{"id":18592,"date":"2024-01-09T10:11:17","date_gmt":"2024-01-09T10:11:17","guid":{"rendered":"https:\/\/uxmag.com\/?p=18592"},"modified":"2024-01-09T11:03:22","modified_gmt":"2024-01-09T11:03:22","slug":"what-makes-users-adopt-a-new-feature-or-tool","status":"publish","type":"post","link":"https:\/\/uxmag.com\/articles\/what-makes-users-adopt-a-new-feature-or-tool","title":{"rendered":"What Makes Users Adopt a New Feature or Tool?"},"content":{"rendered":"\n

\u201cWill anyone actually use this?\u201d It\u2019s a common question from collaborators \u2014 and with good reason.<\/p>\n\n\n\n

A startup\u2019s product might have the best user experience (UX) in the world, but that\u2019s cold comfort when they\u2019re still searching for product-market fit. Even for established products, research from Pendo suggests that 80% of features added are rarely or never used<\/a>.<\/p>\n\n\n\n

UX Researchers don\u2019t often ask users to predict their future behavior<\/a>, since those answers can be unreliable. But for decades, academic researchers have been systematically predicting technology adoption, and you can use the best of what they\u2019ve learned in your practice.<\/p>\n\n\n\n

In this article, we\u2019ll take a look at how the study of technology adoption has developed over time. And you\u2019ll learn some tools that you can start implementing in your research practice today.<\/p>\n\n\n\n

Diffusion of Innovations theory<\/h2>\n\n\n\n

In the early 1960s, Ohio State University sociologist Everett Rogers published a book titled Diffusion of Innovations<\/a>.<\/p>\n\n\n\n

In the book, he synthesized the findings of over 500 multidisciplinary studies covering a wide range of contexts, such as agriculture (e.g., hybrid seed and automated harvesters) and healthcare (e.g. hospital hygiene and cancer screenings). He then distilled major findings into three groups of five: the five categories of adopters, the five characteristics of an innovation that adopters consider, and the five stages of adoption.<\/a><\/p>\n\n\n

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(Credit:\u00a0Hvassing<\/a>)<\/em><\/figcaption><\/figure><\/div>\n\n\n

Rogers found that over time, the groups adopting the innovation have meaningful differences: notably, they are distinguished by their risk tolerance, financial liquidity and resilience, and their status and persuasiveness in the community. Members of each group share similarities in age, education, and conservatism.<\/p>\n\n\n\n

Of the five groups of adopters Rogers identified, the earliest adopters are the\u00a0innovators<\/strong>\u00a0and\u00a0early adopters<\/strong>, followed by the\u00a0early<\/strong>\u00a0and\u00a0late majorities<\/strong>.\u00a0The\u00a0laggards<\/strong>\u00a0are the last to adopt after finally being convinced to incorporate the innovation.<\/p>\n\n\n\n

Rogers then found that each group considers five characteristics of the innovation when choosing whether to adopt it:<\/p>\n\n\n\n

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  1. Compatibility<\/strong>: how well does the innovation work with existing tools, practices, and values?<\/li>\n\n\n\n
  2. Trialability<\/strong>: before you buy it or commit to it, can you try it out?<\/li>\n\n\n\n
  3. Relative advantage <\/strong>of the innovation over alternatives<\/li>\n\n\n\n
  4. Observability<\/strong>: can you see others using the innovation, and are the benefits noticeable?<\/li>\n\n\n\n
  5. Simplicity <\/strong>or complexity<\/strong>: Innovations that are easier to use spread more quickly.<\/li>\n<\/ol>\n\n\n\n

    With a better understanding of innovation and its potential users, Rogers\u2019 framework can then be used to consider what he termed the five stages of acceptance:<\/p>\n\n\n\n

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    1. Awareness<\/strong>, or initial exposure to an innovation without the benefit of much information.<\/li>\n\n\n\n
    2. Persuasion<\/strong>, when a potential adopter becomes interested in and begins seeking information about the innovation.<\/li>\n\n\n\n
    3. Decision<\/strong>, the adopter makes an initial determination to adopt or reject the innovation.<\/li>\n\n\n\n
    4. Implementation<\/strong>, if adopted, where the innovation is used and evaluated.<\/li>\n\n\n\n
    5. Continuation<\/strong>, or an ongoing decision to continue using or ultimately reject the innovation.<\/li>\n<\/ol>\n\n\n\n

      Diffusion of Innovations theory has been highly influential as a sophisticated and pioneering work in this domain. It\u2019s valuable to understand users\u2019 needs and contexts, especially for products seeking to create network effects \u2014 such as a social network or dating app \u2014 where the value increases with the number of users. An important note: as a sociological model it is best used to describe population-level trends rather than predict individual choices.<\/p>\n\n\n\n

      A few suggested takeaways for UX practitioners:<\/p>\n\n\n\n