MaestroQA vs Tethr

Based on feedback from users who trialed both systems, discover the unique strengths of each platform to find your perfect match.

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An honest perspective

We spoke to prospects who trialed both products and asked them to give us honest feedback on both. Here’s what we learned:

Prioritizing Business Insights

Data from Tethr is generally optimized to provide a macro view into business-level insights vs. agent-level performance and insights.

Sole AutoQA Focus

Tethr is focused on automatically scoring customer service tickets. This means, it’s not easy to use for manual QA and calibrations. Oftentimes, companies need to purchase a second tool for manual QA and coaching to be able to drive actionable insights from complex customer conversations or processes that are not detectable with AutoQA.

Big Budgets

Tethr's per-conversation pricing model may result in higher costs for teams handling a large volume of tickets, particularly if an additional solution for manual QA and coaching is required.

Prioritizing Agent Insights

MaestroQA emphasizes agent-level insights while also incorporating business analytics. This approach is rooted in the belief that enhancing agent performance is a direct catalyst for business improvement.

Mix of Manual and AutoQA

MaestroQA blends manual and AutoQA, providing one of the most comprehensive and trusted quality assurance solutions on the market. Its manual QA allows for detailed analysis and coaching while AutoQA provides rapid, customizable insights, ensuring optimal insights and actionable strategies.

Teams Looking to Consolidate Tech Stack

MaestroQA has over the years built out a suite of products that does everything from manual grading, to coaching, to autoQA, etc. We believe this will help customers simplify their tech stack and earn a greater ROI from it.

Final Verdict: MaestroQA vs Tethr

Tethr appeals to teams who really want to go deep with AutoQA and are making that their sole focus or they have the budget for an additional complementary tool to focus on other things like manual QA and coaching.

In contrast, Maestro attracts teams seeking a tool that surfaces insights on agent performance through a mix of manual and AutoQA and who want a single tool that can help them with not just discovering insights but coaching and tracking improvements on them too.

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