Chapter 4 Marketing Research

market research ethics

taking an ethical and aboveboard approach to conducting marketing research that does no harm to the participant in the process of conducting the research

customer insights

the collection, deployment, and interpretation of information that allows a business to acquire, develop, and retain their customers

cookies

text files inserted by a website sponsor into a web surfer's hard drive that allows the site to track the surfer's moves

database

an organized collection (often electronic) of data that can be searched and queried to provide information about contacts, products, customers, inventory, and more

predictive technology

analysis techniques that use shopping patterns of large numbers of people to determine which products are likely to be purchased if others are

Step 7: Prepare the Research Report

The final step in the market research process is to prepare a report of the research results. In general, a research report must clearly and concisely tell the readers—top management, clients, creative departments, and many others—what they need to know in a way that they can easily understand and that won't bore you to tears (just like a good textbook should keep you engaged). A typical research report includes the following sections: An executive summary of the report that covers the high points of the total report An understandable description of the research methods A complete discussion of the results of the study, including the tabulations, cross tabulations, and additional statistical analyses Limitations of the study (no study is perfect) Conclusions drawn from the results and the recommendations for managerial action based on the results

focus group

a product-oriented discussion among a small group of consumers led by a trained moderator

probability sampling

a sample in which each member of the population has some known chance of being included

nonprobability sample

a sample in which personal judgment is used to select respondents

intercept research

a study in which researchers recruit shoppers in malls or other public areas

casual research

a technique that attempts to understand cause-and-effect relationships

4.1 knowledge is power

4.1 Explain the role of a marketing information system and a marketing decision support system in marketing decision making. By now we know that successful market planning means that managers make informed decisions to guide the organization. But how do marketers actually make these choices? Specifically, how do they find out what they need to know to develop marketing objectives, select a target market, position (or reposition) their product, and develop product, price, promotion, and place strategies? The answer is (drumroll . . . ): information. Information is the fuel that runs the marketing engine. There's a famous acronym in the marketing information systems field: GIGO, which stands for garbage in, garbage out. To make good decisions, marketers must have information that is not "garbage"—rather, it must be accurate, up to date, and relevant. To understand these needs, marketers first must engage in various forms of research and data collection to identify them. In this chapter, we will discuss some of the tools that marketers use to get that information. Then in Chapter 5, we'll drill down further on applying market research for decision making via marketing analytics. In the chapters that follow, we will look closely at how and why both consumers and organizations buy, and we will explore how marketers sharpen their focus via target marketing. Before we jump into the topic of market research, here's a question for you: A marketer who conducts research to learn more about his customers shouldn't encounter any ethical challenges, right? Well, maybe in a perfect world. In reality though, several aspects of market research are fraught with the potential for ethics breaches. Market research ethics refers to taking an ethical and aboveboard approach to conducting market research that does no harm to the participant in the process of conducting the research. When an organization collects data, important issues of privacy and confidentiality come into play. Marketers must be clear when they work with research respondents about how they will use the data and give respondents full disclosure on their options for confidentiality and anonymity. For example, it is unethical to collect data under the guise of market research when your real intent is to develop a database of potential customers for direct marketing. A database is an organized collection (often electronic) of data that can be searched and queried to provide information about contacts, products, customers, inventory, and more. Firms that abuse the trust of respondents run a serious risk of damaging their reputation when word gets out that they are engaged in unethical research practices. This makes it difficult to attract participants in future research projects—and it "poisons the well" for other companies when consumers believe that they can't trust them. Although the 2016 U.S. presidential election may seem like a long time ago, it's worth recalling that market research played a more prominent role in it than in probably any other major election in history. Pollsters are essentially the political equivalent of market researchers, and in the postmortem of the election results, much effort has gone into better understanding how so much of the data in advance of election night was misinterpreted. In truth, Hillary Clinton ran one of "the most data-driven campaigns" ever, according to The Economist.1 Unfortunately for her, the Clinton campaign team counted too much on what they "thought" data was telling them, when in reality they were missing key signals from the marketplace all along. You see, while data provide information, the interpretation of that information is essentially subjective—that is, its usefulness is very dependent on how the person charged with culling insights for decision making interprets the data for decision making. There's an old saying in market research: "Let the data speak." But really data can speak only through an interpreter. Unfortunately, as mentioned earlier, often GIGO strikes, and in the end, Clinton's team may have just been seeing what they wanted to see and telling her what they thought she wanted to hear. As a result, on the campaign trail, she virtually ignored voters in several key upper midwestern states that she was convinced were a sure thing—Pennsylvania, Michigan, and Wisconsin, in particular. But voters in those and other supposedly safer states had other ideas, and as a result, Donald J. Trump was the "surprise" victor.2 The key takeaway for you as a student of marketing is that if market research and data interpretation played such a prominent role in the election of the leader of the free world, imagine how powerful the same processes (hopefully better executed) can be in making marketing decisions about all sorts of things. The truth is, the success of products you buy from Amazon, the ads you click (or try to make go away) while enjoying YouTube, the price you pay to Taco Bell for that Burrito Supreme Combo, and nearly every other imaginable product and service that is marketed to the public is heavily influenced by market research and the interpretation of the data. Hence, the content of this chapter is very important for anyone who wants to do marketing well. Back to GIGO again, if the data is bad and the interpretation of it is worse, some rotten marketing decisions are bound to happen! Market research is a huge topic and is the subject of one or multiple courses in any marketing degree program. To help you sort out many of the most important ideas, this chapter gives you a guided tour of the most important concepts in market research, starting with the big picture concept of a marketing information system and then systematically walking you through each step in the market research process. Notice that the title of this section is Knowledge Is Power. That about says it all—without the knowledge that only well-interpreted data can provide, marketers are at a huge competitive disadvantage in their ability to compete through the marketing strategy and planning elements you learned about in Chapter 3. Put another way, when marketers throw perfectly good money against marketing strategies that are based on poorly conducted and interpreted market research, the likelihood of success with consumers is very low. The Marketing Information System Many firms use a marketing information system (MIS) to collect information. The MIS is a process that first determines what information marketing managers need. Then, it gathers, sorts, analyzes, stores, and distributes relevant and timely marketing information to users. As shown in Figure 4.1, the MIS system includes three important components: Four types of data (internal company data, market intelligence, market research, and acquired databases) Computer hardware and software to analyze the data and to create reports Output for marketing decision makers Various sources "feed" the MIS with data, and then the system's software "digests" it. MIS analysts use the output to generate a series of regular reports for various decision makers. Let's take a closer look at each of the four different data sources for the MIS. Internal Company Data The internal company data system uses information from within the organization to produce reports on the results of sales and marketing activities. Internal company data include a firm's sales records—information such as which customers buy which products in what quantities and at what intervals, which items are in stock and which are back-ordered because they are out of stock, when items were shipped to the customer, and which items have been returned because they are defective. Often, an MIS allows both marketers and also salespeople and sales managers in the field to access relevant information through a company intranet. This is an internal corporate communications network that uses Internet technology to link company departments, employees, and databases. Intranets are secured so that only authorized employees have access. Nowadays, savvy marketing organizations make sure that access and usability of this valuable internal information is maximized by creating an appealing interface for employees called a marketing dashboard. A marketing dashboard is a comprehensive display and access system providing company personnel with up-to-the-minute information necessary to make decisions. Marketing dashboards often include such elements as data on actual sales versus forecasts, progress on marketing plan objectives, distribution channel effectiveness, current price competition, and whatever other metrics and information are uniquely relevant to the particular employee's role in the firm.3 Dashboard is a good label because, similar to the dashboard of your car, the idea of a marketing dashboard is to make information contained within the company intranet convenient, attractively displayed, and available in real-time. Marketers often rely on salespeople and sales managers in the field to influence customers to purchase. A great marketing dashboard allows these folks to easily access the company intranet and find information available on the MIS system. This type of sales support by marketing means that the sales force can better serve their customers because they have immediate and well-organized access to information on pricing, inventory levels, production schedules, shipping dates, and their customer's sales history. Marketing managers at company headquarters also can see daily or weekly sales data by brand or product line from the internal company data system. They can view monthly sales reports to measure progress toward sales goals and market share objectives. For example, buyers and managers at Walmart's headquarters in Arkansas use up-to-the-minute sales information they obtain from store cash registers around the country so they can quickly detect problems with products, promotions, price competitiveness, and even the firm's distribution system. Related to company intranets and marketing dashboards is the concept of customer relationship management (CRM), which we'll develop more fully in Chapter 5. Market Intelligence As we saw in Chapter 2, to make good decisions, marketers need to have information about the marketing environment. Thus, a second important element of the MIS is the market intelligence system, a method by which marketers get information about what's going on in the world that is relevant to their business. Although the name intelligence may suggest cloak-and-dagger spy activities, in reality nearly all the information that companies need about their environment—including the competitive environment—is available by monitoring everyday sources: company websites, industry trade publications, and direct field observations of the competitive marketplace. And because salespeople are the ones "in the trenches" every day, talking with customers, distributors, and prospective customers, they are a key to sourcing this valuable information. Retailers often hire "mystery shoppers" to visit their stores and those of their competitors posing as customers to see how people are treated. (Imagine being paid to shop!) Other information may come from speaking with organizational buyers about competing products, attending trade shows, or simply purchasing, using, and even reverse engineering competitors' products, which means physically deconstructing the product to determine how it's put together. Marketing managers may use market intelligence data to predict fluctuations in sales as a result of a variety of external environmental factors you read about in Chapter 2, including economic conditions, political issues, and events that heighten consumer awareness. They may also use the data to forecast the future so that they will be on top of developing trends. Television networks have observed how consumers increasingly binge-watch shows through platforms such as Netflix, and as a result, they have begun to offer their shows in ways that appeal to the changing preferences and expectations of consumers. For instance, Walt Disney Company's network Freeform released the entire 10-episode season of its new sci-fi drama Beyond on both digital and on-demand platforms. It was so successful that eight days later, the network ordered a second season!4 Market Research Market research refers to the process of collecting, analyzing, and interpreting data about customers, competitors, and the business environment to improve marketing effectiveness. (Note that in practice the term marketing research is often used interchangeably with market research, but to be precise, marketing research is broader in scope and often refers to the type of research that academics in marketing conduct about the field, whereas market research refers to the type of research that marketing professionals conduct about markets and consumers.) Although companies collect market intelligence data continuously to keep managers abreast of happenings in the marketplace, market research also is called for when managers need unique information to help them make specific decisions. Whether their business is selling cool fashion accessories to teens or industrial coolant to factories, firms succeed when they know what customers want, when they want it, where they want it—and what competing firms are doing about it. In other words, the better a firm is at obtaining valid market information, the more successful it will be. Therefore, virtually all companies rely on some form of market research, though the amount and type of research they conduct varies dramatically. In general, market research data available in an MIS come in two flavors: syndicated research reports and custom research reports. Syndicated research is general information that specialized firms collect on a regular basis and subsequently sell to other firms. Nielson's Scarborough, for instance, surveys local consumers across the United States in over 100 media markets to understand media trends, shopping habits, consumer attitudes, health-care behaviors, and more. These insights assist clients in media planning, brand strategy, and market development.5 Through Scarborough's research, marketers can discover interesting facts about the American people. Did you know that residents of Greenville, Tennessee, are 21 percent more likely than the average American to have attended a college football game during the past year? Other examples of syndicated research reports include Nielsen's TV ratings and Nielsen Audio's (formerly Arbitron) radio ratings. Experian Simmons Market Research Bureau and GfK Mediamark Research & Intelligence are two syndicated research firms that combine information about consumers' buying behavior and their media usage with geographic and demographic characteristics. And INC/The QScores Company reports on consumers' perceptions of more than 1,800 celebrity performers for companies that want to feature a well-known person in their advertising.6 You'll be interested to know that in 2017, the most highly ranked male lead actors in TV shows included Michael Weatherly (Bull), Mark Harmon (NCIS), Taylor Kinney (Chicago Fire), Jim Parsons and Johnny Galecki (The Big Bang Theory), and Terrence Howard (Empire). Bringing up the rear: Matt LeBlanc (Man with a Plan), Jeremy Piven (The Wisdom of the Crowd), and Jermaine Fowler (Superior Donuts).7 As valuable as it may be, syndicated research doesn't provide all the answers to marketing questions because the information it collects typically is broad but shallow. For example, it gives good insights about general trends, such as who is watching what TV shows or what brand of perfume is hot this year. In contrast, a firm conducts custom research to provide answers to specific questions. This kind of research is especially helpful for firms when they need to know more about why certain trends have surfaced. Some firms maintain an in-house research department that conducts studies on its behalf. Many firms, however, hire outside research companies that specialize in designing and conducting projects based on the needs of the client. Hint: This is a great career path if you love solving puzzles and getting into the weeds about what makes consumers tick! These custom research reports are another kind of information an MIS includes. Marketers may use market research to identify opportunities for new products, promote existing ones, or provide data about the quality of their products, who uses them, and how. Acquired Databases A large amount of information that can be useful in marketing decision making is available in the form of external databases. Firms acquire these databases from any number of sources. For example, some companies are willing to sell their customer database to noncompeting firms. Government databases—including the massive amounts of economic and demographic information the U.S. Census Bureau, Bureau of Labor Statistics, and other agencies collect—are available at little or no cost. State and local governments may make some information, such as automobile license data, available for a fee. In recent years, the use of databases for marketing purposes has come under increased government scrutiny because some consumer advocates are quite concerned about the potential invasion of privacy such use may cause. Using the data to analyze overall consumer trends is one thing—using it for outbound direct mailings and unsolicited phone calls and emails has evoked a backlash in a tidal wave of "do-not-call" lists and antispam laws. Maybe you have noticed that when you sign up for most anything online that requires your contact information, you receive an invitation to "opt out" of receiving promotional mailings from the company or from others who may acquire your contact information from the organization later. By law, if you decide to opt out, companies cannot use your information for marketing purposes. We'll further explore the overall issue of database usage by marketers in the context of the popular phrase "Big Data" in Chapter 5. For now, just know that it's a good bet that every website or mobile link you search—and maybe even every tweet or Facebook message you post today—will wind up in a marketer's database. And speaking of Facebook and marketers' databases, at the start of this chapter, we touched on the critical nature of ethical conduct in market research. In 2018, a major data breach involving Facebook went public, causing normally media-elusive founder Mark Zuckerberg to do an extended and widely viewed CNN interview. He found himself mostly rationalizing and apologizing for Facebook's role in enabling a third party, which said it was using Facebook data for academic research, to sell the data to another firm that then proceeded to use it for commercial purposes. The optics of the major news story were immediately devastating for Facebook's reputation and even sparked a Twitter movement called #DeleteFacebook. Stay tuned for more on the critical role of data security when you read Chapter 5.8 Marketing Decision Support System As we have seen, a firm's MIS generates regular accessible information for decision makers on what is going on in the internal and external environment. But sometimes this information alone (no matter how well organized with a slick marketing dashboard) is still inadequate for decision making. Different managers may want different information, and in some cases, the problem they must address is too vague or unusual for the MIS process to easily answer. As a result, many firms beef up their MIS with a marketing decision support system (MDSS). Figure 4.2 shows the elements of an MDSS. An MDSS includes analysis and interactive software that allows marketing managers, even those who are not computer experts, to access MIS data and conduct their own analyses, often within the context of the company intranet. A few years ago, MasterCard developed an application of an MDSS it called the "Conversation Suite." This product offered marketers a single, intensive source of data and insights to further inform decisions about allocating a firm's massive global advertising budget. The Conversation Suite includes features such as a 40-foot display showcasing various marketing metrics and data visualizations grouped by market, as well as a number of touchscreen computers programmed to make digging into the various sources of information shown on the massive platform easy to perform.9 Typically, an MDSS includes sophisticated statistical and modeling software tools. Statistical software allows managers to examine complex relationships among factors in the marketplace. For example, a marketing manager who wants to know how consumers perceive his or her company's brand in relation to the competition's brand might use a sophisticated statistical technique called multidimensional scaling to create a "perceptual map," or a graphic presentation of the various brands in relationship to each other. You'll see an example of a perceptual map in Chapter 7. Modeling software allows decision makers to examine possible or preconceived ideas about relationships in the data—to ask "what-if" questions. For example, media modeling software allows marketers to see what would happen if they made certain decisions about where to place their advertising. A manager may be able to use sales data and a model to find out how many consumers stay with his brand and how many switch, thus developing projections of market share over time. Table 4.1 gives some examples of the different marketing questions an MIS and an MDSS might answer. Table 4.1Examples of Questions an MIS and an MDSS Might Answer Questions an MIS Answers Questions an MDSS Answers What were our company sales of each product during the past month and the past year? Has our decline in sales simply reflected changes in overall industry sales, or is there some portion of the decline that industry changes cannot explain? What changes are happening in sales in our industry, and what are the demographic characteristics of consumers whose purchase patterns are changing the most? Do we see the same trends in our different product categories? Are the changes in consumer trends similar among all our products? What are the demographic characteristics of consumers who seem to be the most and the least loyal? What are the best media to reach a large proportion of heavy, medium, or light users of our product? If we change our media schedule by adding or deleting certain media buys, will we reach fewer users of our product?

4.2 evidence-based decision making in marketing

4.2 Understand the concept of evidence-based decision making toward gaining customer insights. As a consumer, you inherently know that it's getting easier all the time for organizations to collect huge amounts of data. Data are raw, unorganized facts that need to be processed. Analysts then process, organize, structure, and present the data so that it is useful for decision making. This transformation creates information, which is interpreted data. But there is a downside to knowing too much! All of these data can be overwhelming—and not very useful—if no one has any idea what they all mean. The old saying about the ocean—"water, water everywhere and not a drop to drink!"—can be repurposed as "data, data everywhere and nothing insightful to find!" You are studying marketing at a time in which the buzzwords for marketers are evidence-based decision making, which quite simply refers to a marketer's capability to utilize all of the relevant information available (the "evidence") in order to make the best possible marketing decisions. Sounds logical and pretty easy, right? Well, not so fast on that. Many decisions in marketing end up getting made through more of a READY➔FIRE➔AIM approach, unfortunately meaning that little or no market research went into the decision-making process. Note: Agile marketing, which we discussed in Chapter 3, is not READY➔FIRE➔AIM decision making! Rather, in agile marketing, the idea is to both acquire and analyze the evidence quickly, gaining speedy insights for good decisions. Of course, sometimes more information is available than other times, and in some cases, time pressures can lead to simply making a decision with the information you've got at the moment. But everything else being equal, successful marketers of today and the future are going to have to buy into the mantra of evidence-based decision making and then gear up their firm's data collection and analysis capabilities accordingly—because the alternative is being left in the dust by competitors who do have a strong capability in this area. This is such an important strategic issue for marketers and for firms that a whole new subfield of marketing called data analytics has emerged. This subfield is introduced to you fully in Chapter 5. Closely related to evidence-based decision making is the the concept of customer insights, which at its core refers to the collection, deployment, and interpretation of information that allows a business to acquire, develop, and retain its customers. That is, the insights are the evidence that allows for better decisions! Like Cindy Bean at Campbell, most companies today maintain a dedicated team of experts whose jobs are to sift through all the information available to support market planning decisions. This group does its best to understand how customers interact with the organization (including the nasty encounters they may have) and to guide planners when they think about future initiatives. The job of executing a companywide evidence-based approach to decision making is more complicated than it sounds. Traditionally, most companies have operated in "silos," so that, for example, the people in new product development would have zero contact with anyone in customer service who actually had to deal with complaints about the items they designed. The insights manager is like an artist who has to work with a lot of different colors on a palette—the job is to integrate feedback from syndicated studies, marketing research, customer service, loyalty programs, and other sources to paint a more complete picture the organization can use. As such, this function in the organization usually plays a supporting role across the firm's strategic business units (SBUs). For example, to gain greater insight into the preferences and characteristics of those consumers who made purchases within a specific product line of soups, a product line manager at Campbell could reach out to Cindy Bean's consumer insights team for help. The team would then gather a wide array of data about the specific types of consumers who enjoy soup from that product line as well as other data, such as frequency of purchases by consumer segment and what key factors influence consumption of specific types of soup by consumer segment. Cindy's team no doubt would deliver this information in an easy-to-understand format to highlight the most actionable insights. This analysis would enable the manager of the product line to determine how to better allocate resources to drive market performance of the products. Like Campbell, many organizations are "catching the wave" by adding customer (consumer) insights departments. This growing trend in turn offers a lot of promising job opportunities for graduates who know how to fish for usable knowledge in the huge information ocean.

4.3 steps in the market research process

4.3 List and explain the steps and key elements of the market research process. The collection and interpretation of information is hardly a one-shot deal that managers engage in "just out of curiosity." Ideally, market research is an ongoing process—a series of steps marketers take repeatedly to learn about the marketplace. Whether a company conducts the research itself or hires another firm to do it, the goal is the same: to help managers make informed marketing decisions. Figure 4.3 provides a great road map of the steps in the research process. You can use it to track our discussion of each step. Step 1: Define the Research Problem The first step in the market research process is to clearly understand what information managers need. This step is called defining the research problem. You should note that the word problem here does not necessarily refer to "something that is wrong" but instead refers to the overall questions for which the firm needs answers. Defining the problem has three components: Specify the research objectives: What questions will the research attempt to answer? Identify the consumer population of interest: What are the characteristics of the consumer group(s) of interest? Place the problem in an environmental context: What factors in the firm's internal and external business environment might influence the situation? It's not as simple as it may seem to provide the right kind of information for each of these pieces of the problem. Suppose a luxury car manufacturer wants to find out why its sales fell off dramatically over the past year. The research objective could center on any number of possible questions: Is the firm's advertising failing to reach the right consumers? Is the right message being sent? Do the firm's cars have a particular feature and related benefit (or lack of one) that turns customers away? Does a competitor offer some features and benefits that have better captured customer imaginations? Is there a problem with the firm's reputation for providing quality service? Do consumers believe the price is right for the value they get? The particular objective researchers choose depends on a variety of factors, such as the feedback the firm gets from its customers, the information it receives from the marketplace, and sometimes even the intuition of the people who design the research. Often the focus of a research question comes from marketplace feedback that identifies a possible problem. Volvo, long known for the safety records of its cars, continues to have a tough time competing with luxury brands like Mercedes-Benz, BMW, Lexus, and Audi. Resulting research question: How might Volvo improve its market share among luxury car buyers? The research objective determines the consumer population the company will study. In the case of Volvo, the research might focus on current owners to find out what they especially like about the car. Or it could be directed at non-owners to understand their lifestyles, what they look for in a luxury automobile, or their beliefs about the Volvo brand that discourage them from buying the cars. Actually, the Volvo scenario is a real one, and in contemplating the best move, the company chose to focus on why consumers didn't buy the competing brands. Volvo marketers figured it would be a good idea to identify the "pain points" shoppers experienced when they looked at rivals so that they could try to address these objections with their own marketing activities (a pretty smart approach!). So what did Volvo find out? Its research showed that many car shoppers were too intimidated by the "ostentatious" image of Mercedes and BMW to consider actually buying one. Others felt that too many of their neighbors were driving a Lexus, and they wanted to make more of an individual statement. Volvo's vice president of marketing explained that Volvo owners' "interpretation of luxury is different but very real. They're more into life's experiences, and more into a Scandinavian simple design [of vehicles] versus a lot of clutter. They are very much luxury customers and love luxury products, but they don't feel a need to impress others." Based on the research findings, Volvo developed a new ad campaign, showing consumers that it was OK—and even desirable—to be different. The company even pokes fun at rival luxury brands. In one TV commercial, a sophisticated woman sits at a stoplight in her Mercedes-Benz SUV and checks out her makeup in the rearview mirror. Another woman pulls up next to her in a Volvo XC60—but she's more down to earth. The Volvo driver looks into her own rearview mirror. The difference is she makes a funny face to make her kids in the backseat crack up. The voice-over says, "Volvos aren't for everyone, and we kinda like it that way."10 This Volvo example illustrates the evidence-based decision making approach very well as it has ramped up its research and development (R&D). The insights the company identified led Volvo to double-down on its own uniqueness. This clear positioning and compelling messaging within the luxury car market has contributed mightily to a turnaround in sales and profit performance for the firm. Their lesson learned is that great marketing works—and the odds of doing great marketing go way up when evidence-based decision making yields just the right insights to spark an appropriate strategy change.11

eye tracking technology

A type of mechanical observation technology that uses sensors and sophisticated software to track the position and movement of an individual's eyes to gain context-specific insights into how individuals interact with and respond to different visual elements and stimuli.

step 5: collect the data

At this point, the researcher has determined the nature of the problem to address. She chose a research design that will specify how to investigate the problem and what kinds of information (data) she will need. The researcher has also selected the data collection and sampling methods. Once she's made these decisions, the next task is to collect the data. We noted previously that the quality of your conclusions is only as good as the data you use. The same logic applies to the people who collect the data: The quality of research results is only as good as the poorest interviewer in the study. Careless interviewers may not read questions exactly as written, or they may not record respondent answers correctly. So marketers must train and supervise interviewers to make sure they follow the research procedures exactly as outlined. In the next section, we'll talk about some of the problems in gathering data and some solutions. Challenges to Gathering Data in Foreign Countries Conducting market research around the world is big business for U.S. firms—for the top 50 companies (as measured by revenue), 53 percent of their income comes from work done outside the United States—that totals nearly $23 billion.43 However, as we saw in Chapter 2, market conditions and consumer preferences vary worldwide, and there are major differences in the sophistication of market research operations and the amount of data available to global marketers. In Mexico, for instance, because there are still large areas where native tribes speak languages other than Spanish, researchers may end up bypassing these groups in surveys. In Egypt, where the government must sign off on any survey, the approval process can take months or years. And in many developing countries, infrastructure is an impediment to executing phone or mail surveys, and lack of online connectivity blocks web-based research. For these and other reasons, choosing an appropriate data collection method is difficult. In some countries, many people may not have phones, or low literacy rates may interfere with mail surveys. Understanding local customs can be a challenge, and cultural differences also affect responses to survey items. Both Danish and British consumers, for example, agree that it is important to eat breakfast. However, the Danish sample may be thinking of fruit and yogurt, whereas the British sample has toast and tea in mind. Sometimes marketers can overcome these problems by involving local researchers in decisions about the research design. Another problem with conducting market research in global markets is language. Sometimes translations just don't come out right. In some cases, entire subcultures within a country might be excluded from the research sample. In fact, this issue is becoming more and more prevalent inside the U.S. as non-English speakers increase as a percentage of the population. To overcome language difficulties, researchers use a process of back-translation, which requires two steps. First, a native speaker translates the questionnaire into the language of the targeted respondents. Then, someone fluent in the second language translates this new version back into the original language to ensure that the correct meanings survive the process. Even with precautions such as these, researchers must interpret the data they obtain from other cultures with care.

descriptive research

a tool that probes more systematically into the problem and bases its conclusions on large numbers of observations

cross-sectional design

a type of descriptive technique that involves the systematic collection of quantitative information

step 4: design the sample

Once the researcher defines the problem, decides on a research design, and determines how to collect the data, the next step is to decide from whom to obtain the needed information. Of course, he or she could collect data from every single customer or prospective customer, but this would be extremely expensive and time consuming if possible at all (this is what the U.S. Census spends millions of dollars to do every 10 years). Not everyone has the resources of the U.S. government to poll everyone in their market. So they typically collect most of their data from a small proportion, or sample, of the population of interest. Based on the answers from this sample, researchers generalize to the larger population. Whether such inferences are accurate or inaccurate depends on the type and quality of the study sample. There are two main types of samples: probability and nonprobability samples. Probability Sampling In a probability sample, each member of the population has some known chance of being included. Using a probability sample ensures that the sample represents the population and that inferences we make about the population from what members of the sample say or do are justified. For example, if a larger percentage of males than females in a probability sample say they prefer action movies to "chick flicks," one can infer with confidence that a larger percentage of males than females in the general population also would rather see a character get sliced and diced than kissed and dissed (okay, we wouldn't really use these descriptions in a study, but you get the idea). The most basic type of probability sample is a simple random sample, in which every member of a population has a known and equal chance of being included in the study. For example, if we simply take the names of all 40 students in a class, put them in a hat, and draw one out, each member of the class has a 1 in 40 chance of being included in the sample. In most studies, the population from which the sample will be drawn is too large for a hat, so marketers use a computer program to generate a random sample from a list of members. Sometimes researchers use a systematic sampling procedure to select members of a population; they select the nth member of a population after a random start. For example, if we want a sample of 10 members of your class, we might begin with the second person on the roll and select every fourth name after that—the second, sixth, tenth, fourteenth, and so on. Researchers know that studies that use systematic samples are just as accurate as those that use simple random samples. But unless a list of members of the population of interest is already in a computer data file, it's a lot simpler just to create a simple random sample. Yet another type of probability sample is a stratified sample, in which a researcher divides the population into segments that relate to the study's topic. For example, imagine you want to study what movies most theatergoers like. You have learned from previous studies that men and women in the population differ in their attitudes toward different types of movies—men like action flicks, and women like romantic comedies. To create a stratified sample, you would first divide the population into male and female segments. Then, you would randomly select respondents from each of the two segments in proportion to their percentage of the population. In this way, you have created a sample that is proportionate to the population on a characteristic that you know will make a difference in the study results. Nonprobability Sampling Sometimes researchers do not believe that the time and effort required to develop a probability sample is justified, perhaps because they need an answer quickly or just want to get a general sense of how people feel about a topic. They may choose a nonprobability sample, which entails the use of personal judgment to select respondents—in some cases, they just ask anyone they can find. With a nonprobability sample, some members of the population have no chance at all of being included. Thus, there is no way to ensure that the sample is representative of the population. Results from nonprobability studies can be generally suggestive of what is going on in the real world but are not necessarily definitive. A convenience sample is a nonprobability sample composed of individuals who just happen to be available when and where the data are being collected. For example, if you were to simply stand in front of the student union and ask students who walk by to complete your questionnaire, the "guinea pigs" you get to agree to do it would be a convenience sample. Finally, researchers may also use a quota sample, which includes the same proportion of individuals with certain characteristics as in the population. For example, if you are studying attitudes of students in your university, you might just go on campus to find freshmen, sophomores, juniors, and seniors in proportion to the number of members of each class in the university. The quota sample is much like the stratified sample except that, with a quota sample, the researcher uses his or her individual judgment to select respondents.

Step 2: Determine the Research Design

Once we isolate specific problems, the second step of the research process is to decide on a plan of attack. This plan is the research design, which specifies exactly what information marketers will collect and what type of study they will do. Research designs fall into two broad categories based on whether the analysts will use primary or secondary data (see Figure 4.4). All marketing problems do not call for the same research techniques, and marketers solve many problems most effectively with a combination of approaches. Research with Secondary Data The first question marketers must ask when they determine their research design is whether the information they require to make a decision already exists. For example, a coffee producer that needs to know the differences in coffee consumption among different demographic and geographic segments of the market may find that the information it needs is available from one or more studies already conducted by the National Coffee Association, the leading trade association of U.S. coffee companies and a major generator of industry research. Information that has been collected for some purpose other than the problem at hand is secondary data. Many marketers thrive on going out and collecting new, "fresh" data from consumers. In fact, getting new data seems to be part of the marketing DNA. However, if secondary data are available, it saves the firm time and money because it has already incurred the expense to design a study and collect the data. Sometimes the information that marketers need may be "hiding" right under the organization's nose in the form of company reports; previous company research studies; feedback received from customers, salespeople, or stores; or even in the memories of longtime employees (it's amazing how many times a manager commissions a study without knowing that someone else who was working on a different problem already submitted a similar report!). More typically, though, researchers need to look elsewhere for secondary data. They may obtain reports published in popular and business press, studies that private research organizations or government agencies conduct, and published research on the state of the industry from trade organizations. For example, many companies subscribe to reports such as the National Consumer Study, a survey conducted by syndicated research firm Experian Simmons. The company publishes results that it then sells to marketers, advertising agencies, and publishers. Access to its data is even available in some college libraries. This database contains more than 60,000 data variables with usage behavior on all major media, over 500 product categories, and over 8,000 brands. Data from Experian Simmons can give a brand manager a profile of who uses a product, identify heavy users, or even provide data on what information sources a target market is likely to consult prior to purchase.12 As examples, popular online sources of useful data for marketers include Opinion Research Corporation (ORC), the U.S. Census Bureau and Bureau of Labor Statistics, the American Marketing Association, and LexisNexus. Research with Primary Data Of course, secondary data are not always the answer. When a company needs to make a specific decision, marketers often collect primary data: information they gather directly from respondents to specifically address the question at hand. Primary data include demographic and psychological information about customers and prospective customers, customers' attitudes and opinions about products and competing products, as well as their awareness or knowledge about a product and their beliefs about the people who use those products. In the next few sections, we'll talk briefly about the various design options for collecting primary data. Exploratory Research Marketers use exploratory research to come up with ideas for new strategies and opportunities or perhaps just to get a better handle on a problem they are currently experiencing with a product. Because the studies are usually small scale and less costly than other techniques, marketers may do this to test their hunches about what's going on without too much risk or expense. Exploratory studies often involve in-depth probing of a few consumers who fit the profile of the "typical" customer. Researchers may interview consumers, salespeople, or other employees about products, services, ads, or stores. They may simply "hang out" and watch what people do when they choose among competing brands in a store aisle. Or they may locate places where the consumers of interest tend to be and ask questions in these settings. For example, some researchers find that younger people often are too suspicious or skeptical in traditional research settings, so they may interview them while they wait in line to buy concert tickets or in clubs.13 We refer to most exploratory research as qualitative; that is, the results of the research project tend to be nonnumeric and instead might be detailed verbal or visual information about consumers' attitudes, feelings, and buying behaviors. For example, consumer-packaged-goods (CPG) company Reckitt Benckiser came to believe that for their Finish® dishwashing detergent the best way to compete for market share was to focus on the functional performance of the product. Through their ads, they typically would demonstrate how effective it was at cleaning dishware and glassware, in some cases comparing results to those of direct competitors' products, such as P&G (who, as a competitor in soap, is no slouch). But then, Reckitt Benckiser brought in a market research firm to conduct a series of ethnographic studies (we will cover ethnography later in this section) focused on the observation of families in their homes actually using the product. The result of this research was the realization that a functionally oriented focus on the cleanness of dishware and glassware products resulting from the use of Finish® was masking a more compelling advertising message. This related to the dishwasher's role (and in turn the dishwashing detergent's role) as a central part of the home, one that spanned a wide range of social and family events. As a result of this insight, a whole new advertising campaign was launched that showcased all of the small and big life events in which dirty dishes are produced, closing with the message: "Everything in life creates dirty dishes. Love your dishwasher. Give it Finish®." The campaign met with positive responses from consumers and even earned industry acclaim in the form of a silver trophy at the Cannes Lions Festival of Creativity.14 A focus group is the technique that market researchers employ most often for exploratory research. Focus groups typically consist of five to nine consumers who have been recruited because they share certain characteristics (they all play golf at least twice a month, are women in their 20s, etc.). These people sit together to discuss a product, ad, or some other marketing topic a discussion leader introduces. Typically, the leader records (by videotape or audiotape) these group discussions, which may be held at special interviewing facilities that allow for observation by the client who watches from behind a one-way mirror. As a result of insights it gathered from focus groups, MillerCoors decided to revise the packaging design for one of its brands to brighten it up and better appeal to consumers. The company heard from millennials in focus group sessions that the packaging on its Blue Moon Belgian White Ale was perceived as "dark," "lonely," and "mystical," which prompted the change in packaging to a more "perky" motif.15 Today it's common to find focus groups in cyberspace as well as in person. Firms such as IKEA and Volvo use online focus group sites that resemble other social networking sites. IKEA used consumer consulting boards, also known as a market research online community (MROC), in five different countries to solicit feedback for an update of its catalog.16 An MROC is a privately assembled group of people, usually by a market research firm or department, used to gain insight into customer sentiments and tendencies. MROCs are useful for many market research questions, including those about product ideas, branding strategies, and packaging decisions.17 In a different approach from IKEA's, Volvo launched a focus group via TweetChat, Twitter's chat platform, to gather feedback about advertisements that the firm had developed. Volvo marketers said that the instant feedback they got from consumers helped strike the right balance in the ads. The rapid back-and-forth between the company and the online community allows for real-time data collection.18 The case study is a comprehensive examination of a particular firm or organization. In business-to-business market research in which the customers are other firms, for example, researchers may try to learn how one particular company makes its purchases. The goal is to identify the key decision makers, to learn what criteria they emphasize when they choose among suppliers, and perhaps to learn something about any conflicts and rivalries among these decision makers that may influence their choices. Another qualitative approach is ethnography, which uses a technique that marketers borrow from anthropologists who go to "live with the natives" for months or even years. Some market researchers visit people's homes or participate in real-life consumer activities to get a handle on how they really use products. Imagine having a researcher follow you around while you shop and while you use the products you bought to see what kind of consumer you are. This is basically marketing's version of a reality show—though, we hope, the people they study are a bit more "realistic" than the ones on TV! Descriptive Research We've seen that marketers have many qualitative tools in their arsenal, including focus groups and observational techniques, to help them better define a problem or opportunity. These are usually modest studies of a small number of people—enough to get some indication of what is going on but not enough for the marketer to feel confident about generalizing what she observes to the rest of the population. The next step in market research, then, often is to conduct descriptive research. This kind of research probes systematically into the marketing problem and bases its conclusions on a large sample of participants. Results typically are expressed in quantitative terms—averages, percentages, or other statistics that result from a large set of measurements. In such quantitative approaches to research, the project can be as simple as counting the number of Listerine bottles sold in a month in different regions of the country or as complex as statistical analyses of responses to a survey mailed to thousands of consumers about their flavor preferences in mouthwash. In each case, marketers conduct the descriptive research to answer a specific question, in contrast to the "fishing expedition" they may undertake in exploratory research. However, don't downplay the usefulness of qualitative approaches—initial qualitative market research serves to greatly inform and shape subsequent quantitative approaches. Market researchers who employ descriptive techniques most often use a cross-sectional design. This approach usually involves the systematic collection of responses to a consumer survey instrument, such as a questionnaire, from one or more samples of respondents at one point in time. They may collect the data on more than one occasion but usually not from the same pool of respondents. In contrast to these one-shot studies, a longitudinal design tracks the responses of the same sample of respondents over time. Market researchers sometimes create consumer panels to get information; in this case, a sample of respondents that are representative of a larger market agrees to provide information about purchases on a weekly or monthly basis. Major consumer-packaged-goods firms—like P&G, Unilever, Colgate Palmolive, and Johnson & Johnson, for example—recruit consumer advisory panels on a market-by-market basis to keep their fingers on the pulse of local shoppers. P&G maintains two key advisory panels: one for teens (Tremor) and one for moms (Vocalpoint). With more than 750,000 members weighing in on everything from package design to promotional material, P&G estimates that the loyalty and advocacy of these members have boosted P&G's sales by 10 to 30 percent.19 Causal Research It's a fact that purchases of both diapers and beer peak between 5 p.m. and 7 p.m. Can we say that purchasing one of these products caused shoppers to purchase the other as well—and, if so, which caused which? Does taking care of a baby drive a parent to drink? Or is the answer simply that this happens to be the time when young fathers stop at the store on their way home from work to pick up some brew and Pampers?20 And what about hemlines? Since the 1920s, George Taylor's "hemline index" has posited that the length of women's hemlines reflects overall economic health. The theory originated at a time when women wore silk stockings—when the economy was strong, they shortened their hemlines to show off the stockings; when the economy took a dive, so did the hemlines to cover up the fact that women couldn't afford the fancy stockings. Don't believe it? The same was true in 2009 when runway designs were "shockingly short" and the stock market rallied 15 percent for the year.21 And how about more recently? Well, true to form, through 2017 into January 2018, the market rose 33 percent, only to begin experiencing some waffling through the spring. And guess what? The market was very bullish and skirts were getting shorter. Then, as fall 2018 ready-to-wear collections began to roll out, a look at their longer hemlines suggested the economy and Wall Street might be headed for some tough times. But investors might not want to panic just yet. There's also the "Super Bowl Indicator" to consider, which suggests that a win by a team in the National Football Conference means it will be a good year for stocks. A win by an American Football Conference team suggests a bear market. These and other "superstitions" aren't necessarily accurate, but they illustrate the faith many of us place in correlated events. Place your bets (both on your stocks and on your team)!22 The descriptive techniques we've mentioned do a good job of providing valuable information about what is happening in the marketplace, but by its nature, descriptive research can only describe a marketplace phenomenon—it cannot tell us why it occurs. Sometimes marketers need to know if something they've done has brought about some change in behavior. For example, does placing one product next to another in a store mean that people will buy more of each? We can't answer this question through simple observation or description. Causal research attempts to identify cause-and-effect relationships. Marketers use causal research techniques when they want to know if a change in something (e.g., placing cases of beer next to a diaper display) is responsible for a change in something else (e.g., a big increase in diaper sales). They call the factors that might cause such a change independent variables and the outcomes dependent variables. The independent variable(s) cause some change in the dependent variable(s). In our example, then, the beer display is an independent variable, and sales data for the diapers are a dependent variable—that is, the study would investigate whether an increase in diaper sales depends on the proximity of beer. Researchers can gather data and test the causal relationship statistically. This form of causal research often involves using experimental designs. Experiments attempt to establish causality by ruling out alternative explanations, and to maintain a high level of control, experiments may entail bringing subjects (participants) into a lab so that researchers can control precisely what they experience. For the diaper example, a group of men might be paid to come into a testing facility and enter a "virtual store" on a computer screen. Researchers would then ask the men to fill a grocery cart as they click through the virtual aisles. The experiment might vary the placement of the diapers—next to shelves of beer in one scenario and near paper goods in another scenario. The objective of the experiment would be to find out which placement gets more of the guys to put diapers into their carts.

experiments

a technique that tests predicted relationships among variables in a controlled environment

step 3: choose the method to collect primary data

When the researcher decides to work with primary data, the next step in the market research process is to figure out just how to collect it. We broadly describe primary data collection methods as either survey or observation. There are many ways to collect data, and marketers try new ones all the time. In fact, today, more and more marketers are turning to sophisticated brain scans to directly measure a consumer's brain for reactions to various advertisements or products. This neuromarketing approach uses technologies such as functional magnetic resonance imaging (fMRI) to measure brain activity in order to better understand why consumers make the decisions they do. Some firms have even invested in their own labs and in-house scientists to establish an ongoing neuromarketing research program. Neuromarketing has gained increasing popularity among companies such as Facebook, Twitter, and Time Warner as a tool to understand consumer reactions to elements of various forms of marketing communication. For instance, Samsung and the firm NeuroInsight worked together to analyze the brain activity of iPhone and Samsung users to develop television commercials that appealed specifically to Apple enthusiasts. Their biometric research found that Apple users responded best to ads that identified problems with iPhones and solutions offered by Samsung products. Industry heavyweight Nielson has invested in neuromarketing in a major way, purchasing NeuroFocus and Innerscope to facilitate studying eye tracking, facial coding, and other biometric measures.23 Because most of us don't have access to fMRI machines to conduct market research, we'll focus more in this section on explaining other methods to collect primary data. In contrast to neuromarketing for primary data collection, surveys provide a more traditional approach. Survey methods involve some kind of interview or other direct contact with respondents who answer questions. Questionnaires can be administered on the phone, in person, through the mail, or over the Internet. Table 4.2 summarizes the advantages and disadvantages of different survey methods for collecting data. Table 4.2Advantages and Disadvantages of Survey Data Collection Methods Data Collection Method Advantages Disadvantages Mail questionnaire Respondents feel anonymous Low cost Good for ongoing research May take a long time for questionnaires to be returned Low rate of response; many consumers may not return questionnaires Inflexible questionnaire format Length of questionnaire is limited by respondents' interest in the topic Unclear whether respondents understand the questions Unclear who is responding No assurance that respondents are being honest Telephone interviews Fast High flexibility in questioning Low cost Limited interviewer follow-up Limited questionnaire length Decreasing levels of respondent cooperation High likelihood of respondent misunderstanding Respondents cannot view materials Cannot survey households without phones Consumers screen calls with answering machines and caller ID Do-not-call lists allow many research subjects to opt out of participation Face-to-face interviews Flexibility of questioning Can use long questionnaires Can determine whether respondents have trouble understanding questions Take a lot of time Can use visuals or other materials High cost Interviewer bias a problem Online questionnaire Instantaneous data collection and analysis Questioning very flexible Low cost No interviewer bias No geographic restrictions Can use visuals or other materials Unclear who is responding No assurance that respondents are being honest Limited questionnaire length Unable to determine whether respondent understands the question Self-selected samples Questionnaires Questionnaires differ in their degree of structure. With a totally unstructured questionnaire, the researcher loosely determines the items in advance. Questions may evolve from the respondent's answers to previous questions. At the other extreme, the researcher uses a completely structured questionnaire, asking every respondent the exact same questions, and each participant responds to the same set of fixed choices. You have probably experienced this kind of questionnaire, where you might have had to respond to a statement by saying if you "strongly agree," "somewhat agree," and so on. Moderately structured questionnaires ask each respondent the same questions, but the respondent is allowed to answer the questions in his or her own words. Mail questionnaires are easy to administer and offer a high degree of anonymity to respondents. On the downside, because the questionnaire is printed and mailed, researchers have little flexibility in the types of questions they can ask and little control over the circumstances under which the respondent answers them. Mail questionnaires also take a long time to get back to the company and are likely to have a much lower response rate than other types of data collection methods because people tend to ignore them. Telephone interviews usually consist of a brief phone conversation in which an interviewer reads a short list of questions to the respondent. There are several problems with using telephone interviews as a data collection method. The respondent may not feel comfortable speaking directly to an interviewer, especially if the survey is about a sensitive subject. Another problem with this method is that the growth of telemarketing, in which businesses sell directly to consumers over the phone, has eroded consumers' willingness to participate in phone surveys. In addition to aggravating people by barraging them with telephone sales messages (usually during dinnertime!), some unscrupulous telemarketers disguise their pitches as research. They contact consumers under the pretense of doing a study when, in fact, their real intent is to sell the respondent something or to solicit funds for some cause. This in turn prompts increasing numbers of people to use voicemail and caller ID to screen calls, further reducing the response rate. And, as we noted previously, state and federal do-not-call lists allow many would-be research subjects to opt out of participation in both legitimate market research and unscrupulous telemarketing.24 Using face-to-face interviews, a live interviewer asks questions of one respondent at a time. Although in "the old days" researchers often went door-to-door to ask questions, that's much less common today because of fears about security and because the large numbers of two-income families make it less likely to find people at home during the day. Typically, today's face-to-face interviews occur as part of intercept research, an approach in which researchers recruit consumers in public areas, such as stores or highly trafficked walkways. You've probably experienced this scenario—you're in a public area minding your own business when before you know it, a smiling person holding a clipboard stops you to see if you are willing to answer a few questions. A classic example occurs during a leisurely vacation with the family at a resort hotel when, as you're walking down the corridor to have a leisurely lunch, you encounter a representative of the hotel's timeshare division who starts out with a questionnaire and—if you fit the profile—ends with an invitation to a "free" session on the benefits of vacation ownership. Intercept research offers good opportunities to get feedback about new package designs, styles, or even reactions to new foods or fragrances. However, because only certain groups of the population probably frequent the locale of the intercept, an intercept study may not provide the researcher with a representative sample of the population (unless the population of interest is highly correlated with the characteristics of the respondents). In addition to being more expensive than mail or phone surveys, intercept research has the disadvantage that respondents may be reluctant to answer questions of a personal nature in a face-to-face context. Online questionnaires are extremely popular, but the use of such questionnaires is not without concerns. Many researchers question the quality of responses they will receive—particularly because (as with mail and phone interviews) no one can be really sure who is typing in the responses on the computer. In addition, it's uncertain to what degree savvy online consumers are truly representative of the general population that is purported to be of interest to the researcher.25 Observational Methods A second major primary data collection method is observation. This term refers to situations where the researcher simply records the consumer's behaviors. When researchers use personal observation, they simply watch consumers in action to understand how they react to marketing activities. Although a laboratory allows researchers to exert control over what test subjects see and do, marketers don't always have the luxury of conducting this kind of "pure" research. But it is possible to conduct field studies in the real world, as long as the researchers still can control the independent variables. For example, a diaper company might choose two grocery stores that have similar customer bases in terms of age, income, and so on. With the cooperation of the grocery store's management, the company might place its diaper display next to the beer in one store and next to the paper goods in the other and then record diaper purchases men make over a two-week period. If a lot more guys buy diapers in the first store than in the second (and the company was sure that nothing else was different between the two stores, such as a dollar-off coupon for diapers being distributed in one store and not the other), the diaper manufacturer might conclude that the presence of beer in the background does indeed result in increased diaper sales. When they suspect that subjects will probably alter their behavior if they know someone is watching them, researchers may use unobtrusive measures to record traces of physical evidence that remain after people have consumed something. For example, instead of asking a person to report on the alcohol products currently in her home, the researcher might go to the house and perform a "pantry check" by actually counting the bottles in her liquor cabinet. Another option is to sift through garbage to search for clues about each family's consumption habits. The "garbologists" can tell, for example, which soft drink is accompanied by what kind of food. Because people in these studies don't know that researchers are looking through products they've discarded, the information is totally objective—although a bit smelly! Mechanical observation is a method of primary data collection that relies on nonhuman devices to record behavior. For example, one of the classic applications of mechanical observation is the Nielsen Company's famous use of People Meters—boxes the company attaches to the TV sets of select viewers to record patterns of TV watching. The data that Nielsen obtains from these devices indicate who is watching which shows. These "television ratings" help network clients determine how much to charge advertisers for commercials and which shows to cancel or renew. Nielsen also measures user activity on digital media. The research company has more than 250,000 Internet users across 30,000 sites and 25 countries covering all the potential devices that a consumer would use to access digital media.26 This allows Nielsen to give clients a more updated understanding of how viewers interact with their favorite TV shows. For example, it tracks the number of TV-related tweets people post and provides demographic information including age and gender of individuals who post TV-related tweets.27 Similarly, Nielsen Audio (formerly Arbitron) deploys thousands of Portable People Meters (PPMs).28 PPMs resemble pagers and automatically record the wearer's exposure to any media that has inserted an inaudible code into its promotion, such as TV ads or shelf displays. Thus, when the consumer is exposed to a broadcast commercial, cinema ad, or other form of commercial, the PPM registers, records, and time-stamps the signal. Portability ensures that all exposures register; this eliminates obtrusive people meters and written diaries that participants often forget to fill out.29 Another form of mechanical observation that some firms use is eye tracking technology. This method relies on portable or stationary equipment to track the movement of a participant's eyes, and it can provide greater insight into what people look at and for how long they look at it. For marketers, this provides the opportunity to better understand how consumers engage with various forms of marketing of a visual nature. Examples of its use include tracking the viewing of print, television, and mobile ads, and product placement in televised sporting events. Improvements in the portable or wearable version of eye tracking technology offer greater opportunities for data to be gathered outside of lab settings—in the "real world"—thus offering potential for more applicable insights for marketers.30 Some retailers use sophisticated technology to observe where shoppers travel in their stores so they can identify places that attract a lot of traffic and those that are dead spots. In some cases, these "heat maps" use the signals from shoppers' mobile phones to record their movements through the aisles. Online Research Many companies find that an online approach is a superior way to collect data—it's fast, it's relatively cheap, and it lends itself well to forms of research from simple questionnaires to online focus groups. In fact, some large companies like P&G now collect a large portion of their consumer intelligence online. Developments in online research are happening quickly, so let's take a look at where things are headed. There are two major types of information from online research. One type is information that organizations gather when they track consumers surfing the web. The second type is information they gather more selectively through questionnaires on websites, including, of course, social media sites, through email, or from focus groups that virtual moderators conduct in chat rooms. Most social media platforms, such as Twitter and Facebook, offer numerous ways to analyze trends and conduct market research. By simply searching the latest posts and popular terms—or, as marketers refer to it, "scraping the web"—you can gain insight into emerging trends and see what customers are talking about in real time. One example of this approach is conducting hashtag searches on Twitter. By setting up a few searches with hashtags related to your brand, industry, or product, you can receive instant notifications when customers, clients, or competitors use key terms.31 A very popular approach to online research applies the concept of ethnography defined earlier to understand what consumers discuss about brands online (hint: a lot!). Netnography (cleverly labeled such because it combines the net and ethnography) is a form of qualitative research that tracks the consumption patterns and conversations of online consumers. It focuses on the social groups that customers create to inform one another about products, services, and brands. Companies like Campbell use this approach to identify the "genuine voices" of consumers and how they talk about brands—for example, gaining buyers' suggestions about how they use products to generate new recipes or applications.32 For marketers who want to collect data via surveys on the Web, a crowdsourcing platform, such as Short Task, is an effective medium. Short Task provides a place on the web where market researchers can post requests for one-off tasks that are typically not time intensive but do require human intelligence to be completed effectively. Tasks are divided up into four broad categories: research, data entry, writing, and design. Users can earn minimal amounts of money for completing these tasks. Using Short Task or a similar platform, such as MTurk or CrowdFlower, for collecting market research data can potentially be quicker and less costly than other methods marketers use to gather a large amount of responses because of the large audience of workers available to the firm and the relatively lower prices for them to perform required tasks.33 For market research that requires the inclusion of a specific group of respondents, such a platform may not be well suited, and instead seeking out focused panel data may be more appropriate. You may like to share selfies with friends, but did you know that it's possible companies are diving into Instagram and Pinterest to take a close look at your latest gems as well? Some firms use special software to scan photos to identify logos, facial expressions, and contexts so that they can learn more about how consumers use a client's brands in daily life. There are huge numbers of photos to look at; Instagram alone has about 40 billion photos to share with another 95 million being added every day. The practice is so new that privacy concerns are just starting to bubble up. For now, think twice about what you post.34 Across all of its platforms and forms, the Internet offers unprecedented ability to track consumers as they search for information on Google and other search engines. We've become so accustomed to just looking up stuff online that google has become a verb (as has friend). As consumers enter search terms like "lowest prices on J Brand jeans" or "home theaters," these queries become small drops in the ocean of data available to marketers that engage in online behavioral tracking. How do they know what we're looking at online? Beware the Cookie Monster! Cookies are text files that a website sponsor inserts into a user's hard drive when the user connects with the site. Cookies remember details of a visit to a website and track which pages the user visits. Some sites request or require that visitors "register" on the site by answering questions about themselves and their likes and dislikes. In such cases, cookies also allow the site to access these details about the customer. The technology associated with cookies allows websites to customize services, such as when Amazon recommends new books to users on the basis of what books they have ordered in the past. Consider this one: It is late evening, and you should be studying, but you just can't make yourself do it. So you grab your tablet and sign in to Netflix. And like every other time you sign in, Netflix offers up a bunch of movies and TV shows to tempt you away from the textbooks. But how does Netflix know what you want to see—sometimes they seem to anticipate your tastes better than your friends can! No, there isn't someone sitting at their office whose only job is to follow you around online to guess what you'll want to see next. These surprising connections are the results of predictive technology, which uses shopping patterns of large numbers of people to determine which products are likely to be purchased if others are—except in this case what you're "shopping" for is movies to watch. To figure out what movies or TV shows you are likely to enjoy, Netflix trained teams of people to watch thousands of movies and tag them according to attributes such as "goriness" or "plot conclusiveness." Netflix then combines those attributes with the viewing habits of millions of users.35 And voilà—Netflix knows just what to serve up to satisfy your viewing fix. You can block cookies or curb them by changing settings on your computer, although this makes life difficult if you are trying to log on to many sites, such as online newspapers or travel agencies that require this information to admit you. The information generated from tracking consumers' online journeys has become big business, and in massive quantities, it has become popularly known as Big Data, a topic we will discuss in more detail in Chapter 5. To date, the Federal Trade Commission has relied primarily on firms and industries to develop and maintain their own standards instead of developing its own extensive privacy regulations, but many would like to see that situation changed, and much discussion is afoot at all levels of government regarding online privacy rights. Proponents advocate the following guiding principles: Information about a consumer belongs to the consumer. Consumers should be made aware of information collection. Consumers should know how information about them will be used. Consumers should be able to refuse to allow information collection. Information about a consumer should never be sold or given to another party without the permission of the consumer. No data collection method is perfect, and online research is no exception—though many of the criticisms of online techniques also apply to offline techniques. One potential problem is the representativeness of the respondents. Many segments of the consumer population, mainly the economically disadvantaged and elderly, do not have the same level of access to the Internet as other groups. In addition, in many studies (just as with mail surveys or mall intercepts), there is a self-selection bias in the sample. That is, because respondents have accepted invitations to take part in online studies, by definition they tend to be the people who like to participate in surveys. As with other kinds of research, such as live focus groups or panel members, it's not unusual to encounter "professional respondents"—people who just enjoy taking part in studies (and getting paid for it). Quality online research specialists, such as Harris Interactive, Survey Sampling International (SSI), and Toluna, address this problem by monitoring their participants and regulating how often they are allowed to participate in different studies over a period of time. However, unfortunately, with the proliferation of online data collection, many new and unproven data providers continue to come into the industry. Therefore, in terms of online research, the venerable phrase caveat emptor (let the buyer beware) rules. Metrics Moment More and more, marketing is responsible for the e-commerce aspect of firms' web strategies. Bounce rate is a marketing metric for analyzing website traffic. It represents the percentage of visitors who enter the site (typically at the home page) and "bounce" (leave the site) rather than continuing to view other pages on the site. It is a straightforward metric to understand and is based on the following formula: Bounce rate=Total number of visitors viewing one page onlyTotal entries to the web page Bounce rate=Total number of visitors viewing one page onlyTotal entries to the web page A site's bounce rate is easy to track with tools like Google Analytics. These tools can show the bounce rates on different pages of a website, how the user came to the site (organic search, paid search, banner ad, etc.), how the bounce rate has changed over time, and other data so that the marketer can really dig into where the leak is occurring. Marketers use bounce rates to determine whether an entry page effectively generates visitors' interest. A bounce rate, simply put, is the measure of how many visitors come to a page on a website and leave without viewing any other pages. An entry page with a low bounce rate means that this first page encourages visitors to view still more pages and continue deeper into the website. High bounce rates, on the other hand, typically indicate that whatever visitors encounter on that first "hit" isn't interesting enough to make them want to check out more.36 Apply the Metrics A rule of thumb for website effectiveness is that great websites should fulfill three basic criteria: (1) The site should be attractive, (2) the site should be easy to navigate and get you where you want to go, and (3) the site should have up-to-date information (no old stuff). When you bounce off of a website, does it tend to be for one or more of these reasons? Are any of them more important than others to you? Consider the bounce rate metric we describe. Like any marketing metric, decisions should not be made based on the bounce rate alone. What other considerations should the marketer use to evaluate the effectiveness of a website? There are other disadvantages of online research. Hackers can actually try to influence research results. Competitors can learn about a firm's marketing plans, products, advertising, and other proprietary elements when they intercept information from these studies (though this can occur in offline studies just as easily). Because cheating has become so rampant, some companies today use a new technology called cross-browser digital fingerprinting to identify a specific computer even when that machine is using a different browser to access the same website. This approach allows companies to identify respondents who fake responses or professionals who game the industry by doing as many surveys as possible.37 Data Quality: Revisiting GIGO—Garbage In, Garbage Out We've seen that a firm can collect data in many ways, including focus groups, ethnographic approaches, observational studies, online surveys, and controlled experiments, among others. But how much faith should marketers place in what they find out from the research? This question gets at the center of the efficacy of evidence-based decision making. That is, one can derive consumer insights based on evidence, but without knowledge of the quality of the data that was translated into information and eventually the insights, it's impossible for marketers to gauge the potential of their decisions to actually be the optimal ones! Think of it this way: All too often, marketers who commission a study assume that because the researchers give them a massive report full of impressive-looking numbers and tables, they must be looking at the "truth." Unfortunately, there are times when this "truth" is really just one person's interpretation of the facts. At other times, the data researchers use to generate recommendations are flawed. Early in this chapter we brought up GIGO: "garbage in, garbage out."38 That is, your conclusions can be only as good as the quality of the information you use to make them. Typically, three factors influence the quality of research results—validity, reliability, and representativeness. Validity is the extent to which the research actually measures what it was intended to measure. Validity can be further broken down into internal validity and external validity. Internal validity refers to the extent that the research design was set up in such a manner that what was intended to be measured was accurately measured and not obscured (for instance, by the accidental inclusion of any factors not intended to be included in the study). This is typically accomplished in a highly controlled setting (such as a laboratory) where it is easier to avoid the introduction of extraneous factors that could muddy the results obtained. External validity refers to the extent that research results are practically applicable to the relevant target market (and not just the specific study participants who were intended to represent that target market). Another way of thinking about this is whether the research findings would hold up when leveraged out in the real world. Validity was part of the problem underlying one of the most famous debacles in marketing history—the New Coke fiasco in the 1980s. At that time, Coca-Cola (one of the world's more prolific brands) underestimated people's loyalty to its flagship soft drink after it replaced "Old Coke" with a new, sweeter formula in an attempt to attract more Pepsi drinkers. This blunder was so huge that we still talk about it today even though it happened before your humble authors were even born (well, not quite . . . )! But seriously, every student of marketing should know about this one. In a blind taste test, the company assumed testers' preferences for one anonymous cola over another was a valid measure of consumers' preferences for a cola brand. Arguably, we can also say that the use of a sip test is flawed (and lacking degrees of external validity) in that it is set up so that consumers try the colas in small quantities, as opposed to the larger quantities more typically experienced by consumers when enjoying a can, a bottle, or a glass of cola in a more leisurely setting.39 Coca-Cola found out the hard way that measuring taste only is not the same as measuring people's deep allegiances to their favorite soft drinks. After all, Coke is a brand that elicits strong consumer loyalty and is nothing short of a cultural icon. Tampering with the flavors was like assaulting mom and apple pie. Sales eventually recovered after the company brought back the old version as "Coca-Cola Classic."40 Reliability is the extent to which the research measurement techniques are free of errors. Sometimes, for example, the way in which a researcher asks a question creates error by biasing people's responses. Imagine that a hipster male interviewer who works for El Dorado rum stops female college students on spring break in South Padre Island campus and asks them if they like rum products and would they like a free taste. Do you think their answers might change if they were asked the same questions on an anonymous survey they received in the mail? Most likely, their answers would be different because people are reluctant to disclose what they actually do when their responses are not anonymous. Researchers try to maximize reliability by thinking of several different ways to ask the same questions, by asking these questions on several occasions, or by using several analysts to interpret the responses. Thus, they can compare responses and look for consistency and stability. Reliability is a problem when the researchers can't be sure that the consumer population they're studying even understands the questions. For example, kids are difficult subjects for market researchers because they tend to be undependable reporters of their own behavior, they have poor recall, and they often do not understand abstract questions. In many cases, children cannot explain why they prefer one item over another (or they're not willing to share these secrets with grown-ups).41 For these reasons, researchers have to be especially creative when they design studies involving younger consumers. Figure 4.5 shows part of a completion test that a set of researchers used to measure children's preferences for TV programming in Japan. Representativeness is the extent to which consumers in the study are similar to a larger group in which the organization has an interest. This criterion underscores the importance of sampling: the process of selecting respondents for a study. The issue then becomes how large the sample should be and how to choose these people. We'll talk more about sampling in the next section.

longitudinal design

a technique that tracks the responses of the same sample of respondents over time

information

interpreted data

neuromarketing

the phases by which firms develop new products, including idea generation, product concept development and screening, marketing strategy development, business analysis, technical development, test marketing, and commercialization

market research

the process of collecting, analyzing, and interpreting data about customers, competitors, and the business environment in order to improve marketing effectiveness

reverse engineering

the process of physically deconstructing a competitor's product to determine how it's put together

telemarketing

the use of the telephone to sell directly to consumers and business customers

exploratory research

a technique that marketers use to generate insights for future, more rigorous studies

data

raw, unorganized facts that need to be processed

evidence-based decision making

A marketer's capability to utilize all of the relevant information available in order to make the best possible marketing decisions.

bounce rate

A marketing metric for analyzing website traffic. It represents the percentage of visitors who enter the site (typically at the home page) and "bounce" (leave the site) rather than continue viewing other pages within the same overall site.

marketing dashboard

a comprehensive display and access system providing company personnel with up-to-the-minute information necessary to make decisions

case study

a comprehensive examination of a particular firm or organization

Netnography

a form of qualitative research that tracks the consumption patterns and conversations of online consumers

market intelligence system

a method by which marketers get information about what's going on in the world that is relevant to their business

mechanical observation

a method of primary data collection that relies on machines to capture human behavior in a form that allows for future analysis and interpretation

convenience sample

a nonprobability sample composed of individuals who just happen to be available when and where the data are being collected

research design

a plan that specifies what information marketers will collect and what type of study they will do

market research online community (MROC)

a privately assembled group of people, usually by a market research firm or department, utilized to gain insight into customer sentiments and tendencies

Marketing Information System (MIS)

a process that first determines what information marketing managers need and then gathers, sorts, analyzes, stores, and distributes relevant and timely marketing information to system users

unobtrusive measures

measuring traces of physical evidence that remain after some action has been taken

syndicated research

research by firms that collect data on a regular basis and sell the reports to multiple firms

custom research

research conducted for a single firm to provide specific information its managers need

validity

the extent to which research actually measures what it was intended to measure

reliability

the extent to which research measurement techniques are free of errors

cross-browser digital fingerprinting

an approach to identifying fake responses to online questionnaires by correlating specific computers used with multiple browsers

Ethnography

an approach to research based on observations of people in their own homes or communities

primary data

data from research conducted to help make a specific design

secondary data

data that have been collected for some purpose other than the problem at hand

marketing decision support system (MDSS)

the data, analysis software, and interactive software that allow managers to conduct analyses and find the information they need

representativeness

the extent to which consumers in a study are similar to a larger group in which the organization has an interest

internal validity

the extent to which the results of a research study accurately measure what the study intended to measure by ensuring proper research design, including efforts to ensure that any potentially confounding factors were not included or introduced at any point during the execution of the research study

external validity

the extent to which the results of a research study can be generalized to the population its sample was intended to represent, providing a higher level of confidence that the findings can be applied outside of the setting where the research was conducted

back-translation

the process of translating material to a foreign language and then back to the original language

intranet

an internal corporate communication network that uses internet technology to link company departments, employees, and databases

Step 6: Analyze and Interpret the Data

Once market researchers collect the data, what's next? It's like a spin on the old "if a tree falls in the woods" question: "If results exist, but there's no one to interpret them, do they have a meaning?" Let's leave the philosophers out of it and just say that marketers would answer "no." Data need interpretation if the results are going to be useful. To understand the important role of data analysis, let's take a look at a hypothetical research example. Say a company that markets frozen foods wishes to better understand consumers' preferences for varying levels of fat content in their diets. They conducted a descriptive research study where they collected primary data via telephone interviews. Because they know that dietary preferences relate to gender (among other aspects), they used a stratified sample that includes 175 males and 175 females. Typically, marketers first tabulate the data, as Table 4.3 shows—that is, they arrange the data in a table or other summary form so they can get a broad picture of the overall responses. The data in Table 4.3 indicate that 43 percent of the sample prefers a low-fat meal. In addition, there may be a desire to cross classify or cross tabulate the answers to questions by other variables. Cross tabulation means that we examine the data that we break down into subgroups—in this case, males and females separately—to see how results vary between categories. The cross tabulation in Table 4.3 reveals that 59 percent of females versus only 27 percent of males prefer a meal with low-fat content. Researchers may wish to apply additional statistical tests that you may learn about in subsequent courses (now there's something to look forward to!). Table 4.3Examples of Data Tabulation and Cross-Tabulation Tables Fat Content Preference (number and percentages of responses) Do you prefer a meal with high-fat content, medium-fat content, or low-fat content? Questionnaire Response Number of Responses Percentage of Responses High fat 21 6 Medium fat 179 51 Low fat 150 43 Total 350 100 Fat Content Preference by Gender (number and percentages of responses) Do you prefer a meal with high-fat content, medium-fat content, or low-fat content? Questionnaire Response Number of Females Percentage of Females Number of Males Percentage of Males Total Number Total Percentage High fat 4 2 17 10 21 6 Medium fat 68 39 111 64 179 51 Low fat 103 59 47 27 150 43 Total 175 100 175 100 350 100 Based on the tabulation and cross tabulations, the researcher interprets the results and makes recommendations. For example, the study results in Table 4.3 may lead to the conclusion that females are more likely than males to be concerned about a low-fat diet. Based on these data, the researcher might then recommend that the firm target females when it introduces a new line of low-fat foods.

sampling

the process of selecting respondents for a study