Category Archives: Marketing Research

New England in Fortune’s 100 Best Companies to Work For

CapeCod by laura padgettThe recent edition of Fortune Magazine (07 February) identifies the 100 Best Companies to Work For. Living in New England, it was easy to assume that the majority of firms identified were going to be local firms. For without question, we’re the best at innovation, entrepreneurship, creativity, information technology and marketing – just ask us!

The reality of the situation paints a less than optimistic picture for our region. Of the 100 Best Companies to Work For, only eight are located in New England.

New England in the Fortune Top 100 Best Comanpies to Work ForThree are in the top 50 (Boston Consulting Group, Stew Leonard’s and Bingham McCutchen). Congratulations to the Boston Consulting Group for being ranked second nationally. You really are our cash cow. Stew Leonard’s climbed the most over its 2010 ranking and Bingham McCutchen dropped the most. Four are from Massachusetts, two from Rhode Island and two from Connecticut. Missing are companies from New Hampshire, Vermont and Maine.

The eight New England companies identified employ a total of 26,488 people and have a total annual growth rate of -1 percent. Certainly we can do better. Check that – our long term sustainable economic viability requires that we do better. Make your company fun, rewarding and exciting to work for today. The next list comes out in 11 months. The time has come (to borrow an extreme sports cliche) to go big or go home.


Country-Level Segmentation Using K-Means Cluster Analysis

Cluster Plot

Using data from the International Monetary Fund World Economic Outlook 2009 and The Global Enabling Trade Report 2009 from the World Economic Forum, I thought that it would be interesting to develop macro-level country clusters based on three variables: percent growth in gross domestic product from 2008 to 2009 (GDPG), percent population growth from 2008 to 2009 (POPG) and an assessment of the openness of the country to business endeavors (OPEN: the Enabling Trade Index – ETI) from 2009. Complete data for 119 countries is available, attainable and used in this example.

Cluster analysis is a statistical technique that groups individuals (in this case, countries) into clusters so that the objects in the same cluster are more similar to one another, based upon the characteristics investigated, than they are to individuals in other clusters. All data was analyzed using the open source R statistical package. One of the limitations of cluster analysis is identifying the optimal number of clusters to develop. Using model-based cluster analysis resolves this problem by mathematically determining the optimal number of clusters. For this project, the optimal number of clusters is determined to be five.

On the basis of the k-means cluster analysis, with a target of five clusters as suggested by the model-based cluster analysis, distinct clusters emerge from the data with sizes of 25, 17, 17, 28 and 32. In theory, the opportunity for marketing and business in the countries contained within each cluster should be similar based on the growth (or constriction) of the overall economy, population growth and the overall business climate within the country.

Cluster Results

Cluster 1: Armenia, Austria, Bosnia and Herzegovina, Cote d’Ivoire, Cyprus, France, Gambia, Greece, Indonesia, Jamaica, Lesotho, Macedonia, Madagascar, Namibia, Paraguay, Philippines, Qatar, Senegal, Slovak Republic, Slovenia, South Africa, Switzerland, Uruguay, Venezuela, Zambia

Cluster 2: Bangladesh, Burundi, Cambodia, China, Eqypt, El Salvador, Ethiopia, Guyana, Honduras, Jordan, Malawi, Mauritius, Mozambique, Panama, Tajikistan, Tanzania, Uganda

Cluster 3: Australia, Chad, Kazakhstan, Korea, Kuwait, Mexico, Mongolia, New Zealand, Nigeria, Norway, Poland, Russia, Saudi Arabia, Sweden, Turkey, Ukraine, United Kingdom

Cluster 4: Algeria, Azerbaijan, Bahrain, Belgium, Brazil, Canada, Chile, Columbia, Croatia, Czech Republic, Denmark, Estonia, Finland, Germany, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Moldova, Netherlands, Oman, Portugal, Romania, Spain, Taiwan, United Arab Emirates

Cluster 5: Argentina, Benin, Bolivia, Bulgaria, Burkina Faso, Cameroon, Costa Rica, Dominican Republic, Ecuador, Ghana, Guatemala, Hong Kong, India, Israel, Japan, Kenya, Kyrgyz Republic, Malaysia, Mali, Mauritania, Morocco, Nepal, Nicaragua, Pakistan, Peru, Singapore, Sri Lanka, Syria, Thailand, Tunisia, United States, Vietnam

What does this mean for global marketers? The results are mixed. Countries in the first cluster, on average, are growing in population, have respectable levels of openness for business but their macro-level economies shrunk by an average of 10.84 percent.

Countries in cluster 2 show growth in GDP and population, but have the lowest average score on openness for business. Countries in cluster 3 experienced the largest level of economic loss for the 2008-2009 period, on average 26.56 percent. Countries in cluster 4, on average, enjoy the highest levels of pro-international business policies (as measured by the ETI). Finally, the countries in cluster 5 have the second-best macro-level economies (on average), positive population growth but some trade policies that are edging towards protectionist, as indicated by their average ETI.

The benefits of using cluster analysis for macro-level segmentation are apparent. The more difficult task is determining how to use the results in a way that supports your market entry decisions or global business strategy. Clearly, the most telling result is that this type of blog post can only come from a self-confessed nerd with nothing better to do with his time.


Marketing Metrics, Intelligence and Research: A Basic Overview

Marketing ResearchMarketing metrics, marketing intelligence and marketing research. Although the three are interrelated, important distinctions exist when comparing between them. Astute marketers use all three, in a coordinated effort, to guide their marketing efforts and to support the development of their strategic marketing plans. One commonality is that all three are used to support decisions that impact how firms organize and implement their marketing programs. A brief definition of the three is presented below.

Marketing Metrics

Simply defined, metrics refers to performance measures and operating statistics. Metrics are key performance indicators, allow firms to track performance over time and enable dashboardgreater precision in execution of business activities. To provide practical value, metrics should identify frequency of measurement, frequency of review, source of data, rationale, and be logical. Metrics provide information about the current state of performance and operations. The metrics mantra is: “you can’t improve what you can’t measure”. Metrics serve as the firm’s dashboard.

Marketing Intelligence (aka Market Research)

The information that firms collect and analyze about the market(s) in which they operate, their current and potential customers and their competitors is collectively known as marketing intelligence. This information provides support for decisions regarding the development of appropriate marketing metrics, market opportunities and marketing strategy. Marketing intelligence provides a map of the marketing environment and identifies the landmarks and hazards. Marketing intelligence subsumes marketing metrics.

Marketing Research

Marketing research involves the systematic, objective collection and statistical analysis of data to turn it into actionable information. Marketing research serves as the GPS by providing information that guides the direction of the firm. Marketing research subsumes marketing intelligence. Using the scientific method as its foundation, marketing research consists of a series of steps that include:


  1. Problem definition
  2. Statement of the objectives
  3. Creation of the research design
  4. Choice of research method
  5. Sampling selection/plan
  6. Data collection
  7. Data analysis
  8. Interpretation of the results
  9. Develop the research report
  10. Follow-up/clarification

Accurately defining the problem is the key to conducting relevant marketing research. This task is more difficult than one might think given that symptoms, rather than problems, are the evidence provided by the metrics. For instance, a decline in gross sales volume is a symptom rather than a problem. Before beginning the marketing research process, one must identify the potential underlying cause(s) of the symptom. Researching symptoms rather than problems provides information that possesses limited utility.

Failure to conduct marketing research is one of the top reasons for business failure, especially when considering market entry alternatives. The key is to structure the research so that the benefits received outweigh the costs associated with the research process.

In summary, the three are not mutually exclusive decisions or tools in the marketing arsenal: they are interrelated. By utilizing all three in a cohesive manner, marketers can manage their marketing efforts to ensure maximum impact. Coordinating metrics with marketing intelligence and marketing research provides marketers with the dashboard, map and GPS needed to drive success.