The article below that discusses marketing research and its role within an organization. Address the following points in your essay:

1. Summarize the article by discussing the main points of the article.
2. Relate the theoretical aspects of market research (both qualitative and quantitative) from Chapters 1 and 2, including overall strategic planning and globalization.
3. Discuss the relevance of this article with respect to how advancements in technology have impacted this company's ability to perform market research.
4. What questions might you pose to the author of this article? Do you see any ethical implications within this article?

Introduction

Strategicmarketingis all about understanding customers and competitors and that comes partially frommarketing research. The successful use ofmarketing researchleads to superior financial results and market positions (e.g., [5]; [29]). [26] found thatmarketing researchwas the second most important area that students should have conceptual knowledge in, second only to consumer behavior, but more essential than promotion and advertising, sales, and pricing. This held true for entry-level jobs, mid-level jobs, and upper management-level jobs. Hence, an introduction in businessresearchmethods is often a mandatory module in a core college of business curriculum (e.g., [1]; [24]); andmarketing researchis a mandatory class in most undergraduatemarketingmajor programs.

As an industry,marketing researchhas enjoyed decades of almost continuous year-over-year growth. Between 2006 and 2016, for example, the revenue of the top 50 USmarketing researchfirms grew from $ 7.7 billion to $ 11.6 billion.[3] Globally, in 2016 the market was an estimated $ 44.6 billion. The [3] projects a 19% increase in marketresearchanalysts' positions over a 10-year time span (compared with 7% for other occupations). More recently, growth was further fueled by the Big Data and analytics trends (e.g., [6]; [7]; [13]; [16]; [27]) and scarcity of such skills is already felt by recruiters (e.g., [15]). According to LinkedIn's data, "statistical and data mining" is the second most sought-after hard skill by recruiters as of January 2018.[4]

Business decision makers have voiced their dissatisfaction with commercialmarketing research(e.g., [2]; [9]; [19]). The main complaint is that they would like to get more actionable insights from theirmarketing researchdepartment and they expect more actual return on theresearchinvestments (ROI). Supplier-sidemarketingdirectors complain thatmarketing researchas taught does not reflect the real world and that recent graduates are too academic and lack awareness of the reality ofmarketing research(e.g., [14]; see also [22]; [24]). This situation has likely gotten worse over the past 5-10 years, that is, the ability to produce or consumemarketing researchhas become even more challenging given the Big Data and analytics trends.

How can universities align their requiredmarketing researchclass(es) with commercial practices and what skills, including newer more recent ones (e.g., Big Data), and emerging trends should they cover? In thisarticle, we review the literature onmarketing researchand analytics requirements, and report the results of interviews with a sample of alumni from a US mid-west undergraduatemarketingprogram. Although there is no one size fits all for an undergraduatemarketing researchcourse (e.g., [24]), ourresearchidentifies several (potential) gaps thatmarketing researchand analytics instructors should think about when putting their course or curriculum together.

Previous research on gaps

The general complaint from industry is that there is a lack of actionable insights and too little return on investment inresearchand analytics. Several studies[5] have looked more specifically into what skills are not sufficiently strong.

[18] was probably one of the first to survey practitioners (N= 69) to find out whatmarketing researchskills were most important. The ability to interpret data was found to be the most important, and the ability to define problems was found to be the second most important skill. [25] found that seven out of eights skills that were assessed in his study were perceived to be below average: quantitative skills, ability to conceptualize and definemarketing researchproblems, ability to designmarketing researchprojects, ability to gather data, ability to interpret data, and written and oral communication skills. [10] surveyedmarketingfaculty (N= 191) of Association to Advance Collegiate Schools of Business (AACSB)-accredited universities asking them to assess how well current MBA programs provide students with professionalmarketing researchskills for entry-level jobs. A list of 18 skills was used to identify if/where gaps existed between what commercial practice needs and what academics offers. Many gaps were identified, but among the top three largest gaps: (1) the ability to design marketresearchprojects, (2) the ability to conceptualizemarketing researchproblems, and (3) the ability to interpret the results. [8] interviewing 66 alumni from a Western United States university found that they perceived themselves under-prepared in (1) technical skills (e.g., Excel, SPSS, etc.), (2) quantitative skills, and (3) oral and written communication, and over-prepared in their understanding of themarketingconcept. [28] interviewed 203 practitioners and academics (roughly equal number of both groups). Several topics were called out as necessary at a much higher rate by practitioners than by academics including (1) analysis and interpretation, (2) information usage, and (3) communication and reporting ofresearch. They also asked about what specific analytical techniques should be covered. Here too we see a difference between academics and practitioners, the latter finding a bigger need for factor analysis, discriminant analysis, conjoint analysis, and cluster analysis. The specific reasons why these techniques were found to be important by practitioners is because factor analysis is a common technique in many brand studies (e.g., brand studies are about 6% of the overall globalmarketing researchrevenue[6]); cluster analysis and discriminant analysis are the major tools in market segmentation studies, and conjoint analysis is a standard technique in most product development and improvementresearch(roughly about $ 1 billion is spent annually on conjoint[7]) and probably overall could be considered the most popularmarketing researchtechnique.

Previous studies focused on opinions of academics, alumni, practitioners, or gaps between academic faculty and practitioners. [26] content-analyzed 500 job listings (pulled from Monster.com). Top technical skills asked for across entry-level, mid-level, and upper management-level listings included (1) MS Office with an average of 47% and (2) analytics (e.g., database analysis, data mining, analytics, etc.) with an average of roughly 40%, and having the highest percentage that stated that these skills were required for upper management positions. For the non-technical domain, the top skills included (1) oral and written communication and (2) team and leadership skills; yet even here analytical analysis scored fairly high. [9] took a slightly different approach: They compared perceptions of executives (the consumers ofmarketing research) with perceptions from corporatemarketingresearchers (the producers ofmarketing research). They interviewed more than 800 global executives and asked line managers specifically where theirmarketing researchcounterparts fell short. The top three areas where the line managers perceived the biggest skill gaps are as follows: (1) the lack of understanding of a business issue, (2) the ability to call out the "so-what/now what," and (3) the ability to translate theresearchfindings into actionable recommendations. Gap 2 refers to calling out the business implications of a given result, whereas gap 3 refers to a concrete set of recommended actions. [17] surveyed 33 executives recruited from their LinkedIn network. They used one open-ended question: "Whatmarketinganalytics skills do you think undergraduate students should acquire to become more marketable?" Key topics mentioned included web analytics,marketingmetrics, and predictive analytics.

Study survey methodology

We created an online survey to find out about what topics, alumni felt, could have been addressed better in their undergraduate studies, and specifically with respect tomarketing researchwe wanted to know what skills and knowledge were perceived to be most important. The survey included some general questions as to when they had graduated, what area of business they currently work in, and what their involvement inmarketing researchis. We used the following categories: not involved, minor involvement, moderate involvement, and significant involvement. We also asked them if they felt their undergraduate education had prepared them for their current job. We used two key questions to get insight into whatmarketing researchtopics were missing. The first question was an open-ended question: "Please tell us the top three areas you felt your undergraduate did not prepare you well for." We chose this question to get insight into what, if any,marketing researchtopics were missing in the overall context of their job not justmarketing research. As the list of potential topics is very long, we opted to use an open-ended format. We also wanted to know where any gaps would stand relative to non-marketing researchgaps. This will convey the importance of pursuing changes in themarketing researchcurriculum to a college of business administration. The second question came from our recognition that many of the existingmarketing researchbooks all (1) look very similar and (2) many (in some cases all) dedicate few (or in some cases almost none) pages to important topics such as interpreting data, or client interaction skills. So, an initial list of topics was generated by reviewing a series of relatively well-knownmarketing researchbooks. We added (1) topics that were found in the literature to be important, (2) some topics we knew from our practice to be important, and (3) topics from emerging methodologies such as Big Data and neuroscientificresearch.

We surveyed undergraduate alumni inmarketingand international business from a mid-west AACSB-accredited university. After approval was obtained from the university's Institutional Review Board (IRB), a short Qualtrics survey was sent out to 482 alumni. We ended up with 148 valid responses, that is, a response rate of about 30%. Of the sample, 19.2% graduated in the year 2000 or before, 16.7% graduated in between 2001 and 2005, 20% graduated between 2006 and 2010, 28.3% graduated between 2011 and 2015, and 15.8% graduated between 2015 and 2018. About 45% of the sample said that they had moderate to significant involvement inmarketing research, 39% claimed that they had minor involvement inmarketing research, and 16% had no involvement inmarketing research. Their jobs covered a wide range including branding, advertising,marketing research, product development, social media, and sales. Most respondents had a bachelor's degree (77%), 22% had a master's degree, and 1% had a doctoral degree. In response to how whether they felt their undergraduate training had prepared them well for their job, 75% agreed, whereas 25% did not.

Coding of the open-ended question

The coding process was done step-wise: we first reviewed all the comments and then started grouping comments that were similar together. This review and grouping is an iterative process, and sometimes groups can be merged and comments can be re-grouped. For example, one respondent may call out "Data analysis," and another "Data driven insight." Both responses were categorized under a main theme "Marketing Researchand Analytics." The responses were interpreted and coded by two independent coders. Both coders agreed on how to categorize the individual comments.

Results

As a first analysis, we looked at whether they felt prepared by their undergraduate education varied by functional area of their current job. Table 1 shows the results.

Graph: Table 1. Whether alumni felt prepared versus current job responsibilities.

Undergraduate prepared well?Job responsibilities current job (check all that apply) (N= 148)YesNoBranding (N= 50)80%20%Sales (N= 63)79%21%Market research (N= 36)70%30%Advertising (N= 45)84%16%Product development (N= 29)66%34%Social media (N= 32)88%12%Logistics (N= 17)82%18%Even though, in general, the percentages of respondents who felt prepared are high. We do see that those withmarketing researchresponsibilities have the second lowest percentage of respondents feeling prepared. However, when directly testing whether preparedness was related to the degree ofmarketing researchinvolvement a chi-square analysis turned out to be non-significant.

In Table 2, we show the results of our first open-ended question: "What are the top three aspects that undergraduate education did not prepare you well for?"

Graph: Table 2. Incidence of "top three aspects" (that undergraduate education did not prepare you well for)a [1].

Respondents who are involved in marketing research (N= 123)Respondents who are currently not involved in marketing research (N= 24, 6 respondents had no comments at all)Number of respondents mentioning at least one topic in this category (N)Total count of topics mentioned in this category (C)Number of respondents mentioning at least one topic in this category (N)Total number of topics mentioned in this category (C)Data and analysis314633Marketing223222Sales161611Digital marketing111133Business communications9934Finance2222Management34341 a We left out the miscellaneous comments.

It is interesting and meaningful to see that even though no reference tomarketing researchor analytics was being made in this question, the general topic "Data and analytics" received the most mentions. We also note that "communication" receives a fairly high number of mentions, as does sales. We investigated whether calling out "Data and analytics," as an area where they could have been prepared better in, was related to year of graduation (as coded in intervals, see above). The 2test between graduation and "Data and analytics" was non-significant (2statistic = 12.7;p=.391). The correlation between the original graduation year and the analytics variable was.088 (p=.l340), also non-significant. Hence, the need for more on "Data and analytics" is not just a recent trend.

Table 3 breaks down the specific comments that went into the broader category "Data and analytics."

Graph: Table 3. Incidence of "top three aspects missing" in the "Data and analytics" category (that undergraduate education did not prepare you well for).

Comments (N= 31)N(number of respondents who made this comment)Data analysismore practice with analytical tools10Story telling with data5Big Datadigesting Big and managing Big Data4Data visualization2Using data for decision makingdata-driven decision making2Importance of datavarious types of data2Artificial intelligence2From data to insightsdata-driven insights2Forecasting2Marketing research2Data integration1Data science1Pulling information from data1Segmentation1Sizing1How to apply marketing research techniques1Survey design1Marketing mix modeling1Quantified justification1Dealing with information1Market analysis1Small data1There are a variety of comments under this bucket. If we further try to categorize the comments in Table 2, we see that the biggest subcategory involves data analysis followed by story telling, and surprisingly Big Data.

In Table 4, we report the results of a closed-ended question: "What are the top 3 most important aspects of your job?"

Graph: Table 4. Percentage of top three most important aspects of their job.

Topic (ordered by %important)Part of current positionTop three most important skillsBaseN= 148Client interaction skills85.8%70.3%Interpreting data83.8%50.7%General analytics91.2%39.2%Analytical intuition81.8%18.9%Customer satisfaction studies69.6%17.6%Brand research59.5%16.2%New product idea generation54.7%8.8%Social data62.2%9.5%Marketing mix modeling47.3%8.1%Attribution modeling33.1%7.4%Market segmentation48.0%7.4%Numeracy73.0%6.1%Big Data48.0%5.4%Machine learning and artificial intelligence18.9%4.7%New product concept testing47.3%4.7%Experiments33.1%4.1%U&A studies38.5%2.7%Text analytics27.0%2.7%Neuromarketing research8.8%0.0%It is surprising that the most important aspect called out by the alumni involved client interaction skills. Consistent with previousresearchon practitioner-academic gaps, the second most important topic involves interpretation of data. The third and fourth most important topics involve general analytics and analytical intuition. Fifth, customer satisfaction and brandresearchare being mentioned. Neuromarketing and behavioral economics are not mentioned yet; perhaps, these topics will need more time to become widely recognized need areas. Topics did not change dramatically by graduation year, for all but a few exceptions: machine learning and artificial intelligence,marketingmix modeling, brandresearch(about half of those for whom this was an important topic graduated after 2010), Big Data, and analytical intuition. The overall number of respondents calling out machine learning and artificial intelligence, Big Data, andmarketingmix modeling is too small to report meaningful differences.

Discussion

Researchover the past 20 years and the current studies have identified several gaps: (1) understanding the business issue, (2) defining amarketing researchproblem, (3) designingmarketing research, (4) the ability to analyze data, (5) the ability to interpret results, (6) the ability to translate results into actions and get the insights activated, (7) client interaction skills, and (8) specific types of studies such as customer satisfactionresearch, new product developmentresearch, and brandingresearch. Some of these topics have been found consistently across several studies (e.g., the ability to interpret data), whereas others came out of a single study.

The eight gaps above are not all stand-alone skills, that is, being strong in one skill will also enhance being strong in another. One, understanding a business issue and client interaction skills are closely related. If trust exists between a business decision maker and themarketingresearcher, more information will be shared and hence it is more likely that the business issue will be fully understood (e.g., [11]). Likewise, client interaction skills and information usage are closely related. When decision makers receive business insights, acting on those insights will carry an information usage risk (e.g., [11]). That risk will be reduced with strong client interaction skills.

Implications

First, to close academic-practitioner gaps, we believe it is important to increase content and time dedicated on the eight gaps. Some of them may be more tacit skills and hence should be developed in, as much as possible, "real-world interactions." Internships are great for doing this. Working with real, say local clients, during amarketing researchcourse is something that some schools do. However, there are several reasons why we believe one needs to be cautious here. First, working with real clients takes a significant amount of time and this would go at the expense of spending time on other needed topics. Second, in many cases, the students may not really be prepared enough yet to doanything meaningful. Finally, we believe tacit skills will be picked up fast enough once the student enters the workplace. It is much harder at that point to catch up on foundational skills such as "Analytics."

Second, we believe amarketing researchcourse should limit its treatment of a long list ofmarketing researchtechniques and approaches and offer a more holistic approach where students need to develop a client story from various data sources and analyses. More specifically, instead of discussing the technical details of, say, at-test, or all the nitty-gritty details of sampling, the course should focus more on how to interpret results from a variety of techniques and approaches (e.g., regression, factor analysis, cluster analysis, etc.) and how to read and interpret marketresearchresults and other business information. Seven out of the eight skills have an integrating component. This requires a very different teaching approach. In manymarketing researchtext books, techniques andresearchapproaches are discussed as stand-alone topics. However, in the real world, the challenge is the other way around: there is a problem, and now one needs to choose from a large toolbox and decide what tool is best for the problem at hand. What makes this even more challenging is the fact that there may not be a single best approach. In a practical project, one will have several types of analyses, some quantitative, some qualitative, some may involve statistical tests, others won't. The challenge now is to integrate all this information and decide what it all means if anything and how valid overall you can claim your recommendations are.

Third,marketingundergraduates are more likely to become "consumers" ofmarketing researchmuch more so than that they will become "producers" ofmarketing research. Hence, as an example, they do not need to know how to run a regression, a conjoint, a factor analysis, and so on in R. They do need to know in whichmarketingsituations these techniques can be useful and how they should be interpreted, evaluated and assessed.

Fourth, with explosive growth in data availability, coming up with actionable insights has only become more challenging (e.g., [12]; [23]). [21], [4], and [20] identified an issue thatmarketing researchcourses were too focused on primary data collection and with little attention given to secondary data (e.g., the firm's own data, secondary data from external suppliers, or data scraped from online sources). Dealing with a variety of datasets, and possibly very large datasets, needs to be covered more extensively (see [30]). To fully learn how to deal with Big Data in all its varieties requires special equipment, software, and statistical models to be made useful. That would be out of scope for a basicmarketing researchcourse. However, students could be offered a framework that outlines how to formulate the right questions to ask in a broad sense and explore all of the paths available. Too often, researchers fall back on traditional and outdated approaches and do not leverage the full spectrum of what can be done.

Fifth, customer satisfaction, branding, and new product developmentresearchare ubiquitous and often very significant parts of the budget and allotted time goes to such activities. Hence, we believe these should be covered at least at a basic level.

Finally, this is not unique tomarketing research, we need to encourage students continuing education. For a university, this may mean actively offering post-graduate training on additional topics to give students an opportunity to catch up on new topics.