Running Head: ANALYTICS AND SEGMENTATION 1 Analytics and Segmentation and The Increasing Importance of Social Media Data Bernard J. Karlowicz Jr. Wilkes University Author Note Bernard J. Karlowicz Jr., College of Graduate and Professional Studies, Wilkes University. Correspondence concerning this article should be addressed to Bernard J. Karlowicz Jr. C/O Kathleen Houlihan, College of Graduate and Professional Studies, Wilkes University, Wilkes-Barre, PA 18766. Contact: email@example.com
ANALYTICS AND SEGMENTATION 2 AbstractThis paper explores the rise of complex database lists as a result of the internet and socialnetworks and how this new information, along with new techniques in analytical data mining, ismaking an impact on the marketing discipline, changing forever the ways in which companiescollect, analyze, segment, and act (target) on new data. This paper leverages the informationfrom several published articles which themselves explore unique aspects of the advent of socialdata as a new information source, as well as the association between analytics and marketsegmentation and targeting. Foedermayr and Diamantopoulos (2008), explore the effectivenessof segmentation from the perspective of international companies, offering insights into theirevolving business practices as companies accelerate their investments into analytics as a meansto adapt to change, reduce costs, and capitalize on new opportunities. Jedidi, Jagpal, andDesarbo (1997), dive deep into the mathematical constructs and equation models that underliesthe latest efforts to aggregate social data and allow for the treating of heterogeneity in socialdata. Dibb and Simkin (2000) is a useful article exploring internal relationships in corporateculture, the need to evaluate, question, and change established marketing orthodoxy, and thesensibility of engaging external agencies for segmentation process enhancements and strategicmodifications and data access enhancements. Sheth-Voss and Carreras (2010), discuss some ofthe latest aspects of information theory applied to current data mining and market segmentationpractices, highlighting the struggle to bridge perception/reality conflicts in business today.Roberts (2008) again discusses the opportunities and challenges associated with the collection,analysis, dissemination, and practical application of segmentation data through the corporatelens. Remaining articles are used primarily for a specific quote or thought promotion so as tolend credence to the conclusions of this paper.
ANALYTICS AND SEGMENTATION 3 Analytics and Segmentation and The Increasing Importance of Social Media Data Throughout history, marketing experts have sought means of enhancing their ability tomore properly identify ever more subtle differentiations between target markets. The onset ofthe internet, and in particular social media, have provided marketing organizations a means bywhich to more thoroughly segment markets and identify targets than ever before. “Goodsegmentations convey information. In our view, segmentation is information compression.Segmentation is not useful unless it conveys information about important customer attributes.Ideally the converse is also true; observable customer attributes convey information aboutsegment membership.” (Sheth-Voss et al., 2010). This basic premise underlies the foundationsof this paper, whereby the advent of social media and the newly available data collectionopportunities as a result, allows a glimpse into the hearts and minds of the customer more so thanany data collections prior.But why should an organization care about the hearts and minds of its potential customers? Theanswer to such a question is obvious. By focusing attention on the “winning and keeping” ofcustomers, an organization affords itself the opportunity to take a longer term approach tocustomer engagement, and customer retention (Dibb and Simkin, 2000). The coining of the term“relationship marketing”, first coined by Berry in 1983 (Dibb and Simkin, 2000), discusses themaintenance of customer relationships and building brand loyalty among its customer base. Thisfundamental shift in marketing focus, from mere transactional selling, to the more forwardthinking relationship marketing, should allow an organization to maintain its customer retentionover the long term, enhancing company bottom lines, achieving the much desired economies of
ANALYTICS AND SEGMENTATION 4scale, and developing “a coherent and consistent image of their offerings” where targeted marketsegments are more likely to remain loyal to the company and its product line as the customer andcompany have forged a relationship through the company’s efforts in “recognizing users’differences, leading to an increased understanding of customer needs and decision criteria”(Foedermayr et al., 2008). This basic tenant of evolving marketing practice is where the adventof social media data becomes so significant. In all, of the four areas companies use to segmenttheir potential customer base, namely targeting and positioning tasks, in reducing costs and infostering a firm’s adaptability to environmental changes, it is in the targeting and positioningarea where social media data will become so vitally important (Foedermayr et al., 2008).Key in understanding the significance of social media data is to recognize its limitations andusefulness when contriving a marketing strategy. First and foremost, companies need torecognize that “social media users do not have a strong association between these sites andpurchase decisions. They see them as being more about personal connection, so finding ways toembrace that powerful function is key” (Smart actions for tough times, 2009). Customers can bedivided by age, gender, region, product interest, geography, attitudes, blood pressure or any otherdimension. Segmentations “exist” as soon as we define them. But not all segmentations areequally good for a given purpose (Sheth and Carreras, 2010). The capacity of a company tounderstand the dimensions it seeks, in order to fully quantify a key relationship dimension iscritical to success here. Companies must critically evaluate their own value system, the valueand message conveyed by their product offerings, and the “relationship” that can be extended tothe customer base. The company must evaluate itself empirically, gathering internal data andasking questions on that data in terms of what relationships it can and is willing to offer its
ANALYTICS AND SEGMENTATION 5potential customer. From this position, companies can begin to mine the data presented throughthe rise of social media in an attempt to ascertain where appropriate targets and segments reside.Companies can utilize data garnered through its social media data pursuits to develop moreprecise segmentation models, increase segmentation effectiveness and targeting performance,and identify opportunities to achieve the underlying goal of developing relationships with theircustomers. Market programs can be designed to more effectively pursue niche marketopportunities revealed through the mining of social data and application of Information Theory.A Market researcher can “use a variety of data-reduction methods (e.g. principal components orfactor analysis) to filter the aggregate data by purging measurement error, form clusters(segments) using the reduced dimensions, and then perform multi-group structural equationmodeling” (Jedidi et al., 1997). Essentially, companies need to become better consumers of data.They need to learn how to judge the volumes of data being made available, and begin todetermine what approaches to the data make sense given their newfound identity. Whencompanies begin to ask questions such as “What if we treat these variables as ordinal rather thannominal?” “What if we include current product shares as attributes?” “What if we reduce theattitudinal questions via factor analysis and use the factors in the segmentation analysis?” (Shethand Carreras, 2010), companies are on the beginnings of developing a marketing strategy alignedwith their, and their customer’s interests. Enveloping the utilization of entropy, surprise, andlatent class analysis within the scope of analyzing social data via algorithmic processes such asK-Means testing, Bayes information criterion, and Total Mutual Information, formulate thebeginnings of a novel approach, based on Information Theory, to approach customers by way ofrelationship forging. This co-development lends itself to the establishment of a relationshipbetween the company and the consumer unlike efforts of the past where simple management
ANALYTICS AND SEGMENTATION 6insight or simplistic correlation analysis once owned the road in terms of segmentationevaluation and understanding (Sheth and Carreras, 2010). “Smart firms make above-marketreturns on their investments in customer information, analyzing that information and thenbuilding business strategies around what they have learned.” (Smart actions for tough times,2009). So, in understanding the need for relationship building with the consumer, along withnew insight into the need to develop more robust segmentation and targeting strategies based onsolid, well understood Information Theory principles, companies need to realize the point, andturn their attention to the collection of this vital information available via social media. “If youcan so segment the market that you really understand who is buying and what their motivation is,you can make offers that are most relevant.” (Hopkins, 2009). Hopkins postulates thatcompanies must turn to improving their internal data collection with the aim of improving itsquality, and thus allow an adjoining of this internal data with data collected externally, viaexternal sources such as rating bureaus, social media sites, etc… The leveraging of onlinemarketing channels in conjunction with external data providers and web analytics service willprovide a means by which the company can make better segmentation and targeting decisionswith the aim of forging relationships with their best customers. “The bottom line is that in achallenging economic landscape, marketers must focus on data intelligence in order to succeed.FLaving an in-depth understanding of your existing customers is the first step in learning moreabout your prospects, which ultimately leads to better segmentation, better targeting and bettercampaign performance.” (Hopkins, 2009).
ANALYTICS AND SEGMENTATION 7The final issue that needs to be addressed is the manner in which companies collect data fromsuch external partners as social media sites, bureaus, external data providers, etc… As was sopoignantly addressed in the article ‘I Know all about you’, “The data does need to be bandiedin a compliant way within all privacy laws and codes of conduct.” (Roberts, 2008). Complianceconcerns, SOX compliance, and other regulatory concerns need to be addressed when collectingand managing customer data. Companies need to take care to properly handle such information,and utilize it accordingly. It is my contention that companies should consider leveraging outsideexperts and data collection facilities to provided cleansed and scrubbed data, pre-prepared forcompany consumption, eliminating the risk of data non-compliance. “Another issue worthy offuture research concerns the role of external experts (i.e. market research agencies, advertisingcompanies, consultancies, etc.) in supporting firms with their international segmentationdecisions. Although our exploratory study revealed that external experts are frequently involvedin segmentation decisions, little is known as to what services they offer to the firms that employthem or the benefits in terms of improved segmentation effectiveness that are obtained by usingexternal expertise.” (Foedermayr et al., 2008). In light of this new understanding of the role of social data, the means to evaluate it, andthe impact and insights such efforts bring to the company, it is imperative to understand thepitfalls companies face in developing a marketing plan with this newfound wealth of knowledgefrom the consumer. Dibb and Simkin provide a wonderfully articulate list of common pitfalls(impediments) companies most often face in this regard. The table below is a well researchedlist of said impediments that stand in the way of companies and their means of developingrelationships. Though the purpose of the research is to draw insight into internal relationship
ANALYTICS AND SEGMENTATION 8forging within a company, the same attributes and rules apply when attempting to build externalrelationships, hence my inclusion of this table here in this paper: Dibb and Simkins Observed Barriers Hindering Marketing Planning 1. Poor Grasp of the Marketing Concept 2. Little or No Marketing Analyses Undertaken 3. Strategy Determined in Isolation of Analysis or Formulation of Tactical Programmes 4. Blinkered View of the External Environment 5. Poor and Inadequate Marketing Intelligence 6. Little Internal Sharing of Marketing Intelligence 7. Inadequate Understanding & Support from Senior Management 8. Poor Internal Communications in Marketing, Between Functions/Tiers 9. Planning Activity Fades Out 10. Planning and Personnel Overtaken by Events 11. Lack of Confidence/Conviction 12. Little Opportunity for Lateral Thinking Figure 1 - (Dibb and Simkin, 2000)Companies must evolve to save themselves from the trend of obsolescence throughgeneralization. Niche markets and niche products will dominate the landscape of companysuccess in the coming years. Those companies best prepared to dominate those niches,demonstrating themselves as offering best of breed product lines in subtle markets, along with ameans to truly engage the consumer in relationship building, will find success in the newtomorrow.
ANALYTICS AND SEGMENTATION 9 ReferencesDibb, S., & Simkin, L. (2000). Pre-Empting Implementation Barriers: Foundations, Processes and Actions-The Need for Internal Relationships. Journal of Marketing Management, 16(5), 483-503. Retrieved from EBSCOhost.Foedermayr, E. K., & Diamantopoulos, A. (2008). Exploring the Construct of Segmentation Effectiveness: Insights from International Companies and Experts. Journal of Strategic Marketing, 16(2), 129-156. doi:10.1080/09652540801981579Hopkins, D. (2009). Finding the hidden value of lists and databases. B to B, 94(2), 24. Retrieved from EBSCOhost.Jedidi, K., Jagpal, H. S., & Desarbo, W. S. (1997). Finite-mixture structural equation models for response-based segmentation and unobserved.. Marketing Science, 16(1), 39. Retrieved from EBSCOhost.Smart actions for tough times. (2009). Marketing Management, 18(4), 3. Retrieved from EBSCOhost.Roberts, J. (2008). I Know All About You. NZ Marketing Magazine, 27(1), 28-31. Retrieved from EBSCOhost.Sheth-Voss, P., & Carreras, I. E. (2010). HOW INFORMATIVE IS YOUR SEGMENTATION?. Marketing Research, 22(4), 9-13. Retrieved from EBSCOhost.