Tag Archives: Marketing Research

R You Ready for DIY Statistics and Social Media Marketing Analytics?

The logo for the R statistical software package

This post originally appeared in Social Media Marketing Magazine, Issue 1, Number 6

Statistics. For many current and former students, just the sound of this word evokes nightmares. However, once you learn to master some basic tasks using statistical analysis software, the world becomes your data playground. Thus, the purpose of this column is to introduce you to one of the most powerful statistical analysis software packages (open source!) and to provide examples of how it can be used to build your social media marketing analytics capabilities.

R is one of the most popular statistical analysis software programs available. It is used by statisticians, financial analysts, marketing researchers and social media researchers. To download and install R, go to the Comprehensive R Archive Network (CRAN) site.

You’ll find versions of R built for Linux, MacOS X and Windows. In my opinion, the versions for Linux and Windows work best. Issues for Mac users related to installing and updating additional statistical analysis packages (3311 are currently available – and like R, all for free) are known to exist. Mac users experiencing problems are encouraged to consider installing Virtual Box in order to install and run the Linux version of the R statistical program. After selecting, downloading and installing the base program, visit the Quick-R site for examples of how to use R for statistical analysis.

Two recent additional (or add-on) social media statistical packages are available to be installed in R: RGoogleTrends and twitteR. The former is one of the most difficult R add-ons to install in R (it took me a couple of hours to make it work) and the latter performs many of the same functions of one of the earlier software packages recommended in this column, NodeXL.


RGoogleTrends is not available for download within the R “install packages” option. To install RGoogleTrends, one must visit this site to download the .tar.gz file (I use 7-zip for Windows to unzip the file). Hyunyoung Choi and Hal Varian provide a unique perspective of the power of RGoogleTrends in their 2009 white paper “Predicting the Present with Google Trends”. Joe Rothermich developed an interesting presentation (2011) that illustrates the power of using RGoogleTrends to measure market sentiment and events. Download and read both to get an idea of the power of R from a social media marketing perspective.


The easier of the two R add-on packages to download and install (can be done within the “install packages” option included in the R base package), twitteR provides users with access to the networks of businesses or people who are on Twitter. Using twitteR, one can perform network analysis tasks that include basic statistics. Jeffrey Breen recently presented (2011) an incredible example of how to use R and twitteR to mine Twitter for consumer attitudes. His presentation includes advanced R code for how to replicate/duplicate his research.

Admittedly, none of this is easy. But spending the time to master R, RGoogleTrends and twitteR will make you a better social media marketing researcher. R you up to the challenge?


Does Academic Research Provide Practical Value for Social Media Marketers?

David Berkowitz ForresterThis post originally appeared in Social Media Marketing Magazine, Issue 1, Number 4.

Research you can use; four simple words that sum up my goal for this column. It is an honor and a pleasure to take over the responsibility for writing this column from Caroline Dangson (@CDangson). Caroline established this column as a must read. Her initial three articles, “Who Owns Social Media for Business”, “Co-Creating Value with Customers” and “Twitter is Ready for Advertisers, but are Advertisers Ready for Twitter?” presented thought provoking insight into emerging trends in social media marketing (SMM). Please join me in thanking her for developing a solid foundation on which to build.

Our goal for this column is to share with you cutting edge academic research that provides utility and assists in making your social media marketing research efforts easier. Academic research in marketing is not known for either its readability or its practicality. A few exceptions exist. Academic journals that are written with an eye towards readability and containing an applied focus include Business Horizons, California Management Review, Harvard Business Review and MIT Sloan Management Review. Interestingly, none are focused solely on marketing.

In my opinion, academic research has the potential to provide value to social media marketers IFF (if and only if) it provides instruction or insight into new research tools, methods, concepts and/or constructs. In the area of social media marketing research, in general, marketing academicians lag practitioners in understanding, developing and utilizing applied research tools and techniques. The good news is that this is changing. In addition to current marketing professors who are rapidly re-tooling, a new generation of marketing researchers is making its way through some of the top Ph.D. programs in the world and these researchers are engaged in and excited about SMM.

It is the research of this group, the denizens of SMM research, that we plan to review and share with you each quarter. The goal for this column is to add value to your SMM research skillset and tool kit. This issue, two must-read articles are highlighted and reviewed. The take-aways for each are clearly identified. Once you read this column, and the articles referenced, please come back to leave your comments/questions/suggestions because learning isn’t unidirectional.

The two, initial, journal articles for review are:

Hoffman, Donna L. and Marek Fodor (2010), “Can You Measure the ROI of Your Social Media Marketing?”, MIT Sloan Management Review, Vol. 52, No. 1 (Fall), pp. 41-49.


Hansen, Derek L. (2011), “Exploring Social Media Relationships”, On The Horizon, Vol. 19, No. 1,  pp. 43-51.

Can You Measure the ROI of Your Social Media Marketing?

Because this article has been out for a while, this is not the first review. A good overview of both the article and the importance of determining return on investment (ROI) in SMM is provided by Angela Hausman.  Hoffman and Fodor challenge SMM researchers to adopt a new approach:

“Effective social media measurement should start by turning the traditional ROI approach on its head. That is, instead of emphasizing their own marketing investments and calculating the returns in terms of customer response, managers should begin by considering consumer motivations to use social media and then measure the social media investments customers make as they engage with the marketers’ brands.” (p. 42)

They offer 4 C’s (instead of 4 P’s) to identify the key motivations for social media interaction: connections, creation, consumption and control as well as two case study examples of social media marketing failures. However, the real benefit (take-away) offered by this article is the sample metrics provided on page 44, some easy to operationalize and some more difficult to operationalize. The final gem provided by this article is a traditional 2 x 2 matrix entitled “Strategic Options for Social Media Measurement”. Using the sample metrics based on the strategic options available should provide a solid framework for developing a ROI unique to your business model.

Exploring Social Media Relationships

Hansen’s article offers immediate utility. In my opinion, he sums up the purpose of the paper brilliantly:

“This paper describes some of the techniques and tools needed to make sense of the social relationships that underlie social media sites. As relational data are increasingly made public, such techniques will enable more systematic analysis by researchers studying social phenomena and practitioners implementing social media initiatives”. (p. 44)

The paper documents the development and release of an incredible open source network analysis add-on for Excel. Hansen explains the concept of network analysis and social network analysis (SNA). The later builds on the former and is perfect for studying SMM relationships.

He justifies the study of SNA on page 45:

“Viewing the social world as a network can provide many insights not obtainable in any other way. Social network maps provide overviews of social spaces, highlighting subgroups and individuals that hold important positions within the network. Tracking changes in a network over time provides a powerful evaluation tool that measures previously hard-to-capture insights about social capital development, community formation, and marketing campaigns”.

The take-away from this article is the description of the power of the open source network analysis add-on for Excel: NodeXL. He even shares he is using NodeXL in his courses at the University of Maryland.  For those of you who don’t know me, my life revolves around open source. This add-on excited me so much that I purchased Microsoft Office just to use it (it won’t work in my beloved OpenOffice). After four days of playing with NodeXL, it is clearly a tool that you should explore in order to strengthen your SMM research skillset.

Future columns will be more succinct, but will follow the same format. Each quarter, two “must-read” academic research papers will be highlighted for your benefit. If you have any suggestions for future topics or manuscripts to review, please feel free to contact us.

Finally, since the goal of this column is to add value to your SMM research skills, we end with two questions: 1) Do you find this approach helpful? and 2) Did this column provide you with any take-aways that you can use?


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 Salesforce.com 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.