Plerdy analytics and UX audit examples

This page collects a small set of Plerdy-linked examples focused on behavioral analytics and UX review. One entry measures the impact of a separate chatbot tool with Plerdy as the analytics layer, while the other is a clearer UX audit workflow based on click and scroll data.

Plerdy highlights from included examples

These are selected takeaways from the examples collected on this page, not a standardized benchmark across all vendors.

Largest Reported Conversion Lift

200%

In the Cheqmark measurement example

Reported Unique Click Increase

90.64%

Also from the Cheqmark example

Reported Contact Page View Drop

50%

After chatbot rollout in the same case

Audit Period Example

1 month

In the Kredobank UX audit

Issues Identified

4 major areas

Surfaced in the Kredobank review

Workflow Types

2

Measurement example plus UX audit example

Included Plerdy examples

Cheqmark

Cheqmark: Measuring NoForm chatbot impact with Plerdy

Key results

Unique Page Views

+67%

Unique Clicks

+90.64%

Reported Conversion Lift

Up to 200%

Challenge

Cheqmark, a platform for checklist creation, wanted to improve website performance metrics and reduce dependence on traditional support channels. The challenge in this example was not just implementation, but also measuring how a chatbot changed user behavior across the site.

How the tool was used

Cheqmark implemented the NoForm AI chatbot and used Plerdy's analytics tools to measure the impact of that rollout. Plerdy acted as the measurement layer, tracking behavior before and after implementation through heatmaps, click analysis, and broader user behavior data that helped the team refine placement and usage.

Results

The case reports a 67% increase in unique page views, a 56.17% boost in homepage traffic, a 90.64% increase in unique clicks, and conversion improvements of up to 200% on some template pages. It also reports a 50% decrease in 'Contact Us' page views and a 40% decrease in 'Contact Us' link clicks, suggesting lower reliance on direct support paths.

Takeaways

This is not a pure 'Plerdy caused the growth' story. It is better framed as an analytics example where Plerdy was used to measure and optimize the impact of a separate chatbot implementation.

Kredobank

Kredobank: UX audit example based on click and scroll data

Key results

Audit Period

1 month

Issues Identified

4 major areas

Analysis Inputs

Click and scroll maps

Challenge

Kredobank, one of the largest banks in Western Ukraine, was experiencing user experience issues on its website but lacked concrete evidence about where friction was happening. Without behavior data, it was difficult to prioritize improvements or understand which parts of the site were holding users back.

How the tool was used

Plerdy was used to run a UX audit over a one-month period. The team reviewed click maps, scroll maps, and broader user behavior signals to identify where users were losing momentum and which parts of the site structure were getting in the way.

Results

The audit surfaced four main issues: weak mobile responsiveness, an overloaded homepage, poor visibility of contact information, and inefficient menu navigation. The value of the example is diagnostic rather than growth-oriented: it shows how behavior data can expose specific UX problems that may not be obvious from surface-level analytics alone.

Takeaways

This example fits the cluster best as a UX audit workflow. It is useful because it shows Plerdy in its clearest role here: not as a generic SEO success story, but as a behavior-analysis layer that helps teams identify and prioritize website issues.

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