Top 10 Conversational Analytics Tools & Software to Boost CX & Business Insights

Most companies are drowning in customer data but starving for real understanding. Dashboards can tell you that churn is rising or that your NPS just dipped but they can’t explain why. The answers are hidden in the thousands of phone calls, chat logs, and emails where customers reveal their true frustrations, needs, and emotions.

That’s where conversational analytics tools come in. Instead of treating conversations as noise, they use AI, natural language processing (NLP), and machine learning to transform them into structured insights. With these tools, you can move beyond survey scores and start detecting patterns in tone, intent, and sentiment across every interaction.

And the timing couldn’t be more urgent: as customer expectations rise and business processes grow more complex, organizations need a way to bridge raw conversation data with decision-making. In this blog, we’ll explore the best conversational analytics tools for 2025, what makes them different, and how they can help you not just track performance, but actively shape better customer experiences. Let's get started!

TL;DR

• Conversational analytics tools help teams make sense of customer interactions at scale—automatically surfacing themes, sentiment, intent, and trends that drive action.

• We’ve evaluated the top conversational analytics software based on natural language processing, real-time assist capabilities, automation, integration with existing tech stacks, and ability to close the feedback loop.
• Some of the best conversational analytics tools in 2025 include Zonka Feedback, SentiSum, Qualtrics, Observe.AI, and more, each offering unique strengths across live guidance, AI summaries, and team alignment.
• Zonka Feedback brings together multi-channel data capture, sentiment detection, thematic analysis, verbatim traceability, and AI-powered recommendations to turn every customer call, chat, or survey into clear, prioritized actions. You can get early access or schedule a demo to explore how it helps you elevate customer experience.

Get a Better Understanding of Customer Feedback with Conversational Analytics 

With Conversational Analytics Tool, create surveys in seconds and use artificial intelligence to decode insights from the data collected.

If you want to jump straight to the list of the best AI Feedback Analytics tools, click here. Prefer to understand how AI feedback analytics works and what to look for? Keep reading below.

What are Conversation Intelligence Tools?

Conversational analytics tools are specialized platforms designed to capture, process, and analyze customer conversations across channels like phone calls, live chat, emails, and support interactions. Instead of leaving these conversations as raw transcripts, these tools use natural language processing (NLP) and machine learning to transform conversation data into actionable insights.

What makes these tools valuable isn’t just their ability to listen — it’s their ability to scale. A single manager might be able to review ten customer support calls in a week, but conversational analytics software can process thousands in minutes. This helps organizations:

• Measure customer sentiment across touchpoints and detect negative trends before they hurt customer satisfaction

• Assess agent performance in contact centers with metrics like resolution quality and empathy levels

• Track the volume and distribution of topics in customer interactions to spot emerging pain points and recurring issues

• Surface valuable insights from customer feedback that would otherwise get lost in spreadsheets or siloed systems

In other words, these analytics tools don’t just store conversation data — they convert it into a deeper understanding of customer behavior, customer needs, and business processes. That’s why they’re quickly becoming essential to sales teams, support leaders, and CX managers who want to improve service quality and make better data-driven decisions.

Features to Look for in Conversational Analytics Software

Not all conversational analytics tools are created equal. While every platform promises insights from customer conversations, the best ones go deeper — helping you analyze customer interactions at scale, uncover customer sentiment, and act on findings quickly.

When evaluating tools, make sure they cover these essentials:

• Omnichannel Coverage: The ability to capture conversational data across phone calls, live chat, emails, and in-app conversations ensures you don’t miss valuable signals from different communication channels.

• Accurate Transcription & NLP: Strong natural language processing (NLP) capabilities are critical for handling accents, dialects, and messy real-world speech in contact centers.

• Sentiment & Intent Detection: Go beyond what customers say to understand how they feel, detect intent, and identify pain points hidden in daily customer interactions.

• Topic Modeling & Trend Identification: Tools should automatically group conversations by recurring themes — billing, product issues, feature requests — so you can identify trends without manual tagging.

• Customizable Dashboards & Reports: Easy-to-read analytics dashboards turn raw conversation data into actionable insights your teams can use without needing a data scientist.

• Integration with Existing Tech Stack: Direct connections with CRM, customer support platforms, and business processes make it easier to embed insights into daily workflows.

These core features help you monitor agent performance, improve service quality, and boost customer satisfaction. But to truly future-proof your investment, you should also look for more advanced capabilities.

Advanced Features to Look Out for in Conversational Analytics Tools

While the basics help you analyze conversations, advanced features turn analytics into a growth engine:

• Outcome Attribution: Connecting themes in customer conversations with shifts in CSAT, NPS verbatims, or even churn and revenue impact.

• Predictive & Prescriptive Analytics: Leveraging machine learning on historical data to forecast churn risk, anticipate customer needs, and recommend next best actions.

• Multimodal Analytics: Combining voice, chat, email, and even video into a single conversation analytics platform for a deeper understanding of the customer journey.

• Real-Time Coaching & Agent Assist: AI-driven recommendations that guide contact center agents during live conversations, improving empathy, compliance, and resolution speed.

• Built-In Trust & Compliance: Strong security, anonymization, and governance features to protect customer data and ensure teams across the organization can adopt the tool with confidence.

Together, these features helps you move from simply analyzing conversations to making data-driven decisions that improve customer satisfaction, strengthen customer relationships, and drive operational efficiency.

Top Conversational Analytics Tools to Consider in 2025

Here’s a quick side-by-side comparison of the top Conversational Analytics tools highlighting their standout features, strength, and pricing models to help you make an informed choice.

Best Conversational Analytics Tools to Gather Customer Insights

Let us look at the top conversation intelligence software that can help you unlock insights from every customer interaction and drive smarter decisions.

1. Zonka Feedback

Zonka Feedback is a full-fledged conversational analytics software designed to decode customer voices at scale. What sets it apart is its ability to turn unstructured customer feedback into rich, actionable insights with the help of AI Feedback Intelligence. Whether it’s NPS survey responses, support tickets, live chat transcripts, or app reviews, this AI feedback analytics tool centralizes every form of conversation data and uses natural language processing (NLP) to surface trends, detect emotions, and flag critical issues.

The platform bridges the gap between listening and doing. It doesn't stop at tagging customer sentiment as positive or negative — it tells you why, who’s affected, and what needs attention now. With features like urgency detection, real-time alerts, and role-based dashboards, Zonka Feedback empowers teams across product, support, and operations to act fast and improve customer satisfaction. And thanks to its AI copilots, you can even “ask” the system questions like “What are users saying about onboarding?” and get concise, contextual answers within seconds without manual digging.

Key Features

• Multi-Channel Feedback Collection: Gather feedback via email, SMS, web, in-app widgets, and offline kiosks to track the full customer journey

• AI Sentiment & Emotion Detection: Leverages natural language processing and machine learning to detect not just sentiment, but urgency and emotional tone across customer interactions

• Theme & Topic Analysis: Automatically organizes conversation data into topics and sub-topics so teams can identify trends without sifting through each comment

• Entity Mapping: Analyze feedback by products, locations, or agents for targeted conversation analysis and better ownership of issues

• Role-Based Dashboards: Each stakeholder — from CX heads to product teams — sees insights that align with their metrics and goals

• AI Smart Summaries & Queries: Auto-generated briefs and open-ended question support to help teams quickly gain insights from large volumes of customer conversations

• Automated Alerts & Routing: Configure rules like “if feedback includes ‘wait time’ and negative sentiment, alert support instantly” to close loops fast

• Multilingual AI Feedback Analysis: Collect and analyze feedback in any language and unify your customer interaction data globally

Best For: CX, product, and support teams in mid-to-large organizations looking for a centralized, AI-powered conversation analytics tool to improve customer satisfaction and close the loop across customer conversations.

2. Sentisum

SentiSum is a conversation analytics tool purpose-built for decoding the Voice of the Customer within support conversations. Unlike traditional feedback platforms that revolve around surveys, SentiSum dives deep into customer interactions — analyzing support tickets, live chat logs, emails, and customer phone calls to identify recurring issues, pain points, and sentiment patterns at scale.

Its strength lies in automated tagging and sentiment detection using natural language processing (NLP) and machine learning, turning thousands of support conversations into structured, actionable insights. Whether it’s a sudden surge in refund complaints or negative feedback around a product feature, SentiSum pinpoints it in real time. Built for operational teams, it helps boost customer satisfaction and agent performance by flagging what matters most — without waiting for end-of-month CSAT reports.

Key Features

• Omnichannel Support Analytics: Connects with helpdesks like Zendesk, Intercom, and Freshdesk to unify support emails, live chat, and call transcripts into one feedback intelligence hub

• Automated Tagging & Categorization: Uses AI to auto-label each ticket or conversation with consistent categories like “delivery delays” or “login errors”

• Sentiment Analysis on Conversations: Assigns sentiment to each support interaction, helping teams track emotional tone and prioritize critical customer issues

• Real-Time Trend Detection: Identifies rising issues and customer pain points in real time; sends alerts when specific topics spike across support channels

• Multilingual NLP Support: Processes conversation data in 100+ languages, ideal for global contact centers

• CSAT Driver Analysis: Links feedback themes to customer satisfaction scores to uncover root causes of low CSAT

• Simple, Live Dashboards: Gives support leaders a real-time view of top drivers, sentiment shifts, and topic trends

• Custom Taxonomies & AI Training: Allows enterprises to tailor tagging systems and train models based on historical support data

• Workflow Integration: Syncs with your CRM or helpdesk so structured feedback flows directly into agent workflows and reports

Best For: Support and CX teams in mid-to-large enterprises managing needing structured analysis of tickets, chats, and calls to improve customer experience, detect issues early, and report on contact center performance without manual effort.

3. Qualtrics XM

Qualtrics XM has evolved from a best-in-class survey platform into one of the most comprehensive conversational analytics tools on the market. With the acquisition of Clarabridge, it now offers deep AI-powered feedback analytics that go far beyond structured survey responses — analyzing support tickets, social media, chat transcripts, emails, and even phone calls to extract meaning at scale.

What makes Qualtrics unique is its ability to unify both structured and unstructured feedback in a single platform. Through its Text iQ and Voice iQ engines, it turns open-ended responses into categorized themes, detects sentiment and emotion, and ties everything back to key business metrics. This allows CX and VoC teams to go from gathering feedback to acting on it — with predictive insights, automated workflows, and customizable dashboards built for scale. It’s particularly well-suited for large organizations looking to connect customer feedback with real outcomes like churn reduction, upsell opportunities, and operational improvements.

Key Features

• Advanced Feedback Collection: Capture multichannel feedback via surveys, website intercepts, emails, chat, IVR, and more with rich logic and branding options

• Text iQ (Text Analytics Engine): Uses NLP and machine learning to analyze open-text comments, extract themes, and detect sentiment, emotion, and intent

• Voice iQ: Transcribes and analyzes voice calls, identifying conversation patterns, keywords, and caller sentiment across support or sales interactions

• Predictive Analytics (Stats iQ): Surfaces key drivers of NPS, CSAT, churn risk, and more using correlation and regression modeling on structured and unstructured data

• Real-Time Dashboards & Alerts: Visual dashboards with role-based views, trend tracking, and instant alerts based on feedback triggers

• Closed-Loop Ticketing & Workflows: Automatically route negative feedback or urgent topics to the right teams for follow-up, with ownership tracking and resolution status

• CRM & Tool Integrations: Connects with Salesforce, Slack, customer support platforms, and data warehouses for embedded insights and actionability

• Multilingual Analytics: Analyze global customer conversations in multiple languages with consistent sentiment scoring and topic mapping

• XM Suite Expansion: Includes modules for customer, employee, brand, and product experience — enabling organizations to tie employee engagement to CX outcomes

Best For: Large enterprises and mature CX teams that want to manage complex customer journeys and high feedback volumes with a need for unified experience management platform to analyze customer conversations across every channel.

4. Enthu.AI

Enthu.AI is a powerful, voice-first conversational analytics tool designed specifically for contact centers and support teams. It automates what traditional QA teams do manually — listening to calls, scoring agent performance, and flagging compliance issues — using AI and speech analytics at scale. Where most platforms focus on sampling a small percentage of interactions, Enthu.AI analyzes 100% of calls to ensure no insight is missed.

What sets Enthu apart is its blend of accessibility and depth. From real-time sentiment detection to Auto QA scoring and live agent assist, it delivers enterprise-grade call intelligence without the overhead or cost of legacy systems. This makes it ideal for fast-moving teams that need accurate speech-to-text transcription, agent performance tracking, and compliance monitoring — all within a platform that’s fast to deploy, easy to use, and competitively priced. With its Agentic AI capabilities, Enthu doesn’t just analyze — it helps agents act in the moment, turning live feedback into better outcomes.

Key Features

• Auto QA Scoring: Automatically scores 100% of calls against custom quality scorecards (e.g., greetings, policy mentions, empathy shown)

• Speech & Sentiment Analytics: Detects sentiment shifts, silence duration, talk ratios, and emotional cues during voice calls

• Live Agent Assist & Alerts: Guides agents during calls and alerts supervisors when conversations go south (e.g., negative sentiment, silence)

• Keyword & Topic Tracking: Monitors phrases like competitor names or escalation requests to flag coaching or compliance risks

• Agent Performance Dashboards: Tracks quality scores, sentiment trends, and compliance metrics for each agent in real time

• Call Library & Search: Stores and indexes all calls with advanced search filters for training and QA review

• CRM & Telephony Integration: Works with tools like Aircall, RingCentral, and CRMs to ensure insights flow into your existing systems

• Compliance Monitoring: Checks if agents followed mandatory scripts and flags deviations

• Coaching & Feedback Workflows: Enables targeted coaching by identifying low-scoring calls and sharing call snippets with agents

Best For: Companies handling large call volumes looking to automate call monitoring, improve agent performance, and drive better call outcomes.

5. Gong

Gong is a category-defining conversational analytics software purpose-built for B2B sales and revenue organizations. Unlike traditional call recording tools, Gong delivers revenue intelligence by deeply analyzing sales calls, meetings, and emails to surface actionable insights that correlate directly with outcomes — like quota attainment, win rates, and deal health. Its strength lies in tying every conversation to real pipeline impact.

What makes Gong a leader in AI feedback analysis is its ability to track patterns in rep behavior, detect buying signals and objections, and forecast deal success based on conversational data. From talk-to-listen ratios to competitive mentions, Gong captures and interprets every signal. With automatic recording, transcription, and sentiment analysis layered with CRM enrichment, it creates a unified system of record for sales conversations.

Key Features

• Auto Call & Meeting Recording: Seamless recording of sales calls from Zoom, Microsoft Teams, and dialers without manual input

• Accurate Transcription & Indexing: Business-tuned transcripts with keyword search across all calls for fast access to insights

• Conversation KPIs & Analytics: Tracks rep talk time, interruptions, sentiment shifts, and topics discussed — turning behavior into data

• Deal Risk & Forecasting: Uses AI to flag silent deals, low engagement, or missed next steps; forecasts deal success based on patterns

• Keyword & Competitor Tracking: Monitor how often competitors, pricing, or key features come up — and in what context

• Scorecards & Coaching: Build and apply sales scorecards; managers can leave timestamped feedback directly in call replays

• Call Libraries & Sharing: Create searchable playlists of top-performing calls for onboarding and knowledge transfer

• CRM & Email Integration: Connects to Salesforce and email to enrich deal data and automatically log call activities and notes

• Analytics Dashboards: Visualize rep performance, deal momentum, and talk patterns of top closers for targeted enablement

• Privacy & Redaction Controls: Redact sensitive data and manage user access to stay compliant in regulated industries

Best For: Mid-to-large B2B sales and revenue teams looking to optimize sales conversations, improve coaching, and gain full visibility into deal health, especially where phone and video interactions drive the sales cycle.

6. Chattermill

Chattermill is an AI-powered feedback analytics platform that helps you get clarity across massive volumes of unstructured feedback. It unifies data from surveys, support tickets, reviews, social media, and chat logs into one centralized system, then uses deep learning to extract sentiment, themes, and emotion. Its key strength? Making sense of messy, qualitative data fast.

Designed to break down silos, Chattermill connects disparate feedback streams across teams and reveals what’s really driving NPS, CSAT, and retention. From detecting issues like “checkout delays” in support tickets to identifying “pricing confusion” in survey responses, Chattermill connects the dots with pinpoint precision. It’s built for organizations that want to go beyond dashboards and actually act on what customers are saying, at scale and in real time.

Key Features

• Unified Feedback Hub: Aggregates data from surveys, chats, social, app reviews, support, and more into a single dashboard

• Theme & Sentiment Detection: Automatically tags topics (e.g., Delivery, Pricing, UX) and detects positive, neutral, or negative sentiment

• Driver Analysis for NPS & CSAT: Correlates themes with NPS sentiment and other key metrics to identify what’s impacting scores

• Real-Time Trend Monitoring: Surfaces emerging issues, spikes in complaints, and sentiment changes across time

• Customizable Taxonomy: Lets teams build their own feedback hierarchy, tailored to industry or product-specific categories

• Multi-language AI: Analyzes customer feedback in multiple languages, ideal for global brands with localized CX

• Role-Based Dashboards: Tailored insights for product, support, marketing, or ops teams with click-to-drill-down access

• Integrations & APIs: Connects to Salesforce, Zendesk, Slack, and data warehouses for bi-directional syncing and alerts

• Security & Compliance: GDPR and SOC 2 compliant, with encryption and access controls for sensitive feedback data

Best For: Mid-to-large enterprises with multiple feedback channels and high volumes of unstructured customer feedback, especially those looking to tie qualitative feedback directly to NPS, CSAT, and churn insights.

7. Keatext

Keatext is a streamlined, AI-powered conversation intelligence platform that helps you make sense of unstructured customer feedback across channels. Whether you’re analyzing open-ended survey responses, support chat logs, product reviews, or social media comments, Keatext turns raw conversational data into structured, actionable insights—without requiring a data science team.

What sets Keatext apart in the crowded space of conversational analytics tools is its accessibility and speed. Its natural language processing (NLP) engine automatically detects themes, sentiment, and key drivers of customer satisfaction, allowing teams to monitor customer interactions in real time and identify emerging issues or opportunities. With a focus on ease-of-use, Keatext is a practical analytics tool for mid-sized businesses and cross-functional teams looking to analyze customer conversations and improve service quality, product experiences, and customer relationships—fast.

Key Features

• Unified Data Analysis: Collect and analyze feedback from surveys, chats, reviews, social media, support tickets, and more in a single dashboard

• Automated Theme Detection: Extract key topics from free-text feedback with no manual tagging needed

• Sentiment Analysis: Score sentiment at both the comment and theme level to gauge what’s working and what’s not

• Focus Recommendations: Prioritize improvements using AI-generated quadrant analysis that shows impact vs. performance

• Interactive Dashboard: Dive into customer insights with click-through themes, real-time trends, and filters by sentiment, metadata, or time

• Multi-Language Analysis: Automatically detect and analyze feedback in multiple languages—ideal for global brands

• Customization & Training: Merge, rename, or create custom topics, with machine learning improving over time

• Integrations & API: Sync with tools like Zendesk, or push/pull insights via API for full tech stack alignment

• Reporting & Exporting: Create shareable Voice of Customer reports with visualizations and download options

Best For: Mid-market CX, product, and marketing teams seeking fast, AI-powered analysis of customer conversations without the overhead of a full enterprise solution.

8. Lumoa

If most conversational analytics tools feel too complex or require weeks of setup, Lumoa offers a refreshing alternative: it’s built to be intuitive, fast to deploy, and powerful enough to uncover key drivers behind your customer satisfaction and NPS—all without a data science team. Designed for mid-sized companies or distributed teams that want to act on feedback quickly, Lumoa brings together all your unstructured feedback—from surveys, online reviews, emails, and support tickets—and uses AI to instantly analyze sentiment, categorize themes, and surface insights in plain language.

What truly sets Lumoa apart is its multi-language feedback analysis and its Generative AI summaries, enabling non-analysts to instantly understand what customers are saying about specific features, experiences, or service touchpoints. Unlike enterprise-heavy platforms, Lumoa doesn’t overwhelm—you get clarity, not dashboards full of noise.

Key Features

• AI-Driven Categorization: Instantly tags feedback with business-relevant topics using models trained across industries

• Sentiment Analysis at Scale: Measures and trends sentiment across themes, segments, and customer touchpoints

• Multi-Source Feedback Intake: Unified analysis of in app surveys, NPS, emails, support tickets, and online reviews

• Generative AI Summaries: Auto-summarizes what users are saying about a feature, region, or team—no digging required

• Volume-Based Pricing & Unlimited Users: Democratizes insights without additional licenses or user-based restrictions

• Feedback Assignment & Alerts: Turn feedback into actions by routing issues, assigning comments, and setting alerts

• Multi-Language Understanding: Combines multilingual input into unified insights, ideal for global teams

• Segment Filters & Benchmarks: Compare sentiment, themes, and NPS drivers across time, location, or product

• Easy Integration & API Access: Connects with CRMs, Power BI, and other tools for flexible feedback management

Best For: Mid-sized CX, customer success, and product teams that want powerful, easy-to-use customer feedback analytics—especially those running NPS or in app surveys and needing to collect contextual user feedback across channels without complex tooling.

9. CallMiner

If your organization is sitting on mountains of voice data and needs industrial-strength analytics to extract insights from every conversation, CallMiner is hard to beat. Built for large-scale contact centers, CallMiner offers one of the most robust conversational analytics platforms, specializing in real-time and post-call voice analysis, acoustic sentiment detection, and agent performance optimization.

What makes CallMiner stand out among conversational analytics tools is its ability to process millions of hours of customer calls, transcribing and analyzing both what was said and how it was said. Beyond just sentiment analysis, it evaluates tone, pitch, silence, and overtalk—critical indicators of customer satisfaction and friction. While it now supports omnichannel feedback by analyzing chat and email as well, its core strength remains voice, making it ideal for enterprises where customer conversations happen at scale.

Key Features

• Enterprise-Grade Voice Analytics: Transcribes and analyzes every voice interaction using AI and acoustic signals

• Real-Time and Post-Call Insights: Live alerts for escalations + deep post-call analysis

• Agent Performance Scoring: Custom quality metrics with automated scoring for every call

• Emotion & Behavior Detection: Detects stress, frustration, silence, and interruptions in voice tone

• Custom Topic Detection: Track call drivers like complaints, cancellations, or upsells

• Omnichannel Feedback Analysis: Unified analysis of chat, email, and voice interactions

• Integrated Coaching & Compliance Tools: Automate workflows for agent improvement and policy adherence

• Role-Based Dashboards: Tailored insights for QA teams, execs, and contact center leaders

• APIs & Data Export: Push insights to BI tools or CRMs for richer decision-making

Best For: Large enterprises with high voice volumes that need deep analytics for QA, compliance, and performance to transform raw customer calls into actionable insights at scale.

10. Observe.AI

Observe.AI is a next-gen conversation analytics software built for modern contact centers that want to do more than just record and transcribe customer phone calls. Unlike older QA tools that focus only on post-call evaluations, Observe.AI actively supports customer service agents in real time with AI-powered suggestions, live call coaching, and instant knowledge surfacing. Its core promise: turn every customer interaction into a growth opportunity and drive measurable impact on agent performance, CSAT, and compliance.

What makes Observe.AI stand out is its dual engine of real-time agent assist and fully automated quality assurance—making it possible to analyze 100% of customer interactions across voice and multiple channels. From improving first-call resolution to slashing after-call work, it blends generative AI with robust speech analytics to reduce manual tasks and enhance customer support teams’ productivity. For customer experience leaders and sales managers aiming to align contact center insights with broader business objectives and data-driven decision making, Observe.AI becomes a cornerstone in the existing tech stack.

Key Features

• Speech Analytics & Transcription: AI-powered transcription and sentiment analysis across 100% of customer phone calls.

• Real-Time Agent Assist: Live prompts surface knowledge base articles and objection handling cues during calls.

• Automated QA: Scores every call using customizable QA scorecards for compliance and performance.

• Generative AI Summaries: Auto-generated call summaries with key points and outcomes pushed to CRMs.

• Agent Coaching Insights: Tracks individual performance trends to support targeted coaching and improvement.

• Knowledge AI: Natural language search pulls relevant answers from internal documentation instantly.

• Trend & Outcome Analysis: Correlates conversation topics with CSAT, churn, and other business outcomes.

• Security & Compliance: Built-in PCI redaction, role-based controls, and support for HIPAA, GDPR, and more.

• CRM & Contact Center Integrations: Works with Genesys, Five9, AWS Connect, and leading CRMs to sync insights with your stack.

Conclusion

In today’s customer-driven landscape, conversational analytics is mission-critical. Every customer call, chat, or email contains signals that directly impact satisfaction, loyalty, and revenue. Without the right tools, these signals remain hidden, leaving businesses reactive instead of proactive.

By investing in conversational analytics, companies gain the ability to elevate customer experience, improve agent performance, and strengthen retention. The payoff is tangible: faster resolution times, more empathetic service, and data-backed decisions that prevent churn before it happens.

For teams looking for a modern solution, Zonka Feedback’s AI Feedback Intelligence stands out. It combines multi-channel data capture (from surveys, in-app feedback, support tickets, call transcripts and reviews) with AI-driven sentiment and thematic analysis, and a unified response inbox that ensures no insight or customer issue slips through the cracks. You also get real-time alerts, workflow automation, and AI-powered recommendations that helps you move from passive listening to active, operational intelligence.

Get early access to AI Feedback Intelligence or schedule a personalized demo to see how Zonka Feedback can turn your conversational data into a growth engine.