Heap acquires Auryc for session replay insights into user behavior

Phil Wainewright Profile picture for user pwainewright June 1, 2022 Audio mode
Summary:
Heap announces its acquisition of session replay specialist Auryc, adding qualitative insights to its quantitative analysis of digital user behavior

Rachel Obstler, Heap, screengrab from Zoom call
Rachel Obstler, Heap (screengrab from Zoom call )

Heap, which automates collection and analysis of digital interactions, today adds qualitative analysis of user behavior with the acquisition of Auryc, a leading provider of session replay software. While Heap collects quantitative data of website and mobile app behavior — analyzing user journeys collectively to discover moments of friction or opportunity — Auryc adds the ability to drill down on individual sessions and understand the context in which those moments occur.

Here's a concrete example. Let's say the quantitive analysis surfaces a choke point where people are dropping off, such as a product page where they have to choose between different options. With the addition of Auryc, Heap users can now simply click through from the choke point to see exactly what's happening in individual user sessions, and understand the context leading up to the issue. As Rachel Obstler, EVP of Products at Heap, explains:

The first thing you want to do is find where people are getting stuck. You want to do it from a quantitative point of view, because it tells you where the biggest impacts possibly are — the most people are getting stuck here, this is the highest value place to improve. Then the second you find it, the immediate instinct is, now I want to watch it.

Typically, that next step has meant going to another tool, finding the sessions and downloading them, a process that might take several hours. Very often, the temptation is to simply guess what's happening rather than going through all that extra effort. With Auryc now becoming a native part of Heap — an integration that's due to be delivered in the summer — the session replay will be available simply at the click of a button within the quantitative analysis. Obstler continues:

This makes it literally, you found the point, click a button, watch it, watch another one, watch another one. It makes it so easy ... No one has to be technical, to be able to find these points of friction. Anyone can basically see a point and then watch it and understand what's going on.

Getting stuck or sailing through

The acquisition rounds out Heap's offering, which started out collecting the complete data set of user interactions on a website or mobile app, and then last year added a data science layer to help identify areas of interest across that dataset. Session replay is the next step, as Ken Fine, CEO of Heap, explains:

The technology says, something's happening here. What's happening? So now, this allows you to apply some basic, old-fashioned, qualitative human judgement — let me look. This is our hotspot, this is where people are getting stuck, where they're struggling, or maybe they're sailing through. Let me click in and look at examples of three, five, seven, 10, 12, whatever you like, journeys in that exact spot.

The obvious use case is for product managers and marketing folk who want to make sure the digital experience is as intuitive and fluid as possible. But another use case comes out of customer support, where having solved an issue for one individual, an agent might then look into whether others have encountered the same problem. Fine elaborates:

You're working in customer support, and people are complaining about getting stuck, and you're using session replay to look at their experiences. You can now work backwards to say, I wonder if this is a common place that people get this, or is it specific to this one person? So the workflows can go both directions — from find a hotspot and watch it, or watch it and then see if it's a hotspot.

This is a use case that might also be relevant in engineering or customer success as Obstler explains:

You're getting a piece of feedback, which is singular, from a customer, and you're trying to figure out, 'Is this a real problem? Was it a one off thing? Is it a bug that needs to be fixed? Is it a workflow problem that we need to improve?'

Being able to watch it back and apply the analytics to it — how many people has this happened to in the last year, month, week? Is this something that is worthwhile fixing? It immediately allows you to first validate it and then quantify it, and figure out where it falls in your investment priorities.

This combats the difficulty of interpreting exactly what is happening when looking at data about user behavior. She adds:

One of the big challenges with data is really understanding what it represents, or making sure that you don't misunderstand it. That's another layer to why it's so important to bring together the session replay and the analytics, that you can do an analysis and then immediately understand what it represents — and really trust that it represents what you think it represents.

Capturing context

Auryc also has a 'voice of the customer' capability, where it can insert a simple survey at any point in a user journey, with the advantage that it also captures the context in which the survey reponse was given. Obstler explains:

You may have someone who actually answered a survey and said, 'This product sucks.' What you can do is, you know exactly when they wrote it, you can watch exactly what they did, before they wrote it, and understand what is making them feel this way.

So you can integrate all three of those things together, not just the analytics, not just watching what people are actually doing so you understand the flow, but also their sentiment and what may be driving that sentiment. Putting those three things together in a way that you just can't do today with separate tools, because you can see the sentiment, but you don't know exactly what happened.

Terms of the acquisition were not disclosed. The deal brings talent as well as technology, with Jinlin Wang, CEO of Auryc, now becoming Heap's Chief Strategy Officer, and other members of the team coming on board in key roles. Fine says:

They have a similar vision as we do, which is this combination of quantitative and qualitative. They're essentially a team of very talented technologists who spent the last five years trying to solve the same problem and using a relatively similar technology stack. So our ability to leverage the talent of that team and integrate them into our team is, we think, very high.

Recognizing that customers may already be working with other session replay tools, Heap is also supporting integration with other tools, starting with LogRocket. Fine says:

We're building an open platform. You can either use our integrated solution, which we're obviously building through the Auryc acquisition, or starting with LogRocket, if you're already a LogRocket customer, we can turn on that integration, combine the two. In the future, if you're using some other platform already and you want to integrate that with Heap, we've built the APIs to do so.

My take

Digital is great for automating at scale, but the downside is that individual user experiences become harder to track. Yet the promise of digital is a more joined-up, frictionless experience for everyone. How to reconcile these two goals? Heap offers a data-driven solution that helps surface issues and then be able to drill down into individual experiences and understand what the data actually means. With many companies still grappling with siloed datasets that get in the way of seeing the whole picture, this is a refreshing approach to a big issue for digital builders.

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