Technology Adoption Lifecycle

What is the technology adoption lifecycle? 

The technology adoption lifecycle is a description of customer behavior related to the acceptance of a new product or feature, which is often broken into innovators, early adopters, early majority, late majority and laggards.

For example, Apple iPhones, Facebook and Teslas — products that are dominating today’s headlines — once were only popular to a select few who either understood the innovation in front of them or were brave enough to try something new. These so-called early adopters help to get products off the ground, provide crucial design feedback and, if they are successful, help to spread the word among their peers. On the other hand, there are products that once were staples of our daily lives that no longer cross our minds.

This ebb and flow is best captured in a technology adoption lifecycle, which is based on a model first introduced by researcher Everett Rogers in 1962 as part of his study on market behavior. This model, which has evolved for our digital economy, still includes the five key adoption lifecycle stages and attempts to describe and explain how consumers approach and adopt new products and innovations. The five technology adoption lifecycle stages are usually depicted laid out over a bell curve with the area below the line representing the number of customers grouped by their psychological inclinations.

What are the technology adoption lifecycle stages?

The technology adoption lifecycle stages organize customers over five categories based on a determination of how fast or the degree to which a person is ready to adopt a new product or service when compared to the rest of the population. The five stages and their percentage distribution, based on Rogers’ research, are:

1. Innovators (2.5%) 

Innovators include those that are eager to try and adopt new products. These consumers are willing to take risks and are usually younger, have more financial flexibility and are regularly in tune with sources of innovation, such as entrepreneurs.

2. Early Adopters (13.5%) 

The next group to adopt new technology products, encompassing a little more than one-tenth of the population, are early adopters. While early adopters also tend to be younger, have more financial flexibility and have a higher education level when compared to late adopters, they are also more likely to be opinion leaders (or be considered “influencers”). This group closely watches for new innovations in the market but is notably more selective than innovators when making purchasing decisions.

3. Early Majority (34%)

Rounding out the first half of the bell curve, the early majority is more conservative and risk-averse when it comes to financial investment decisions and look toward influencers and early adopters for feedback. This group is more active in research and adoption than late majority and laggards, but are key to driving market share growth for a product.

4. Late Majority (34%)

The late majority catch on to a new innovation well after the average consumer does usually due to a high level of skepticism about the benefits of a new product or service and having less financial flexibility than earlier adopters. The late majority also commonly only interacts with early majority consumers. This is an indication that a product has reached full maturity in the market.

5. Laggards (16%) 

Laggards are the last group in the technology adoption stages. Laggards show an aversion to change and are not influenced by opinion leaders. This group tends to focus more on the reliability of products they already use, but also may have very little financial flexibility to take risks when it comes to buying innovative products. Finally, this group of individuals tends to only be in contact with and trust close friends and family instead of influencers or early adopters.

How can my business leverage the technology adoption lifecycle?

Understanding the technology adoption lifecycle is another way to perform customer segmentation, including behavior segmentation, so marketing, development and sales strategies can be refined and updates prioritized to match where your product’s maturity is.

While no model can completely predict customer behavior, when used in coordination with other customer success and product experience tools, your company can be armed with more data and insights to help make more quantitative decisions about next steps.