My post-secondary education was in social sciences, which meant I spent a lot of time doing research. In the upper division blocks everyone in my program was required to take two classes: quantitative analysis and qualitative analysis. This was stressful for two reasons: as a social science student I was averse to math, and as a social science student we also objected to subjectivity. While my qualitative analysis course could best be described as painful (mostly due to a bad professor), the lessons I learned have been among the most applicable in my career.
Context matters.
Once you have established your KPIs, you will be measuring and monitoring in a quantitative manner; there is no other way to measure success in a scalable way. However, there are going to be a few instances in which quantitative analysis will be needed and desired.
If you have any substantial change in KPIs qualitative analysis will tell you why. For instance, if you set daily active users as a KPI, and have a dashboard that displays performance and it decreases suddenly, you'll need to do an analysis to understand why: was the an outage, did a large customer just churn,is there a seasonal variance in usage?
Another instance where taking a qualitative approach will be helpful is in program improvement. Qualitative interviews, which rely on a limited number of pre-determine questions and skills probing can help uncover additional learning needs, understand why a facilitator is under performing, or why one module isn't as effective as it should be.
Qualitative analysis of aggregate quantitative metrics can also assist you in determining the efficacy of your learning solutions and the health of your business. We hope you enjoyed our series on product enablement KPIs. If you have questions, feel free to ask in the comments.
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