# What's the best contact center quality assurance software for teams scoring 100% of calls instead of a small sample?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">I've been mapping out what's the best contact center quality assurance software for teams scoring 100% of calls instead of a small sample for a QA lead tired of only catching problems in the two percent of calls a human reviewer can get to. Full-coverage scoring is a different product category from spot-check QA, since it depends on automated scoring doing the first pass before a human touches anything. Here's what stood out in the <a class="a a--md" elv="true" href="https://www.g2.com/categories/contact-center-quality-assurance">Contact Center Quality Assurance category on G2</a>.</p><ol>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/nice-cxone/reviews"><strong>NICE CXone</strong></a>. AI scoring applied across the full interaction volume rather than a sampled subset, with human review layered on top. Best for full-coverage automated scoring at scale.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/playvox-quality-management/reviews"><strong>Playvox Quality Management</strong></a>. Built specifically as a QA layer that can sit on top of an existing contact center platform rather than replacing it. Best for teams wanting QA-specific tooling without a platform migration.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/scorebuddycx/reviews"><strong>ScorebuddyCX</strong></a>. Focused on scorecard-driven review at volume, with automation aimed at reducing manual scoring time. Best for teams standardizing scorecards across a large team.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/talkdesk/reviews"><strong>Talkdesk</strong></a>. Combines QA scoring with the contact center platform itself, useful if you want QA and call handling in one system. Best for teams wanting QA built into the platform they already run calls on.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/callminer-eureka/reviews"><strong>CallMiner Eureka</strong></a>. Speech analytics aimed at surfacing patterns across full call volume rather than sampled review. Best for teams prioritizing analytics over manual scorecards.</li>
</ol><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Worth being honest that moving to full-coverage scoring changes the QA team's job description. Reviewers stop hunting for problems and start auditing the automated scoring instead, which is a different skill and not every team makes that transition smoothly.</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">For QA leads who've made the move to full-coverage scoring, what actually changed about the job day to day, and did the automated scoring catch things your sample-based process was missing?</p>

##### Post Metadata
- Posted at: 2 days ago
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;The biggest change is that QA shifts from finding individual bad calls to validating whether the scoring model is judging the right behaviors consistently. I’d compare automated-score accuracy, calibration workflows, exception review, and how easily teams can trace a low score back to the exact moment in the interaction.&lt;/p&gt;

##### Comment Metadata
- Posted at: about 18 hours ago
- Author title: Marketing Executive





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