Customer Segmentation, Leapfrogging, Switching, and Cannibalization in the Context of Disruptive Technological Change
Deepa Chandrasekaran, Gerard J. Tellis, and Gareth M. James, 2018, 18-134-10
All business executives marketing products/technologies should realize that disruptive technologies are always on the horizon. The big dilemma for incumbent firms is to evaluate whether or not to introduce these disruptive technologies and cannibalize their own successful offerings. The challenge for entrant firms is to know who to market these technologies to.
Deepa Chandrasekaran, Gerard Tellis, and Gareth James propose that when evaluating whether or not to introduce new disruptive technologies, and when, it is important to know which adopter segments drive market growth versus cannibalization and what the size is of these segments by category and country. They address the following questions:
- How can one model the diffusion and growth of successful technologies?
- Can one estimate sizes of adopter segments from such a model?
- How do the adopter segments vary in size across categories and countries?
- How do adopter segments contribute to cannibalization and disruption for incumbents? Can one measure the extent of cannibalization by a new successive technology from the model?
The authors develop a generalized model of the diffusion of successive technologies with partial substitution, tested on large, multi-country datasets of technological succession. Their model includes a separate rate of disengagement from the old technology, which represents the extent to which adopters of the preceding technology abandon it in favor of the new technology. Low disengagement implies low cannibalization. Further, they define and model five new adopter segments of successive technologies that they term pure switchers, bold and doubtful leapfroggers, maven, and cautious innovators.
Findings and Strategic Insights
Key findings are the following:
- Their generalized model of the growth of new technologies provides superior fit to data on both penetration and sales data for successive technologies than existing multi-generational models which are geared towards modeling data on successive generations of the same technology.
- The new segmentation enables estimation of the influence of technology cannibalization on the prior technology’s adoption curve, as well as the influence of leapfrogging vs. switching on the new technology’s adoption curve. In general, the authors find that the composition of the five segments varies by technology, across markets, and even across successive technologies that serve the same basic need.
- The percentage of leapfroggers, in the early life-cycle of the new technology, is significantly higher in developing than developed markets, and vice-versa for innovators.
- Major incumbents often fail during the takeoff of new technologies due to the under-estimation of leapfroggers (opportunity cost) or pure switchers (real cost). Their model and analysis provide a better strategic understanding of how adopter segments for a newer technology may drive sales to marketers. Such analyses can prevent disruption on the emergence of a new technology.
Their findings suggest that senior managers of strategy and managers of new products should be careful not to underestimate cannibalization by switchers and market growth via innovators (especially in developed countries) or leapfroggers (especially in developing countries). Managers should target their marketing efforts appropriately to these consumer segments in these countries.
Deepa Chandrasekaran is Assistant Professor, Department of Marketing, University of Texas at San Antonio. Gerard J. Tellis is Professor, Neely Chair of American Enterprise, and Director of the USC Marshall Center for Global Innovation, and Gareth M. James is Director of the Institute for Outlier Research in Business, E. Morgan Stanley Chair in Business Administration, and Professor of Data Sciences and Operations, both at the Marshall School of Business, University of Southern California.
This study benefits from the Christian and Mary Lindback grant for minority and junior faculty, a grant from Don Murray to the Center for Global Innovation, Marshall School of Business, University of Southern California and a research grant from the Institute of Asia Consumer Insights. The authors thank Bilal Jahangir, Pongkhi Bujorbarua, Eric Yu, and Hei Man for their research assistance, and Raji Srinivasan and participants at the AMA-EMAC Invitational Symposium, and seminars at UTSA, UT Austin, Wharton and Yale for their helpful comments.
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