Optimización Continua con KPIs

Understanding data is critical to improving the user experience on any digital platform. Behind every metric or KPI is a real person trying to achieve a specific goal. Properly analyzing this data allows us to identify problems, understand behaviors and develop effective solutions that truly impact user satisfaction and, therefore, business success.

How to identify user pains through data analysis?

Quantitative data analysis provides us with valuable information about user behavior. To correctly identify the problems they face, we must examine different metrics and look for significant patterns.

In the case analyzed, two important graphs were observed:

• Abandonment rate: it showed significant peaks on Mondays and Tuesdays.
• Error rate: It showed a slight increase on the same days, although not as pronounced as the abandonment rate.

Digging deeper into this data, it was discovered that there was an active promotion on Mondays and Tuesdays starting at 7 PM. This promotion was attracting 25% more users from the core segment (men and women 25-35 years old). The correlation between the increase in traffic and the abandonment rate suggested a server performance problem, not the promotion itself.

What to do when we identify a performance problem?

Once we have identified that the problem lies in the server's ability to handle the increased traffic during promotions, the next logical step is to:

1. Communicate with the infrastructure team.
2. Request server optimization.
3. Implement dynamic resource allocation based on demand.

This solution allows to keep the promotion successful while improving the user experience, avoiding abandonment due to long loading times.

How to complement quantitative analysis with qualitative data?

Quantitative data shows us the "what" is happening, but qualitative data helps us understand the "why". In the example analyzed, a review was presented that revealed:

• 71% of users across all segments wanted to be able to shop without registering.
• One specific comment mentioned: "On FODIS I can place my order without having to register, that's wonderful".

This qualitative feedback provides two crucial insights:

1. There is a clear demand for a specific functionality (purchase without registration).
2. The competition (FODIS) already offers this functionality, which generates unfavorable comparisons.

How to respond to the competitor's competitive advantage?

When we identify that the competition offers a functionality valued by our users, it is essential to act quickly. The proposed solution was to implement a "guest checkout" that would allow:

• Make purchases only with email.
• Send purchase notifications to the email.
• Register the email in the database for future marketing actions.

This simple but effective solution responds directly to the need expressed by users and eliminates the competitive disadvantage.

Why is it important to understand the user behind the data?

The analysis presented reinforces a fundamental lesson: behind every KPI is a person trying to achieve their goals. It is not simply about improving numbers, but about understanding the real pains of the user to optimize their experience.

This user-centric approach makes it possible to:

1. Identify problems that really matter.
2. Develop solutions that address specific needs.
3. Improve user satisfaction and retention.
4. Maintain competitiveness in the marketplace.

Data analysis, both quantitative and qualitative, is only the first step. The real value lies in translating those insights into concrete actions that improve the user experience and, therefore, business results.

Have you had similar experiences analyzing data to identify user issues? What techniques have you found most effective in understanding the needs behind the numbers? Share your experiences and learnings in the comments.