Universal Containers (UC) recently implemented new Sales Cloud solutions. UC stakeholders believe that user adoption is best measured by the login rate.
Which two additional key metrics should the consultant recommend? (Choose two.)
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A. B. C. D.AB
When measuring user adoption of new Sales Cloud solutions, it's important to consider metrics beyond just the login rate. The login rate is an initial indicator of user engagement, but it doesn't provide a comprehensive picture of how users are utilizing the system or the overall effectiveness of the implementation. Therefore, in addition to the login rate, the consultant should recommend the following two key metrics:
B. Activities logged: Tracking the number of activities logged by users is an essential metric to assess user adoption. Activities can include tasks, calls, meetings, and other interactions recorded in the Sales Cloud system. By monitoring activities logged, the organization can determine how effectively users are utilizing the system's features to capture customer interactions and track their progress. A higher number of activities logged indicates increased engagement and adoption of the Sales Cloud solution.
D. License assignments: Measuring license assignments provides insights into the extent of user access and participation in the Sales Cloud. By monitoring the number of licenses assigned to users, the organization can assess the adoption rate across different teams or departments. This metric helps identify any disparities or gaps in user adoption, allowing the organization to take corrective measures such as additional training or support for underutilized user groups. Additionally, tracking license assignments can help identify if the organization needs to adjust its licensing structure based on user needs and roles.
While both A. Data quality score and C. Login lockouts may provide valuable insights, they are not directly related to measuring user adoption of the Sales Cloud solutions.
A. Data quality score focuses on the accuracy, completeness, and consistency of data entered into the system. While data quality is important for system effectiveness, it does not directly reflect user adoption. Data quality can be improved by implementing data validation rules, training users on data entry best practices, and conducting regular data hygiene initiatives.
C. Login lockouts indicate the number of times users are locked out of the system due to failed login attempts. While excessive lockouts may indicate user issues or system configuration problems, it is not a direct measure of user adoption. Tracking login lockouts is more relevant for assessing login issues, security concerns, or system performance.