class: middle, title-slide # Marketing ## 5: Marketing Analysis ### Dennis A. V. Dittrich ### 2021 --- layout: true <div class="my-footer"> <span><img src="img/tcb-logo.png" height="40px"></span> </div> --- # CRM: A Key Decision Tool for Marketers .col-7[ **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 ] ??? Customer relationship management has been embraced by many successful firms. Customer relationship management, or CRM as it usually called in conversation, is defined on this slide. Marketers know that one way to more finely segment consumers is to allow them to personalize products. That’s the idea behind this ad, and one of the reasons why marketers value CRM. A systematic tracking of consumers’ preferences and behaviors over time in order to tailor the value proposition as closely as possible to each individual’s unique wants and needs CRM facilitates one-to-one marketing --- # CRM Facilitates One-to-One Marketing .col-7[ One-to-one marketing includes several steps 1. **Identify** customers and get to know them in as much detail as possible. 2. **Differentiate** among these customers in terms of both their needs and their value to the company. 3. **Interact** with customers and find ways to improve cost efficiency and the effectiveness of the interaction. 4. **Customize** some aspect of goods or services offered to each customer. ] ??? CRM facilitates one-to-one marketing, a process which is composed of four interrelated steps: Step 1: Identify customers and get to know them in as much detail as possible. Step 2: Differentiate customers by their needs and value to the company. Step 3: Interact with customers; find ways to improve cost efficiency and the effectiveness of the interaction. Step 4: Customize some aspect of the products you offer each customer. --- # Examples of CRM in Action .row[ .col-6[ USAA * No matter where on the globe you are, no matter what time of day or night, a USAA representative is able to pull up your profile. Amazon.com * Amazon tracks visits so that it can customize advertisements, product promotions, and discounts for each shopper. Disney’s MyMagic+ * Visitors can book events in advance, reserve times on rides, and review the park activities that they have experienced in the past ] .col-6[ ![](img05/solomon_rprc9e_fullppt_051.jpg) * Visiors can use the wearable Magic Band to make transactions while in the park. * Disney big advantage is the amount of data it can collect on visitors’ behavior and actions. ]] ??? DISCUSSION NOTES: To fully appreciate the value of a CRM strategy, consider the experience of USAA, which began as an insurance company catering to the military market and today is a leading global financial services powerhouse. Unlike State Farm, Allstate, and other traditional insurance providers, USAA does not provide field agents with an office; in fact, USAA’s employees conduct business almost entirely over the phone. But ask any USAA member how they feel about the service and you’ll get a glowing report. USAA’s success is built largely upon its state-of-the-art CRM system. No matter where on the globe you are, no matter what time of day or night, a USAA representative is able to pull up your profile. Its well trained staff expertly use CRM technology to strengthen their long-term customer relationships and, more importantly, get customers to move many or all of their business over to USAA, including banking, credit cards, money management, investments, and financial planning. Amazon.com is another company who has mastered the use of CRM to enhance customer relationships. For loyal users, Amazon tracks visits so that it can customize advertisements, product promotions, and discounts for each shopper. This helps keep customers engaged during each of their visits and helps ensure that they continue to come back for more. In 2014, Disney launched MyMagic+, a new system that allows Disney World visitors to more efficiently plan out their vacation experience and reduce the need to carry around tickets and other items previously necessary to tour the park. Visitors can book events in advance, reserve times on rides, and review the park activities that they have experienced in the past, to name a few of the main features. MyMagic+ is designed to be partnered with a wearable computer called the Disney Magic Band, which enables users to verify all of the actions they have taken through the MyMagic+ system without carrying around receipts or other forms of proof. In addition, they can use the wearable Magic Band to make transactions while in the park. The benefits and convenience for visitors is obvious, but for Disney another big advantage is the amount of data it can collect on visitors’ behavior and actions. These data better enable the firm to understand how to communicate with each customer and manage each relationship more effectively. --- .row[.col-8[ ![](img05/solomon_rprc9e_fullppt_052.png) ] .col-4[# Customer-Related Metrics]] ??? Firms that successfully make use of CRM have a different mind-set, different goals, different measures of success, and generally look at customers in a different way when compared to firms that don’t use CRM. Four critical characteristics of CRM are shown in Figure 5.1. * Share of customer: Because it is always easier and less expensive to keep an existing customer than to get a new one, CRM firms try to increase their share of customer, not share of market; this is the percentage of an individual customer’s purchase of a product over time that is the same brand. For this reason, CRM focuses on increasing a brand’s share of customer. * Lifetime value of the customer: Lifetime value is the potential profit a single customer’s purchase of a firm’s products generates over the customer’s lifetime. Estimating LVC requires that the firm first estimate future sales across all products for the next 20 or 30 years, and then that the firm attempt to figure out what profit the company could make from this customer in the future. * CRM firms view customers differently – as assets. Customer equity is defined as the financial (net) value of a customer throughout the lifetime of the relationship. * The final characteristic that makes CRM unique is the fact that organizations focus on high-value customers. This means the firm prioritizes its customers and customizes communications accordingly. --- # Share of Customer .col-7[ 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. ] ??? Because it is always easier and less expensive to keep an existing customer than to get a new one, CRM firms try to increase their share of customer, not share of market; this is the percentage of an individual customer’s purchase of a product over time that is the same brand. For example, if Amazon’s database records indicate that a given patron has purchased three books by a certain author, the CRM aspect of this system would try to increase share of customer by automatically sending an email to that individual offering him or her the opportunity to preorder a new book which has been written by the author, but not yet released. If the firm can get the consumer to buy additional books from favored authors, it has increased its share of customer. This is where CRM’s ability to customize and personalize marketing promotions to individual consumers can be helpful. --- # Customer Equity and Lifetime Value .row[ .col-7[ **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 ] .col-4[ ![](img05/solomon_rprc9e_fullppt_053.jpg)]] --- # Customer Prioritization .col-7[ 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. ] ??? Using a CRM approach, the organization prioritizes its customers and customizes its communications to them accordingly. For example, some bank customers generate a lot of revenue because they pay interest on loans or credit cards, while others simply use. The bank as a convenient place to store a small amount of money and take out a little bit each week to buy beer. Banks use CRM systems to generate a profile of each customer based on factors such as value, risk, attrition, and interest in buying new financial products. This automated approach helps marketers decide which current or potential customers it will target with certain communications or how much effort it will expend to retain an account—all the while cutting its costs by as much as a third. For example, customers who patronize casinos frequently will receive more direct mail offers from the casino, and higher value perks or incentives in an attempt to entice them to stay, compared to the that which would be sent to casual or infrequent gamblers. Remember that 80 /20 rule . . . in a CRM world, 80% of the profits often come from 20% of the customers. --- # CRM: Transforming Customers into Corporate Assets .row[.col-7[ CRM leverages database technologies to customize customer interactions based on: * Share of customer * Lifetime value * Customer equity * Customer prioritization .question[ Are their limitations, or even dangers, to viewing customers as financial assets?] ] .col-5[ .question[ Insights from CRM are largely based on transactional data that reflects past behaviors of current customers. What about non-customers? ] ]] ??? DISCUSSION NOTES: Insights from CRM are largely based on transactional data that reflects past behaviors of current customers. What about non-customers? What if attitudes underlying behaviors change in ways that aren’t picked up in customer transactional data? What about the human side of the relationship? Trust? Commitment? --- # Big Data: Terabytes Rule .row[.col-7[ 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** describes how everyday objects (e.g., cars and refrigerators, etc.)are connected to the Internet and in turn are able to communicate information throughout an interconnected system ] .col-5[ ![](img05/solomon_rprc9e_fullppt_054.jpg) ]] ??? As more consumer experiences shift into the digital space and new means of connecting and interacting with both individuals and corporations becomes possible and widely accepted, the amount of data available to marketers is increasing exponentially. According to SAS, a leading provider of data analytics software, “Big Data refers to the ever-increasing volume, velocity, variety, variability and complexity of information.” * Each action you take online leaves a digital imprint, and all of those imprints have the potential to yield valuable insights for a wide range of stakeholders within society. * As new technologies continue to enhance the ways we connect to people, machines, and organizations, the volume and complexity of Big Data will continue to increase. * The Internet of Things is a term that is increasingly used in articles and stories on technology trends to describe how everyday objects (e.g., cars and refrigerators, etc.) are connected to the Internet and in turn are able to communicate information throughout an interconnected system.14 Areas that would become part of this network include medical devices, cars, toys, video games—the list goes on and on. --- # Insights from Big Data .col-7[ Big Data can provide competitive advantages in three main areas: 1. Identifying new opportunities 2. Transforming insights into better products 3. Delivering timely information more efficiently and effectively ] ??? Marketers can create competitive advantages based upon their use and analysis of Big Data through three main mechanisms: 1. Identifying new opportunities through analytics that yield greater return on marketing investment. 2. Transforming insights into products and services that are better aligned with desires of consumers. 3. Delivering communications on products and services to the marketplace more efficiently and effectively. These insights can enhance firm profits, but may also benefit society as a whole (see next slide on Google Flu). --- # Big Data Creation, Sources, and Usage .col-7[ Millions of pieces of information that make up Big Data originate from two source categories: * Direct path * You submit a request for information form in which you supply personal information, including features of the product that appeal to you. * Indirect path * Data creation is a by-product of another action. * A company that uses Big Data might know that consumers who purchase green detergent products, register as Democrats, and hold college degrees are more likely than average to purchase a hybrid vehicle. ] ??? The millions of pieces of information that make up Big Data originate from both direct and indirect paths. Here are two examples to illustrate how this works: 1. Direct path: You shop for a car online and see a model that you like. You submit a request for information form in which you supply personal information, including features of the car that appeal to you. That information is stored in the car dealership’s database, and a salesperson pulls it up later on before she contacts you about the car. 2. Indirect path: On the other hand, data creation can be a by-product of another action. A company that uses Big Data might know, for example, that consumers who purchase green detergent products, register as Democrats, and hold college degrees are more likely than average to purchase a hybrid vehicle. A person who fits this profile might receive a communication about a Honda Prius or other hybrid car even though he or she has not (yet) specifically requested information about these vehicles. --- .row[.col-9[ ![](img05/solomon_rprc9e_fullppt_055.png)] .col-3[# Sources of Big Data for Marketers]] ??? Big Data can come from many sources. These sources can be both within and outside of the organization and created and compiled from different groups. --- # Social Media Sources .col-7[ Web scraping Sentiment analysis * Measuring brand attitude by assessing the context or emotion of online comments * If your brand’s name appears a lot of time with terms like “awful” or “sucks,” you probably have a problem. ] ??? With an increasing array of social media sites that boast large number of consumers interacting with each other, with brands, and with other entities, a wealth of information is being produced about how individuals feel about products and just about everything else in their lives. It is not uncommon today for consumers to either praise or condemn a product online. Hint: If your brand’s name appears a lot of time with terms like “awful” or “sucks,” you probably have a problem. Many companies engage in Web scraping, using computer software known as web crawlers to extract large amounts of data from websites. Sentiment analysis is a process by which analysts seek to identify changes in customers’ attitude toward a brand by assessing the context or emotion of comments provided. --- .row[ .col-6[ ![](img05/solomon_rprc9e_fullppt_056.jpg)] .col-6[## Brand mapping ### Nielsen Brand Association Map The closer a word appears to the map’s center, the stronger the association. Similarly, the proximity of words to each other reflects the strength of their relationships in the online posts. ]] ??? DISCUSSION NOTES: Nielsen’s BAM (Brand Association Maps) analyzes online consumer conversations and plots the words and phrases most commonly associated with a given brand. --- # Corporate IT Sources .col-7[ CRM Databases Web Analytic Databases Enterprise Resource Planning (ERP) Databases Accounting-Related Databases ] ??? Corporate sources that live within the organization might include CRM databases, Web analytic databases (e.g., Google Analytics), enterprise resource planning databases, and even accounting-related databases. While each of these and more can contain a treasure trove of information on an organization’s consumers, unfortunately these systems live in departmental “silos”; one group in the company may not share this information with others in the firm, so each group gets only an incomplete picture of its customers. Marketing needs to be the function within the organization that cuts across these groups in order to mine these databases and connect the dots. --- # Government and NGO Sources .col-7[ Increased types and amounts of government-generated data are accessible to enterprising marketers. * Example, U.S. Census (www.census.gov) ] ??? Provided by the government and non-governmental organizations. These types of data could be most anything from extracted U.S. Census results to data on the economic conditions in developing countries that allow marketers to better understand the demographics of consumers at home and the opportunities for global expansion. --- # Commercial Entity Sources .row[.col-7[ 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 .question[ How do you feel about your data being sold to other firms in aggregate form, even if their anonymity is preserved? Would you be willing to trade off this information in order to receive added customer benefits? ] ].col-4[ ![](img05/solomon_rprc9e_fullppt_057.jpg) ]] ??? Many companies today collect data in large quantities to sell to organizations that can derive value from them. For some provider firms, this activity is their primary source of revenue; for others, it is a nice additional source of revenue over and above their principal business activities. The data are sold in aggregated form so that it’s not possible to identify the actions of a specific consumer, but scanner data still provide extremely useful information to both manufacturers and retailers about how much shoppers buy in different categories and which brands they choose. DISCUSSION NOTES: It may surprise students to know that many credit card companies, such as American Express and MasterCard, sell purchase data to advertisers so that they can better target their ads. Supermarkets like Safeway and Krogers’ have for many years sold scanner data—data derived from all those items that are scanned at the cash register when you check out with your loyalty card (which just happens to have your demographic profile information in its record!). How do students feel about their data being sold to other firms in aggregate form, even if their anonymity is preserved? If students view this practice negatively, ask them whether they would be willing to trade off this information in order to receive added customer benefits? --- # Partner Database Sources .row[.col-5[ 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 ] .col-7[ Wal-Mart is well known for employing this approach through its vendor management system known as Retail Link, which provides real-time purchase data to suppliers, making it possible for them to track purchase data for their products in real time. * Vendors are able to manage the process of replenishment so that they can ensure that their products are available for consumers exactly when and where they need them. * For marketers, this provides a valuable source of purchase data in real time that they can use to analyze purchase patterns within different Wal-Mart locations. * Wal-Mart saves on the costs of having to manage this process themselves. ]] ??? Many firms today have adopted a channel partner model in which there is a two-way exchange of information between purchasing organizations and their vendors through shared information technology systems. If you’re the producer of a product that is sold by a large retailer, such as Wal-Mart, think about the information and insights you could gain from access to the consumer information that a key retailer may gathers from its interactions with shoppers in its stores. --- # Data Mining .row[.col-5[ 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 .question[ Should it be (il)legal for companies to collect and sell your personal information without your knowledge? ] ] .col-7[ Cellular operators have begun signing deals with business partners who are eager to market products based on specific phone users’ location and calling habits. * Such **reality mining** is the collection and analysis of machine-sensed environmental data pertaining to human social behavior with the goal of identifying predictable patterns of behavior. * If reality mining catches on, phone companies’ calling records will become precious assets. And these records will only grow in value as customers use their phones to browse the web, purchase products, pay bills, and update their Facebook pages. ]] ??? Big Data can easily exacerbate the problem of information overload, in which the marketer is buried in so much data that it becomes nearly paralyzing to decide which of it provides useful information and which does not. Most marketing information systems include internal customer transaction databases, and many include acquired databases. Often, these databases are extremely large. To take advantage of the massive amount of data now available, a sophisticated analysis technique called data mining is now a priority for many firms. This refers to a process in which analysts sift through Big Data (often measured in terabytes) to identify unique patterns of behavior among different customer groups. In a marketing context, data mining uses computers that run sophisticated programs so that analysts can combine different databases to understand relationships among buying decisions, exposure to marketing messages, and in-store promotions. These operations are so complex that often companies need to build a data warehouse (which can cost more than $10 million) simply to store and process the data. DISCUSSION NOTES: * Cellular operators have begun signing deals with business partners who are eager to market products based on specific phone users’ location and calling habits. * Such reality mining is the collection and analysis of machine-sensed environmental data pertaining to human social behavior with the goal of identifying predictable patterns of behavior. Reality mining was declared to be one of the “10 technologies most likely to change the way we live” by Technology Review Magazine. * If reality mining catches on, phone companies’ calling records will become precious assets. And these records will only grow in value as customers use their phones to browse the web, purchase products, pay bills, and update their Facebook pages. --- # Structured and Unstructured Data ![](img05/solomon_rprc9e_fullppt_058.png) ??? Data derived from data mining efforts can be broadly classified as structured and unstructured data. Structured data are data that (1) are typically numeric or categorical; (2) can be organized and formatted in way that is easy for computers to read, organize, and understand; and (3) can be inserted into a database in a seamless fashion. Conversely, unstructured data are often qualitative in nature and do not possess all three of these properties. --- # Unstructured Data .row[.col-6[ 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. ] .col-6[ .question[ Imagine that you are the social media manager for a consumer brand. * You are fortunate to have a lot of likes and followers and a high level of interaction as well, but you believe that this is only the tip of the iceberg. * You know that all of these comments from your customers could be a source of a lot of great information—the only problem is that there are thousands of them flooding in, and you’re only one person. * How could you possibly find the time to effectively analyze their contents and discern valuable patterns from all of this information? ] ]] ??? Unstructured data contain nonnumeric information that is typically formatted in way that is meant for human eyes and is not easily understood by computers. A good example of unstructured data is the body of an e-mail message. The e-mail carries a lot of meaning to a human but poses a greater challenge for a machine to understand or organize. DISCUSSION NOTES: * Have students look up the Facebook/Twitter/Instagram profiles of popular consumer brands, like M&M’s, or popular retailers, like H&M. * Discuss the quantity and types of information that is available through these sources. Note that relevant comments on these brands may also be bound on the pages of consumers and even non-consumers. Ask the student to: * Imagine that you are the social media manager for a consumer brand. * You are fortunate to have a lot of likes and followers and a high level of interaction as well, but you believe that this is only the tip of the iceberg. * You know that all of these comments from your customers could be a source of a lot of great information—the only problem is that there are thousands of them flooding in, and you’re only one person. * How could you possibly find the time to effectively analyze their contents and discern valuable patterns from all of this information? --- # Ethical / Sustainable Decisions in the Real World .row[.col-7[ Software algorithms are a part of our daily lives. Solid Gold Bomb t-shirt company used algorithms to modify British phrase, “Keep calm and carry on.” Facebook may have selectively chosen which types of stories appeared in its “Trending Topics.” Should social media companies who use algorithms to select news stories for display and distribution on their platforms be required to provide transparency into the inner workings of the related algorithms? ] .col-5[ .question[ * Can you think of other examples where algorithms are used? * (Why) is this a concern? * What do you think about human intervention to “correct” algorithms? Is this ethical? ] ]] --- # Uses of Data Mining ![](img05/solomon_rprc9e_fullppt_059.png) ??? Data mining has four important applications for marketers: 1. Customer acquisition: Many firms include demographic and other information about customers in their database. For example, a number of supermarkets offer weekly special price discounts for store “members.” These stores’ membership application forms require that customers indicate their age, family size, address, and so on. With this information, the supermarket determines which of its current customers respond best to specific offers and then sends the same offers to noncustomers who share the same demographic characteristics. 2. Customer retention and loyalty: The firm identifies big-spending customers and then targets them for special offers and inducements other customers won’t receive. Keeping the most profitable customers coming back is a great way to build business success because—here we go again!—keeping good customers is less expensive than constantly finding new ones. 3. Customer abandonment: Strange as it may sound, sometimes a firm wants customers to take their business elsewhere because servicing them actually costs the firm too much. Today, this is popularly called “firing a customer.” For example, a department store may use data mining to identify unprofitable customers—those who don’t spend enough or who return most of what they buy. For example, data mining has allowed Sprint to famously identify its customers as “the good, the bad, and the ugly.” 4. Market basket analysis: Develops focused promotional strategies based on the records of which customers have bought certain products. Hewlett-Packard, for example, carefully analyzes which of its customers recently bought new printers and targets them to receive e-mails about specials on ink cartridges and tips to get the most out of their machines. --- # Data Scientists: Transforming Big Data into Winning Insights .col-7[ 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 PhDs * Six-figure starting salaries ] ??? A data scientist is someone who searches through multiple, disparate data sources in order to discover hidden insights that will provide a competitive advantage. These individuals frequently have Ph.D.s, often command six-figure starting salaries (according to Glassdoor.com, the median salary as of 2014 was $115,000), and are becoming an increasingly important source of competitive advantage for organizations that want to leverage Big Data. Traditional data analysts often looked at one data source, whereas data scientists typically look at multiple sources of data across the organization. --- # Big Data: Summary .col-7[ Mining of Big Data can provide marketers with valuable new insights … But also presents difficult new challenges! * Technological challenges * Analytic challenges * Ethical challenges .question[ Does knowing how companies seek to use personal information change your perspective of marketing? ] ] ??? DISCUSSION NOTES: * Instructor should ask the extent to which students were aware of data mining practices by marketers. * How does increased knowledge of these topics and business practices impact their view of marketing? * How will increased knowledge of these topics and business practices influence their own online consumption behaviors? --- # Marketing Analytics .col-7[ **Marketing analytics** comprises technologies and processes that enable marketers to collect, measure, analyze, and assess marketing effectiveness. ] ??? Increased emphasis on marketing analytics enables marketers to increase accountability and justify investments into marketing activities. --- # Connect Digital Marketing Channels to Marketing Analytics .row[.col-7[ 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 ] .col-5[ ![](img05/solomon_rprc9e_fullppt_0510.jpg) ]] ??? Digital marketing channels are those specific means of distribution through which digital marketing communications can be delivered to current and potential customers. --- .row[ .col-7[ ![](img05/solomon_rprc9e_fullppt_0511.png)] .col-5[## Major Digital Marketing Channels]] ??? The options for investment in digital marketing channels are diverse with consumers spending large amounts of time on traditional websites, social networking sites, and search engines, to name a few areas. Digital marketing channels are typically broken up into four main categories. Within these, there are multiple types of marketing efforts and campaigns that marketers can develop and track. --- ## Comparing Value of Digital Marketing Investments .col-7[ 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 * Search engine optimization (SEO) Compare average cost per customer transaction ] ??? For marketers, investments in digital marketing are especially attractive because their cost is often directly tied to specific actions users take. For instance, Google’s paid search ads can be purchased or bid on based on a cost per click in which the cost of the advertisement is charged only each time an individual clicks on the advertisement and is directed to the Web page that the marketer placed within the advertisement. This method of charging for advertisements is common for online vendors of advertisement space. Other methods of purchasing advertisements digitally include cost per impression, in which the cost of the advertisement is charged each time the advertisement shows up on a page that the user views. Companies that sell online advertising space commonly use both of these methods of charging for advertisements. Cost-per-click purchases of advertisements are typically more expensive, as they demand a higher level of interaction from the user. Cost-per-impression ad purchases can provide a good value. However, the cost-per-impression structure requires a greater leap of faith because it’s not so easy to measure the value of an impression (or view of an advertisement). Search engine optimization is a systematic process to ensure that your firm comes up at or near the top of lists of typical search phrases related to your business (i.e., Google). Once you’ve done all the calculations, you can compare the average cost per customer transaction (see next slide for examples). --- ![](img05\table5.png) --- # Predictive Analytics .col-7[ 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. ] ??? Up to this point, we’ve looked how marketing analytics can be leveraged to better understand how current marketing channels and initiatives are performing. Another intriguing area for any marketer is the ability to actually predict the future and thus better understand the value of their marketing campaigns even before they implement them. Predictive analytics techniques use large quantities of data and variables that the analysts know relate to one another to more accurately predict specific future outcomes DISCUSSION NOTES: * Vodafone Netherlands is the second-largest mobile carrier in the Netherlands. As the organization’s senior information architect for business intelligence noted, “We have a reasonably large number of customers, a limited marketing budget, and the need to understand how to apply the money effectively and get the best results.” * Vodafone had a wealth of information and wanted to have the capabilities to identify opportunities in order to more effectively predict consumer behavior and better tailor service offerings to consumers based on the information. * One way that Vodafone was able to create value from predictive analytics was through the understanding of winter roaming patterns and, in particular, which of their customers were most likely to go skiing. * Through the firm’s analysis, they were better able to identify and predict which customers would fall within the category of going skiing in the winter and target them exclusively with a campaign that was tailored to offer great value for winter roamers. --- ## Marketing Metrics and Predictive Analytics .row[.col-7[ 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? ] .col-5[ .question[ What types of purchase patterns and behaviors (available to banks and credit card issuers) are likely to be associated with whether or not a student goes away for spring break? Are there indicators of preferred locations? How could marketers use this information to come up with targeted offers and customized services? ] ]] --- # Metrics for Marketing Control .col-7[ 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 ] ??? In a data rich and data-driven world, organizations have the ability to gain a more detailed understanding than ever before of what’s going on both inside and outside their operations. For marketers, this means having the ability to show more clearly a return on their various investments and to use this knowledge to develop and execute marketing plans and strategies. --- # Key Marketing Metrics .row[ .col-6[ **Click-through rate** `$$\frac{\text{click-throughs}}{\text{impressions}}\times 100$$` **Conversion rate** `$$\frac{\text{number of goal achievements}}{\text{number of website visitors}}$$` ] .col-6[ **Cost per order** `$$\frac{\text{advertising costs}}{\text{orders}}$$` **Margin of sales** $$\text{selling price per unit (\$)} - \text{cost per unit (\$)}$$ ]] .row[.col-7[ **Churn rate** `$$\frac{\text{number of customers lost at end of prior period}}{\text{number of customers at beginning of prior period}}\times 100$$` ]]