What’s really happening in your sales calls or support chats? What do your top-performing reps do differently in conversations?
Conversational analytics tools help answer those questions. They turn everyday conversations—phone calls, chats, and meetings—into insights your team can act on. But not all tools do the same job.
While some tools use AI to analyze what was said, others, like Analytic Call Tracking, focus on who called, why, from where, and what happened next. They help you organize conversational data so your downstream tools can interpret it.
So, which tool is right for your workflow? Let’s look at the top conversational analytics tools available right now.
If you’re running digital campaigns that generate customer phone calls, you need a way to track which efforts are working. Analytic Call Tracking does exactly that. It captures the raw conversation data your team needs to measure return on investment (ROI) and feed into downstream analysis tools.
This isn’t a traditional conversational analytics software platform. It doesn’t transcribe or analyze speech. Instead, it captures the structured data like call recordings, outcomes, campaign sources, and timestamps.
Think of it as the missing layer that makes your conversation intelligence platform useful.
Analytic Call Tracking is ideal for marketers who care about attribution, conversions, and customer journey mapping. It improves operational efficiency by offering flexible plans that support startups and agencies, without locking you into long-term contracts.
If your focus is campaign performance and customer engagement, this tool sets you up to succeed. You can track which ads drive calls, log customer behavior patterns, and pass clean data to analytics or transcription platforms to gain insights that guide your next move.
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Gong helps sales teams understand what happens during calls, meetings, and emails. It records and analyzes customer interactions, then uses artificial intelligence to uncover patterns that drive better results.
Sales leaders use Gong to see how top performers sell, what objections slow deals, and which behaviors lead to closed-won opportunities. It connects conversation data to your sales pipeline so you can take clear action based on actionable insights.
Gong helps you identify trends in rep behavior and deal success. If you’re looking to strengthen training, fine-tune sales strategies, and shorten sales cycles, Gong offers a data-backed path forward.
Gong delivers valuable insights into how your team sells and why some deals succeed. It helps you pinpoint opportunities to refine messaging, train better, and standardize what works across the team.
Gong is designed for mid-size to enterprise sales teams and typically involves a long-term contract. Smaller teams may find it more than they need, both in cost and complexity.
Pricing is not available to the public.
SentiSum focuses on support conversations across every channel, not just calls. It helps teams understand what customers are saying and why they’re reaching out by analyzing conversations across live chat, emails, tickets, and phone calls using natural language processing.
The platform simplifies complex data by automatically tagging and categorizing conversations. It helps support teams focus on improving customer interactions rather than sorting through disorganized input.
SentiSum is a solid option if you’re looking to boost customer satisfaction and align your support strategy with the voice of the customer. It helps you address pain points and refine support operations with clear, real-time visibility.
SentiSum gives teams a simple way to spot recurring issues before they escalate. It’s useful for companies that receive high volumes of support messages and want to extract customer feedback without manual sorting.
Some advanced features have a learning curve. The export functionality can feel restrictive for teams that need full data access outside the platform.
Chorus records and analyzes sales calls, meetings, and emails so teams can understand what drives deals forward. It captures every interaction and surfaces the moments that matter, helping leaders improve performance across the pipeline.
Sales teams use Chorus to track follow-up commitments, flag buying signals, and improve messaging. The platform connects conversation analysis to revenue outcomes so you can adjust strategies based on how customers interact throughout the sales cycle.
If you want to strengthen customer relationships and build a deeper connection between conversations and outcomes, Chorus can help document what works at every stage of engagement.
Chorus helps teams review real conversations and extract customer insights. It improves team alignment and helps leaders scale winning behaviors across their reps.
Some features can be tricky to locate in the interface. Teams might need some time to adjust to its layout and functionality.
Pricing is not publicly available.
CallMiner helps contact centers process large volumes of customer conversations using advanced analytics. It focuses on uncovering trends in customer calls, evaluating contact center performance, and improving service quality.
The platform uses machine learning and natural language processing to transcribe and assess calls. It can detect silence, monitor script adherence, and perform sentiment analysis to flag emotional shifts or customer frustration.
Team leaders rely on CallMiner to evaluate agent performance, spot compliance issues, and coach reps more effectively.
CallMiner is useful for managing all your data from conversations in one place. If improving oversight and automation are part of your business objectives, this platform offers a strong analytical foundation.
CallMiner gives deep insights into how conversations unfold. It helps teams manage risk, improve scripts, and track customer retention by surfacing patterns across thousands of calls.
Setup can be time-consuming. Some users find the search functionality limited when trying to locate older conversations.
CallMiner does not list specific pricing details publicly.
Avoma helps teams get more value out of meetings by recording, transcribing, and summarizing conversations. It supports the entire meeting lifecycle, from scheduling and agendas to follow-ups and insights.
The platform uses artificial intelligence to generate structured notes, extract action items, and sync insights to CRM systems. It’s useful for sales, customer success, and product teams that want to avoid manual note-taking and stay aligned across departments.
Avoma supports data-driven decision making by turning meetings into a clear record of priorities and progress. If you’re looking to provide valuable insights across teams and simplify documentation, this tool can help streamline your workflow.
Avoma adds structure to meetings and helps capture customer needs clearly. It also supports team collaboration and keeps single customer conversation threads documented across touchpoints.
Some users experience delays with meeting recordings or inaccuracies in speaker recognition. A few features, like previous call imports, may be harder to find.
Choosing the right conversation analytics software comes down to more than just checking off features. The goal is to turn routine conversations into actionable insights that align with real workflows.
Whether you’re in sales, support, or marketing, your tool should help you gain valuable insights from customer conversations and then translate them into meaningful action.
Consider these factors when evaluating your options:
Look for high-quality transcription that captures every detail clearly. Accuracy matters when you need to revisit specific phrases or tie conversations back to results. Some tools also let you bookmark or search through long voice calls, which saves time.
Some platforms surface insights while the conversation is happening. Others perform a full analysis after the interaction ends. If your team includes contact center agents, real-time alerts might help. If you’re a manager reviewing trends, post-call summaries could be more useful.
Tools with natural language processing can detect hesitation, frustration, or confidence in a caller’s tone. These features help uncover hidden customer emotions and can flag calls that need follow-up, especially useful when analyzing customer interactions at scale.
They also support a deeper understanding of how customers feel and why they respond the way they do.
To keep teams aligned, your analytics must integrate with CRM systems and other tools in your existing tech stack. When data flows across systems, teams stay aligned and reduce duplication.
Great platforms go beyond phone calls. Whether it’s chat, email, or social, analyzing data across multiple channels helps you track the full customer journey. This can improve how your team engages at every step and lead to a better customer experience.
When collecting customer data, you also take on the responsibility to protect it. Make sure your tool meets standards like the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA). Advanced data security and encryption should come standard.
If your team doesn’t want to use it, it won’t matter how advanced it is. Look for intuitive dashboards, flexible pricing, and features that support growing teams.
Before you choose a platform that transcribes or scores conversations, make sure your data is clean and organized. Analytic Call Tracking gives you the structure that every conversational analytics tool needs, including recorded calls, outcome tagging, source tracking, and campaign attribution.
When you can tie every call back to a specific ad, keyword, or landing page, you gain a clearer picture of what drives results. Analytic Call Tracking helps you collect and manage this data without hassle.
It works well on its own for marketing and ROI tracking, and it also fits perfectly into a broader analytics stack. If you later decide to add conversation intelligence, sentiment scoring, or coaching insights, you will already have the foundation in place.
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Conversational analytics is the process of analyzing spoken or written interactions between customers and businesses. This includes analyzing customer conversations from calls, chats, and emails to understand tone, intent, topics, and outcomes using technologies like natural language processing and machine learning.
The four types of data analytics tools are:
Together, these approaches help teams understand performance, anticipate outcomes, and choose the next steps more effectively.
The best conversation intelligence software depends on your goals. Gong and Chorus are strong choices for sales teams. SentiSum supports customer support teams. CallMiner works well for large-scale contact centers. Analytic Call Tracking supports all of them by providing the structured conversation data needed for deeper analysis.
A conversational tool is any software that enables, manages, or analyzes communication between businesses and customers. This can include chatbots, call tracking platforms, AI transcription tools, or full-scale analytics software that captures and analyzes human language across various channels.
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