Heap

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.

Hybrid Cloud

Amazon Web Services  (AWS )

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.

On-premises

Amazon Web Services  (AWS )

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.

Public Cloud

Amazon Web Services  (AWS )

What do you like best about the product?

I like that the UI is very simple and easy to use.

What do you dislike about the product?

The way we set up Heap with auto capture results in a lot of overhead to sift through many events. I would prefer if we had a specific plan of what we want to capture instead of everything. Also, I don't think it's as enterprise-level as some other analytics tools out there.

What problems is the product solving and how is that benefiting you?

Heap helps us understand user behavior on our site and tailor custom experiences based on user actions and attributes.