Glassbox: Enterprise Customer Intelligence and Session Replay

My main use case for Glassbox  was to track the customer journey and session replays, capturing the analytics setup of the customer portals.

We had applications where a customer would come and fill in many large forms. There were interactive elements to choose from as an onboarding journey and we implemented Glassbox  there to track drop-off points, where users were spending more time. If there was a drop-off, we wanted to understand the exact reason and how customers were behaving with the onboarding process.

We also saw many errors, JavaScript errors, and front-end errors on the portal. Glassbox could identify broken flows, which helped us significantly.

The best features Glassbox offers are the tagless sub-capture, which I believe is very fast to implement compared to other tools, and it has strong session replay with enterprise-grade capabilities that work very well for larger applications.

Tagless implementation made the implementation faster because there is no need for constant tagging updates. Other vendor tools often require that on a regular basis, so considerable effort was saved there. In terms of strong session replay, Glassbox's offerings were more comprehensive than competitor tools, allowing us to see real-time visibility into issues.

Glassbox positively impacted our organization because we got a one-stop solution to track all different journeys, different dashboards, and different applications. We could do all the analytics around how users were behaving and what interactions were occurring. Glassbox is used extensively by research, UX, and marketing teams, and it has made a positive impact.

Glassbox can be improved because it is somewhat complex and there is a steep learning curve that requires training. Making it simpler would help. Secondly, it is somewhat overkill for basic analytics. Working in a startup, it is very expensive and the pricing is not very transparent. If I want to use a dashboard like Google Analytics  or Mixpanel , it is quite expensive and complex, so having a lighter feature set for small-scale SMBs could be beneficial.

I have used Glassbox for about three years.

Glassbox is stable.

Glassbox's scalability is excellent as it is a complete enterprise tool, so we have no issues in that regard.

Customer support is good. We had an enterprise plan, so we had a relationship manager, which made everything easy. We did not encounter many technical issues, so not much support was needed. Learning was easy as well, with many available courses and content to set up. Once you work with a couple of applications, it becomes easier.

Previously, I had a mix of solutions, which included Google Analytics , Adobe Analytics , ContentSquare , and Quantum Metric . We switched to Glassbox to streamline into one solution.

The setup was seamless, and the support and implementation team were really helpful.

We saw a return on investment with Glassbox as we recovered the cost of implementation. The two main metrics were a better customer experience with fewer support issues and improved technical efficiency.

My experience with pricing, setup costs, and licensing was that the pricing was enterprise negotiated pricing based on sessions and features captured, along with a feature module, making it quite complex.

Before choosing Glassbox, we did not evaluate many other options. We got a very good recommendation about Glassbox and moved forward, although we had checked out Quantum Metric  and ContentSquare .

My advice for others looking into using Glassbox is that if you are a startup or a small company, do not use Glassbox. There are easier to implement and cheaper tools for simple requirements. However, if you are an enterprise company needing one tool for everything, a complete end-to-end implementation with sufficient resources in terms of money and time, then use Glassbox as it is scalable and enterprise-grade.

Glassbox is a powerful digital experience platform with complete visibility into user behavior through multiple features. If you have the time and money to invest, Glassbox is a very good tool. I would rate this review a nine out of ten.

Our main purpose for using Glassbox  is to capture user sessions and user activity on the live site. Based on that captured data, we create funnels and reports to check the customer impact for specific services or categories that are failing and identify which countries are impacted.

For example, if a person is trying to purchase a product and add a laptop into the cart but encounters intermittent errors during this process, and then receives errors when clicking the checkout button stating they are unable to checkout, Glassbox  captures this real customer experience. When this happens, specific error messages are displayed on the screen, and Glassbox highlights it as an alert with a 5XX response status code.

From a day-to-day perspective, we have created specific dashboards and reports that provide alerts if any unknown activity occurs on the live site. When a customer faces a real issue, we receive alerts and notifications that help us understand what is happening.

Glassbox now has GIA as an AI integration that provides analysis very quickly without needing to watch the entire session. Based on previous results, the analysis is accurate 90 to 95 percent of the time regarding possible reasons why a user faced an issue. Based on that analysis, we can make a report and get things done to prevent errors.

The best features that Glassbox offers are reporting and the funnel. These two use cases help us most as we can determine the expected count for user behavior and compare it to earlier weeks and days from the same period. In the report section, we can identify specific alerts that are being triggered on a regular basis so we can capture and analyze them and fix them in the longer term.

The funnel feature helps us check user impact and identify which countries or specific areas the website is failing in. With this feature, if a customer is facing a cart page error, we can check how many users were impacted at that specific time and which regions those users are experiencing errors. We can also check what products those customers are trying to add. Based on that information, we can create a report and check comparisons. When we share it with the business team, they can determine if the issue is widespread and work on it with higher priority, or if it has lower impact with fewer users affected, indicating an intermittent error that can be worked on with lower priority.

Glassbox has had a positive impact on my organization through all the features it provides. As AI is advancing and its adaptability within the app itself integrates many use cases, the reports, funnels, dashboards, GIA features, and integrations that Glassbox provides help us address issue behavior and work on resolutions. Additionally, it creates reports that we can share with other teams so they can determine if the impact is wider. To prevent errors quickly, Glassbox captures reproducible customer errors. If an error is not reproducible, Glassbox does not capture it and can mark it as a false alert. This is how we prevent false alerts and capture only genuine alerts.

There are some areas where Glassbox does not capture genuine issues. For example, during login procedures involving multifactor authentication in someone's personal use case, if a user is failing at login, Glassbox sometimes does not capture the actual error because the error is intermittent or not continuous. Glassbox occasionally skips that and misses it.

Glassbox is a heavy tool and not a normal one. There are sometimes issues with Glassbox itself where some alerts do not get captured or the GIA integration does not show correct results, but it is being learned and improving.

I have been using Glassbox for around two years.

Glassbox is stable most of the time.

Glassbox's scalability is stable according to our organization's requirements. When an issue arises, there is a slight delay of three to four seconds to load data at heavy data loads, but once it starts, it does not lag or hang significantly.

Most of the time, when any activity needs to happen, we receive prior information regarding any expected delays or errors. Sometimes we do not have that information, but when we reach out to them, we receive a quick response and the issue is fixed.

Before Glassbox, we had different dashboards that captured errors, but we were not able to check what the actual user was experiencing regarding the issue. If an issue existed, we could only check which user faced the issue or what behavior we were getting, and that was the final result. With Glassbox, we can check real customers and identify which regions they are failing in.

Glassbox has helped us save considerable money and time. For example, if an issue needs to be solved by manually checking many users to determine whether the issue persists, Glassbox provides real customer data and real customer user sessions. Based on that analysis, what previously required eight people to manually check the data can now be done by three to four people using Glassbox while working in parallel.

We receive alerts that we have specified and set based on scenarios we have encountered earlier. We set a time frame or alert specific to those scenarios so we receive notifications and can capture issues earlier. Before a real customer is impacted, Glassbox itself tests using bot users that run accordingly. When those bot users fail, we know that this is the issue behavior we can expect. We attempt to replicate these issues ourselves to confirm they are problems we can foresee. Glassbox helps us know about those things earlier, providing us time before real users are also impacted and face the same issues. By escalating to the desired teams, we help prevent those errors.

I do not have additional items to address regarding needed improvements at this time.

I am not completely aware of the pricing, setup cost, and licensing, as the admin team or the business team has handled that. We are not involved in knowing the license costs or the setup that has been done. We simply use Glassbox and its features on a daily basis.

If an error is not reproducible, Glassbox does not capture it and can mark it as a false alert. This is how we prevent false alerts and capture only genuine alerts, which is how Glassbox has helped us overall.

The questions were precise, and overall, it was a good experience. I would rate Glassbox nine out of ten.