AI Sentiment & QA Analyzing customer emotions and monitoring service quality with AI.
Every day, contact centers handle a large number of customers from multiple channels, including phone calls, chat, emails, and social media messages. Traditional quality control, which involves randomly listening to only a portion of call logs, is insufficient for accurately assessing service quality and improving customer experience.
AI Sentiment & QA is a function developed to address this problem by using AI to analyze conversations between customers and agents across all channels, instead of randomly listening to calls from only one channel. This allows for systematic and timely assessment of customer sentiment, service quality, and the identification of areas for improvement.
AI Sentiment (Customer Emotion Analysis) What is
AI Sentiment uses AI to analyze speech, text, and conversational context, considering factors such as:
- Tone and Pitch: Detects loudness, speed, and rhythm of speech to identify anger or urgency.
- Keywords and Phrases: Detects positive words (e.g., thank you, impressed ), negative words (e.g., terrible, dissatisfied, change suppliers ), or critical warnings (e.g., I will sue, Consumer Protection Board, please speak to my supervisor ) .
- Sentiment Flow: Analyzing how emotions shift from negative to positive.> Plus (successful problem solving) or plus -> Delete (due to a service error)?
This information is then used to assess customer sentiment trends, such as:
- Positive — Customers are satisfied, feel helped, or accept the solution;
- Neutral — Customers are normal, providing information or asking questions without strong emotion;
- Negative — Customers are dissatisfied, anxious, disappointed, confused, or likely to complain.
compare: Traditional QA vs. AI QA
| Comparison topics | Traditional QA (random inspection by people) | AI QA |
| Inspection quantity | Only 1-2% of all lines are randomly inspected. | 100% verifiable on all lines and channels. |
| Accuracy | There may be bias depending on each individual QA perspective. | The same standards, 100% impartial. |
| Assessment speed | It took several days after the call ended. | Get results instantly in real-time , or within minutes of ending the call. |
| Handling crisis situations. | Knowing about it after it has already happened means it’s too late to stop it. | A real-time alert notifies the supervisor to intervene immediately. |
| Staff skill development | The results are summarized monthly, and time is spent working on topics to develop skills. | Development is targeted and on a daily basis. |
AI QA (AI-powered cable quality assessment) What is
AI QA, or AI Quality Assurance, is the use of AI to monitor and evaluate the quality of service provided by staff based on organizational criteria. Examples include:
- Greeting & Closing ( using a script for greetings and closing sales) ,
- Verification & Compliance ( verifying customer identity and informing them of legal requirements),
- Empathy & Professionalism ( showing empathy and using polite language), and
- First Contact Resolution (FCR) ( resolving customer issues on the first call ).
AI Wrap-up and AI Summary What is the difference between
These two words are often used interchangeably, but each has a different scope of function.
AI Summary
This involves using AI to summarize key points from conversations, such as
- what the customer was discussing,
- their problem or need,
- what information or actions the staff member has already taken, whether
- the problem has been resolved,
- what follow-up is required,
- and what concerns or dissatisfactions the customer expressed.
The results are typically presented in the form of short, easy-to-read text, paragraphs, or headings.
AI Wrap-up
It has a broader scope than AI Summary. In addition to generating summary messages, the AI will help manage information after the conversation ends and save it to the system, such as:
- Select a Disposition Code or problem classification label
- , specify the Contact Reason,
- categorize the problem,
- identify the relevant product or service,
- record the resolution
- , specify the case status,
- create a task list
- , suggest an urgency level
- , prepare a message for recording in the CRM or ticket,
- and send data to other systems via API.
AI Wrap-up / AI Summary work?
The AI process is designed to be smooth and secure, and is divided into four steps as follows:
Capture (Data Acquisition): The system receives data from various sources, such as telephone conversations, and converts the speech to text in real-time, or extracts data from chat channels. The AI then separates the text and arranges the events in chronological order.
Analyze
(Contextual analysis and key information extraction)AI analyzes conversation transcripts to find necessary information: the purpose of the contact, the problem, the main idea, the context, the emotions, and the customer's true needs.
Summarize
(In summary)AI groups the data and creates a structured summary based on a business-defined template.
Auto-Save
(System Entry) The summarized information will be sent directly to the CRM system (e.g., Salesforce, Zendesk) or the company database. Alternatively, a human-in-the-loop approach can be used, where a staff member reviews and corrects the summary before entering the data into the relevant system.
The template can be customized to suit each organization’s workflow based on specified topics, such as:
Customer Service Jobs
- Reason for contact,
- Customer problem,
- Investigation step,
- Solution,
- Resolution status,
- Follow-up tasks,
- Appointment date,
- Case number.
Sales
- Product of interest,
- customer needs,
- budget,
- expected decision timeline,
- decision-maker,
- objections or concerns,
- next step,
- follow-up date.
Debt collection
- Reasons for non-payment,
- amount mentioned,
- agreed payment date,
- payment method,
- agreed terms and conditions,
- risk of default,
- next follow-up.
Hospital or clinic work.
- Reason for contacting,
- relevant department or service,
- appointment date,
- required documents,
- instructions given by staff,
- forwarding tasks.
Before and after AI Wrap-up / AI Summary
Example dialogue
The customer called to report being unable to log in to their member account after changing mobile phones. Upon investigation, we found that the customer’s account was still linked to the old phone number. Therefore, we proceeded to verify their identity and change the phone number. The customer can now log in normally, and there are no further follow-up tasks required.
Examples of results from AI.
Contact Reason: Unable to log in to member account.
Customer Issue: Customer changed phone number and cannot receive OTP code from old number.
Action Taken: Staff checked information, verified identity, and updated new phone number.
Resolution: Customer successfully logged in and received OTP.
Case Status: Resolved.
Follow-up Required: No
Disposition Code: Account Access – Resolved
Benefits of AI Wrap-up / AI Summary
Reduce post-graduation work hours. Officials no longer need to spend minutes writing summaries every time; AI can summarize the information instantly after the conversation ends.
The records use the same standards. Manual note-taking varies depending on the experience and writing style of each staff member. AI can generate notes based on standard organizational structures and terminology.
Reducing data loss: AI can detect important issues such as appointment dates, agreements, reference numbers, or steps to follow up on that staff may forget to record after multiple ongoing conversations.
Smooth case transfer is ensured when the customer contacts back or the case is transferred. A new staff member can immediately review the summary to understand the situation, reducing the need for repeated questions and preventing customers from having to explain the same details multiple times.
The data can be further analyzed. The summarized information can be used to analyze problems, solutions, customer sentiment, and service quality, helping to improve service efficiency and refine KPIs.
From the conversation. Providing information that helps organizations make better decisions.
AI Wrap-up / AI Summary aims not only to reduce the time staff spend typing records, but also to transform conversations previously in the form of audio files or long text messages into structured data that is searchable, shareable, and analyzed.
When designed appropriately within an organization’s workflow, this function can help organizations…
- Reduce post-call workload,
- increase call readiness,
- elevate data recording standards,
- minimize loss of crucial information,
- speed up case transfer,
- provide comprehensive CRM data,
- facilitate case review for supervisors,
- and incorporate customer needs into product and service development.
It is crucial that organizations choose an AI Wrap-up/AI Summary solution that can adapt templates to actual workflows, integrate with existing CRM systems, and include appropriate data verification and security measures.
Reduce post-call time and transform every conversation into actionable information.
Let AI help you generate summaries, suggest dispositions, and prepare data for CRM or ticket management based on your organization’s workflow.
Frequently Asked Questions about AI Wrap-up / AI Summary
Can AI Wrap-up / AI Summary operate in real-time?
AI Summary can generate summaries of information both during and after a conversation (Post-contact Summary). The choice depends on the use case, system resources, and speed requirements.
Can AI Wrap-up / AI Summary replace all human personnel?
AI should not replace all human personnel, especially for tasks involving sensitive data such as monetary amounts, agreements, appointment dates, legal information, or medical data. Humans should always verify this information before recording it.
Can the system summarize in Thai?
This is possible if the Speech-to-Text and language model adequately support Thai, but it should be tested with the actual accent, terminology, and voice quality of the organization.
Can the AI Wrap-up / AI Summary automatically select a problem classification code (Disposition Code)?
AI can analyze and suggest code from conversational content, but it’s advisable to have a human review its accuracy, especially during initial deployment, before allowing the AI to handle it independently.
Can the AI Wrap-up / AI Summary integrate with your existing CRM?
Connectivity is possible if the CRM system supports API, Webhook, or Integration Interface. The mapping between the data in the Summary and the fields in the CRM should be clearly defined.
How does AI Summary differ from a Transcript?
A transcript is the complete text taken from a conversation. AI Summary is the process of organizing and condensing the key information from the transcript into an easy-to-understand format.
Does the AI Wrap-up / AI Summary need to record every call?
Depending on the system design, AI may work with streaming audio, recorded audio, or transcripts already generated by other systems. Organizations should establish recording and data storage policies in accordance with relevant requirements.
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