Freshworks improves feature adoption by 20% with Heap
Founded in 2010, Freshworks offers customer engagement software. The company has over $100 million in annual recurring revenue and now serves over 150,000 organizations. Freshdesk, a product from Freshworks, is a cloud-based customer support software and ticketing system. The product helps companies streamline customer conversations in one place, automate repetitive work, and resolve issues faster.
Before Heap: a siloed view into customer behavior
Freshdesk’s in-house data lake provided data for processing and scrutiny, but the data was incomplete and difficult to analyze and understand without an engineering background. Access to the data was limited, because the only data available was what the Freshdesk team had hard-coded into the product. Getting to the right data often required writing complex queries. As a result, the team had to do complex ad hoc analysis and customer interviews to understand product adoption — both tactics made it challenging to get a complete view into customer behavior.
After Heap: a breakthrough in feature adoption
Using Heap, the Freshdesk team discovered that adoption and usage of its Ticket Templates feature was low. To solve this issue, the product management team introduced a tour to nudge non-adopters with an in-app message explaining the feature. The team then used Heap funnels to track which users created and applied templates after viewing the tour — leading to critical insights on how best to optimize the interface. Explains Gireesh Subramanian, Freshdesk Director of Product Management, “We were able to increase adoption of templates by 20% by making the feature more discoverable and making tweaks. Heap data was at the core of this. From a business perspective, our customers are now more productive and have more time.”
Additionally when a product revamp was launched, Freshdesk shipped Table View, a new way for teams to visualize their queue of tickets. With Heap, the product management team was able to see that adoption for the feature was low, as the icon to switch to this option wasn’t easily discoverable. Armed with this insight, the team shipped changes that made the option easier to find with the help of a simple text dropdown, and doubled the number of people discovering the new feature.
A drop off in dropoffs
Freshdesk recently revamped its onboarding experience to drive higher conversion rates from trial to paid customers. Heap played a pivotal role in defining the new experience. The product and designs teams leveraged Heap’s virtual events tool to quickly evaluate how the new onboarding experience impacted product engagement and feature adoption. They also set up funnels to measure where dropoffs in the onboarding flow and signup flow were highest — this analysis resulted into micro-optimizations to the flow, such as excluding unnecessary steps during signup. “With Heap, we could see what worked well and what didn’t,” Gireesh explains. “Based on this data, we were able to decide which features to focus on, front and center in the new workflow.”
Understanding customer cohorts
Heap also enables Freshdesk to analyze feature usage and customer retention by user segment. Armed with this data, the teams can quickly make impactful improvements. The teams now aggregate data by customer properties (such as company size) to understand who has low adoption, how different types of customers use Freshdesk, and who doesn’t complete certain user flows. The team also monitors daily, weekly, and monthly paying user trends to dive deep into patterns and factors that affect retention. They also monitor customer segments by geography, so they can identify where revenue comes from, where churn is highest, and the top customers in each region. This data informs critical business decisions, such as how to best allocate resources to regions and customers. Per Gireesh, “We’re now able to build, measure, and iterate, and do so with confidence.”
Recently the Freshdesk design and research teams wanted to interview qualified customers on how to improve the company’s Ticket Activities feature. The teams used Heap to determine the top 100 users of the feature, and contacted them for their insight. “Since we were able to zero in on who our top users of the feature were in Heap and reach out to them, we got a lot of actionable insights,” says Gireesh. “These were users who cared and also had problems and wanted to be heard. They were our target for the revamp too, and we got to hear from them directly.”
A culture driven by data
A data-driven culture can be a competitive advantage, but it can only be effective if stakeholders across the organization can easily access and understand the data. With Heap, teams are independently able to discover the insights that add value to their unique role. “Different teams have varying data needs — some require granular data, others need aggregate high-level visualization. We’ve been able to achieve both with Heap,” says Gireesh.
Heap has also helped Freshdesk share and gain more value from its data, without causing an extra burden on its engineering and other technical teams. In Gireesh’s words, “Heap has consolidated our data, and made it easier to access and visualize it. Our teams now access data in a self-serve manner to understand user behavior metrics and feature adoption at an aggregate level.”
This access to data has lasting effects. For example, the product team now comes up with new and innovative ways to explore and analyze user behavior to gain insights that improve both the product and the customer experience. As a result of the team’s success, use of Heap has expanded from Freshdesk to all Freshworks’ product lines. Having quick and easy access to data has streamlined processes and discussions, which is critical as the company scales to more customers. “Heap has influenced the way of thinking at Freshdesk,” Gireesh explains. “We started out with one team adopting Heap, but the fact that usage has spread across teams within the organization is testament to Heap’s ease of functionality and usefulness. With access to data on products across the organization in a single tool, as an organization we’ve made tremendous progress on cultivating a data-driven mindset.”
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