Predictive Marketing

Market Segmentation


The Situation

A major business to business publication – Personal Information Technology Magazine* – faced a surprising turn of events. Coming off a record year in ad sales, in a growing market, by the second quarter of the new year the publication was facing a steep decline in ad sales. The marketing team searched for answers.

Was it a result of a lackluster effort by the sales force? Had the emergence of a new competitor changed the dynamic in the marketplace? Or did the explanation lie somewhere else?

The Challenge

A series of one on one meetings with key advertisers and agencies revealed that the problem was in how the publication was perceived. Their leading competitor promoted their readers as “brand specifiers” who were the key decision makers in the buying process. This assertion was strongly reinforced by the primary focus of their editorial content: product reviews.

Cluster 1 Cluster 2 Cluster 3
Job Title Senior Management Mid-level Management IT Management
Job Function Corporate, Finance Varies IT
Company Size Mid to Large Small to Medium Small, Medium, Large
Size of Budget Large Small Medium
Purchase Role Final Approval Brand specifier Recommender
Editorial preference How to Product reviews Industry news
Publication Most Read Personal Information Technology Magazine Competitor A Competitor B

In contrast to the leading competitor, the Personal Information Technology Magazine team found that the “how to” focus of their editorial created a perception among advertisers that the publication’s readers were end users of the technology who had little or no influence in the buying process. Advertisers had little incentive to spend their money reaching such an audience.

The Solution

Fortunately, a leading market research firm had just conducted a study of more than 20,000 subscribers at twenty-five information technology publications. Over 100 questions were asked of each of the subscribers who participated in the study. Among the information collected in the study on each reader was company size, job title, job function, information technology products used, bought, their role in the buying process, and the size of their budget.

Predictive marketing provided the key insights that turned the tide. After arranging to get the raw data from the study, cluster analysis was applied to the data in the study. In cluster analysis, groups of buyers who display similar characteristics and behavior are identified and segmented. Cluster analysis is a data mining technique that allows the data to reveal it own story, as is shown in the table above.

The Results

Based on this information, the readers of Personal Information Technology Magazine clearly belonged to the first cluster. And the characteristics of that cluster revealed a group of decision makers that were very attractive to advertisers – senior corporate managers who had the final say on how large budgets for personal information technology products were spent. The publication built a brand campaign around the “Corporate Volume Buyer” that succinctly summed up the characteristics of the cluster that their readers belonged to. The campaign was a hit with advertisers and re-established the publication as a leader in its market. The bottom line: the brand campaign increased ad sales 30%.

*The name of the publication has been changed to protect confidentiality

Predictive Marketing