Turn customer conversations into actionable business intelligence.
Qualiteam.ai is an AI Conversation Analytics Software that automatically analyzes 100% of customer and partner conversations to uncover the business information hidden inside every interaction. Instead of manually reviewing a small sample of conversations, your teams gain visibility into customer feedback, customer satisfaction, recurring issues, churn risk, product insights, and emerging trends.
Qualiteam.ai transforms unstructured customer conversations into structured business insights that help organizations understand what customers are experiencing and make better decisions based on real interactions.
You define which insights matter to your business. Qualiteam.ai then analyzes every conversation and automatically extracts those insights at scale.
Churn risk report
Sample dataHigh churn risk by request type
Compare risk concentration across common customer requests.
| Request type | Total | High risk | Rate |
|---|---|---|---|
| Refund / Cancellation request | 70 | 31 | 44.3% |
| Billing / Payment issue | 180 | 62 | 34.4% |
| Technical issue / Bug | 220 | 59 | 26.8% |
| Onboarding issue | 120 | 25 | 20.8% |
| Pricing question | 90 | 16 | 17.8% |
Conversation Analytics is the process of transforming customer conversations into structured business insights. Conversation Analytics Software uses artificial intelligence to analyze conversations across channels and uncover patterns, customer sentiment, product feedback, customer intent, and other signals that matter to your business.
Before
Customer conversations
Every day, customers share valuable information through chats, emails, calls, and messaging platforms. These conversations contain information about customer satisfaction, recurring problems, feature requests, churn risk, and customer needs that can be difficult to identify through manual reviews alone.
After
Structured business insights
With Qualiteam.ai, you define the insights that matter to your business, and the platform automatically extracts them from every conversation. These configurable data points are called attributes within Qualiteam.ai.
Identify customers showing early signs of disengagement or potential churn.
Organize conversations according to the type of issue or request raised by the customer.
Understand customer satisfaction based on signals within the conversation.
Identify product ideas, feature requests, usability issues, and other feedback shared directly by customers.
Identify signals such as upgrade opportunities, cancellation requests, escalation risks, or purchasing intent.
These insights can be measured, filtered, compared, and analyzed over time, helping teams understand what is happening across their customer conversations.
Although both technologies analyze customer conversations, they answer completely different business questions.
Focuses on measuring how well agents handled each conversation. It evaluates communication quality using configurable criteria such as response quality, policy compliance, empathy, or escalation handling.
Focuses on understanding what conversations reveal about your business. Instead of evaluating agent performance, it extracts structured business information that helps organizations identify trends, customer needs, operational challenges, and opportunities for improvement.
Together, these two capabilities provide a complete understanding of both team performance and customer experience, while remaining independent systems designed for different objectives.
If you're looking to evaluate agent performance alongside business insights, explore our conversation intelligence software to discover how Qualiteam.ai combines AI-powered conversation evaluation with advanced conversation analytics.
Learn moreConversation Analytics Software turns customer conversations into structured insights through four clear steps.
Securely connect your communication platforms to automatically analyze customer conversations from supported channels, including chats, emails, calls, and messaging platforms.
Define the insights that matter to your business and the information you want to extract from your conversations.
Qualiteam.ai then uses AI to automatically extract those defined insights from every conversation, making Conversation Analytics Software adaptable to different industries, teams, and business goals.
Once insights have been extracted, teams can filter, segment, compare, and analyze customer conversations using structured business data.
Monitor trends over time, understand insight distributions, and compare results across relevant conversations, teams, products, customer segments, communication channels, or time periods.
Every insight remains connected to its original conversation.
Teams can drill down from reports and results directly into the customer interactions behind them, providing the context needed to understand individual conversations and the trends they reveal.
Every defined insight is automatically extracted and categorized using AI, allowing your teams to move from reactive support to proactive decision-making.
A support team handles thousands of customer conversations every month. The company can see that customer satisfaction is declining, but a general CSAT score alone does not explain why customers are dissatisfied or which issues create the most negative experiences.
Instead of manually reviewing hundreds or thousands of conversations, the company wants to understand:
To answer these questions, the analysis starts with an individual customer conversation.
Step 1 of 5: Start with an individual customer conversation
Step 1 of 5
Customer:
“I’ve been trying to withdraw my funds since yesterday. It still says pending. Can you tell me what’s happening?”
Agent:
“Your withdrawal is currently being reviewed. Please allow additional time for processing.”
Customer:
“This is the third time I’ve contacted support about this. Nobody can tell me when it will be completed.”
One conversation alone provides limited context. It does not tell the company whether this is an isolated case or part of a larger problem.
Step 2 of 5
The company defines the insights it wants conversation analytics software to extract from every conversation.
For this use case, the conversation can be transformed into structured data:
One customer conversation has now become structured, measurable business data.
The insights are configurable. Different companies can define the information they want Qualiteam.ai to extract based on their own processes, customers, and business questions.
Step 3 of 5
The real value of conversation analytics appears when the same analysis is performed across thousands of customer conversations.
For example, Qualiteam.ai can show customer dissatisfaction by request type:
This allows the company to see that withdrawal-related conversations generate significantly more dissatisfaction than other request types.
Instead of relying on a general CSAT score, teams can identify which types of customer requests are associated with the highest levels of dissatisfaction and understand where to focus their attention.
Step 4 of 5
Identifying that withdrawal-related conversations generate more dissatisfaction is only the first step. The team can then investigate the conversations behind the result to understand what is actually driving the negative experience.
Within dissatisfied conversations related to withdrawal delays, the main negative experience drivers are:
This reveals a much more actionable insight.
The problem is not simply that customers dislike the withdrawal or verification process. The analysis shows that customers become especially dissatisfied when withdrawals are delayed and support cannot provide a clear timeframe for completion.
Teams can also open the original conversations behind any metric to understand the context and verify what customers are actually saying.
Step 5 of 5
Once the root cause is understood, different teams can act on the same insight.
Investigate why withdrawal processing times are increasing.
Improve guidance for agents so customers receive clearer information about expected processing times and next steps.
Review whether customers should receive proactive status updates instead of contacting support repeatedly.
Continue monitoring the same insights to see whether dissatisfaction around withdrawal-related conversations decreases after the changes are implemented.
This example demonstrates how conversation analytics software can help companies move from a general business signal to a specific, actionable insight.
Instead of simply knowing:
“Customer satisfaction is declining.”
The company can understand:
“Withdrawal delays are generating the highest dissatisfaction. The main driver is the lack of a clear processing timeframe, particularly among customers who need to contact support multiple times.”
That is the type of insight that teams can actually act on.
The true value of conversation analytics software lies in turning customer conversations into insights that are easy to explore, understand, and act on.
Qualiteam.ai transforms extracted insights into interactive reports and dashboards, allowing organizations to monitor customer behavior, identify emerging trends, measure operational performance, and investigate the conversations behind every insight.
Distribution
Sample dataNegative experience driver
Total conversations: 10,574
Conversation analytics becomes even more valuable when critical situations are detected automatically.
Qualiteam.ai allows organizations to configure real-time alerts based on configurable insights or conversation evaluation results, helping your teams respond immediately instead of discovering critical issues weeks later.
Live monitoring
Churn risk increases or accounts show signs of friction.
Churn risk attribute
Estimated customer satisfaction drops below your target threshold.
Estimated CSAT
Complaint volumes exceed predefined operational limits.
Conversation volume
Specific insights (like legal risk or billing issues) appear more frequently.
Custom attribute
Conversation Evaluation scores fall below expected quality levels.
Evaluation score
By combining conversation analytics with intelligent alerts, organizations can proactively identify business risks, protect customer relationships, and react faster to emerging trends.
Every customer-facing department generates valuable conversation data. Qualiteam.ai transforms that information into structured business insights, making conversation analytics software valuable across multiple teams and industries.
Whether you're looking for customer experience analytics software to improve customer satisfaction or customer conversation analytics to understand business trends, Qualiteam.ai helps every department make better decisions using real customer interactions.
Identify recurring issues, complaint drivers, and satisfaction signals to improve the customer experience.
Flag churn-risk signals, understand adoption challenges, and prioritize conversations that require attention.
Provide clients with structured conversation insights alongside conversation-quality evaluation.
Understand recurring objections, partner requests, conversation outcomes, and potential account risks.
Organize product feedback, feature requests, usability issues, and operational friction into trends that teams can prioritize.
Customer Interaction Analytics uses artificial intelligence to process chats, emails, calls, and messaging platforms. The platform automatically extracts structured AI attributes, making it possible to identify trends, customer sentiment, product feedback, and churn risk without manually reviewing conversations.
Traditional surveys capture feedback from only a small percentage of customers. Qualiteam.ai infers customer satisfaction directly from 100% of conversations by analyzing conversational signals such as tone, customer effort, conversation outcomes, unresolved issues, and resolution clarity.
Qualiteam.ai allows organizations to define the insights they want to extract from their conversations. Within Qualiteam.ai, these configurable insights are called attributes, making the software adaptable to different industries, departments, and reporting requirements.
Yes. Results remain connected to the original customer conversations, allowing teams to drill down into individual interactions and gain the context behind each insight.
Organizations that rely on customer communications can use Conversation Analytics Software to transform conversations into structured business insights. This includes SaaS, e-commerce, fintech, iGaming, logistics, healthcare, BPOs, contact centers, and other organizations managing customer and partner conversations.
Turn customer conversations into structured business insights with Conversation Analytics Software.