After-call work (ACW) consists of tasks agents perform immediately after a customer interaction. For an agent, ACW includes updating customer records, making call notes, tagging calls for categorization, scheduling follow-up tasks, and more.
According to reports, call centers expect agents to finalize post-interaction tasks in approximately five minutes. And call notes or call summarization take up much of their time. Hence, manually inserting call notes is tedious, low-quality, and inefficient.
Now, let’s understand how manual call summarization impacts call center efficiency.
Manual Call Summarization Inefficiency
Let’s understand the time and money wasted on manual call summarization for a call center with 100 agents.
How can you control the cost incurred on manual summarization? Let’s discuss the most cost-effective alternative to manual call summarization.
Convin helps reduce call center inefficiencies by 3X. Talk to our experts!
The Solution–Convin’s AI-driven Auto Summarization
Through Convin’s Generative AI-powered Automatic Summarization technique, the total cost of unproductive hours can be reduced, and efficiency can be improved.
Here are some key advantages and ROI levers of Auto Summarization;
1. Save Time and Cost
Currently, agents spend around 5 minutes in post-call summarization.
- Agents handling 30-35 calls daily spend (Calls/day * Summary Time/call) = 162.5 minutes/day summarizing each.
- This translates to (Daily Time * Working Days) = 3,900 minutes or (3,900 minutes / 60 minutes/hour) = 65 hours per month.
- Assuming a 144-hour work month and $ 419 salary, agent time costs (Salary / Work Hours / Minutes/Hour) = ₹4.05 per minute.
- Monthly Savings per Agent: Automating summaries could save each agent Monthly Time Saved = (Daily Time * Working Days) 3,900 minutes. This translates to potential cost savings of (Time Saved * Cost per Minute) = ₹15,795 per month.
Scalable Savings: In a 100-agent call center, this translates to potential monthly savings of (Cost Saved/agent * # Agents) = ₹1,579,500 and annual savings of (Monthly Savings * 12 months) = ₹18,954,000.
2. Reduce Call Abandonment Rate
By automating tasks like call summaries, agents can immediately resolve customer issues. This reduces wait times and call abandonment rates and keeps customers happy with a quicker and more efficient service experience.
3. Reduction in Agent Burnout
Taking repetitive tasks like summaries off agents' plates combats burnout, boosting morale and job satisfaction. This translates to a happier, more motivated workforce with lower turnover rates.
4. Better Customer Experience
AI-powered call summaries flow directly into CRM systems, giving agents instant access to a concise customer history. This empowers them to personalize support and resolve issues faster, boosting customer satisfaction.
Results first, payment later.
Assessing AI Call Summarization
AI summarization leverages advanced technologies like Natural Language Processing (NLP) and machine learning to create concise and accurate summaries from lengthy documents.
Natural Language Processing (NLP): NLP, an AI branch, aids in document summarization by understanding and interpreting human language, identifying key sentences and ideas, and parsing the document's semantic representation.
Machine Learning: Machine learning algorithms, trained on large datasets, identify important information patterns in texts like news articles and call transcripts. Models like transformers and neural networks are crucial for concise summaries.
These tools utilize AI to produce concise and fluent summaries and retain the essential information from the original text.
Advantages Over Manual Methods:
- Speed: AI can process and summarize vast amounts of text much faster than humans, making it ideal for real-time applications.
- Scalability: AI systems can handle large-scale summarization tasks without fatigue, such as daily summarizing thousands of call transcripts or news articles.
- Objective Analysis: AI provides an unbiased perspective, focusing purely on the data without any subjective influence, which is crucial for generating multiple reference summaries.
Thus, AI is revolutionizing document summarization by providing efficient, accurate, and cost-effective solutions. Automatic summarization systems will become even more valuable in various applications as technology advances.
Leveraging AI software development services can further enhance call center efficiency. AI solutions can be tailored to specific needs, ensuring seamless integration and optimal performance. These services offer comprehensive support, from implementation to maintenance, ensuring that your call center reaps the full benefits of AI-driven automation.
Switching from manual to AI-driven call summarization not only saves time and money but also improves overall call center efficiency and customer satisfaction. Get in touch with Convin today to learn how to calculate ROI for your call center business.
ROI: AI Summarization vs. Manual Summarization
AI summarization significantly boosts ROI compared to manual methods by providing concise and fluent summaries that enhance productivity and decision-making.
Using advanced summarization algorithms and natural language generation techniques, AI creates extractive summaries by focusing on important sentences, ensuring a comprehensive understanding of relevant documents.
Convin’s Summary feature streamlines post-call work, offering key highlights and critical moments from each conversation.
What Went Right?: Highlight agent accomplishments and imitate effective tactics to encourage
What Went Wrong?: Acknowledge mistakes, promote development, and deal with areas for improvement in conversations.
What Could Agent Improve?: Learn how to perform better in the upcoming conversation & get a perfect call score
AI summarization saves time, increases accuracy, and improves performance, offering a substantial ROI advantage over manual summarization.
The Convin team has successfully assisted several clients in switching from manual call summarization to AI-driven automatic call summarization, saving them time and money.
It’s never too late to make the switch to automation. Get in touch today to learn how to calculate ROI for your call center business.
FAQs
1. Which AI is best for summarizing?
OpenAI's GPT-4 and Google's BERT are among the top AI models for summarizing due to their advanced natural language processing capabilities.
2. Why is abstractive summarization better than extractive summarization?
Abstractive summarization generates new sentences and captures the main ideas more coherently and succinctly. In contrast, extractive summarization simply selects and combines existing sentences, which can lead to redundancy and a lack of coherence.
3. What is AI summarization?
AI summarization uses artificial intelligence algorithms to condense a document or a set of documents into a shorter version, maintaining the key points and essential information.
4. Are AI summarizers accurate?
AI summarizers can be quite accurate, especially with recent advancements. However, their accuracy depends on the algorithm's quality and the text's complexity.
5. Which model is the best for text summarization?
Models like OpenAI's GPT-4, Google's BERT, and T5 (Text-To-Text Transfer Transformer) are currently among the best for text summarization.
6. Which is the best method for text summarization?
Abstractive summarization is generally considered better for producing coherent and concise summaries, although extractive summarization is still helpful for certain applications.
7. What are some popular AI-powered summarization tools?
Several AI-powered summarization tools and platforms are available today.
OpenAI's GPT-4: Known for its high-quality generated summaries and versatility in handling different text types.
Google's BERT: Effective for extracting key sentences and generating summaries that maintain the context of the original document.
SummarizeBot: A platform that uses AI to provide document summarization for various formats, including PDFs and web pages.
SMMRY: A tool designed to simplify the process of summarizing news articles and web content quickly and efficiently.
