Saving 27 Hours/Month, Doubling Insights: Tegus Success Story

Problem and Pain Points

Tegus faced issues related to decentralized feedback data sources, manual categorization, disorganized data, and an unclosed feedback loop. They were seeking a more efficient and systematic approach to address these pain points and improve their feedback analysis process.

The main pain points in Tegus’s feedback analysis process:

• Decentralized feedback data sources: The lack of a centralized feedback repository made it harder to get evidence to support decisions or to do quick product discovery, and the process of manually collecting data from Slack channels, support tickets from Zendesk, sales and discovery calls recorded with Gong, and feedback surveys from Hotjar and their website was time-consuming and required substantial effort.

• Manual sorting and categorizing of feedback, especially when it pertained to multiple product areas. This manual categorization was taking 6-10 hours a week of each PM’s time – and about the same for each Product Designer. The team wanted to “spend time on analysis, not classification.”
  
  

• Feedback organization hindered insights. Without the proper organization of feedback, it was challenging to effectively identify patterns and real user problems, uncover opportunities for new initiatives or improvements to existing products. This hampered the ability to gain valuable insights from customer feedback and act on this feedback to enhance customer satisfaction.

• Unclosed Feedback loop: Tegus’s team wanted to follow up with customers to let them know their feedback has been acted upon.

Solution

A Comprehensive Solution to Tegus’s Feedback Challenges
After researching and comparing different solutions, from knowledge repositories to product and roadmapping platforms, Tegus found in Birdie’s feedback analytics platform a comprehensive solution to address all challenges across their product feedback lifecycle management:

• Single Source of Truth for Feedback: Birdie created a feedback river by connecting all of Tegus’s feedback sources, seamlessly integrating Support Tickets from Freshdesk, Sales Meetings Transcripts from Gong, and feedback forms captured via their website. No more hunting for scattered feedback; everything was now neatly and instantly accessible in one place.

• Noise Reduction with AI Magic: Birdie’s AI came into play, extracting valuable insights while filtering out the noise; irrelevant comments, messages from salespeople, and ad bots were no longer cluttering Tegus’s data landscape. Relevant topics began to be automatically extracted, analyzed, and grouped, enabling instant discovery of trending themes, main offenders, and root causes among different customer groups.

• A tailored and flexible taxonomy: Tegus’s product team had the freedom to create Topic Folders tailored to their product management process and structure, with the added benefit of having any changes (so common in fast-growing organizations) reflected in every feedback. Birdie’s fully customizable taxonomy allowed the team to have control over their feedback organization.

• Effortless Analysis: Birdie simplified the process of analyzing feedback for Tegus’s product team. Pre-built features assisted them in prioritizing what truly mattered: they could instantly access the most requested issues and features through user-friendly views. Additionally, with Birdie’s taxonomy, matching feedback to their roadmap initiatives became straightforward.

Results

The adoption of Birdie yielded impressive results for Tegus. They achieved substantial time savings, reclaiming 27 hours per month previously spent on feedback data categorization, aggregation, and report creation. Birdie’s AI capabilities also drastically reduced the analysis time for 300 hours of sales conversations to just 5 hours, enabling Tegus’ product team to be able to uncover up to 2x more insights due to a nearly 100% coverage of the calls and to act swiftly and timely on these customer insights.

These efficiency gains translated to significant cost savings, contributing to increased overall productivity and effectiveness within the Product team. Moreover, the team’s credibility within the company also grew, as they could now deliver more informed and impactful decisions based on a deeper understanding of customer feedback.