What metrics do you find most helpful to measure the success of an internal tool?
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Are there any specific metrics or indicators you track that reflect the increased demand for your products and features?
Increase in sales revenue28%
Increase in market share47%
Higher user engagement57%
Higher retention rates50%
Growth in customer base29%
Growth in user adoption58%
Positive feedback or ratings from customers33%
Other (comment below)
Lack of AI awareness30%
Improper Data Governance 33%
Unclear AI Regulations 56%
Lack of Strategic Vision from senior leadership 40%
Improper Data pipelines20%
Lack of Algorithmic Audits3%
Lack of Responsible and Ethical AI practices 40%
Lack of experts in the team 16%
I often start with these metrics when evaluating the success of an internal tool:
1. User satisfaction: Interview or survey users to ask how satisfied/dissatisfied they are with the tool. This may be a more qualitative metric than #2 and #3 below.
2. User adoption: Consider the number of new users using the tool each week.
3. User engagement: The number of daily/weekly/monthly/etc active users of the tool (you can pick the frequency that makes sense for the tool).
4. Business impact: This depends on what you are trying to accomplish with the tool and may or may not be available to you to measure. Consider, are you trying to decrease/increase an operation metric or costs perhaps? Check those metrics to see if anything has changed for better or worse.