Why Fivetran switched to Heap for detailed analytics

Results

Increased

Expanded

customer engagement

data-driven culture

Problem

Had a lack of understanding of user behavior and the triggers that led users to use their product.

Solution

Switched to Heap & integrated with Chameleon to gain deep user behavior insights.

Fivetran is an automated data movement platform that allows you to synchronize and transfer data seamlessly from your data sources to multiple data clouds. As a series D company, Fivetran has experienced monumental growth by simplifying the ELT (Extract, Load, and Transform) process for different companies. It has the functionality to support customer needs around six primary features: data movement, data transformation, data security, and data governance.

In this case study, we talk to Andrew Morse, Product Manager at Fivetran responsible for the Dashboard, the name of Fivetran’s UI. Customers can manage their “connectors” or pipelines from sources to destinations, transformations, understand their usage, and more.

What was Fivetran looking for? 

Fivetran wanted a solution that would enable their Product and Marketing teams to report more effectively on how users are interacting with the product and what is driving users to their product. They had three strategic focus areas that they wanted to improve with the help of Heap. 

  1. Self-serve analytics. Fivetran wanted to better support their PLG motion without having to rely on analysts from analytics while also providing more data to product managers to help include more data in their work.

  2. Friction points. Fivetran wanted to understand what users were doing within their app, whether or not they struggled to set up connectors and make data-backed decisions when it came to updating their UI.

  3. Understanding User Behavior. Fivetran wanted to better understand what users were going into their system to do. What was triggering users to go into the product and why? Was it a good reason, like adding a new connector? Or was it a bad reason, like checking out an issue or a bug? 

"Due to a lack of knowledge about the trigger and the absence of a linear user flow, as users may perform a variety of actions," explains Andrew Morse, Product Manager at Fivetran, "we were eager to gain a deeper understanding of users' intentions and their approach to accomplishing tasks."

Focusing on the above areas meant that Fivetran could collect enough actionable, valuable data to enable them to improve their UX. The next task for Fivetran was finding the right providers that would support them to do just that. 

The switch to Heap 

When Fivetran began their analytics journey, they quickly found that their existing solution fell short when it came to the depth of data they needed to self-serve out of the Fivetran app. 

"Our previous tool,” says Andrew, “even though it was an integrated tool, it was always a little bit difficult to get the product marketers to build the reports they needed and do what they needed to. I think it was just like a lack of some of the functionality from an ease of use standpoint."

Fivetran needed a solution that could inform their strategies with accurate data. “We weren't getting the level of analytics that we really wanted to self-service,” says Andrew. “We looked at a bunch of different analytics software and eventually we landed on Heap." 

Fivetran also wanted to utilize in-app messaging and microsurveys as a way to improve their UX. They needed an in-app messaging solution that could integrate with Heap and enable the team to set rate limits on the in-app messages they were creating. Chameleon was the answer.

We can get Chameleon events into Heap so we can report on them, which is helpful for understanding if an in-app message was effective in driving the outcome that we are looking for.

headshot-fivetran-andrew-morse

- Andrew Morse, Product Manager

Chameleon and Heap were also instrumental in helping Fivetran know more about what was causing their users to actually use Fivetran. “We used Chameleon to build a segment in Heap for a small number of users,” says Andrew. “We then sent that over to Chameleon who gave everybody a micro survey the next time they logged in.” 

These multi-choice questions helped Fivetran break down what users were doing on the product. Andrew and his team could then use Heap to dive further into the data from a quantitative perspective. Where did users go? What pages were they accessing? Because users’ journeys were often nonlinear, Fivetran also utilized Heap’s session replay to understand exactly how users were behaving and using different elements of the product. 

“We built a small segment of users in Heap and sent that over to Chameleon,” says Andrew. “That way we could target them with a microsurvey the next time they logged in, asking what they accomplished that day. From that data, we were able to start understanding the breakdown of what users were doing. But the more valuable part came when we went back into Heap.”

“Because our user paths aren’t linear, it was extremely valuable to see exactly why users were making certain choices with session replay," says Andrew. “All of our data goes into Heap, so we have session replays for everything. You just have to decide which you want to watch. So in this case, I could watch the sessions for people that responded in a specific way so I could learn more about that group of users and their journey.”

The solution: How Heap supported Fivetran in achieving their goal of better understanding user behavior 

Fivetran switched to Heap for its detailed analytics and easy user interface. Its integration with Chameleon meant seamless data movement between the two, enabling Fivetran to hold teams accountable for measuring and reporting on user analytics. With Heap and Chameleon, Fivetran has been able to: 

  • Improve product features based on detailed data from events

Chameleon’s microsurveys present questionnaires to users within the product. Any issues reported through these surveys are analyzed alongside user behavior funnels on Heap. Fivetran’s goal is to identify any causal relationship between reported issues and specific patterns or behaviors observed in user interactions.

The other thing we could do, which was really cool, was take the survey results and see how they impacted user behavior. For example, if a user says they came in for a certain issue, we can then see what they did after that and how that compares to other users.

headshot-fivetran-andrew-morse

- Andrew Morse, Product Manager

  • Report bugs more effectively

If a customer reports an issue via a Chameleon Microsurvey, Fivetran was able to go into Heap and see what they were doing before they encountered the issue, not only within the funnel but also in terms of the guidance that Fivetran was offering in-app and how that could be improved as to avoid the issue being repeated. They could also make improvements to the surveys if users weren't being as clear as they could be about the issues they were experiencing. 

  • Understand the triggers behind users’ use of Fivetran

Using Heap and Chameleon meant that Fivetran can now monitor what users are doing and why on their product. At the beginning of their journey, Fivetran felt they were making educated guesses and not able to know what exactly was triggering their users to sign into the platform. Now, they know that a large portion of users logs into Fivetran to understand the status of their connectors or data pipelines. 

[As a result] we’re now working on how to improve the user experience so that when [users] are looking to understand the status of the system overall and all of the connectors, they have a landing page where they can access all that data easily.

headshot-fivetran-andrew-morse

- Andrew Morse, Product Manager

  • Measure the effectiveness of in-app messaging 

Fivetran is able to send event data from interactions with Chameleon Experiences to Heap and understand whether an in-app message was effective and if it resulted in the outcome that the Product Marketing team was looking for.

  • Effectively implement A/B experimentation 

They used Heap segments to create A/B tests of Chameleon Experiences and find what messaging and UI were most effective in driving them to perform key actions on the product. 

The wins: What did Heap and Chameleon bring to the table for Fivetran?

Switching to Heap and Chameleon has given Fivetran more accountability and reporting for Product and Marketing. Before Heap, Fivetran could only complete some result reporting. Now, they’re able to analyze and report causation-related data with every release. 

"It was a lot of work to do the reports,” says Andrew. “We didn't do it with every release, but now we have a lot more sort of out of the box there. So there's definitely more accountability from Product & Marketing for outcomes and experimentation." 

Fivetran is now also able to tap into powerful, actionable data about what users are doing on their product. With the help of Chameleon, Fivetran could utilize in-app messaging and microsurveys to hear from users, and then plug that information into Heap for quantitative insights. Andrew and his team were then equipped with the right knowledge to fix and improve different elements of the user flow.

Finally, Fivetran also experienced more customers coming forward to be a part of their beta releases as a result of identifying and addressing bugs that were highlighted through different pieces of feedback. "I think we found like ten to fifteen bugs that maybe if we didn't have that, we wouldn't have noticed before the GA release,” says Andrew.

Since adopting Heap + Chameleon, Fivetran has been able to expand the adoption of these tools across their organization. Once Andrew began sharing the insights he had gained and best practices for the tools, he was able to empower teams to self-serve insights. In fact, they’ve seen everyone from PMs to Designers to Marketers, to the Analytics team utilizing these tools in innovative new ways. 

Fivetran's switch to Heap for analytics transformed their understanding of user behavior, driving innovation and growth. With comprehensive data insights, they improved products, addressed bugs, and measured the impact of in-app messaging. This data-driven approach enhanced customer engagement and fostered a culture of continuous improvement.

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