To determine current reliable and valid user adoption metrics that predict the likelihood of users adopting new systems, tools, or processes. The information will be used for implementation in user experience work.
- There are four types of user adoption. Internal adoption is when existing users start to use new features. External adoption is when existing users start using existing features. Adoption flags are when new users adopt new features. A green flag is raised when they are successful. Routine adoption is when existing users adopt existing features.
- The formula for calculating the adoption rate is number of new users / total number of users. When measuring the adoption rate, it is important to use the number of potential users not the total number of employees.
- Time to first key action measures the time it takes for a new user to use a new feature.
- The average time spent with the product is a good measure of how successful the implementation of the product has been.
- Adoption rates can be improved by product education, being proactive, and better on boarding.
- There is a considerable amount of information available regarding adoption rates. The difficulty is that much of what we have identified appears to be superficial. Any attempt to get more comprehensive information was unsuccessful, with companies requiring either a sign-up or representative contact. Given this, we suggest a change in direction for future research.
Proposed next steps:
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We suggest further research to identify the best practices around the adoption of new processes, tools, or processes. For each of the practices identified, we would provide an overview of the practice, the reason it is considered best practice, and 1-2 examples of its use.
To complement this, we suggest 5-7 insights regarding the adoption of new processes, tools, or processes. The insights could include tools that assist in measuring adoption, current developments in this area, examples of companies that have developed successful processes around adoption, and the relevance of adoption rates.