What is the Late Majority?

Late majority refers to the second to last segment of a population to adopt an innovative technology. The adoption of innovative products can be broken into five primary segments: innovators (the first to adopt), early adopters, early majority, late majority and laggards. These groups are plotted along a bell curve to give rough percentages of population to each group. The late majority accounts for roughly 34% of the population and will adopt a new product only after seeing that the majority of the population already has successfully adopted it.

Understanding the Late Majority

The late majority is typically older, less affluent and less educated than the early segments in the technology adoption lifecycle. The early adopters and the early majority are younger, more familiar with technology in general and value it enough to spend the money at an early stage. In fact, the early adopters are the easiest for companies to capture as long as their product is innovative enough, but both the early majority and late majority require better value propositions.

Companies evaluate how their products will fare by taking into account the time necessary for more than 50% of the market to adopt a new product. It may take a long time for the majority to adopt groundbreaking products and it often requires discounting to access the more reluctant segments. Usually it is the late majority that gets the biggest price discount to entice them to buy after the early majority has all bought in. Laggards tend to hold out until there is no other option to fulfill the same function.

The History Behind the Early and Late Majority Model

The terminology for the various stages of adoption grew out of the academic study of the diffusion of innovation in agriculture. This splitting of the population along a bell curve with labels to capture the characteristics of the groups grew out of studies on fertilizer use, livestock antibiotics and other innovations that are now standard in the agriculture industry. The original studies started with just the categories of early majority, majority and non-adopters, but this evolved as they looked into how the complexity of an agricultural practice also played a role in diffusion and adoption. As more and more studies looked at these issue, the model was revised with more finer categories and applied to the bell curve.

This adoption model is now commonly applied to the information and communication technology sector. Interestingly, many of the observations hold up whether you are looking at seed selection in the 1950s or machine learning in the 2000s. The more complex a technology is, the longer it will take to penetrate through the early adopters and on to the early and late majorities. With technology, however, the innovation pace can be so fast that the laggards actually skip entire iterations of technology before ending up with what is usually a much more polished, user-friendly product being forced on them.