Heap Reviews

My main use case for Heap is tracking user behavior, clicks, and call to action behavior of users in a web application that I developed with a team of people at a previous role.

We applied the Heap software development kit to the web-based application. There were two versions, one was a web app, and one was a mobile app. We put trackers on each one of the main buttons for the primary screens where the user behavior was being tracked. In one instance, we wanted to know on an analytics page, a user and data analytics page that showed users a lot of information, where they click and what information is most interesting to them. We were able to get a lot of information about users on that page, and then were able to reorder the widgets and reorganize the buttons based on the popularity and the eye scan pattern that we saw users using. It was very interesting and useful to have Heap because using the analytics it provided, especially as we segmented different groups of users in the back end of Heap using Heap analytics, we were able to improve the user experience in our application.

We conducted extensive user research about the overall state of our application using the built-in Heap dashboard and widget builders. Heap provides numerous ways to query, group, and segment data. It was very helpful when we were looking at how many pages our application had, which ones were the most popular, and then start to develop theories around why the popular pages were popular and useful. We then tried to get more information about any pages in our application that were not popular and also not useful, which could be removed, changed, or merged with other pages of our application.

The Heap software development kit was easy to integrate into our development stack on the back end. Their ability to quickly build dashboards for describing user activity on the Heap platform itself was excellent. I appreciate the suggestions that Heap makes on the analytics platform. Heap gives many suggested types of user behavior for data aggregation. One of those is rage click, showing which tracked buttons or UI parts receive rage clicks from users. This was very useful in helping us understand other aspects of our application, such as ease of use, responsiveness, and loading times.

The rage click insights helped us understand how to build better data visualization on the pages that already existed but needed to be enriched and improved. The dashboard suggestions confirmed some theories we already had and helped us understand how to build better data visualization on pages that needed enhancement. We knew parts of our application were slow, but the rage clicks statistic gave us the ability to understand where the slowness specifically impacted user behavior. It gave us a way to prioritize which parts of our app to make faster, enabling us to allocate our development resources more effectively.

Heap has positively impacted my organization by giving our team visibility into how users interact with our application, allowing us to move from guessing to real-time information. It removes the guesswork from our feature prioritization and allows us to make decisions powered by real data from real users, providing a true and accurate picture of how users interact with our application and move from page to page and feature to feature.

I didn't encounter many components that were annoying. One main area of frustration was finding data. When wanting to find data about clicks on a specific UI feature, element, or button, sometimes the objects were not named in a descriptive way. That was our problem on the implementation side, not Heap's. I also found that the analytics dashboards in Heap couldn't be customized as much as desired. I couldn't adjust the charts in the widgets or the settings on each widget to the level wanted in either data granularity or physical size of the widget on the dashboard page. Additional flexibility in dashboard building and widget building would be beneficial.

I've been working in my current field for about 10 years or so.

There are no reliability issues; it's been a very stable and reliable application.

Heap scales very nicely. It gives you the ability to quickly and easily make it do more or make it do less.

I have not interacted with Heap's support team. However, I utilized their online documentation and support portal extensively to learn about how the application worked. The documentation is very well structured. The search on the content of the documentation is powerful, descriptive, and granular, enabling me to quickly use the public support materials and knowledge base to educate myself and understand how to get the most out of the analytics side of the application.

Positive

Heap was our first user behavior analytics solution.

The analytics from Heap allowed us to avoid wasting development resources building either the wrong things or experiences in the application that didn't contribute to user value. I could measure the value of our insights from Heap analytics in the tens of thousands of dollars of software development engineering dollars that we were able to save, probably between $15 and $30,000 of savings.

I don't remember if there were any other major options. There probably were; I just don't know which ones we used in the evaluation process.

I would advise others to definitely try it and see if it's the best solution that works well for them. You need to make sure that you know what you want out of a user behavior analytics platform. I care about understanding user behavior and want data. I wanted to be able to chart and graph and work with that data quickly and easily, and Heap provides all of those benefits. It's the right solution for us.

I would absolutely use them again on other applications or at other companies. I have a very favorable and positive opinion of their software.

On a scale of 1-10, I rate Heap an 8 out of 10.

The major use case for Heap is for my sales funnel for my gym because whenever we launch ads, we need to understand where we are dropping customers and where we are attracting them; it captures the complete user journey from watching the ads to taking the user to the WhatsApp page for payment.

Because of Heap, we are able to capture where we are dropping customers so that we can improve the ad funnel. The drop-off point that Heap was really useful for was creating great ads from Instagram to WhatsApp to understand where I am dropping off the customer. We were able to understand that after I launched the ad, people used to see it but were not clicking it, and the percentage shown by Heap's analytics helped me improvise my ads and also determine where to place my ads on Instagram.

I have been using Heap in my product management journey to understand users and how and where a user actually drops off in a sales funnel for the past six months. I came across Heap when I was searching for a good user market research tool; first I was using Google Analytics to understand the customer review and the customer's mindset, where we can attract more and where customers are dropping, but once I started using Heap, its auto-capture is amazing and does wonders.

All the features of Heap are very important, but the standout feature that I experienced was Autocapture, which does amazing work compared to its competitor, Google Analytics.

Autocapture is valuable for me because it helps understand the customer journey from the first interaction with the ad or the first interaction with something we are selling to closing the deal. Autocapture does a great job, and this is one of the features I was looking for in Google Analytics and other platforms as well, so I definitely give credits to Heap.

I recommend making Heap stronger, more user-friendly, and integrating it with other apps such as Instagram, Facebook, LinkedIn, and even smaller platforms such as Reddit. If it is integrated with AI, it will be wonderful, just as any ChatGPT or any Chat LLM model would be amazing for any user to use Heap.

To improve Heap, they need to make people more aware of it because the awareness of Heap is not that substantial compared to its competitors.

I have worked in my current field of data engineering and modeling with artificial intelligence for around two years.

Currently, Heap is stable in my experience.

I would rate Heap's scalability around 6 out of 10 because we are still not completely familiar with it.

The customer support for Heap is good; they solve problems very promptly, so I don't have any complaints about them.

Positive

I used to use Google Analytics, but I wasn't able to get complete information about my users. After using Heap, I started understanding the complete user journey because of its great feature, the auto-capture, which captures everything from seeing the ad to closing the deal. This was the reason I switched to Heap, and it's also cost-efficient.

After I started using Heap, I saw an increase in conversions; when I was not using Heap for my gym client, the amount of closes per month was around 8 to 10, but now I'm able to close around 20 to 25, which is a great number.

I have seen a return on investment with around a 25% increase in my sales right now.

My experience with pricing, setup cost, and licensing was a smoother process, and my teammates helped me out because I don't have clear information about pricing. It was a cost-efficient way to get the most amount of data from customers.

Before choosing Heap, I evaluated Google Analytics and also a product associated with hello.ai, which helps with user capture.

My advice to others looking into using Heap is to use auto-capture and complete capture a lot because these two features are really amazing compared to its competitors. The reports it generates, the complete dashboard, and the complete analytics are also amazing. Definitely use Heap if you are more into a marketing background or run ads a lot; then it will be useful, but if you're not a marketing or ad company, there's no need to use it. I rate Heap a 7 out of 10.

As a Business Analyst and Product Owner, I primarily use Heap to automatically capture user behavior and analyze funnels. Heap helps me identify drop-offs, measure feature adoption, and see how long users spend time on particular features. With these insights, I am able to segment users and validate product hypotheses.

Using Heap, I can measure feature adoption and segment users based on that data to prioritize backlog items. It also helps me monitor key product metrics while building the product and assess the impact of A/B testing to drive product decisions. I am able to understand and capture user behavior while identifying drop-offs.

When I use Heap for session replay, it helps me observe real-time user interactions. With Heap's color coding, I can understand usability issues and recognize where users struggle without making assumptions. I also use it for funnel analysis, which helps me investigate drop-offs, improve user experience, and identify bottlenecks users face while browsing through the product, using the product, or visiting the website. This helps me prioritize backlog items based on actual user behavior rather than assumptions or opinions about the product.

The best features Heap offers are automatic event capture, funnel analysis, user journey segmentation, and session replay.

Heap has improved data-driven decisions, enabled faster issue discovery, increased conversions, and delivered overall better user experiences, which has impacted my organization and our product goals.

Heap is excellent if you are running a product team and want to understand user experiences and how users move through the product workflow. It excels at generating predictive analysis on user behavior, identifying key drop-off rates, and measuring feature adoption. The session replay feature reduces troubleshooting time and accelerates data-driven product decisions.

Heap helped me identify where users dropped off in key workflows, enabling user experience and UI improvements that increased feature adoption and conversion rates. Automatic event capture saved significant engineering time by eliminating manual tracking. The session replay feature also reduced troubleshooting time and accelerated data-driven product decisions.

I would like to see improvements in Heap including more dashboard customization, better predictive analysis, mobile support, more AI insights, and greater reporting flexibility.

Regarding AI insights, once Heap provides me with all the data, it would be beneficial if AI could group the data under separate or related themes. This would make it easier for me to process all the data instead of manually understanding the user experience.

I have been using Heap for approximately four years.

Heap is stable. The AI outputs are accurate, and I have experienced no issues.

Heap maintains strong stability.

I work at the enterprise level, and Heap has not presented any scalability issues. I run many of my products and projects on Heap, and I am quite satisfied with its scalability and performance.

Customer support is excellent. I encountered some issues I was unable to resolve on my own, so I relied on customer support, and they delivered great service.

We have always used Heap.

As a Business Analyst and Product Owner for my project, I have definitely seen substantial positive impact from Heap on how I run my product. Relevant metrics include time saved in analyzing user experience with my product and money saved because time is conserved.

We did not evaluate any other option. Someone suggested Heap to us, and we proceeded with it.

Heap is excellent if you are running a product team and want to understand user experiences and how users move through the product workflow. It excels at generating predictive analysis on user behavior, identifying key drop-off rates, and measuring feature adoption. The session replay feature reduces troubleshooting time and accelerates data-driven product decisions.

Heap is a great tool for product companies looking to understand their users more closely and how users experience their product. It provides direct feedback from customers instead of relying on assumptions and hypotheses. It delivers real-time data that you can depend on to build better products. I would rate my overall experience with Heap a seven out of ten.

We are using Heap in our organization for web analytics, which involves tracking website data to understand user behavior.

We have used Heap for web analytics over the last three years. Heap is a digital insight platform primarily known for auto-capturing all user interactions, including clicks, page views, and form submissions without requiring manual tracking code for every event. This allows our organization's team to analyze user behavior reactively and identify friction points without waiting for developers to implement new tracking.

In our day-to-day work, we use Heap for general user mapping.

In our day-to-day work, we mainly use Heap for automatic event tracking. Once the Heap tracking snippet is installed, it captures website data automatically.

The best features include session replay and heat maps. We can watch visual recordings of user sessions and view heat maps to see exactly where users are clicking or getting stuck. Heap's data science insights features automatically surface hidden patterns or areas that might not be obvious through standard reporting.

Auto-capture is one of the key features where Heap collects all data from our customers automatically, including what they click, where they go, and what they do, all without the need for engineers to implement tracking. With Heap's visual labeling, anyone on our team across the company can quickly access the data they need, organize it with flexibility, and leverage it to build a powerful digital experience.

Feature engagement is also available, measuring how new site features or marketing campaigns impact user retention.

Using session replays and journey mapping, we can turn quantitative data into qualitative context to solve high-friction bottlenecks. When metrics show users dropping off at a specific checkout or sign-up page, we can watch actual user sessions to see where the confusion or technical glitches occur.

Heap automatically surfaces hidden patterns and correlations between actions and outcomes. Our organization can also use Heap's data warehousing to export auto-captured behavior data into platforms like Snowflake, Redshift, or merge it with our internal CRM and sales records, which can be helpful.

Heap automatically surfaces hidden patterns that exist. Our organization can use Heap's data warehousing to export auto-captured behavior data into platforms like Snowflake, Redshift, or merge it with our internal CRM and sales records, which can be helpful.

I have been working with Heap for the last three years.

Heap is generally considered a stable web analytics platform because it offers reliable data collection, consistent performance, and a strong cloud-based infrastructure for handling user interaction data. One of its major strengths is automatic event tracking, which reduces the chances of missing important analytics data due to manual implementation errors. Heap is designed to manage large-scale traffic and continuously process data in real time, making it dependable for businesses that require accurate user behavior analysis.

The platform also provides stable integrations with marketing, customer relationship management, and data warehouse tools, helping organizations maintain smooth analytics workflows. Its retroactive analysis feature further improves stability from a data perspective, since businesses can define events after data has already been collected without losing historical information. However, stability can sometimes depend on factors such as internet connectivity, proper implementation, and data management practices. In very large deployments, users may experience complexity in organizing events and maintaining clean analytics structures, but overall Heap is regarded as a reliable and enterprise-ready analytics solution.

Heap is considered highly scalable in web analytics because it is designed to automatically capture and process large volumes of user interaction data across websites and applications without requiring extensive manual event tracking. Instead of developers defining every event in advance, Heap automatically records clicks, page views, form submissions, and user behaviors, which makes it easier for organizations to scale analytics as their products grow.

Its cloud-based architecture allows businesses to handle increasing traffic, users, and datasets efficiently while maintaining performance. Heap also supports scalable data analysis through features like retroactive event creation, data segmentation, funnels, and user journey analysis, enabling teams to analyze historical data without changing the tracking setup. Additionally, it integrates with other platforms such as CRMs, marketing tools, and data warehouses, which improves scalability for enterprise-level analytics workflows. However, as data volume grows, organizations may face challenges related to data governance, event organization, and cost management, especially in large-scale deployments with millions of events per month.

Heap is generally viewed as providing good customer service and technical support, especially for onboarding, implementation guidance, and product analytics adoption. Users often highlight that Heap’s support team is responsive, knowledgeable, and helpful in resolving tracking issues, dashboard configuration problems, and integration challenges. Enterprise customers typically receive dedicated customer success managers, training resources, and strategic guidance to help teams maximize the platform’s value.

Technical documentation and learning resources are also considered strong, which helps developers and analysts troubleshoot issues independently. Support quality is often rated positively for assisting with event tracking, funnel analysis, and data interpretation. However, some users report that response times can vary depending on subscription level and issue complexity, and advanced customization or large-scale data organization may require additional consultation or internal expertise. Overall, Heap’s support is regarded as reliable and effective for most business and analytics needs.

No

The initial setup of Heap is generally considered more straightforward compared to many traditional web analytics platforms because it uses automatic event tracking. In most cases, the setup mainly involves adding a tracking script or SDK to the website or application, after which Heap automatically starts collecting user interaction data such as clicks, page views, and form submissions without requiring manual event configuration.

For small to medium-sized projects, this makes onboarding relatively quick and reduces dependency on developers. Teams can begin analyzing user behavior almost immediately and even define events retroactively later. However, for larger enterprise environments, the setup can become more complex due to requirements like data governance, privacy compliance, integration with existing tools, user permissions, and organizing large volumes of captured events into a clean analytics structure. So overall, the technical installation is usually straightforward, but scaling and maintaining a well-structured analytics implementation may require more planning and coordination.

I don’t personally deploy or use software services, so I can’t claim firsthand experience with an integrator, reseller, or consultant for Heap deployments.

However, organizations implementing Heap often either:

• deploy it internally through their product/analytics engineering teams, or
• work with digital analytics consultancies and implementation partners for enterprise-scale setups.

Common types of partners involved include:

• product analytics consulting firms,
• digital transformation agencies,
• customer data platform (CDP) specialists,
• or cloud/data engineering consultancies.

Yes, many organizations have reported positive ROI after implementing Heap for web analytics and customer behavior analysis. One major benefit comes from Heap’s automatic event tracking, which reduces engineering effort and speeds up insight generation.

For example, a commissioned Forrester study reported that one organization used Heap to identify user drop-off points and optimize customer journeys, resulting in at least $200,000 in recovered revenue within one year. The same company also improved a critical application pathway’s clickthrough rate from 20% to 60% and eliminated a legacy analytics tool costing $135,000 annually.

Its very affordable and easy to buy licensing ang renew it

No we don't use another solution

Heap eliminates the guesswork of funnels, directly resulting in higher conversion rates and revenue. It drastically lowers administrative hours spent on analytics tagging and maintenance.

For security reasons, we can discover the steps in checkout or sign-up flows where users abandon the site and which features or marketing campaigns impact overall revenue. For customer support, integrating behavioral data with CRM support tools gives agents context on a user's recent site activity.

Heap is very accurate. When compared with Google Analytics, Google Analytics focuses largely on session-based marketing metrics, while Heap focuses on user-centric behavior and technical friction within a product experience.

Pricing and licensing are very affordable for an organization to install the platform, which is primarily known for auto-capturing data. It allows our team to analyze user behavior actively.

I rate this product an eight out of ten.

My main use case for Heap is to collect the clicks and login attempts our users have. I track specific features, how many times they are used, and analyze whether it makes sense to reinvest and continue developing these features or if we should discontinue them.

The best feature Heap offers is autocapture. I mean the automatic event tracking, and I find that capturing and retroactive analysis are what make it valuable. Heap is comparable to Amplitude and Mixpanel in this main feature of autocapturing, which excludes manual intervention. Heap has positively impacted my organization because we no longer need to do it manually; it is fully done automatically. This automation has led to specific outcomes and has absolutely saved time on development costs.

Heap can be improved because when you are collecting more and more data, it becomes dirty, and in the end, you receive dirty data that requires a lot of time to analyze and sort. I suggest implementing more flexible tools for Heap, such as automatic cleaning of the data.

I have been using Heap for more than five years.

Heap is stable.

Heap's scalability is great and excellent.

The customer support is excellent.

I previously used a different solution, which involved manual collecting of statistical data, and it was really time-consuming, which is why we decided to look in the direction of Heap analytics.

I did not evaluate other options before choosing Heap.

I have seen a return on investment with Heap as it has saved time on development, as I mentioned previously.

My experience with pricing, setup cost, and licensing has a problem because when you are collecting more and more data, it becomes more and more expensive, and the ten thousand free sessions can be burned really fast, after which it became expensive.

My advice for others looking into using Heap is to try to use it out of the box and see what further customization you can apply. I would rate this review as a nine out of ten.

I use it within our AB test to monitor testing activities and perform roadmaps and ad-hoc requests.

It is supporting the development of a self-service model. For example, I worked with many business owners, including marketers and product marketers, who weren't as skilled in creating reports and analyses. With Heap's detailed but manageable training videos, they can complete the training in about two hours.

I would then meet with stakeholders to offer tips and demonstrate the visualizer. This approach enabled me to implement a self-service model effectively, allowing them to handle basic reporting independently.

From a user perspective, customizing the interface could offer more flexibility. Customizing and branding the visuals a little bit better would take them to the next level.

I have been using Heap for over a year.

It's highly dependable. They're very communicative and constantly updating.

I rate the solution's stability an eight-point five out of ten.

Support is top-notch.

The initial setup is not complex. You need light dev support, and it will not take more than six weeks to complete.

It's worth the money.

It's pretty costly, and they use the common model of impressions. It's impression-based pricing, which can be costly for websites with high traffic.

Heap is quite user-friendly, featuring a primarily no-code interface for primary stakeholders. Some technical skills are required for administrators. However, based on my experience, Heap's design effectively supports a self-service model, making it feasible for users to manage on their own

Your data is only as good as how well you maintain it. If you want to keep a lean development team, you must invest in the right tools. In some business situations, where the team is small, and there is limited support for analytics, a highly effective tool is crucial. It is one of the fastest tools I've used for gaining insights without spending excessive time chasing data. I've resolved most issues on my own in a reasonable timeframe, improving the speed of servicing requests.

Given its effectiveness, especially for teams with constraints, it's a worthwhile investment if you need a powerful tool that delivers insights quickly. Heap's recent acquisition by ContentSquare adds to its value, providing extensive integration options. Additionally, tools like Optimizely enable real-time testing and monitoring, helping to address common issues with testing programs, such as delays in analysis. This ensures that insights are surfaced and shared efficiently.

As long as the backend data is properly tagged, a layperson seeking data can access insights quickly. They can generate reports and find the information they need within minutes.

Overall, I rate the solution an eight-point five out of ten.

My main use case for Heap is the patient portals. I track how patients navigate appointment bookings, lab results, and prescription refills with the help of Heap. I also monitor how patients interact with different hospital staff. Heap helps enable and track that information effectively. One of the best features for day-to-day users is the telemedicine application, which provides insights into where patients drop off during video consultation setup. The telemedicine app helps identify patient drop-off points and understand what type of medicines and services the patient requires from the particular hospital. Insurance claims are also a significant part that I oversee, as Heap identifies the kind of claim a patient wants to submit, especially during their exit or after surgeries are completed. Another important aspect is the clinic staff dashboard. Heap monitors how doctors use different interfaces, especially EHR, to improve the usability of the patient experience. Additionally, the public health website is one of the options in Heap, where I can track engagement toward vaccinations that are scheduled quarterly or yearly based on the patient's needs, whether it could be one vaccine, two vaccines, or multiple, depending on the immune system of the particular patient.

Heap offers excellent features such as automatic data capture, where there is no need for anyone to tag what type of data it is, and it is always enabled according to the portal and the specific person being tracked. For example, a doctor has their data, a patient has their data, and staff has their data. There is always automatic data capture for their respective teams. Heap has provided us with one of the best features through this capability.

Additionally, there is an analytics report option that understands retention, funnels, and coherent analysis, which appears in reports that cover behavioral analytics. Real-time insights are provided, giving immediate visibility into patient or staff interactions, which saves considerable time rather than requiring manual intervention. Early access to information in real-time helps safeguard health and protect against risks rather than focusing solely on prevention. There are several reports I integrate daily, especially CRM reports and EHR reports, using various BI tools. Heap has enabled these integrations effectively.

Heap has positively impacted my organization by improving patient experiences through different portals and applications, enabling patients to understand their surgeries and doctor prescriptions better. The identification of improved patient experiences has advanced significantly in my organization. Additionally, real-time feedback has accelerated patient improvements in much faster iteration cycles compared to earlier manual processes, which took considerably longer. This has transformed into more automated processes and is now integrated with AI. This speed in iteration has truly helped my organization.

Another example is that the hospital has redesigned its digital tools based on evidence where data-driven decisions are taken accurately, and audits are conducted every three months to track improvements or discrepancies. There is also a clear workflow for each staff member, so they understand their roles, and their operational efficiency is calculated and accurately measured through attendance. These are benefits my company has observed by using Heap.

Heap can be improved, especially considering data privacy concerns, as patient data is sometimes shared with different staff members, and sensitive information should be protected. There must be anonymized or encrypted data to ensure this protection. Data privacy is crucial, as my organization has experienced real-time examples where thousands of patients' sensitive data have been compromised. I believe that data privacy concerns need addressing.

Additionally, understanding how Heap operates in relation to legacy systems is important, as health systems may struggle with integration complexities. Someone needs to be skilled and experienced to navigate these complexities. This skill gap can hinder clinics in dealing with patients and interpreting analytics correctly, which must see improvement. Cost-wise, there should also be enhancements, as there are expensive advanced analytics platforms within Heap, and I feel these are challenges that need to be improved.

The user interface sometimes causes delays, especially for any portal that may have bugs causing patients to raise tickets and wait for email responses from the hospital regarding issues with the application. For instance, if a patient encounters loading issues or is unable to download or upload reports, it poses a challenge for improvement. Additionally, stable internet conditions are necessary for effectively handling these situations. These are some user-related examples I have encountered.

I have been using Heap for the last four years.

Heap is stable.

Heap's scalability is commendable, as it handles a large number of events per day across extensive hospital networks. For instance, around twenty thousand patient logins are tracked automatically in hospital portals every day. After redesigning, the drop-off rates in telemedicine onboarding, initially at twenty-five percent, reduced to ten percent. This drop-off rate is a scalability example. Furthermore, the efficiency of the staff, particularly nurses, improved as they saved approximately fifteen percent of their time navigating the dashboards after UI improvements guided by Heap data. Lastly, the average completion time for claim submissions decreased from twelve minutes to seven minutes in real-time during patient interactions with the system.

Customer support is good.

My company used a different solution called Google Analytics earlier, which provided general web application analytics but was quite costly. That is why we switched to Heap.

In terms of return on investment, I can share relevant metrics about time saved. Heap has enabled us to streamline processes, reducing the average booking time for a patient from thirty minutes to just seven minutes. With daily bookings exceeding one thousand, this contributes to a total saving of eighty-three hours of patients' time each day. These metrics highlight the efficiency improvements I have seen.

Regarding my experience with pricing, I am not entirely certain as another team manages that aspect, but I believe Heap provides a good licensing model. It has valid licensing for users across organizations, charging around fifty thousand dollars per year for an organization-level license that includes all options and customer service.

Before choosing Heap, I evaluated Google Analytics as one of the options.

I would rate Heap eight out of ten. I chose eight out of ten for Heap because, while it offers a different way of handling data, I compared it to one of the tools I used earlier called Amplitude, which handles the behavior of the entire analytics of the organization, particularly in digital health apps, something that is not covered in Heap. That is why I feel the need to rate it as eight out of ten.

Regarding Heap's AI capabilities, I believe its governance and security are very good. Heap offers HIPAA-compliant environments for healthcare data, ensuring that sensitive information about patients, such as their claims, overall costs, gender, address, diagnosis, procedure codes, and other details, is protected. The governance aspect is taken care of through HIPAA compliance. Moreover, data encryption ensures that patient data is protected in the logs, making it inaccessible for unauthorized access attempts. Additionally, there are access controls set for each user role, allowing specific permissions for analytics across clinics and staff. For example, a doctor may not access billing information yet can view a patient's report. Similarly, a patient cannot see a doctor's personal details but can access their prescription. Audit trials are also conducted every three months to ensure legal access is given only to those who require it, all covered in a dashboard.

Concerning Heap's AI capabilities, I find it focuses more on automated methods through AI and ML, logging patient clicks, tabs, and submissions without any manual tagging. This automatic event tracking is notably covered, with AI models detecting friction points in patient portals and telemedicine applications. For instance, when patients interacted with different portals, it was flagged that around forty percent of them dropped off at the insurance step, but Heap's AI helped redesign the process, reducing that drop-off to fifteen percent. Additionally, Heap maintains coherent analysis based on the varying groups of patients and staff who frequently handle the users' portal alongside occasional users.

My advice for others considering using Heap is to ensure they understand their needs. If someone is involved in a digital analytics platform and seeks automation and tracking, especially in the healthcare industry, Heap organizes everything correctly for patients, doctors, and staff. It plays a crucial role in patient portals, telemedicine applications, and HR dashboards. If these are their requirements, then Heap is the best option. I have provided this review a rating of eight out of ten.

We've been using Heap for some time, mainly to understand how users interact with our application and identify the most important features. Our product owner finds it valuable for this purpose. As a QA team, we use Heap's session replay and event capture features to debug issues our customer support team reported. When a support ticket comes in about a bug or issue, we review the session replay and event logs to see how the user encountered the problem and where the error occurred. This has been helpful for us.

What I like best about it is the session replay feature. It saves a lot of time. I don't need to go and debug or replicate issues multiple times. We can go to the session replay for a few minutes. We can ask when the issue occurred, go to that time in the replay, and see whether the user made a mistake or if there's an app caching issue. That has been very helpful.

I can describe how data visualization tools have impacted our decision-making process from a QA perspective. These tools have helped show us how users are interacting with our product. This allows us to focus on creating more user-centric test cases. We can see which features are used most and focus our testing efforts there.

However, for more detailed information about data-centric decision-making, it would be best to contact our product owner. We're primarily using these tools for test case development and to guide our development process.

Before using the tool, we faced challenges when clients reported bugs. It was hard to replicate issues because clients didn't share exactly how they used our application. It would take us one or two days to replicate the problem four or five times. This was frustrating for us.

After integrating the solution's analytics, we bought their session review feature. This was very helpful for debugging. We could check exactly what the client did, making it much easier to reproduce and fix issues. It significantly improved our ability to respond to bug reports.

Based on my experience, there's some room for improvement. The application is a bit slow. Also, I must read through old documentation when I need to check for new features. It's not very user-friendly. Once you're in the application, it's easy because it has many features. But for first-time users, you have to go through all the documents, which can be challenging.

I haven't faced any issues with the solution's stability. 

The tool is scalable but depends on memory optimization. It's very good for our admin project and some other projects—we've had no problems. But it's very slow when we have a live event, and I try to check the data in Heap. The data comes in after a delay. I expected it to be real-time, but it's a bit slower. My company has two users. 

I haven't contacted the tool's customer support yet. 

The tool's deployment and integration is easy. You just need to define what needs to be integrated. 

The solution is expensive. 

I would recommend Heap to others. I'd advise them to try it and see how it integrates with their application. It's worth testing for a few months to see the benefits.

My advice about Heap is that it can boost your understanding of how users interact with your application. It gives you insights into how your product performs in terms of external quality.

The tool is also really helpful for customer support and QA teams. It allows them to debug issues much more quickly. I rate it an eight out of ten. 

We use Heap to create user metrics, and track page visits, feature usage, and user workflows after engaging with features.

The product's most valuable feature was the ready-made availability of defining events, creating visuals, and storing the data in the database.

The product could benefit from more advanced UI features. Additionally, onboarding new users could be improved by providing a weekly workshop or certification program on how to use and implement it. 

The product is generally stable, but the billing can be heavy based on usage and requires monitoring to control costs.

The platform is used widely across our organization and can be scaled to accommodate various teams, particularly the product and customer engagement teams.

The support team helped create events, name them, label data, and establish workflows. However, their response time could be improved.

The initial setup process was straightforward. 

We implemented the product in-house, and the support from the Heap team was instrumental in the initial setup.

The product generates a good return on investment. 

Heap's pricing can be heavy according to the usage and requirements for control billing.

I would advise potential users to try a demo account to get a holistic view of how they can implement their solution on Heap. This will help determine if it solves their use case.

I rate the product a seven out of ten. 

I used the solution for implementation, debugging, and Q&A.

When I started, I was very new to that. So, I went through the first requirement to understand how it would be helpful for the implementations and the data analytics we needed to capture. It was related to financial matters, specifically a BFSI project I was working on. We wanted to understand how the form journey in Heap started and how the cross-platform journey functioned. This presented some challenges, but we addressed them step by step. We also took some help from the Heap teams and reviewed the documents their support team provided. Through this, we analyzed the cross-channels and user behavior on the website and how the platform operated across different devices.

It's similar to Google Analytics, and there are more facilities here. You have more navigation. You can track customer behavior with your project, such as how the customer envisions, navigates, uses CPA, and every touch point on the website. You can plan to optimize the phases and the customer behavior of the journey.

We can understand the customer journey. You can explain the customers' behavior, where they are engaging your product, and where they are engaging with your mediations on the website. This will give you optimistic insights to make decisions about your product journey.

The solution could be cheaper.

I have been using Heap for one year.

Support is good because every team has some capabilities. Their product is reliable, and we use it successfully. This implies that they are capable of providing support. Secondly, the frequency of contact is important. However, if we have a higher number of tickets, there are delays. There is always a ticket queue, and priorities must be assigned. Once priorities are set, they can provide solutions because every ticket has its level of importance. 

The initial setup is easy. The prerequisites are basic HTML, CSS, and JavaScript.

It's more expensive. However, it also provides a free version. It depends on each, such as how the customer is trying to use it and the plan's actual benefits. Heap has multiple plans. You can start with the KeyOne, and it depends on the users. You can upgrade yourself on the placement.

There were associated technical managers who helped us with data synchronization. For example, if we wanted to get data from Heap to our internal sources, such as Google Cloud, we used tools like Alteryx. These managers assisted us with pulling the data via APIs or other necessary methods.

It is pretty easy, and anyone can use it. It is focused on healthcare products, e-commerce products, and the BFL Five project. Additionally, it can provide product details. Some SaaS companies are also using this product.

I recommend the solution.

Overall, I rate the solution a seven out of ten.