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2025.1 Release Notes

New Features & Enhancements in GermainUX 2025.1 – Available as of .

MONITORING AND ANALYTICS FEATURES

AI‑Powered Session Replay Summary

Customers: AllBirds, ANZ Bank, eBay, MedPro Staffing

GermainUX’s AI-Powered Session Replay now automatically summarizes key user actions and behavioral insights within each session. This eliminates the need to manually watch full replays—saving time while preserving full context on the user experience. This mechanism can be customized to extract custom insights that are specific to your use case.

🔍 Example Use Cases:

  • Amazon eCommerce
    Summarized replay captures search behavior, clickstream, hesitation points, and checkout engagement.

    image-20250818-164717.png

    AI-Summarized Session Replay on Amazon Store – GermainUX

  • Salesforce CRM
    Summary highlights key user tasks, tab switching, form interactions, and delays in CRM workflows.

    image-20250818-165039.png

    AI-Summarized Session Replay on Salesforce – GermainUX

  • Shopify eCommerce
    AI-generated summary identifies navigation flow, product interactions, cart activity, and friction points.

germainux - session replay - ai summary - allbirds.png

AI-Summarized Session Replay on a Shopify Store – GermainUX

How it works:

Deploy or inject one of the Real User Monitoring components of GermainUX and customize your AI prompt:

  • GermainUX RUM JS to be injected directly into the Web Application UI (e.g. Salesforce Experience Cloud, SAP, Shopify, etc).

  • (or) GermainUX RUM Extension to be deployed directly onto the User Desktop, for the applications that do not allow JS injection (e.g. Salesforce Lightning, etc).

  • Prompt Creation: You can create prompts to define the depth of analysis you want GermainUX to provide when summarizing a session.

Example

Below is an example of a prompt that leverages several preconfigured GermainUX KPIs:

image-20250819-182907.png

AI Prompt to analyze Session Replay - GermainUX

More details on Session Replay or Prompt editing.

AI-Powered Conversation Friction Detection

Customers: Large US-Based Healthcare, MedPro Staffing

GermainUX’s AI Service now automatically detects friction points within chat and conversation flows— across any chat platform, including WhatsApp, RingCentral, and others.

This capability helps identify breakdowns in communication, delayed responses, escalations, sentiment shifts, or repeated questions that impact user or agent experience.

Important: When using an online LLM, and for optimal compliance and security, automatic Anonymization can be enabled before any data is sent to the LLM:

image-20250819-180834.png

Anonymize flag - GermainUX

AI-Powered Labels for Scripted Categorization

Customers: MedPro Staffing

GermainUX now supports AI-generated labels for data categorization.

High-Volume data (using existing Scripted Categorization mechanism)

  • Used for high-volume data, such as JavaScript console events.

  • Data is categorized through custom scripts (existing categorization mechanism) that are performant at scale.

  • New labels for these categories can be AI-generated to make them human-readable, improving clarity and reducing manual effort.

  • Example Use Case: JavaScript console events are typically high volume errors that occur in the browser console. In this case, we can use a script to categorize errors based on the similarity of their stacktrace and message (out-of-the-box config is already provided for this). We can then use AI to generate a human readable label for the error based on the stacktrace.

Screenshot 2025-08-18 at 16.58.32.png

Example Config

Screenshot 2025-08-18 at 16.59.13.png

Example Prompt Config

Screenshot 2025-08-18 at 17.04.21.png

Example Data (using new Categorization Tester feature)

AI-Powered Fact Categorization

Customers: US Based Largest Healthcare

GermainUX’s fact categorization also supports a completely new mechanism of categorization utilizing one of several LLMs (Large Language Model).

Low-Volume Data (using new AI Categorization mechanism)

  • Used for low-volume data, such as User Feedback.

  • GermainUX’s AI service handles the entire categorization process.

  • It uses a customizable prompt to classify and update each fact accordingly.

  • Example Use Case: User Feedback data is typically low volume data where an end user provides feedback on your website. We can use AI-Driven Fact Categorization to extract sentiment data from the user comments.

    • Categorization example 1: Angry, Disappointed, Happy, etc.

    • Categorization example 2: Positive, Negative, Neutral, etc.

Screenshot 2025-08-18 at 17.06.17.png

Example Config

Screenshot 2025-08-18 at 17.06.29.png

Example Prompt Config

Screenshot 2025-08-18 at 17.08.38.png

Example Data (using new Categorization Tester feature)

AI Admin Screen

Customers: N/A

AI Settings

This AI Settings screen provides a centralized control over all AI capabilities. From this interface, each AI feature can be individually enabled or disabled as needed.

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AI Settings - GermainUX

AI Prompts

Ability to customize any AI prompt.

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AI Prompt Screen - GermainUX

RingCentral Call Insights

Customers: MedPro Staffing

GermainUX now supports monitoring of RingCentral, enabling visibility into frictions that occured during a phone call. In other words, GermainUX does not monitor the actual call, but instead integrates with Ringcentral in order to collect the call transcript and the call summary (either AI-generated or human-written) and looks for frictions that occured during those.

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RingCentral - GermainUX

Use Case:

Track and analyze how long calls last when made through RingCentral, identify what went wrong — and correlate this data with agent activity, system performance, or CRM usage.

Example: RingCentral Call Analysis

AI-driven detection of friction patterns in conversations that occurred on RingCentral:

image-20250807-210818.png

AI Call Friction Detection on RingCentral – GermainUX

Additional analytics are available to visualize when and why frictions occurred, including duration, root causes, and agent or bot response patterns.

image-20250807-210448.png

AI Call Friction Detection on RingCentral (cont’d) – GermainUX

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RingCentral Call Insights on a Drillthrough Dashboard - GermainUX

How it works

This integration uses the SIP protocol over WebSocket to exchange messages and capture real-time call data.

Once the call data is collected, GermainUX’s AI prompts can be applied to analyze the conversations.

Example: AI Prompt for Interview Analysis

Below is an example of a GermainUX AI prompt configured to analyze interviews conducted via RingCentral:

image-20250819-180103.png

AI Prompt to detect Friction in a Phone Call via RingCentral - GermainUX

Salesforce Omni-Channel Chat Insights

Customers: MedPro Staffing

GermainUX now monitors Salesforce Omni-Channel to detect and resolve friction that occurs during conversations between employees and customers. End-users may communicate through text messages, in-app chat, or WhatsApp. Once a conversation ends, GermainUX automatically generates a summary of the interaction and highlights the issues that didn’t go well.

Whether it’s routing delays, agent overload, or dropped interactions, GermainUX provides deep visibility and AI-driven insights into every part of the Omni-Channel experience.

This gives you the clarity needed to improve agent productivity and customer satisfaction—all directly from your GermainUX workspace.

Salesforce’s Omni-Channel User Interface:

omnichannel-ui.png

Omni-Channel User Interface

Detailed Conversation Insights are available on the GermainUX Drillthrough Dashboard:

omnichannel.png

Chat Insights on Omnichannel detected by GermainUX

How it works

For flexibility, GermainUX can monitor Omni-Channel chats in two ways:

  • RUM JS injection – GermainUX RUM JS injected directly into the Omni-Channel UI

  • Salesforce REST API integration – monitoring through Salesforce’s REST APIs

Once the chat data is collected, GermainUX’s AI prompts can be applied to analyze the conversations.

image-20250819-174514.png

Interview-specific AI Prompt for OmniChannel - GermainUX

Learn more: Salesforce Omni-Channel Monitoring.

ChannelTalk Monitoring Message Collection & Analysis

Customers: MedPro Staffing

GermainUX now supports automatic collection and analysis of messages sent and received via ChannelTalk.

How It Works:

This is made possible through ChannelTalk’s new API, which allows GermainUX to monitor messages exchanged between agents, bots, and customers.

This enables real-time visibility into conversational flows, performance, and potential issues within the ChannelTalk platform.

Learn more: ChannelTalk Monitoring Details.

SAP Customer Experience — Enhanced Monitoring in GermainUX

Customers: eBay, PepsiCo

GermainUX’s monitoring mechanism for SAP Customer Experience has been enhanced as follows:

For SAP Customer Experience, GermainUX functions similarly to how it works with platforms like Shopify or Salesforce Experience Cloud.

Shopping Experience Events (SAP Customer Experience / SAP Hybris)

While monitoring SAP Customer Experience, GermainUX detects and analyzes in real time what occurs throughout the shopping journey.
The following events are available out of the box—additional events can be added as needed:

  • Open chat.

  • Close chat.

  • Add product.

  • Remove Product.

  • Start Checkout

  • Enter Payment info.

  • Complete Checkout.

Example of a User Session Recorded and Available for Replay in the GermainUX Workspace:

image-20250807-135946.png

SAP CX User Session Recording/Monitoring & Replay - GermainUX

As a reminder, GermainUX captures and stores complete user sessions, enabling teams to replay the exact user journey through the SAP Customer Experience (or Hybris) storefront. This includes:

  • Page views and navigation flows

  • Clicks, hovers, scrolls, and form inputs

  • Errors (JavaScript, network, API, etc.)

  • Friction events (e.g. rage clicks, dead clicks)

  • Transactional steps (add-to-cart, checkout attempts, logins, etc.)

Each session is enriched with performance metrics, user context, and automated root cause analysis, making it easy to understand what happened and why—without requiring users to manually reproduce the issue.

Error detection, analysis & resolution (SAP Customer Experience / SAP Hybris):

One critical event for this client is to prevent error when at all possible, or detect them, analyze them, then whenever possible and considered safe, automatically resolve them, in real-time.

Examples of errors that may occur during the order process:

image-20250807-134249.png

“Oops Pricing … unavailable” in SAP Customer Experience / SAP Hybris - GermainUX

image-20250807-134315.png

“..technical difficulties..” in SAP Customer Experience / SAP Hybris - GermainUX

Advanced Data Privacy

Customers: All

GermainUX now supports multiple exclusions using the same KPI and field name combination. This is particularly useful when applying simple pattern-based exclusions to substrings within a larger string—allowing for more manageable configurations instead of relying on a single complex pattern.

image-20250711-104628.png

Data Privacy 1: JohnSmith1 and Org: ExampleOrg

image-20250711-104643.png

Data privacy 2: ********* and Org: **********

Example:

KPI: JavaScript Console Event

Field: details

  • Data Privacy Rule 1: JohnSmith1*********

  • Data Privacy Rule 2: ExampleOrg**********

Before:
"JohnSmith1 and Org: ExampleOrg"

After applying both privacy rules:
"********* and Org: **********"

This enhancement enables more flexible and granular privacy controls, ensuring sensitive information is effectively masked across all relevant data fields.

BP Re-Process Dialog

Customers: MedPro Staffing

In the Business Process (BP) Re-Processing dialog, "KeyValue" has been replaced with "CorrelationID" to more clearly indicate the intended input value.

This improves usability by aligning the field label with the actual correlation mechanism used in Business Process monitoring and analytics.

image-20250618-143210.png

Learn more: Business Process Monitoring and Analytics.

Cart Abandonment Report

Customers: AllBirds, Catherine Michiels

The Cart Abandonment automated report is now available out of the box (OOTB)—preconfigured and ready to use without additional setup.

image-20250712-171324.png

Cart Abandonment Report - GermainUX

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Frictions Report - GermainUX

Out-of-the-Box (OOTB) Reports

GermainUX offers a wide range of preconfigured reports, ready to use out of the box. These reports cover both eCommerce and CRM/ERP use cases.

eCommerce Reports:
  • Broken Checkout (synthetic monitoring)

  • Integration Down (e.g., AI apps, chatbots)

  • Static Broken Link

  • Negative Feedback

  • Orders

  • Abandoned Carts

  • Drop-offs

  • Frictions (e.g., no search results)

  • Process Performance
    (e.g., Landing Site → Checkout, Start → End Chats)

  • Products Viewed

  • Sold Out Products

  • Technology Performance

CRM / ERP Reports:
  • URL Down (synthetic monitoring)

  • Integration Down (e.g., AI apps, chatbots)

  • Frictions

  • Process Performance
    (e.g., Start → End Chats, or any business process the client cares about)

  • Technology Performance

As with all features in GermainUX, users can customize these reports or create entirely new ones based on their specific needs.

Chrome Extensions Updated to Manifest V3 

Customers: One of the largest US-based Healthcare Organization

As part of Google Chrome’s transition to Manifest V3 (MV3), all Chrome extensions must be updated to comply with the new standard.

With the 2025.1 release, GermainUX has published updated versions of the following extensions, now fully compatible with MV3:

Color Coding for Any SLA, Metric, or Measure

Customers: All

As of version 2025.1, GermainUX now supports color coding for any metric on any portlet, based on any configured SLA.

Previously, color coding was limited to duration-related metrics. It now also applies to a broader range of measures, including:

  • Count

  • Percentile

  • Failure rate

  • And more

Why does this matter? This enhancement ensures the GermainUX workspace consistently highlights the metrics that matter most—based on the SLAs defined by your organization.

image-20250730-125457.png

Color coding for any SLA, any metric, any measure - GermainUX

Exclusion of HTTP Status Codes and URLs (Website Crawler)

Customers: All

GermainUX’s Website Crawler now supports the ability to exclude specific HTTP status codes and URLs, giving you greater control over which issues are reported.

What you can exclude:
  • HTTP Status Codes:
    Exclude any status code (e.g., 404, 503, etc.) so GermainUX only flags failures or statuses that are meaningful to your organization.

image-20250618-203355.png
  • URLs:
    Exclude specific URLs—useful for ignoring known or irrelevant pages, or avoiding false positives caused by services like Cloudflare.

Example: Exclude 404 errors from Cloudflare-hosted pages that are not actual issues.
This prevents unnecessary noise in your reports and keeps the focus on real problems.

image-20250711-082619.png

Example: exclude Cloudflare - GermainUX

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Example (cont’d): exclude Cloudflare - GermainUX

More details: GermainUX Website Crawler Documentation.

Fact Categorization Tester

Customers: American Airlines, Allan Gray

GermainUX now supports a testing mechanism for fact categorization.

How It Works:

In the Categorization view, simply click the play button on the right panel.
This action processes the available historical data for the selected time period and displays the categorized results under each newly identified category.

This feature helps validate categorization accuracy and ensures meaningful insights before deploying categorization logic in real time.

image-20250711-135019.png

Test Categorization Button on Categorization View - GermainUX

KPI Filter Now Supports "OR" Statements in Timeline Events

Customers: AllBirds, American Airlines, eBay

The KPI filter within Timeline Events now supports "OR" conditional logic, allowing for more flexible and granular filtering.

Example:

You can now create a Custom Insight that captures events where:
Error Type = Timeout OR Error Type = NullPointer

This enhancement enables more powerful drillthrough and segmentation of event data based on multiple matching criteria.

image-20250711-110325.png

Example: OR Condition for a KPI Filter on a Portlet - GermainUX

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Custom Insights visible on Replay Timeline - GermainUX

More details: Custom Insight / Custom Tab.

Migration from ShopifyEvent to ShopEvent Model

Customers: Allbirds, CatherineMichiels

GermainUX now stores Shopify events in the updated ShopEvent model.

What This Means:
  • Full support for the current Shopify data model

  • Improved compatibility and stability with future Shopify updates

  • No change in how events appear in GermainUX—just a more reliable source

Example: Shopify events such as Add to Cart, Checkout Started, or Product Viewed can be automatically inserted into recorded sessions for deeper insight and replay context.

image-20250618-134531.png

Shopify Events shown in a Session Replay - GermainUX

Learn more: Shopify Event Integration Details.

Multi-Tab Monitoring (Salesforce)

Customers: MedPro Staffing

GermainUX now tracks the number of tabs a user opens while working in Salesforce.

While the active tab has always been monitored, this enhancement adds visibility into how often users open additional tabs—providing deeper insight into user behavior and potential workflow inefficiencies.

Example: Tab Opened detected by GermainUX.

image-20250712-165600.png

Tab Opened - GermainUX

Mute / Unmute Reports

Customers: American Airlines, MedPro

GermainUX now allows individual workspace users to mute or unmute automatic reports.

  • This functionality is available only to users logged into the workspace.

  • It does not apply to reports sent via email to recipients without workspace access.

  • Behavior is consistent with GermainUX’s existing alert muting logic.

image-20250808-125423.png

Scripted Portlet

Customers: MedPro Staffing

Ability to customize a portlet through scripting (not just configuration settings, as has been the case). Similar to the Table Portlet, except this Scripted Portlet is fully generated from the code you write.

For example, you could build a real-time portlet that displays various metrics in an Excel-like table:

image-20250826-202129.png

Scripted Portlet Example - GermainUX

Time Intervals

Customers: eBay, Largest US-Based Healthcare Organization

Time Intervals Now Fully Available!

All Time Interval options have now been added across the GermainUX workspace — including areas like the Report Editor — where they were previously missing.

This enhancement ensures a consistent and complete experience when analyzing data across different time ranges.

image-20250711-134517.png

Time intervals - GermainUX

Time Zone Options for Action Services

Customers: ANZ Bank, eBay

GermainUX now supports using a time zone of your choice when executing actions via the Action Service.

🔧 How It Works:
  • Timestamps such as queryStart and queryEnd are evaluated based on the time zone of the environment where the Action Service is running.

    • For example, if the service is running in a container or server configured with UTC, the queries will use UTC timestamps.

  • Automated Reports executed by GermainUX backend services follow the configured time zone for each specific client environment.

This ensures accurate scheduling and data processing, aligned with your local or preferred time zone settings.

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Automated Report sent in User’s Timezone - GermainUX

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Time zone setting option for a GermainUX user


💡 TIPS

💡 Tip: Use CTRL + S to Quickly Save Your Work in GermainUX

Did you know you can quickly save any updates in the GermainUX workspace by pressing Ctrl + S? It's a simple time-saver!

💡 Tip: Export Session Replays — Individually or at Scale!

GermainUX gives you two powerful options to export session replays, depending on your needs:

🔹 Export an Individual Session Replay

Gain access to all the raw details captured in a single session, including clicks, movements, transactions, errors, and events.

How: Open a Session Replay → Click the Export button (top-right corner).

image-20250807-180214.png

Export Raw Details from a Session Replay - GermainUX

🔹 Export Session Replays at Scale

Extract high-level user experience insights across multiple sessions — e.g., customers placing orders, adding products to cart, or encountering CRM issues.

How: Drill down into a Story Beat KPI → Navigate to the Drillthrough Dashboard → Click the Export button.

image-20250807-180422.png

Export User Experience Insights for one or many Session Replays, at once - GermainUX


CLIENT TESTIMONIALS

See What Users Say about GermainUX on Shopify!

Customers: AllBirds, ProAirTools, CatherineMichiel

We thank our customers for posting such great reviews—it means the world to us!

More details: Customer reviews about GermainUX on Shopify.

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GermainUX Customer Reviews on Shopify Marketplace

See What Users Say about GermainUX on Salesforce AppExchange!

Customers: Airline, Financial Institution, Insurance Broker, Largest Healthcare

We thank our customers for posting such great reviews—it means the world to us!

More details: Customer reviews about GermainUX on SFDC AppExchange Marketplace.

image-20250127-010157.png

GermainUX Customer Reviews on SFDC AppExchange Marketplace

Hear from a CIO that has used GermainUX for 8 Years!

Customers: Financial Institution

Listen to what the CIO of a large financial institution says about their 8 years of using GermainUX:

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CIO says GermainUX is “a critical piece of observability for his IT operations”


SECURITY AND VULNERABILITIES FIXES

Customers: All customers are required to apply the following patches to update Germain

In alignment with SOC 2 compliance, patches have been developed for vulnerabilities identified in GermainUX version 2024.3 and earlier. Please generate a support ticket or contact Germain support for assistance.

Vulnerability

Severity

Scope

Detected

Reviewed

Resolved

Affected versions

Fix implemented in

Link

[CVE-2024-50379]

HIGH

catalina [10.1.26] -> [10.1.34] -> [10.1.35]

12/22/2024

12/23/2024

2/17/2025

2024.1+

2024.1.65, 2024.2.97, 2024.3.4

https://nvd.nist.gov/vuln/detail/CVE-2024-50379

[CVE-2025-24970]

HIGH

netty-handler [4.1.100.Final] -> [4.1.118.Final]

2/15/2025

2/17/2025

2/17/2025

2024.1+

2024.1.65, 2024.2.97, 2024.3.4

https://nvd.nist.gov/vuln/detail/CVE-2025-24970

[CVE-2024-23450]

HIGH

elasticsearch [7.17.16] -> [7.17.27]

2/15/2025

2/17/2025

2/17/2025

2024.1+

2024.1.65, 2024.2.97, 2024.3.4

https://nvd.nist.gov/vuln/detail/CVE-2024-23450

[CVE-2025-22228]

HIGH

spring-security-crypto [6.2.7] -> [6.3.8]

3/22/2025

3/24/2025

3/24/2025

2024.1, 2024.2, 2024.3

2024.1-67, 2024.2-115, 2024.3-64

https://nvd.nist.gov/vuln/detail/CVE-2025-22228

[CVE-2024-52316]

HIGH

tomcat [10.1.26] -> [10.1.39]

3/22/2025

3/24/2025

3/24/2025

2024.1, 2024.2, 2024.3

2024.1-67, 2024.2-115, 2024.3-64

https://nvd.nist.gov/vuln/detail/CVE-2024-52316

[CVE-2024-22371]

HIGH

camel-support [4.0.3] -> [4.0.4]

4/26/2025

4/28/2025

4/28/2025

2024.3+

2024.3-74

http://web.nvd.nist.gov/view/vuln/detail?vulnId=CVE-2024-22371

[CVE-2025-31650]

CRITICAL

tomcat [10.1.39] -> [10.1.40]

5/3/2025

5/5/2025

5/5/2025

2024.1, 2024.2, 2024.3

2024.1-69, 2024.2-122, 2024.3-74

http://web.nvd.nist.gov/view/vuln/detail?vulnId=CVE-2025-31650

[CVE-2024-52979]

CRITICAL

elasticsearch [8.15.5] -> [8.16]

5/3/2025

5/5/2025

5/5/2025

2025.1

2025.1-0

https://nvd.nist.gov/vuln/detail/CVE-2024-52979

[CVE-2025-48734]

HIGH

commons-beanutils [1.9.4] -> [1.11.0]

5/30/2025

6/2/2025

6/2/2025

2024.3

2024.3.86

https://nvd.nist.gov/vuln/detail/CVE-2025-48734

[CVE-2025-27817]

HIGH

kafka [3.7.2] -> [3.9.1]

6/14/2025

6/16/2025

6/16/2025

2024.2, 2024.3

2025.1-0

https://nvd.nist.gov/vuln/detail/CVE-2025-27817

[CVE-2025-41234]

HIGH

spring-web [6.1.15] -> [6.1.21]

6/14/2025

6/16/2025

6/16/2025

2024.2, 2024.3

2025.1-0

https://nvd.nist.gov/vuln/detail/CVE-2025-41234

[CVE-2025-4949]

CRITICAL

jgit [6.7.0.202309050840-r] -> [

6/14/2025

6/20/2025

6/20/2025

2024.1, 2024.2, 2024.3

2024.1-73, 2024.2-142, 2024.3-86

https://nvd.nist.gov/vuln/detail/CVE-2025-4949

[CVE-2025-48988]

HIGH

tomcat [10.1.41] -> [10.1.42]

6/21/2025

6/23/2025

6/23/2025

2024.1, 2024.2, 2024.3

2024.1-74, 2024.2-146, 2024.3-98

https://nvd.nist.gov/vuln/detail/CVE-2025-48988

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