How GenAI auto-call summarization increases ROI and improves workflows

Artificial intelligence (AI) is at the core of any customer-centric digital transformation, and strategies that do not prioritize AI and automation are quickly neglected by executive leaders. While being a relatively new type of AI, Generative AI (GenAI) has quickly proven crucial to leading organizations due to its ability to drive personalization and workflow efficiency at scale, resulting in both cost savings and revenue increases. As explained by Gartner, “By 2026, more than 80% of enterprises will have used generative artificial intelligence (GenAI) application programming interfaces (APIs) or models, and/or deployed GenAI-enabled applications in production environments, up from less than 5% in 2023”.  While there are numerous benefits of GenAI, this blog will focus on one simple yet impactful use case: auto-call summarizations. Continue reading to learn how and why GenAI auto-call summarization helps increase agent productivity, drive process efficiency, and reduce operational costs.

The importance of post-call notes and the challenge

Over 30% of customers state that repeating the same issue multiple times is the most frustrating part of the service experience. This is why post-call notes are critical — they help document historical customer information so that any agent has the insights they need to quickly pick up a conversation exactly where it was left off. While helping agents create seamless experiences, call notes or summaries help supervisors assess agent performance and the quality of each customer engagement to create personalized training and further boost satisfaction rates. 

While critical, a manual post-call documentation process is often repetitive and time-consuming. It requires note-taking throughout the call and a consolidation of these notes once over. Compared to the average handle time (AHT) of 10 minutes, it takes agents an average of 6 minutes to wrap up and summarize a call. In other words, two-thirds of an agent's time is spent on call notes and summarizations instead of helping the next customer. For a contact center striving for operational efficiency, that’s a massive amount of time and, by default, cost! To maximize productivity and organizational profits, agents often feel rushed to proceed to the next call, impacting call notes and summaries where agents insert incomplete notes or perhaps omit them altogether. The impact? Important context and engagement details are lost, resulting in incomplete historical data for future reference. This introduces the opportunity for various forms of risk, including future broken customer experiences, additional call auditing needs, and less comprehensive agent training. Even if done well, manual note-taking is a bothersome task for agents, taking up valuable time that could be better spent elsewhere.

What is GenAI call summarization and what are the benefits?

So what is Generative AI, and how can it help?

Generative AI is an advanced form of artificial intelligence with the ability to understand and create new data. Built with machine learning (ML) algorithms, it’s able to analyze speech patterns, identify keywords, and extract essential information to create new types of content — in this case, call summaries. Speech-to-text transcription is used to transform raw customer interactions into concise, actionable summaries with impressive speed and accuracy. As a result, workflows and processes can be optimized, making it easier to pick up a conversation exactly where it was left off. This completely eliminates the need for manual note-taking and post-call summaries, instead allowing agents to stay focused on delivering better customer experiences. In addition, supervisors are given reliable and consistent historical notes and insights to simplify their ability to identify where they can lend the greatest value (i.e.: agent coaching, customer outreaches, etc.) — together driving a higher-performing customer support operation. 

Automated call summaries are pushed to the CRM or service management platform, in this example, the ServiceNow platform, making it easy for agents and supervisors to get a unified view of engagement data and performance.

What's the ROI increase from GenAI summarization?

Let’s take this a step further. While it makes work easier for agents and supervisors, how much money could GenAI auto-call summarization save your organization? Is it worth the investment? In this section, we’ll take you through an example showcasing the cost reduction expected for Acme Contact Center (Acme CC) if deploying GenAI-powered auto-call summarization. 

Acme Contact Center Performance Details

Acme Contact Center (Acme CC) is running a 24/7 contact center, serving customers 365 days a year. The organization has 100 agents handling a total of 2000 calls per day. As mentioned previously, completing a post-call summary takes an average of 6 minutes. Acme CC’s agents are slightly faster and complete their post-call summaries in an average of 5 minutes. According to Indeed, the average salary for a contact center agent in the US is $17.42 per hour. In this use case, Acme CC is paying their agents $17 per hour. 

How much time does each agent spend on post-call
summaries per day?

20 calls x 5 minute summary = 100 minutes per agent per day

100 minutes / 60 minutes = 1.667 hours per agent per day

1.667 / 8 hour work day = 21% of the agent's day is spent on call summarization

What's the cost for the contact center?

1.667 hours x $17 hourly = $28.339 per agent per day

100 agents x 28.339 = $2834 per day

$2834 per day x 365 days = $1,034,410 per year

Conclusion

Acme CC’s agents spend 21% of their working day summarizing call notes, equating to over a million dollars of salary payouts — time and money that could easily be better served performing more complex tasks with the help of GenAI. 

Increase ROI and simplify workflows and processes with GenAI automated call summarization

In summary, GenAI auto-call summarization has the potential to significantly reduce time spent on manual note-taking while drastically increasing organizational ROI. If you found this topic interesting, you might also like the article “Why Do We Need AI? A Guide to Conversational AI.”

If you’re ready to put GenAI to the test for your organization, schedule a consultation with one of our experts. They’ll take you through a personalized demo designed to show you how your organization can solve your specific problems.