Use Cases

You can see what kinds of analysis are possible with Hackle MCP through real examples. Each case includes the prompt used and a link to the result that Claude generated.

The charts and responses in the result links are examples; actual responses vary depending on your workspace data and the point in time.

User trend analysis

Visualizing daily active users

Visualize and analyze daily active users in detail

Draws the DAU trend as a chart and interprets the fluctuation patterns and key change points along with it.

→ View result

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Visualizing weekly retention

Visualize and analyze weekly retention in detail

Visualizes the weekly retention curve by cohort and presents the differences between cohorts along with hypotheses for their causes.

→ View result

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Active user changes over the past 3 months

How have active users changed over the past 3 months?

Summarizes the active user trend for a specific period and explains the change pattern in natural language.

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User behavior analysis

Comparing conversion rates by user path

Which user path has the highest conversion rate?

Compares the conversion rates of multiple user paths and analyzes the characteristics of the most effective path.

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Feature launch impact analysis

How a new feature affected stickiness

How did the new feature affect user stickiness?

Compares stickiness before and after the introduction of the new feature and evaluates the degree and significance of the change.

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Retention changes after a new feature launch

How has retention changed after the new feature launch?

Compares the retention change pattern based on the feature launch point.

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Measuring marketing message performance

Push message engagement analysis

Which push message had the highest engagement rate?

Sorts push campaigns by engagement rate and summarizes the common traits of the high-performing messages.

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Effect of an in-app message design change

How did the in-app message design change affect the click rate?

Compares the click rate before and after the design change and evaluates the significance of the change.

→ View conversation

Tips

• Ask a simple question first, then add depth with follow-up questions. Rather than a long question that includes every condition from the start, looking at the result and then asking follow-up questions like "Why did it drop at this point?", "Show me just this cohort", or "Draw it as a chart" leads to deeper analysis.

• If you need a visualization, request it explicitly. Requests like "Draw it as a chart" or "Visualize and analyze it" will generate a chart in the appropriate form.