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Chapter Five Marketing Analytics: Welcome to the Era of Big Data Marketing: Real People, Real Choices, 8e Solomon, Marshall, and Stuart Copyright © 2016 Pearson Education, Inc. 5-1 Chapter Objectives • Explain how marketers increase long-term success and profits by practicing customer relationship management • Understand Big Data, data mining and how marketers can put these techniques to good use • Describe what marketing analytics include and how organizations can leverage both marketing analytics and predictive analytics to improve marketing performance • Identify how organizations can use marketing metrics to measure performance and achieve marketing control Copyright © 2016 Pearson Education, Inc. 5-2 Real People, Real Choices: Decision Time at Teradata Corporation • Which option should be pursued? – Option 1: Continue on current course and focus on short-term product launch in order to provide more time and resources for future re-launch – Option 2: Launch the product and brand in a “twoprong” release – Option 3: Delay the cloud product launch, accelerate efforts to rebrand Aprimo, then launch cloud product and new brand together Copyright © 2016 Pearson Education, Inc. 5-3 CRM: A Key Decision Tool for Marketers • Customer relationship management (CRM) involves systematic tracking of consumers preferences and behaviors over time in order to tailor individualized value propositions – Allows firms to get “up close and personal” – A process by which firms enact their customer orientation – Capture information at each customer touchpoint Copyright © 2016 Pearson Education, Inc. 5-4 CRM Facilitates One to One Marketing • One-to-one marketing includes several steps – Identify customers and get to know them in as much detail as possible – Differentiate among these customers in terms of both their needs and their value to the company – Interact with customers and find ways to improve cost efficiency and the effectiveness of the interaction – Customize some aspect of goods or services offered to each customer Copyright © 2016 Pearson Education, Inc. 5-5 Table 5.1: Four Steps of One-to-One Marketing Copyright © 2016 Pearson Education, Inc. 5-6 Examples of CRM in Action • USAA • Amazon.com • Disney’s MyMagic + Copyright © 2016 Pearson Education, Inc. 5-7 Figure 5.1: Characteristics of CRM Copyright © 2016 Pearson Education, Inc. 5-8 Share of Customer • Its easier and less expensive to keep a current customer than it is to acquire a new one. – Many firms look to increase share of customer, instead of share of market. • Share of customer is the percentage of a given customer’s purchases in a category over time – Enables company to grow sales and profits at a lower cost, relative to new customer acquisition Copyright © 2016 Pearson Education, Inc. 5-9 Customer Equity and Lifetime Value • Lifetime value of a customer is how much profit a firm will make on a customer • Customer equity is financial value of a customer relationship – Takes into account monetary investments to acquire and maintain relationship LVC Tool Copyright © 2016 Pearson Education, Inc. 5-10 Customer Prioritization • Not all customers are equal … at least, not in terms of profitability! • CRM systems enable marketers to identify priority customers and customize communications and special offers accordingly – For example, a firm may emphasize personal selling for contacting high-volume customers, while using direct mail or telemarketing to communicate to low-volume customers Copyright © 2016 Pearson Education, Inc. 5-11 CRM: Transforming Customers into Corporate Assets • CRM leverages database technologies to customize customer interactions based on: – Share of customer – Lifetime value – Customer equity – Customer prioritization Are their limitations, or even dangers, to viewing customers as financial assets? Copyright © 2016 Pearson Education, Inc. 5-12 Big Data: Terabytes Rule • Big data is a popular term to describe the exponential growth of structured and unstructured data – Internet data can be hard to analyze using traditional approaches – Internet of Things Copyright © 2016 Pearson Education, Inc. 5-13 Insights from Big Data • Big Data can provide competitive advantages in three main areas: – Identifying new opportunities – Transforming insights into better products – Delivering timely information more efficiently Copyright © 2016 Pearson Education, Inc. 5-14 Big Data Predicts Infectious Disease Copyright © 2016 Pearson Education, Inc. 5-15 Big Data Creation, Sources, and Usage • Millions of pieces of information that make up Big Data originate from two source categories: – Direct path – Indirect path Copyright © 2016 Pearson Education, Inc. 5-16 Figure 5.2: Sources of Big Data for Marketers Copyright © 2016 Pearson Education, Inc. 5-17 Social Media Sources • Web scraping • Sentiment analysis – Measuring brand attitude by assessing the context or emotion of online comments • Brand mapping Copyright © 2016 Pearson Education, Inc. 5-18 Nielsen Brand Association Map Copyright © 2016 Pearson Education, Inc. 519 Figure 5.3: Corporate IT Data Sources Copyright © 2016 Pearson Education, Inc. 5-20 Government and NGO Data • Increased types and amounts of governmentgenerated data are accessible to enterprising marketers. – U.S. Census – Index of Economic Freedom – Bureau of Transportation Statistics – Recalls.gov Copyright © 2016 Pearson Education, Inc. 5-21 Commercial Entities • Many companies today collect data in large quantities to sell to other organizations – Credit card purchase data – Supermarket scanner data • Data sold in aggregate form • May be a primary or secondary source of revenue for the firm Copyright © 2016 Pearson Education, Inc. 5-22 Partner Databases • Two-way information exchange between purchasing organization and suppliers • Provides benefits to buyers and sellers – Real-time demand signals – Replace inventory with information – Fewer stock-outs Copyright © 2016 Pearson Education, Inc. 5-23 Data Mining • The biggest data challenge for many firms is determining what to do with it all! • Data mining refers to process by which analysts sift through Big Data to identify unique patters of behavior – Data warehouses – Data brokers – Reality mining Copyright © 2016 Pearson Education, Inc. 5-24 Figure 5.4: Structured and Unstructured Data Examples Copyright © 2016 Pearson Education, Inc. 5-25 Unstructured Data • Data analysts have traditionally focused on structured data – More readily obtainable – Computers today can easily analyze a large number of data points. • Deriving meaning from unstructured data is more difficult, but potentially more valuable – New technologies are making this process easier Copyright © 2016 Pearson Education, Inc. 5-26 Ethical/Sustainable Decisions in the Real World • Data brokers are companies that collect and sell personal information about consumers, including: – Religion and ethnicity – User names – Income – Medication they take, and more … • Acxiom acknowledges it has on average 1,500 pieces of information on 200 million+ Americans Should it be legal for companies to collect and sell your personal information without your knowledge? Copyright © 2016 Pearson Education, Inc. 5-27 Data Scientists: Transforming Big Data into Winning Insights • Being able to transform data into insights is a challenging proposition! – Requires understanding of advanced analytics as well as way companies interact with consumers • Data scientists search through disparate data sources to discover hidden insights – Advanced degrees, often Ph.D.’s – Six-figure starting salaries Copyright © 2016 Pearson Education, Inc. 5-28 Figure 5.5: Uses of Data Mining Copyright © 2016 Pearson Education, Inc. 5-29 Big Data: Summary • Mining of Big Data can provide marketers with valuable new insights … • But also presents difficult new challenges! – Technological challenges – Analytic challenges – Ethical challenges Does knowing how companies seek to use personal information change your perspective of marketing? Copyright © 2016 Pearson Education, Inc. 5-30 Marketing Analytics • “Half the money I spend on advertising is wasted – I just don’t know which half.” – John Wannamaker, 19th century Philadelphia Retailer • Marketing analytics comprises technologies and processes that enable marketers to collect, measure, analyze, and assess marketing effectiveness Copyright © 2016 Pearson Education, Inc. 5-31 Connecting Digital Channels to Marketing Analytics • Marketers have long faced challenges in determining campaign and channel effectiveness • Digital marketing has become an increasingly important element of the marketer’s toolbox – More and more people spending increasing time online – Much easier to track consumer behavior in response to digital marketing actions Copyright © 2016 Pearson Education, Inc. 5-32 Figure 5.6: Major Digital Marketing Channels Copyright © 2016 Pearson Education, Inc. 5-33 Comparing Value of Digital Marketing Investments • Cost-per-click – Advertiser is charged only when user clicks on ad – More expensive, requires greater interaction • Cost-per-impression – Advertiser is charged each time ad shows up on user page – Less expensive, but not as easy to measure Copyright © 2016 Pearson Education, Inc. 5-34 Predictive Analytics • Up to now, discussion of marketing analytics has focused on validating prior investments – Focus on understanding current performance • Predictive analytics use large quantities of data to more accurately predict future outcomes Copyright © 2016 Pearson Education, Inc. 5-35 Marketing Metrics and Predictive Analytics • Marketing metrics enable firms to assess performance of current initiatives. • Predictive analytics is a “crystal ball” through which marketers can predict the success of future initiatives. What factors might a bank card issuer use to help predict student customers’ spring break location choices? Copyright © 2016 Pearson Education, Inc. 5-36 Metrics for Marketing Control • Marketing control means the ability to identify deviations in expected performance – both positive and negative – as soon as they occur – Enable marketers to adjust their actions before greater losses or inefficiencies are accumulated Copyright © 2016 Pearson Education, Inc. 5-37 Key Marketing Metrics • Click-through rate (Click-throughs /Impressions) X 100 • Conversion rate # of goal achievements/# of website visitors • Cost per order Advertising costs/Orders Copyright © 2016 Pearson Education, Inc. 5-38 Real People, Real Choices: Decision Made at Teradata • Lisa chose option 2 – Implementation: Lisa’s team launched the cloud product at a major industry trade show, even as they applied data from their research to the creative development of the Teradata brand. – Measuring Success: The market took notice . One major analyst firm welcomed the new approach so much that it renamed the annual category research report “Integrated Marketing Management.” Copyright © 2016 Pearson Education, Inc. 5-39 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America Copyright © 2016 Pearson Education, Inc. 5-40