Top 7 Conversation Analytics Software for Customer Service & Sales Teams

Conversations with customers are packed with valuable insights, but only if you have the right tools to uncover them. That’s where conversation analytics software comes in. These platforms analyze every call, chat, and message to help customer service and sales teams understand what customers say, how they feel, and what actions to take next.

Customer support teams use it to solve problems faster, coach agents more effectively, and raise CSAT scores. Sales teams use it to spot deal risks, surface coachable moments, and improve their process to close more revenue.

Unlike traditional analytics tools that just track call times or keyword mentions, conversation analytics goes deeper. It uncovers real meaning, detects customer emotion, and automates tedious QA tasks like scoring agent performance. Without it, teams are flying blind, relying on small, biased samples and missing the bigger picture.

Our software, Level AI, was built to analyze 100% of interactions to get you richer insights, faster feedback, and a clearer view of your customers’ needs, without the guesswork.

In this article, we’ll break down the top 7 conversation analytics tools for CX and sales teams, starting with Level AI and how we help support teams unlock real customer intelligence with the power of AI.

Keep reading or jump straight to the relevant product below:

Software Options for Customer Service Teams

1. Level AI

2. Qualtrics

3. Sprinklr

4. Dialpad

Software Options for Sales Teams

5. Gong

6. Invoca

7. HubSpot

Conversation Analytics Software for Customer Service Teams

1. Level AI: Uncover What Customers Really Mean, Not Just What They Say

Level AI is a conversation analytics platform that gives CX teams a clear view of every customer interaction, uncovering not just what was said but also what customers actually mean and feel.

Our platform captures true customer intent, real emotions, and patterns across all conversations. This helps support teams spot issues faster, coach agents more effectively, and create smoother customer experiences.

Below, we’ll show you how Level AI analyzes conversations, monitors agent performance effectively, and uncovers gaps in your existing customer service to strengthen service operations at every level.

Go Beyond Keywords to Detect True Intent

Many conversation analytics platforms claim to accurately identify intent (the primary meaning behind a customer’s words), but often fall short because they rely on rules-based systems that use keyword matching instead of true artificial intelligence.

For example, a customer might call in with an intent to request a refund, express frustration with a service, or inquire about purchasing a new product.

However, many conversation analytics tools rely on natural language processing (NLP) techniques like keyword-matching to classify interactions based on exact words or phrases, while missing subtle conversational nuances.

For instance, a keyword-matching system might easily spot conversations where a customer says, "I need to make a return," or "I want a refund," while failing to correctly categorize phrases using other keywords like "I want to exchange this" or "I want my money back."

While this approach can be useful, it presents numerous problems, such as:

• It's time-consuming and requires additional effort because you must enter multiple keyword variants to capture the same intent.
• Even when the right keywords are in the mix, these systems can still get intent wrong if they’re missing the greater context. For example, they might treat “I want to pay my bill” and “I can’t pay my bill” as the same thing because both mention “pay” and “bill”: when one’s a routine task and the other’s a red flag. Without real context, they miss what really matters.

Level AI’s Scenario Engine overcomes these limitations by using call center voice analytics and semantic intelligence to achieve near-human understanding of what’s being said during a conversation. Our software refers to intents as scenarios and identifies these by understanding the context and meaning behind the words in an interaction.

For example, if a customer says, “I’ve already called twice and my issue still isn’t fixed,” Level AI recognizes the frustration and unresolved problem, and automatically tags the conversation as an “Escalation” scenario for immediate follow-up.

Scenarios are marked using conversation tags to make it easier for you to find past conversations.

All conversational tags are searchable and filterable, which comes in handy when identifying interactions where certain intents were expressed or when generating reports.

Beyond Positive and Negative: Capture the Full Emotional Spectrum

Most customer sentiment analysis tools boil customer emotion down to a simple scale: positive or negative. But real conversations are rarely that clear-cut. When software lacks the ability to grasp tone, nuance, and emotional shifts, it delivers an incomplete, and often misleading, picture of how customers actually feel.

This kind of binary classification may capture surface-level sentiment, but it misses the deeper emotions that drive satisfaction, loyalty, or frustration. A more advanced approach is needed, one that identifies a full spectrum of emotions and tracks how they change throughout the interaction.

That’s where a more context-driven solution makes all the difference. Instead of just labeling sentiments as positive or negative, Level AI picks up on the full range of human emotion. It doesn’t just hear what customers are saying, it understands how they feel. Level AI detects:

• Anger
• Annoyance
• Disapproval
• Disappointment
• Worry
• Happiness
• Admiration
• Gratitude

Similar to conversation tags, our software uses sentiment tags to highlight instances where a given emotion occurred in a conversation. They’re also searchable and filterable for future conversation analysis and reporting.

To gauge quickly how a customer feels during a conversation, every interaction gets a Sentiment Score from 0 to 10, with 0 being the most negative and 10 the most positive. This score gives teams a fast, reliable way to understand overall sentiment at a glance.

Level AI’s Sentiment Score uses a weighted calculation that emphasizes emotions a customer expresses later in the conversation, such as whether their issue was resolved, as these better reflect the customer's feelings and the agent's performance.

For example, if a customer calls in angrily about a defective product but ends up satisfied after receiving a replacement, Level AI assigns a higher weighting to post-resolution happiness. This ensures the Sentiment Score accurately represents the customer’s lasting sentiment about the product, service, or brand.

Performance Insights at Scale, Without Manual Review

Many QA teams review agent calls manually, which means slow feedback, spotty scoring, and only a tiny fraction of conversations ever get looked at (typically only 1 to 2%).

It’s a process containing some guesswork and bias. Reviewers might focus too much on one call, miss key details, or score agents differently for the same behavior. Instead of coaching agents and fixing issues, teams get buried in paperwork, and major performance problems slip through the cracks.

Level AI’s InstaScore consistently analyzes all agent-customer interactions with full accuracy, auto-scores agents against your company’s rubrics, and displays performance as a single percentage value for every conversation:

For example, InstaScore can measure whether a customer service agent:

• Greeted the customer warmly
• Demonstrated deep product knowledge
• Provided clear next steps
• Remained patient with the customer
• Displayed empathy for the customer’s problem

Managers can click on a specific interaction's InstaScore to view more details about why that conversation received that assessment. This method of auto-scoring allows you to rapidly sample all your customer conversations for the best- and worst-performing agents.

Level AI’s InstaReview also allows you to quickly find conversations that are worth looking into further based on specific criteria:

• High number of requested assists by an agent
• Frequent quality or compliance flags
• Longer duration than average
• Low customer satisfaction

Our software uses AI speech analytics to indicate such conversations using specific tags to help identify calls worth further review:

After finding such calls, you can initiate coaching sessions directly from the dashboard to address any performance gaps.

After rolling out Level AI’s InstaScore and building targeted action plans, a global design and marketing firm boosted their QA scores from 60% to 88%. With better agent training and better-quality checks, they raised CSAT, cut down on unnecessary refunds, and saved over $30 million.

Get Instant Visibility into Live Customer Conversations

Without live monitoring, managers are left guessing which calls need their attention. They often rely on basic metrics like duration or customer hold time, which don't tell the full story. A long call might mean a problem, or it might just be a slow conversation.

Without hearing the actual conversation, it’s easy to miss when a customer is getting frustrated, an agent is struggling, or an upsell opportunity is slipping away. By the time anyone notices, it’s usually too late to fix the problem.

Live call monitoring gives managers real-time access to conversations, so they can spot issues early, guide agents in the moment, and preserve the customer experience before small problems turn into bigger ones.

Level AI’s live monitoring tool, Real-Time Manager Assist, provides instant visibility into ongoing customer conversations by showing key details like customer sentiment, agent performance, and estimated deal size, all in real time. Supervisors can quickly spot which calls need attention without having to listen to every word.

Our call center agent monitoring software also allows managers to intervene or guide agents on the spot to enhance service and sales performance. For example, if a customer’s sentiment turns negative during an interaction, managers can see this instantly and decide how to respond, such as through Call Barging or Call Whispering:

• Call barging allows managers to join a live call directly to resolve complex issues or manage escalations.
• Call whispering allows managers to guide agents with prompts, talking points, and key information in real-time during ongoing conversations, without the customer knowing.

(See our latest article on How to Monitor Call Center Performance.)

Go Beyond Surveys to Understand Customer Experience

Relying on traditional post-call surveys to understand customer perceptions often leaves you with a skewed and incomplete picture. Surveys rarely get a 100% response rate, and even the feedback is usually from those experiencing the strongest emotions, like delight or frustration. The majority of customers who had an average or mildly positive experience sometimes don’t respond at all.

Most customer experiences, like small annoyances, minor delays, or average service quality, often get missed. This creates a blind spot. Instead of hearing from the full range of customers, you're making decisions based on the loudest voices, not the majority experience. That means real problems may stay hidden, and opportunities to improve the typical customer journey can slip by unnoticed.

Surveys still play an important role (these let you ask your audience the questions you want to ask), but they can’t tell you everything. To capture the broader, unfiltered voice of your customer base, you also need a way to understand what customers are saying in their actual conversations. That’s where Level AI’s Voice of the Customer Insights comes in.

VoC Insights automatically analyzes all interaction data and extracts typical VoC metrics like CSAT, NPS, and CES directly from every customer who contacts your support team, giving you a fuller and more accurate view of customer experience in intuitive dashboards:

Beyond standard metrics, Level AI’s VoC Insights also uncovers more subtle patterns you may not have noticed, like a spike in complaints about long hold times or repeated questions about a product’s warranty during sales calls.

A buy-now-pay-later company used Level AI’s VoC Insights to spot what their chatbot was missing. By updating it with the questions customers actually cared about, they avoided a flood of support calls during Black Friday and Cyber Monday. Call volume only rose 6%, not the 150% they expected, saving the company approximately $2 million.

(Read our latest article on top SurveyMonkey alternatives.)

Another CX metric we offer is the Inferred Customer Satisfaction (iCSAT) score. It gives you a clear, single-number view of how satisfied a customer really was during an interaction. iCSAT looks at three things: how the customer felt, how much effort they had to put in, and whether their issue actually got resolved.

• The Resolution Score assesses whether a customer’s issue was fully or partially resolved, highlighting any gaps in service delivery or sales follow-up.
• The Sentiment Score evaluates the customer’s overall emotional tone throughout the interaction, capturing feelings like frustration or gratitude that impact satisfaction.
• The Customer Effort Score measures how much effort a customer exerted, such as navigating complex menus or repeating account details, which can erode their experience.

It’s a reliable way to measure satisfaction based on what actually happened, not just what the customer said afterward.

iCSAT is measured on a 1-to-5 scale (1 being very dissatisfied and 5 being very satisfied). It helps managers instantly identify unmet customer needs, such as frequent complaints about long hold times, and address them proactively.

Make Sense of Every Customer Touchpoint, All in One Dashboard

Customer data is everywhere in CRMs, call logs, and survey tools, but it’s often stuck in separate systems. That leaves support teams with incomplete reports and a fragmented view of what’s really happening. Without a clear picture, tracking agent performance or spotting trends affecting customer experience is tough.

Level AI’s unified reporting and analytics tools bring all your data into one view, consolidating everything so you can make better sense of it.

Our Query Builder lets you create tailored analytics dashboards by combining Level AI-specific data like sentiment tags, InstaScore, and VoC metrics, with data from external sources, allowing you to answer questions such as:

• Which customer intents are most linked to successful upsells or cross-sells during support conversations?
• How does mentioning a loyalty program or special offer affect customer sentiment over the course of a call?
• Is there a connection between negative sentiment early in a call and the likelihood of needing multiple escalations?
• Do conversations that start with a billing issue but end with a resolved sentiment tend to have higher CSAT scores?

Once reports are generated, Level AI’s roles and permissions system makes it easy to control access, specifying which team members can view or edit any call center analytics dashboard and share them via email for ready collaboration.

Schedule a free demo today to learn how Level AI’s conversation analytics software can help you improve your customer support operations.

2. Qualtrics: Omnichannel Customer Feedback Insights

Qualtrics is a customer experience management platform that uses AI-powered conversation analytics to deliver real-time insights across multiple channels. It's most useful for generating VoC data through surveys and gaining a better understanding of customer and employee experiences.

Qualtrics' key features include:

• Real-time feedback collection from 27 channels, including calls, chats, and social media
• Advanced speech and text analytics
• Custom survey creation and analysis tools
• Automated workflows via Qualtrics xFlow
• Omnichannel analytics engine that unifies data from calls, emails, and app reviews

Qualtrics does not publicly disclose detailed pricing. You can contact the sales team for a custom quote.

3. Sprinklr: Real-Time Impact Analysis & Alerts

Sprinklr is an AI-driven call center platform that uses conversation analytics to provide unified insights across 30+ digital and voice channels. It’s most useful for enterprise teams seeking to analyze customer interactions, optimize agent performance, and maintain conversation context for seamless experiences.

Key Sprinklr features include:

• Multichannel data capture from voice, SMS, live chat, and social media
• AI-driven sentiment analysis and intent detection
• Impact analysis tool to evaluate factors affecting CSAT, AHT, and NPS
• Real-time alerts for live conversations with low CSAT or missed SLAs
• Customizable dashboards with over 5,000 metrics for tailored reporting

Sprinklr offers custom pricing plans only for enterprise customers.

4. Dialpad: Live Call Monitoring with Unified Insights

Dialpad is a unified communications platform with advanced conversation analytics powered by proprietary AI. The platform offers real-time transcription and insights tailored to business-specific language.

It’s most useful for teams looking to improve agent coaching, monitor live calls, and streamline workflows with actionable conversation data.

Notable features include:

• Real-time transcription and sentiment analysis for live call monitoring
• Custom Moments to track keywords like competitor mentions or refund requests
• AI-powered call summaries and recaps generated by DialpadGPT
• Real-Time Assist cards for on-the-spot speech coaching
• Integrations with Salesforce, Zendesk, and an open API for custom automations

Dialpad offers pricing starting at $15 per user per month for the Standard plan. More advanced plans for support or sales-specific features range from $39 to $80 per user per month.

Conversation Analytics Software for Sales Teams

5. Gong: Analyze Sales Calls for Deal Intelligence

Gong is a revenue intelligence platform that uses AI-driven conversation analytics to capture, transcribe, and analyze sales calls, meetings, and emails. This helps teams optimize performance and close more deals.

The platform provides valuable insights into customer interactions and coaching opportunities, focusing on deal intelligence and market trends.

Gong’s key features include:

• Real-time call transcription and sentiment analysis
• Deal Warnings to flag at-risk deals based on predefined patterns
• Interaction Insights for detailed analysis of key metrics
• CRM integrations with Salesforce and HubSpot
• Call Spotlight to highlight key takeaways and action items

Gong only offers custom pricing that varies based on your team size and company needs.

6. Invoca: Revenue Execution Platform to Connect Marketing & Sales Teams

Invoca is an AI-powered conversation intelligence platform designed to enhance the performance of marketing and sales teams by analyzing phone conversations in real-time.

It’s most useful for attributing call conversions to marketing campaigns and optimizing digital ad spend, with a standout Signal AI for actionable call insights.

Key features include:

• Signal AI Studio for building custom AI models trained on business-specific call data.
• Integrations with CRMs, ad platforms, and analytics tools like Salesforce, Google Ads, and Adobe Experience Cloud.
• Impact analysis to measure how calls influence revenue and marketing ROI.
• Real-time data streaming to automate optimizations across tech stacks.

Invoca does not disclose pricing but offers three premium pricing plans (Pro, Enterprise, and Elite). You can contact their sales team for a demo and a quote.

7. HubSpot: Manage Deals with Conversation Data

HubSpot Sales Hub is a CRM-integrated platform with conversation intelligence tools that automatically capture and analyze customer calls. Managers can use these insights to provide better coaching and analyze performance more effectively.

HubSpot’s key features include:

• Automatic call recording and transcription
• Real-time coaching insights
• Integration with Zoom, JustCall, and Kixie
• Custom reporting to analyze call outcomes, objections, and competitive trends
• Automated workflows triggered by conversation data

HubSpot’s conversation intelligence software is available in the Sales Hub Professional plan. There are four pricing tiers for users, including:

• Free: $0/month for limited access
• Starter: $20/month per seat
• Professional: $100/month per seat
• Enterprise: $150/month per seat

Empower CX Teams with Level AI’s Conversation Analytics Software

Level AI’s secure and customizable Generative AI capabilities, advanced intent detection, and sentiment analysis functionality enable organizations to fully implement call center quality assurance best practices. This helps CX teams uncover recurring customer issues and hidden insights that could improve agent performance and the overall customer experience.

Curious how conversation analytics software can improve your contact center operations? Schedule a demo with the Level AI team today.