Measure and Optimize Internal Tools Fin Analytics
Fin Analytics
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Measure and Optimize Internal Tools

Even if teams use an out-of-the-box CRM like Zendesk, they often pair that system with an internal tool to view and update customer information. Optimizing the usability and effectiveness of these tools can have a huge impact on team productivity.

Data scientists and engineers spend a huge amount of time and effort developing new features to streamline process and efficiency for their business partners. Without the proper data, it’s hard for them to know the impact of the tools they built and the areas of opportunity to improve.

On top of that, reproducing, troubleshooting, and eliminating software bugs is a frustrating and expensive part of software development. Engineers often receive inaccurate or unclear details about the issue and sometimes it’s hard to reproduce and fix the bug regardless. And, reproducing issues after they happen and writing detailed bug reports is extremely time consuming for agents as well.

How Fin Can Help

  • Know which agents are leveraging a new tool or feature and how they’re interacting with it
  • Send a video with every bug ticket for on-demand big reproduction and easy QA
  • Understand the long-term performance impact of new features and RPA efforts

With Fin Analytics, you can tighten feedback loops across your organization to surface issues faster than ever. Agents can quickly flag bugs without disrupting their current workflow or having to create a detailed bug report. Integrate your bug reporting system into Fin Analytics to automatically send alerts through systems like Slack, Asana, Airtable and more.

Engineers receive a video with every bug ticket to always have the right level of information to efficiently solve the issue. When agents encounter a glitch, you can replay the session to reproduce the exact chain of events that led to the bug – seeing exactly what the agent saw as it initially happened. Having the ability to tag and annotate interactions gives agents a voice to participate in improving the tools and processes that impact their everyday work. And, you save valuable engineering resources so your team can focus their time on higher leverage projects.

Engineers and data scientists can measure and analyze the adoption of new tools to deeply understand team behavior. Identify whether ease of use, level of training, or something else is hindering usage and adoption to prioritize next steps for improvement. Pinpoint the specific features or workflows that people are struggling with and then watch the relevant interactions to understand pain points and product opportunities. After rollout, leverage our event stream to quantify the impact of your team’s work by evaluating any changes in behavior before and after launch.


Common Use Cases for
Fin Analytics

Building a modern operational infrastructure for high performance teams.