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Operators, publishers and other industry participants typically group mobile content services in a logical manner based on technology or delivery method. In a typical operator a product director will oversee multimedia messaging or mobile Web and will work with counterparts in the marketing department to promote these services. An analysis of consumer behavior shows that end-users may have very different perspectives on which services belong together. For example, the demographic profile of the consumer segment that accesses movie listings or entertainment news is very different from the profile of the end-user group for mobile access to travel information and maps.
M:Metrics built segments of the market for mobile content and applications based on the demographic profiles of consumers of those services. Specifically our segmentation model was based on statistical clustering using six demographic attributes of users for 45 mobile content categories. For the purpose of this model the demographic variables – age, gender, household income, employment, education and ethnicity – were given scalar numerical values.
The model yields three broad segments each with two sub-segments as illustrated in Figure 1 below. Content categories that are similar cluster closer together horizontally in the graphic. Thus mobile chat and ringtone downloads are the two services that are most dissimilar in terms of the demographic make-up of active users during the reporting period.
The segments are named to reflect the base of users or the services of which they are comprised:
The Early Adopter segment includes Web posting of mobile video, the service with the youngest age profile; dating services and men’s content services which skew heavily male; and mobile video consumption a service that skews heavily in terms of appeal to non-Caucasians. Not surprisingly given its name this segment is the smaller than other groupings comprising about 27.1 million consumers that engaged in at least one of these activities in a month.
The Internet Services segment includes mobile access to news content category with the oldest user base; financial account access which has the most educated base of subscribers; and financial and sports news access, which is heavily male. Weather and personal e-mail access are the two most popular services in this segment with an active monthly user base of 15.8 million and 17.2 million respectively. Overall this segment included about 34.6 million people who engaged in any of these activities in a month.
The Communications and Entertainment segment is distinguished by services such as text messaging which skews less towards non-Caucasians compared with any other service; it includes playing mobile games which has the least educated base of users; and ringtone downloads-content categories with the heaviest female skew. The large numbers of people which send text messages, take photos, or play games makes this the largest segment with almost 111 million subscribers. The segment also includes listening to FM radio which has a user base of 1.1 million making it the least-used of the 45 data services that were included in the analysis.
The cluster analysis is illustrative of a market where services that are functionally alike appeal to different target markets. For example, the base of users of video messaging services is more similar to that for online dating services than it is with the population which used photo messaging services, which is broadly similar to the market for text messaging. The outcome of the analysis augurs for a revisiting of how operators, major publishers and others view how services should be marketed and bundled.
Operators invest substantial resources to build and maintain segmentation models that are often optimized to focus on attractive groups in terms of contract size and type, loyalty and use of voice services. Mobile content and applications are a continuously expanding group of services that add complexity to the business of packaging and marketing carrier services as these become a more important piece of the ARPU pie. The segmentation model presented here is dynamic as the demographic profile of end-user groups for some services will change as these are more broadly adopted. This type of analysis will be necessary to inform marketing of mobile services based on a more holistic view of subscriber preferences and behavior.
Questions or comments about this column? Please e-mail Seamus at smcateer@mmetrics.com or RCR Wireless News at rcrwebhelp@crain.com.
