Marketing Analytics: Big Data Era PDF

Summary

This document is a lesson on marketing analytics and the use of big data. It details different elements of marketing and customer relationship management (CRM)

Full Transcript

Marketing Analytics: Welcome to the Era of Big Data Marketing: Real People, Real Choices, 8e Solomon, Marshall, and Stuart 5-1 Chapter Objectives Explain how marketers increase long-term success and profits by practicing...

Marketing Analytics: Welcome to the Era of Big Data Marketing: Real People, Real Choices, 8e Solomon, Marshall, and Stuart 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 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 “two- prong” release – Option 3: Delay the cloud product launch, accelerate efforts to rebrand Aprimo, then launch cloud product and new brand together 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 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 5-5 Table 5.1: Four Steps of One-to-One Marketing 5-6 Examples of CRM in Action USAA Amazon.com Disney’s MyMagic + 5-7 Figure 5.1: Characteristics of CRM 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 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 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 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? 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 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 5-14 Big Data Predicts Infectious Disease 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 5-16 Figure 5.2: Sources of Big Data for Marketers 5-17 Social Media Sources Web scraping Sentiment analysis – Measuring brand attitude by assessing the context or emotion of online comments Brand mapping 5-18 Nielsen Brand Association Map 519 Figure 5.3: Corporate IT Data Sources 5-20 Government and NGO Data Increased types and amounts of government- generated data are accessible to enterprising marketers. – U.S. Census – Index of Economic Freedom – Bureau of Transportation Statistics – Recalls.gov 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 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 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 5-24 Figure 5.4: Structured and Unstructured Data Examples 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 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? 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 5-28 Figure 5.5: Uses of Data Mining 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? 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 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 5-32 Figure 5.6: Major Digital Marketing Channels 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 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 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? 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 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 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.” 5-39

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