This chapter explains why the purchase funnel – sometimes known as the “consumer decision journey” or the “consumer buying path” – is a valuable analytical framework for marketing experts engaged to provide an external expert opinion to inform the finder of fact in litigation matters. The value inherent in the purchase funnel framework is that, unlike most economic analyses or analyses grounded in the strategy literature, the purchase funnel does not treat consumers as making a single discrete decision. Instead, it recognizes that for each decision that any one consumer makes, the consumer must pass through a series of distinct hurdles progressing from awareness to consideration, conversion, and post-purchase. Laying out these steps can be helpful in a large variety of litigation contexts.

The problems referred to in the title of this chapter concern evaluating a given variable when it is one of several that have combined to bring about a result. In some cases, there is an easy market solution. Imagine that you contract to buy a house and then the beautiful kitchen stove, one of many things that attracted you to the property, is destroyed before you close the transaction or occupy the property. How much should the price now be reduced? Here there is an upper limit based on the cost of a comparable replacement appliance. A more precise valuation would also be easy if identical houses, lacking this one feature, had recently been sold. The stove is just a piece of the larger transaction and, with these convenient facts, there is not much of a “component valuation problem.” Additionally, the stove is unlikely to have been of greater value because of its interaction with other items in the house; colors and sizes are fairly standardized. “Conjoint analysis” – a term that usually refers to survey evidence that tries to elicit the value of a component – is therefore unnecessary, or at least uncomplicated, because value does not depend on an interaction among variables in a way that is not directly observed. It is also interesting because it does not present a difficult game theory problem, or result that might be described in common parlance as something that depends on the relative bargaining skill of the parties.

Online advertising has quickly become one of the most important avenues through which brands reach consumers. It is lauded as one of the most effective ways for a business to grow, acquire new customers, and spread information.1 By some estimates, Internet advertising is a nearly $300 billion business.2

Marketing analyzes the behavior of buyers and sellers and often does so at the individual or segment level. Thus, differences among sellers or heterogeneity among buyers are often areas of focus for marketing analysis. Much of the class certification process involves assessments regarding the similarity – or lack thereof – in class members’ situations. This has made marketing and its analytic tool kit for examining markets at the disaggregate level well suited to provide insight into key issues in class certification.

This chapter demonstrates that analyzing what people post on social media sites can yield powerful evidence for use in commercial litigation. This kind of analysis is a natural way of listening in on people’s conversations about products, services, brands, trademarks, and patents, all of which are often the subject of high-stakes lawsuits. An argument is made that an expert who could commission an opinion survey could now also commission a social media analysis, which will contribute to a more persuasive and often more time-appropriate body of evidence upon which to rely. Examples of the use or potential use of social media in litigation are presented, including cases that used social media evidence, such as the US government’s lawsuit against Lance Armstrong; a case involving a meat byproduct sometimes referred to as “pink slime”; a case centering on an allegedly deceptive Super Bowl beer advertisement; and many cases involving disputes having to do with intellectual property. Finally, we compile and discuss a number of issues relating to the use of social media in litigation. These issues include questions about social media’s authenticity, the best way to preserve it, and several other analytical and legal questions. The chapter concludes with a discussion of how social media analysis can migrate from the periphery of litigation evidence toward having a more central role.

Data is the lifeblood of the digital economy. Much of the data in use today is generated by the everyday activities of consumers as they communicate, shop, travel, work, or engage in routine interactions with other consumers, businesses, and government entities through digital systems, platforms, and media. This has led to an enormous accumulation of data about individual consumers that can directly or indirectly provide information about their characteristics, preferences, activities, or behaviors.

Puffery is a concept that purports to be about things consumers ignore and don’t rely on. It is in fact a concept about things courts ignore and won’t rule on. At the moment, marketing and other empirical work has essentially nothing to say about puffery in the courts; puffery consists of precisely the elements of advertising for which courts neither require nor allow empirical evidence of consumer reaction.1 That doesn’t make the doctrine wrong, but it does mean that explanations for the doctrine should not be founded on unsupported, mostly unsupportable judicial assertions about how consumers think and what advertising claims they disregard. Instead, this chapter will argue, puffery should be about what kinds of advertising claims are too difficult to evaluate for their truth in judicial settings. That’s an epistemological determination that judges are actually well qualified to make, unlike the idea that consumers don’t rely on puffery.

Surveys in trademark, trade dress, and false advertising cases often focus on liability. For example, in trademark cases, the focus of survey evidence has often been on whether consumers confuse the two marks. Similarly, survey evidence in false advertising cases has focused on whether the at-issue advertising claim misleads or deceives consumers. Surveys that address these issues of alleged confusion or deception measure consumer “perception,” and the results are often the centerpiece of a plaintiff’s liability arguments. While such questions may be central to cases that seek an injunction or aim to prevent the issuance of a new trademark, they are less relevant in questions of impact or injury.

Conjoint analysis is a commonly used methodology in marketing – it can provide crucial information for new product development,1 product line extensions,2 design of product packaging,3 pricing,4 and various other applications for which it is important to understand consumer preferences. Because conjoint analysis can help market researchers, managers, and ultimately anyone else answer the question of which attributes of a product impact consumer purchase decisions, and to what extent, the method has become more and more frequently applied in the realm of litigation cases.5 For example, in the legal domain, conjoint surveys can contribute to understanding and determining purchase reasons, consumer valuations, and potentially associated damages in matters with claims regarding product liability, false advertising, lack of disclosures, data/privacy breaches, infringement of intellectual property, and antitrust issues. Even though conjoint analysis seems to be a useful instrument when tackling certain legal challenges involving consumer purchase decision-making, courts have frequently rejected conjoint analyses from allowable evidence due to concerns regarding the validity or applicability of its results. The reasons for factfinders’ skepticism are manifold and range from lack of specific expertise to misapplications of the technique. While lack of expertise can be preempted through careful selection of a proficient expert, the process of conducting a reliable conjoint analysis presents hurdles and challenges to anyone: sometimes, conjoint analysis is simply an unsuitable methodology for the question at hand, and at other times intricate aspects of the survey design or sample selections are disregarded. In the same vein, experts have expressed on various occasions that the application of the conjoint methodology may run into conceptual problems such as ignoring supply-side factors when determining consumers’ loss for a specific product characteristic that may have been promised but was not provided. This chapter outlines common applications of conjoint analysis in litigation, describes the basic concepts and approaches in properly applying conjoint analysis, and points to misapplications of conjoint analysis in litigation matters. It will also make evident how conjoint survey design, data analysis, and use of results in litigation matters depend on the complexities of each case.

There is a long-standing consensus on the need to fight poverty and eliminate it. Some fifty-five years ago, the American President Lyndon B. Johnson launched a “War on Poverty” in his 1964 State of the Union Address. Nevertheless, poverty is still a striking problem. In the United States, more than 46 million Americans lived in poverty in 2012.2 Worldwide, billions live on less than eight US dollars a day,3 and hundreds of millions on less than one dollar a day.4 Poverty is a complex, multifaceted, and persistent problem.5

In 2014, two titans in the food industry squared off in the Supreme Court of the United States. POM Wonderful, LLC is a well-known beverage producer, largely credited with ushering in America’s love affair with pomegranate juice. POM Wonderful produces a number of pomegranate-based beverages. One such beverage is a “Pomegranate Blueberry” juice that consists primarily of, well, pomegranate and blueberry juice. Not to be left out of the bourgeoning pomegranate juice market, the Coca-Cola Company began manufacturing and selling its own version of a pomegranate blueberry juice drink: Minute Maid Enhanced Pomegranate Blueberry Flavored 100% Juice Blend. It consists of 99.4 percent apple juice.