Automated monitoring is broken—we hope to change that with ExperienceAI

February 2, 2021 By: Trevor Pyle

At this year’s Quantum LEAP we announced ExperienceAI, Quantum Metric’s new machine learning engine. In short, ExperienceAI works by surfacing the anomalies that impact the KPIs you care about, identifying which segment(s) are disproportionately impacted, and proving the validity of the issue with a curated list of session replays—all within minutes. If you are interested in getting beta access, click here to sign up! If you are new to Quantum Metric and want to get an overview of the platform schedule a demo with our team!

For now, let’s dive into how into why we are investing in machine learning at Quantum Metric!


Why machine learning at Quantum Metric?

Like much of what we do here at Quantum Metric, the concept of ExperienceAI was driven by our customers. We listened to direct feedback (such as interviews, surveys, etc) and gathered inferred feedback (things like usage patterns, engagement, etc). That is, we practiced what we preached and followed the tenets of Continuous Product Design. Our customer’s feedback helped us determine a simple guiding principle for ExperienceAI. They needed to do more with less. Why? 

Their digital products are now the face of their brand. In-store experiences are limited, so the digital experience needs to be flawless on every platform. For brands who–before the pandemic–saw digital as a secondary channel, this transition isn’t exactly easy. The tables have turned, and these brands need an easy but effective way to surface issues that were impacting their digital audiences. 

But the product, operations, and analytics teams don’t want to be inundated with alerts or spend hours setting up monitoring. Teams are leaner than ever and the digital ecosystem is too complex. They want to monitor every permutation of their audience, but they don’t have the time or resources to manually monitor every customer interaction.  

They wanted more from our data. More accessibility. More speed to insight. And most importantly, they wanted Quantum Metric’s dataset to be approachable for everyone (regardless of technical skill or role.)  

Teams don’t want to spend time chasing down issues, setting up alerts, or even thinking about what isn’t working. They want to set these tasks on autopilot so they can spend more time building what’s next. We dived deep into the “why” behind ExperienceAI at Quantum LEAP. If you missed the product announcement, catch the recording below. 

Quantum Metric Product Updates: LEAP 2021 

In fact, we are just getting started with ExperienceAI. The foundation of the Quantum Metric platform in tandem with ExperienceAI is why we (our team and our customers) are so excited about its potential.

Let’s take a look at a few of the foundational reasons we believe ExperienceAI is going to change the way you think about machine learning and deliver on the promise of automated monitoring.


Put good in, get good out

It’s like the opposite of what your grandma would tell you when you ate candy (or at least my grandma). Every good ML engine consumes dataand lots of it. They need an incredible amount of data in order to create more predictability and accuracy. They also need variety and depth in order to arrive at insightful conclusions. In short, you need really, really good data. 

Good news! Quantum Metric captures the richest set of customer-centric data on earth. Fullstop. 

Quantum Metric automatically captures hundreds of metrics, errors, and events at the session level for every customer that visits your web or mobile application. Hundreds of events, errors, and other metrics are collected out of the box, and the list grows (automatically) as your application or website expands. 

So why are we this passionate about capturing as much data as possible?

The answer is simple—more data leads to more context. Excellent customer experiences are like a symphony. Everything (frontend, backend, APIs, UX, everything) needs to work together working together in order for them to operate. The server needs to respond, the messaging needs to be clear, the mobile layout accurate, and about 2671 other things or so. 

If someone is rapidly scrolling on a page, for instance, maybe it’s because an API has failed and the offer they are looking at doesn’t match what an email campaign promised. Bad (and good) experiences don’t often happen in silos. In order to build the artificial synapses that lead to insightful conclusions, you need signals for every aspect of the customer experience. You need a comprehensive, accurate, and real-time dataset that comes in three distinct flavors in order the understand the full context behind the customer experience. 

However, many AI/ML engines are focused on one particular type of dataset, such as infrastructure, business-level, or sentiment. Siloing data can create insight gaps, which can make even the best data unreliable. 

When teams don’t evaluate the entire digital customer experience, this leads you (and everyone else) to think “this AI thing just doesn’t understand my business.” The scope of Quantum Metric’s capture, combined with our proprietary machine learning models, will ensure that monitoring is reliable and accurate.


Removing obscurity from traditional AI insights

Does this scenario feel familiar? 

You’re somewhere between validation and concern. You have just received a flurry of notifications and now you are checking out an anomaly (powered by AI detection). You’ve got more API 500s than a cactus has thorns. It seems bad, but is it?

Quantum Metric ExperienceAI aims to answer questions, not create them. At the end of every insight, dashboard, and alert, there is visual validation, in the form of Session Replay. And from that single experience, you can quantify the opportunity cost of the issue at hand across your entire population.  

The customer’s perspective is the indisputable truth. Traditional analytics are often abstracted away from the actual customer experience, only providing charts and graphs that are representative of what the customer actually experienced. Aggregate data visualizations combined with Session Replay makes it easier for teams to empathize with customers, in addition to equipping teams with all of the technical details they need to identify the root cause of the problemevery API call, click tap, request, response, etc. For technical and non-technical audiences alike, Session Replay simply is the fastest way to get to that “aha!” moment. 

Combining Session Replay with ML-generate insights makes it easier for organizations to trust the data being presented. Session replay helps teams to validate issues and align around the next steps.


Don’t call it a feature

Let’s drop the buzzwords for a second and talk about superheroes. To better understand the scope of ExperienceAI, let’s talk about Ironman. Ironman is a character from the Avengers franchise and his suit is pretty nifty, to say the least. It has rockets, ion blasters, and jet boosters. It probably even has windshield wipers and cupholders. Overall, the suit as a standalone has some very valuable features and functionality. The suit can be equated to the Quantum Metric platform.  

We see ExperienceAI as a power mechanism (or the Arc Reactor if we want to be precise). The Arc Reactor enables the suit to do everything it already does, but faster, better, and with more intelligence. 

We see ExperienceAI empowering the Quantum Metric platform and allowing you (like Ironman) to be superhuman. ExperienceAI isn’t just a feature or even a singular addition to the platform, it’s an engine for insights. ExperienceAI is going to constantly process petabytes of data, create historical benchmarking, and form a silhouette of your standard day to day operations so it can surface anomalies 24/7/365. ExperienceAI is going to proliferate insights throughout the entire platform, adding even more actionability to multiple parts of the Quantum Metric platform. 

All this to say that ExperienceAI is not a one and done. We’ve invested heavily in a world-class data science team and patent-pending ML techniques. This first manifestation of ExperienceAI is only the beginning. 


Seeing is believing—sign up below if you are interested in the beta!

These days, just about everything (and every software company)  has “AI”. I think my refrigerator even has AI. This is not to disparage companies who are doing incredible AI/ML work. It’s certainly not to comment on any Colorado-based companies who just revealed a major new product enhancement that has”AI” in the name. It’s simply to say that words like artificial intelligence and machine learning have come to be used very liberally.

Until this point, we at Quantum Metric have been very pragmatic about how we describe the platform. We built a lot of intelligence into the platform. We created ways to query across incredible amounts of data. But until this point, we didn’t want to call what we were doing machine learning or artificial intelligence. That’s since changed. ExperienceAI is leveraging true Machine Learning techniques, with the potential to grow towards true Artificial Intelligence. Patent-pending data science, months of model testing, and some incredibly smart engineers have helped us achieve this milestone. We are proud of what ExperienceAI is and what it will become.

We know there is a lack of trust around the concepts of AI/ML and we believe ExperienceAI has the potential to change that. The first step in that journey is to see how it works for yourself. If you are a Quantum Metric customer, click here to sign up for our beta interest list. If you are not quite a customer, click here and we will let you know when we can take you on a tour of Quantum Metric ExperienceAI.


Missed the product announcement keynote? Check it out here!

Interested in Learning More?

Get a demo