Understanding AI Call Analytics
More companies are embracing artificial intelligence (AI) to help them deliver a better customer experience. Contrary to the assumption that AI eliminates jobs, companies realize that AI can free employees to do their best work by eliminating menial tasks and focusing them on what’s most important. This is especially true for quality management.
Random Spot Checking in Quality Management
Ensuring high-quality customer service can be daunting for supervisors. If you’re a supervisor you’re very aware that you don’t have the time to monitor or review every call that comes through when each of your frontline employees manages 30 or (easily) more calls per day. Alternatively, you could monitor about 4 to 8 calls per employee per month – or more if a specific employee needs improvement – but then you likely are asking yourself:
- Which calls should I monitor?
- Are the calls I choose an accurate representation of an employee’s performance?
- Which calls have a bigger impact on my business (either positively or negatively)?
AI Removes the Guesswork for Supervisors
Fortunately, advances in artificial intelligence have made it easier than ever before to know which calls deserve your attention. The specific technology that does this is called Generative AI. Generative AI is a type of artificial intelligence that can create new and original content, such as images, music, or text, on its own. It analyzes patterns in existing data and then uses those patterns to generate new content.
In the case of call monitoring, AI can transcribe a call using natural language processing (NLP), analyze the call, and then tag a call by sentiment (e.g., positive, negative, neutral) by looking at words or phrases in context. For example, artificial intelligence can look at the following two sentences and know that the word incredible is being used to convey positive or negative emotions:
- “The service I’ve received is incredible! I plan on coming back soon.”
- “It’s incredible that the company still hasn’t fixed the issue despite multiple complaints.”
How Intermedia Leverages Sentiment Analysis to Help Supervisors
Intermedia Interaction Analytics uses AI to transcribe inbound/outbound calls and voicemails. The AI engine then analyzes the transcript by evaluating words in the context of the conversation and counts the number of positive/negative words. Based on the ratio of positive and negative words it attaches a sentiment tag to each transcription.
Supervisors can search their call recordings by sentiment and read or listen to the transcript. Since every call is a mix of positive, negative, and neutral comments, Interaction Analytics provides a breakdown of the number of words in those categories.
AI Identifies Important Keywords and Phrases
AI can help supervisors focus on the right calls by making it easy to search calls by keywords or phrases. Additionally, AI can proactively flag a call if it comes across a word or phrase.
Key Phrase Use Cases
Sentiment by Topic
Supervisors can search using a keyphrase and then use sentiment analysis to identify the areas of their business that are causing frustration or dissatisfaction among customers. For example, if sentiment analysis reveals that customers frequently complain about long wait times, supervisors can re-examine their workflows or employee schedules. Similarly, if sentiment analysis reveals that customers are unhappy with a particular product feature, supervisors can work with their product team to address the issue.
Improve Business Responsiveness
Keyword alerts can help supervisors stay informed about what customers are saying in real time. By setting up alerts for specific keywords or phrases (e.g., “broken”, or “closed”), supervisors can be notified when customers mention an issue or problem. This allows supervisors to respond to customer feedback quickly and address any issues before they escalate.
Certain topics may require greater oversight from supervisors, especially if they work in a highly regulated industry. Keyword alerts can flag conversations for supervisors if a sensitive topic is being discussed. For example, a bank may want to flag calls that mention “fraudulent charge” or “breach”.
On a positive note, businesses may want to flag a conversation that could clue them in on potential revenue opportunities. They could flag conversations that use phrases like, “specials or promotions” or “discounts or coupons”. They could even flag conversations that say “missing” to see if there’s a new feature or product they could develop.
Let Artificial Intelligence Help You Today
AI-powered sentiment analysis and keyword alerts are powerful tools that can help supervisors improve the customer experience. By using these technologies to understand customer sentiment and respond to feedback quickly, supervisors can identify and address pain points, improve customer satisfaction and loyalty, and ultimately drive revenue growth.
Intermedia Interaction Analytics is an off-the-shelf AI tool designed to business improve their customer experience by making it easier to focus on the calls with the greatest biggest impact. Click here to learn more.