08.06.2020

Automatic analysis of conversations in a contact-center: 5 use cases

Five main examples of using speech analytics in the Oki-Toki service for internal and outsourced contact centers.

Automatic analysis of conversations in a contact-center: 5 use cases

One of the interesting developments for call centers lately is call analysis software. Now it allows you to automatically process up to 100% of all conversations. The two technologies at its core, Natural Language Processing (NLP) and Artificial Intelligence, open up a veritable treasure trove of operational and business information. The question is what to do with it? Let’s look at five main examples of the use of speech analytics in this article translated by us.

1. We fight operator violations and customer fraud

Typically, in a contact center, supervisors and QA only listen to 1-2% of calls. Records of the rest of the calls just “lie on the shelf” until some incident occurs, such as a complaint against the operator, a problem with a transaction, or a breach of confidentiality. Having these records in such a case will of course help to understand what went wrong, but only the damage will have already been done. Modern speech analytics software will be able to quickly analyze all call records in a row, identify service problems, and, based on the cases found, either warn operators or notify managers that the situation needs to be corrected. Some applications can even do this on the fly, right during a call. Operators, realizing that each call is monitored and checked for compliance with established standards, will try to prevent violations, which, in turn, will avoid reputational and financial losses. As for the clients, they are, of course, always right, except when they are wrong. And speech analytics can not only detect, but also predict the likelihood of fraud on the part of the client.

2. We increase the efficiency of operators and reduce turnover

Most supervisors and Quality Assurance (QA) staff can listen to only a few calls per agent per reporting period. And then, if you’re lucky. But listening is still an important tool to ensure that operators are on the right track: learning, developing, complying with regulations and quality standards. At the same time, the task of the supervisor is to find signs of improvement or deterioration in the quality of the operator’s work by monitoring and comparing with the criteria. However, if only a small part of the calls is listened to, then it is difficult to draw conclusions, since there is a high probability that a really “unsuccessful” call has been caught. Unlike a supervisor, speech analytics software will be able to “listen” to all calls. Tracking keywords and phrases, paying attention to script compliance, analyzing speech and its tonality, the analyzer will evaluate each call on a variety of parameters. As a result, the identified gaps in the skills and knowledge of operators can be corrected by correcting the errors. When working with beginners, this will help increase their learning rate and, as a result, reduce churn during the all-important initial period of work. Speech analytics will also help to “keep abreast” of the emotional state of the operators, as it analyzes the tonality and mood of both participants in the conversation. And if the operator shows signs of stress, frustration, anger, or other negative emotions, this will inevitably be detected, and the manager can be alerted that the operator needs help: participation, additional training, or maybe just advice.

3. Anticipate, understand and improve performance

It’s one thing to know and track key customer experience metrics, and quite another to understand why they are the way they are. Using speech analytics software, you will be able to accurately predict the satisfaction (or loyalty) rating that a client would give after a particular call, based on the tone and vocabulary used. This means that you can get that satisfaction rating for every interaction, instead of relying on the opinions of a small subset of customers that would be collected by a special survey. Linguistic analysis will allow you to extract from conversations the phrases and phrases used by customers that describe what they like or dislike about your products, quality of service and procedures. When enough of them accumulate, it will be possible to expand the analysis of your indicators with the collected data – this will help to understand why customers give such ratings and what they would like you to improve.

4. We study customers and competitors

If you listen to only a portion of the available conversation recordings, as is usually the case for training and control purposes, this means that most of the useful information obtained during these interactions is not used by you. In conversations with operators, customers often provide a lot of invaluable details in passing, such as how you use your products, your price levels, availability and after-sales service, and most importantly, how you compare to your direct competitors. These conversations are a river full of golden sand, which usually needs to be “washed” through thousands of surveys, while through the efforts of your operators it already lies in your pantry, among unheard conversations. Your marketing and sales teams need to take a close look at what they can glean from conversations with customers and build on that knowledge in all their decisions, from product development to marketing, pricing, and channel selection.

5. Make more sales

Choosing only on the skill level does not guarantee happy customers. First of all, this is due to the fact that he will have to wait too long for a consultation. Dynamic routing takes into account the skills of specialists, and also estimates the predicted waiting time. This allows you to provide better customer advice within a given level of service. For example, if the approximate wait time for a specialist with the desired skill is too long, “reserve” operators can be added to the queue, who will serve the client faster, albeit possibly at a less competent level. Old wisdom says that any interaction with a client or potential client is an opportunity to either develop a relationship, or increase loyalty, or close a deal. With sales, as with anything else, relevance is important, otherwise it is easy to spoil a relationship that is still fragile. How do you know when it’s time to propose? To do this, you need to clearly understand why a person makes a decision to buy just then, and not later, or in this way, and not in another. You can try to guess the motives of the client or rely on intuition, but it is best to listen to what the clients themselves have to say about how they made their decisions. Speech analysis will allow you to do this by identifying what feelings and in what situations lead to a particular behavior, and what happens as a result. After that, it will be possible to redesign sales, eliminating behavior that does not lead to new sales and retention of existing customers, and rewarding those that produce the desired results. You can rewrite your scripts and business processes so that the best moments of communication are used to increase the final check (up- and cross-selling). And in outbound follow-up campaigns, it will be possible to focus on identified (or predicted) customers with negative experiences. There are many more use cases for speech analytics than you can probably imagine. And even if you don’t currently have the opportunity to buy software with such functionality, you can use speech analytics in your business by giving the recordings of conversations for processing to the provider of this software “as a service”. And this is great news. Unearthing the treasure trove of state of affairs hidden in your audio files so far can be amazingly transformative. We, at Oki-Toki , are also working in this direction, and we expect to soon provide you with services for solving the tasks of monitoring call center operations, automating sales and after-sales service using speech analytics.

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