Bundles and Heaps of Performance!
April 20, 2021

Bundles and Heaps of Performance!

Benjamin Smith | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source

Software Version

Enterprise

Overall Satisfaction with Heap

At our organization, Heap is used widely across departments. As the power of deep product analytics has gained visibility in the company every team (all of them!) has started consuming Heap data. The primary business problem Heap addresses for us is product feature improvement with an eye towards unlocking the path to each new user's "A Ha!" moment in our product.
  • Retaining historical data means that I can track things retroactively. After Product launches a new feature Heap starts capturing our data immediately, without having to do any tagging. Then when we start analyzing we're all confident that we have everything captured and in our data warehouse. It makes it easier for our data team to sleep at night!
  • Heap's "Snapshot" ability is a hidden super tool. We now use it to trigger JS functions on a number of key events that push data to our support tools, CRM, and customer success platform. And it can all be done without any Engineering time. This is a big ROI proposition for us.
  • The connection to our cloud data warehouse was a key requirement, and it has been easy to use and reliable. Other competitors did not have this, requiring other ETL tools to get all the data into our databases. Heap is also continually improving the cloud connection--at time of writing they are beta testing 4 hour syncs (as opposed to the industry standard 24 hour rate)!
  • The primary problem we have is the complexity of the user interface for reporting. Management and infrequent users, without a background in SQL, have to invest time in learning the UI in order to do their own analytics. Heap has great training resources, but my team still has to build reports when requested because leadership doesn't have the capacity to invest in learning Heap.
  • Custom colors and other front-end graphing customization that tools like Tableau and Looker have would make Heap a one-stop shop. Currently we pipe most of our Heap data into our cloud warehouse and then to a dashboarding tool for company metrics reporting.
  • At Boardable we use data from Heap to calculate a Product Qualified Lead score, and a churn score, to first qualify Free Trial accounts and assign them to Sales reps and then to find customers at risk of churning. Having the ability to find the highest opportunity prospects has made our Sales team a lot more efficient (70% of our trials spend less than 5 minutes in the product and we keep those off the Sales team's desk, focusing them on the 30% that are indicated to convert, which brought our overall conversion rate up 40% month-over-month).
  • Heap is critical for our Growth team to optimize the user journey to find the value in our product as quickly as possible. We formed the Growth team and bought Heap at the same time, and the first couldn't operate without the second. Our first big win using Heap was improving our sign-up flow (a very common blind-spot for product led companies), increasing the number of successful sign-ups by 200%.
  • Saving person-hours: Heap has freed up so many hours of time (20/wk ~= $1000/wk) that we were spending doing analytics manually. Taking things off the Engineering team's plate was key, and Heap more than pays for itself just in the amount of time we get back.
The data tracking and management is a 10. The dashboarding and report building is confusing for non-experts and requires a lot of training time (hence the 9). For me it is great and entirely usable, but for non-data analysts it is not easy to use out-of-the box. However, I think the power under the hood more than makes up for the complexity of the front-end UI.
Heap's performance is incredible. After 12 months of usage they have captured many million user sessions and retain every user interaction. Despite this massive amount of data, queries resolve in seconds, typically. The data connection to our warehouse has been very reliable and we haven't seen any down time there or on heapanalytics.com.
I was able to start finding value after three days of usage, because I understood their value proposition from the start and had specific parts of our product I needed to analyze. Once we made the purchasing decision it took four weeks before other teams could really start using it, with their own reports and tracking fully implemented and built out. Working with their implementation team was great, and we went in with the expectation that it would take at least a month to get it fully up and running.
Pendo did not meet two of our key requirements: auto-capture of every user interaction (Pendo only captures events you manually tag, which becomes a part-time job on its own as the product changes), and a data warehouse integration (custom ETL pipelines have to be built and managed, another part-time job, or a 3rd party solution has to be added on). Amplitude seemed fine, but at the time of our decision Heap met all our requirements and came highly recommended from thought leaders in our business network. Heap has continued to develop new features at a rapid pace and I would make the same decision again!

Do you think Heap delivers good value for the price?

Yes

Are you happy with Heap's feature set?

Yes

Did Heap live up to sales and marketing promises?

Yes

Did implementation of Heap go as expected?

Yes

Would you buy Heap again?

Yes

Heap IS product analytics, and user action tracking. We deliver a product on many platforms, and prior to Heap we couldn't follow users as they move from web to mobile, etc. Heap is great at capturing this entire picture and letting us dive into the whole user journey. For discovering how your product is really being used, where users are really finding value, Heap is great.
It does not handle non-user data well. One thing that Marketing really wants to tie in is ad spends and customer acquisition costs, but since those are calculated monthly and not tied to individual users we can't connect it into Heap. I've also wanted to pull in server error logs and server performance (large payloads, slow page loads), but again since they're not tied to specific people it can't be understood in the universe of Heap.