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PCU (Peak Concurrent User)
from Activation
Metrics type
Units of measure
More - better
Check frequency
The maximum number of users concurrently using the app or website during a specific time period.
Why it is important
Tracking Peak Concurrent Users (PCU) is crucial for e-commerce stores as it helps identify the maximum load on the app or website infrastructure at a specific time. This metric is essential for capacity planning, ensuring that the system can handle peak user demand without performance issues or downtime.

By understanding the peak usage, businesses can optimize server resources, enhance user experience, and make informed decisions to scale infrastructure when necessary.
Measurement specific to the chosen method for determining peak concurrent users
Calculation example
Let's say you are monitoring user activity every minute, and you have the following user counts recorded during a specific hour:

Minute 1: 10 users
Minute 2: 15 users
Minute 3: 18 users
Minute 4: 12 users

The PCU for this specific hour would be 18 users since that was the highest user count observed within any one-minute interval during that time period.
Affected metrics
Affecting metrics
Installs on Active Devices
Connecting metrics

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Suggested slices for dashboards
by Product Launch
by Flash Sales or Limited-Time Events
by Geo
by Device Type
by Seasonal or Event-Based Trends
by Audience Segment
The revenue impact pathway
Available in JetMetrics Lite only
Questions to be Answered
1. How does the PCU metric correlate with changes in user engagement strategies or major app updates, and what insights can be gained for optimizing server infrastructure to accommodate peak usage?
2. Are there specific app features or events that consistently lead to higher PCU, and how can these be emphasized for better user experience during peak concurrent usage periods?
3. Can you identify any correlation between the timing and frequency of push notifications or in-app messages and changes in the PCU metric?
4. How does the PCU metric differ between users who have completed the activation process and those who haven't?
5. What impact do limited-time promotions or exclusive offers have on the PCU metric, and how can these promotions be optimized for increased server capacity during peak usage?
6. How does the geographic location of users influence the PCU metric, and are there opportunities for localized server optimization?
7. What is the correlation between the PCU metric and user satisfaction scores, and how can improvements in user satisfaction contribute to a higher PCU and overall server stability?
Possible causes of worsening
Tactics to improve this metric
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