus Analytics Indicus Analytics makes software based analytics products on various facets of Indian economy and Indian consumer. The customer segments served by Indicus are, among others: Insurance, Retail, Banking, Healthcare, Telecommunication, Advertising and Media, Durables, FMCG, Educational Institutions and Financial Services.
Mattersight Corporation Mattersight provides a software-as-a-service using predictive customer analytics, speech analytics, and behavioral analytics technologies to analyze and improve contact center performance and agent interactions. It uses a data analysis system that listens to the way customers respond on the telephone, analyzing communication patterns, grammar, word choice, tone, volume, pauses, and other communication metrics. Mathematical algorithms then interpret vocal features, compare them to their databases, and arrive at a personality profile for each customer, who is then matched with a service agent with whom the customer is most compatible.
Customer insight The above components only cover the scope of customer analysis or marketing analysis. Best practice is now expanding to including customer data management, behavioural analysis, predictive analytics, consumer research and database marketing.
Customer intelligence Customer satisfaction and market research surveys, often mined via text analytics, which can additionally be applied, for customer intelligence purposes, to contact center notes, e-mail, and other textual sources.
Human sensing Human sensing (also called human detection or human presence detection) encompasses a range of technologies for detecting the presence of a human body in an area of space, typically without the intentional participation of the detected person. Common applications include search and rescue, surveillance, and customer analytics (for example, people counters).
Eric Bradlow Eric Thomas Bradlow is K.P. Chao Professor, Professor of Marketing, Statistics, Education and Economics at the Wharton School of the University of Pennsylvania and faculty director of the Wharton Customer Analytics Initiative. He is known for his work on marketing research methods, missing data problems, and psychometrics. He is a fellow of the American Statistical Association and a fellow the American Education Research Association.
Speech analytics Speech analytics provides categorical analysis of recorded phone conversations between a company and its customers. It provides advanced functionality and valuable intelligence from customer calls. This information can be used to discover information relating to strategy, product, process, operational issues and contact center agent performance. In addition, speech analytics can automatically identify areas in which contact center agents may need additional training or coaching, and can automatically monitor the customer service provided on calls.