New: Speech To Text API improves customer service
According to research by Google, 61% of people searching for products on their mobile devices want to be able to call the companies that show up in their search results. Overall, 52% of customer interaction takes place by phone call. Even in a world where customers prefer self-service and millennials are turning to text-based communication, the telephone remains a vital customer service channel.
However, for data-driven companies, the potential of unstructured data such as voice calls can't always be fully explored for the following reasons:
- Voice calls take place using speech, rather than the text (on which big data and machine learning algorithms already work well).
- The customer service agent is focused on providing great service and, rightly, that shifts mental focus away from taking accurate notes.
- Generally, humans have to listen to call recordings in real-time and so they can be a time-consuming.
Contexta360's Speech To Text API new in store
Now there’s an API in the KPN API Store that solves that problem: the Speech To Text API by Contexta360.
Contexta360 uses machine learning to uncover insights in voice calls and turn them into a rich source of knowledge. With the Speech To Text API, you can apply big data analysis to all of your customer interactions. Aside from telephone calls, you can also feed it with e-mail, social media and any other text-based customer service history.
With the Speech To Text API, you can rapidly categorize and label customer service calls and other interactions. From there, you can detect trends, track the topics that are most important to customers and your business, and analyse customer satisfaction trends over time. You can build the API directly into your existing customer management platform or into your own customer tools.
Turning speech into text
Throughout the history of computing, humans have had to learn to think and communicate like computers. As a developer, you know that to instruct a computer, you must use a programming language. And if you want to work with a computer, you must learn how to use the relevant applications. With tools like Contexta's API, we are able to make computers understand humans by turning voice calls into useful data. Contexta's API takes the audio from a customer service call and transcribes it at around twice the speed of the call itself. The resulting transcript is an accurate textual representation of the call that even identifies each participant.
Turning voice calls into useful data is a 3-step process:
- Transcribe the call from speech to text.
- Analyse that text.
- Use the outcome to improve your service.
Contexta's Speech To Text API works with German, Dutch and English.
Picking up on sentiment
The really hard part is to get past all the ambiguity, inferred meaning and cultural context that we humans throw into conversations without realising. This is where Natural Language Understanding comes in. The API takes the transcript and analyses it to understand the content of the conversation. With that understanding, it can categorise the call, track how the customer’s sentiment changes throughout and look out for industry-specific keywords.
How Speech To Text can help you
Here's an example. Let's say you run a small contact center. Each day, hundreds of people call your contact center with sales questions and support queries. To help train and motivate your team of agents, you want to measure 3 things:
- Time to resolution.
- Customer satisfaction.
- Cross-sell opportunities.
You could do this manually. A team lead could spend a few hours each week listening to call recordings and checking, by hand, if the customer was left satisfied and that the agent did their best to cross-sell other products. With hundreds of calls per day, the team lead could only ever dip into a few calls per agent. And it can be boring work. Not only could the team lead’s morale suffer but they might miss important details as their attention wanes.
With the Speech To Text API, you could check every single call and without taking up staff time. The API looks out for key phrases and words in calls, such as those that indicate a cross-sell or a successful resolution to the call. It can even generate transcripts so that human managers can quickly and easily review call content without having to listen to them in real-time.
Ready to know more?
We made a trailer for you in which Pranav, one of our developers, tells you more about the API.