How to automatically detect pain points

Establishing routines for automatic pain point detection is a crucial step in proactively addressing potential issues for your business. This includes setting up systems and processes to monitor various pages and flows on your site.

Here are some ways to use Contentsquare to help you establish routines in detecting pain points:

Alerts

Alerts play a crucial role in delivering real-time notifications when specific conditions or thresholds are met. By configuring alerts for key pages, CTAs, or flows, you can proactively detect and resolve issues, prioritizing improvements that have the most significant impact on the user experience

Learn more how to deploy a strong alerting coverage on your site

Dashboards

While Alerts allow you to receive automatic updates about the KPIs you care about the most, Dashboards provide a personalized interface where you can track your key KPIs in one place.

Common use cases for KPI monitoring

Dashboards are designed to meet various needs, allowing you to easily grasp the performance of different campaigns, the scope of different teams, and specific pages, all in a single view.

Below you can find a few examples of different types of Dashboards, representing some common use cases for KPI monitoring.

Dashboards for E-Merchandising 

Dashboards for Category performance

Dashboards for Acquisition channels 

Frustration score

The Frustration Score helps you automatically find issues in your digital product. It's crucial for measuring user frustration, prioritizing actions, and improving UI/UX over time.

You can use the Frustration score to:

• Track the Frustration Score over time for individual pages.
• Identify pages with the highest user friction by analyzing the entire user session.

Monitor the health of an individual page by using the Frustration score in Dashboards

1. Set up a dedicated Dashboards to track frustration scores over time.

2. Create segments for different frustration levels to compare their impact on key site KPIs. (e.g, medium frustration (score between 10 and 40

3. Add a line chart for monitoring the frustration level for your key page based - you can choose between the Median, 90th percentile, 95th percentile, or 99th percentile.

Learn more about using the Frustration score in Dashboards

4. Determine if higher frustration scores affect KPIs, like subscription conversions or checkout page visits.

5. Create alerts to be notified when page scores deviate from the norm, indicating potential new insights.

6. Navigate to Session Replay and segment by the page you're looking to visualize the detected frustration.

7. Click on the Frustration Score icon next to each Session Replay to see which Frustration Metrics contributed to the high score and understand what caused the highest frustration for those sessions in the Session Replay list.

Example of a Dashboards dedicated to monitoring different levels of frustration across the Checkout pages

Detect bugs and issues after a page redesign/ site revamp

1. Navigate to the Insights from the main menu, set your Analysis context, and choose a mapping.

2. Identify page groups with potential for improvement by examining their Frustration scores; higher scores indicate greater opportunities.

3. Check potential improvements by examining associated insights along with their business impact.

4. Watch Session Replay to visualize the user interactions generating insights on your site.

5. Depending on the insights and the issue, gain a better understanding of the root cause by navigating to other Contentsquare capabilities(e.g., go to Impact Quantification to quantify the overall impact of fixing the issue, or to Zoning Analysis/Journey Analysis/Error Analysis to confirm your hypothesis about the root cause).

Example of an analysis using Insights in identifying friction with Promo Codes

Utilizing Insights, it was found that 4000 sessions faced friction with the checkout voucher field. Within an hour of flagging this insight, the code was adjusted to allow orders under £30 to enjoy the discount, leading to a substantial reduction in friction.

Utilizing Smart Zone Selector in Zoning analysis

The smart zone selector helps you identify and prioritize zones on your page. It highlights which zones have the highest amount of a certain metric, e.g. Click rate or Revenue.

Common use cases for using the Smart Zone Selector

Identify potential click recurrence frictions in the Checkout stages

1. Apply a segment of users that 'Did not Transact' (and transact for comparison) on a Payment Page to quickly identify which payment options may be causing frictions.

2. Click on the 'Smart' button inside 'Edit zones.' In the side panel that opens, click on the use case for which you want to surface the matching zones. To see if there is a zone that generates frustration, switch between the Top Click Rate and Top Click Recurrence.

3. Make a note if any of the zones stand out.

4. Refine potential root causes by utilizing other Contentsquare capabilities. For example, watch a session replay to confirm if a detected click recurrence is due an error and is not the expected behavior for that specific page element.

Zoning analysis of the Payment page using the Smart Zone Selector

Zoning analysis shows that PayPal option has a higher tap recurrence among users with no transactions. A closer look at the Div structure and reviewing the Session replay reveals that the entire box isn't clickable, only the circle, causing confusion/friction in some sessions.

Identify high performing content during Peak season/ key campaign periods

1. Change the Analysis context to match the timeframe before and after the redesign of your page.

2. Click on the 'Smart' button inside 'Edit zones.' In the side panel that opens, click on the use case for which you want to surface the matching zones (e.g., Top revenue and Top click rate).

3. Identify which content drives the most revenue and engagement. 

4. Reorganize content based on its impact and popularity.

Zoning analysis of a mobile menu using the Smart Zone Selector

The zoning analysis reveals that the highest revenue generator is not the most clicked entry on the menu.

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