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Aiquinox(Redefining Performance Monitoring)

Discover Impactful Performance Issues with AI Analytics.Cut through the Noise of Traditional analytics & Monitoring with Powerful AI

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The Modern Digital Experience Stack

In today’s world, product teams have moved from shipping once a month, to once a week, to multiple times per day. They also run A/B tests, have feature flags, and are personalizing content for their users. The set of things that can go wrong has grown enormously. Teams now rely on a variety of softwares to monitor their apps, but most solutions aren’t built to surface these problems efficiently.

The Modern Digital Experience Stack

In today’s world, product teams have moved from shipping once a month, to once a week, to multiple times per day. They also run A/B tests, have feature flags, and are personalizing content for their users. The set of things that can go wrong has grown enormously. Teams now rely on a variety of softwares to monitor their apps, but most solutions aren’t built to surface these problems efficiently.

Product Analytics

Raising More Questions than Answers

Most product analytics solutions do an excellent job and surfacing quantitative insights, like revealing the percentage of users that failed to complete a conversion step. However, this is where their utility starts and ends. You’ll only be informed of what happened, and be left wondering.

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Session Replay

Unclear what Sessions are Valuable

Software teams often struggle to realize the full potential of session replay software due to the sheer volume of sessions collected. The majority of solutions do very little to point you towards meaningful experiences, so teams are left manually sifting through meaningless sessions looking for something interesting

Eliminate

A Sea of False Positives

Solutions specializing in issue monitoring and frustration signals often generate hundreds or thousands of alerts per day, but the vast majority of them have little to no impact on the end user’s experience. To make matters worse, the most impactful errors often have low incidence, making them even harder to discover and prioritize.

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The MDES

Modern Digital Experience Stack

In today’s world, product teams have moved from shipping once a month, to once a week, to multiple times per day.

They also run A/B tests, have feature flags, and are personalizing content for their users.

The set of things that can go wrong has grown enormously.

Teams now rely on a variety of software to monitor their apps, but most solutions aren’t built to surface these problems efficiently.

“Streamline user authentication with robust Single Sign-On (SSO) support, allowing users to access the application seamlessly with their existing credentials.”

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Extracting Signal from Noise

Stack The best of breed options in the market now are solutions like AIquinox AI -which combine session replay, analytics, and issues together.

But even with that, there’s so much data available that it can take days — or sometimes weeks — to understand what’s going wrong.

Let’s look at each product are a individually to see why this is so hard...

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Product Analytics - RMQAS

Raising MoreQuestions than AnswersSession

Most product analytics solutions do an excellent job and surfacing quantitative insights, like revealing the percentage of users that failed to complete a conversion step.

However, this is where their utility starts and ends. You’ll only be informed of what happened, and be left wondering.

“Use SSO login tokens to securely launch the application in a browser tab, ensuring a smooth and secure user experience.”

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Session Replay - USV

Unclear what Sessions are Valuable

Software teams often struggle to realize the full potential of session replay software due to the sheer volume of sessions collected.

The majority of solutions do very little to point you towards meaningful experiences, so teams are left manually sifting through meaningless sessions looking for something interesting.

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IM & FS - A Sea of False Positives

Issue Monitoring & Frustration Signals

Solutions specializing in issue monitoring and frustration signals often generate hundreds or thousands of alerts per day, but the vast majority of them have little to no impact on the end user’s experience.

To make matters worse, the most impactful errors often have low incidence, making them even harder to discover and prioritize.