CX directors and support managers evaluating conversation intelligence software typically hit the same sorting problem: most vendor evaluation guides mix B2B deal intelligence tools with contact center QA platforms as if they solve the same problem. They do not. This guide ranks six conversation intelligence platforms by the problems they actually solve for CX and support teams with 50 to 500 agents.
How We Ranked These Tools
The criteria below reflect what CX directors and support managers at 50-to-500-seat contact centers prioritize. Revenue forecasting and deal cycle analysis were excluded from weighting.
| Criterion | Weighting | Why it matters |
|---|---|---|
| Contact center QA automation | 35% | Automated scoring of 100% of calls is the foundation of any scalable quality program. Manual sampling covers 3 to 10% of calls and cannot surface systemic issues, according to ICMI contact center research. |
| Coaching assignment from call data | 25% | Evaluation data without downstream coaching is reporting, not improvement. This measures whether low-performing behaviors trigger training actions. |
| CX insight depth | 25% | Support teams need to understand customer effort, friction patterns, and satisfaction drivers, not just agent compliance scores. |
| Integration with existing stack | 15% | Most contact centers have existing telephony, CRM, and ticketing infrastructure. Conversation intelligence that does not connect creates data silos. |
Deal intelligence and pipeline correlation were not weighted. Those capabilities matter to B2B sales teams, not contact center QA programs.
According to Forrester's contact center technology research, automated QA scoring at 100% call coverage surfaces coaching opportunities that manual sampling systematically misses. This is the primary driver of QA investment at mid-to-large contact centers.
What is the best conversation intelligence software for CX teams?
The best conversation intelligence software for CX teams depends on the primary use case. For contact center QA programs that need 100% call coverage with automated scoring, Insight7 leads because scoring criteria are fully configurable and connect directly to coaching assignments. For omnichannel CX programs correlating call data with survey responses, Qualtrics XM provides the broader data model. Match the platform to the use case before evaluating features.
Insight7
What it does: Insight7 automates QA scoring across 100% of contact center calls using customizable weighted criteria, then connects evaluation scores to coaching assignments without requiring managers to manually review each call.
Who it's best for: CX directors and QA managers at contact centers with 30 to 500 agents who need automated scoring against their own evaluation criteria and a direct path from QA scores to coaching actions.
Key features:
Pro: Insight7 closes the QA-to-coaching loop automatically. When an agent scores below threshold on a specific criterion, a targeted practice scenario is generated and routed to the supervisor without a separate manual step.
Fresh Prints used Insight7 to expand from QA scoring into AI coaching, enabling agents to practice flagged skills immediately rather than waiting for the next scheduled session.
Con: Out-of-box scoring requires 4 to 6 weeks of criteria tuning before scores reliably align with human reviewer judgment. Teams must invest setup time before evaluation data is training-ready.
Pricing: From $699/month for call analytics; AI coaching from $9/user/month at scale (Q1 2026).
Insight7 is best suited for contact center QA managers and CX directors who need automated 100% call scoring against custom criteria with a direct path to coaching assignment.
Gong
What it does: Gong is a revenue intelligence platform that analyzes B2B sales calls to surface deal risks, pipeline signals, and coaching opportunities, with call data feeding directly into CRM and forecast models.
Who it's best for: Enterprise B2B sales teams with complex deal cycles where pipeline accuracy depends on conversation signals alongside CRM data. Not optimized for contact center QA programs.
Key features:
Pro: Gong's revenue intelligence layer is additive for pipeline forecasting and deal reviews in ways that contact center QA platforms cannot replicate. The correlation between specific talk tracks and close rates gives sales leaders a data layer that affects revenue decisions directly.
Con: Gong is not purpose-built for contact center QA. Automated scoring against customizable evaluation rubrics is not a native capability. Teams that need 100% call scoring against their own criteria will find Gong's workflow insufficient.
Pricing: Enterprise; pricing on request (Q1 2026).
Gong is best suited for enterprise B2B sales teams where deal intelligence and pipeline correlation depend on call data, not for contact center QA programs measuring agent compliance.
How does conversation intelligence software improve CX team performance?
Conversation intelligence improves CX team performance by closing the gap between what agents do on calls and what coaching programs can address. Automated scoring of 100% of calls, as Insight7 provides, surfaces the specific agent behaviors driving low CSAT or compliance failures. That data makes coaching targeted rather than generic, which is why teams that connect scoring to coaching see faster criterion-level improvement than those using monitoring alone.
Tethr
What it does: Tethr is a conversation analytics platform that uses AI to detect customer effort, friction, and emerging agent issues across call recordings without requiring manual scorecard configuration.
Who it's best for: CX managers at mid-to-large contact centers who want AI-detected insights on customer effort and friction without building evaluation criteria from scratch.
Key features:
Pro: Tethr surfaces friction patterns that QA managers would not think to score manually. This makes it useful for discovering new coaching needs rather than only measuring criteria that already exist in a rubric.
Con: Criteria are AI-detected, not configurable against specific evaluation standards. Teams that need scores to match their existing QA framework or training program language will find Tethr insufficient for compliance and behavioral scoring.
Pricing: Enterprise; pricing on request (Q1 2026).
Tethr is best suited for CX managers who need AI to surface customer effort and friction patterns automatically, rather than score against predefined agent evaluation criteria.
Qualtrics XM
What it does: Qualtrics XM is an enterprise CX platform combining customer survey data with conversation analytics to measure service quality and agent performance across channels.
Who it's best for: Enterprise CX directors managing omnichannel programs where customer survey data and call analytics need to appear in a single analytics environment.
Key features:
Pro: Qualtrics XM is the strongest platform for correlating agent evaluation scores with customer survey responses. Teams can measure whether agent behavior changes after training translate into improved customer-reported satisfaction.
Con: Evaluation criteria are designed around survey logic rather than behavioral rubrics. Teams that need precise agent evaluation criteria aligned to training language face significant configuration overhead.
Pricing: Enterprise; pricing on request (Q1 2026).
Qualtrics XM is best suited for enterprise CX directors who need to connect agent performance data with customer survey results in a single analytics environment.
Salesforce Einstein
What it does: Salesforce Einstein is a native AI layer within Salesforce that adds call summarization, transcription, and activity intelligence to CRM records without requiring a separate platform.
Who it's best for: B2B sales and support teams already embedded in Salesforce who need basic call summarization without adding a standalone conversation intelligence platform.
Key features:
Pro: Salesforce Einstein removes the platform switch for teams that live in Salesforce. Call summaries and activity signals appear directly in Opportunity and Contact records without requiring a data export.
Con: Transcription accuracy and QA evaluation depth are limited compared to purpose-built conversation intelligence platforms. Enterprise users have noted the built-in Salesforce tools are insufficient for detailed QA evaluation workflows.
Pricing: Salesforce add-on; pricing varies by Salesforce edition (Q1 2026).
Salesforce Einstein is best suited for Salesforce-native B2B teams that need basic call summarization embedded in CRM records rather than a dedicated conversation intelligence platform.
Zendesk QA
What it does: Zendesk QA automates evaluation scoring for support teams already using the Zendesk suite, with CSAT-linked scoring that surfaces conversations needing review.
Who it's best for: Support teams of 20 or more agents already in the Zendesk ecosystem who want QA built into existing workflows without a separate platform.
Key features:
Pro: Zendesk QA removes friction for Zendesk-native teams by embedding QA directly into the support workflow. Managers get agent-level scorecard data without leaving the Zendesk interface.
Con: Training assignment is not automated. Managers must manually translate QA scores into coaching actions, which does not scale automatically with agent headcount.
Pricing: Add-on to Zendesk suite; pricing on request (Q1 2026).
Zendesk QA is best suited for Zendesk-native support teams that need embedded QA without adding a separate conversation intelligence platform.
If/Then Decision Framework
Use these branches to match your organization's primary use case to the right platform. Each branch names a specific mechanism rather than a generic benefit.
FAQ
How can conversation intelligence software increase average deal size?
Conversation intelligence increases deal size by surfacing the specific behaviors correlated with larger deals: multi-stakeholder engagement, objection handling patterns, and talk-to-listen ratios that distinguish top performers. Gong's revenue intelligence layer is the strongest platform for this use case because it connects call behavior to CRM deal data and identifies replicable patterns. For contact centers focused on CX quality rather than deal size, Insight7 surfaces the conversation patterns that drive customer retention and cross-sell conversion.
CX Director building a scalable QA program? See how Insight7 handles automated call scoring and coaching assignment, see it in 20 minutes.
