Outbound Calls Made Intelligent with Voice Intelligence

Discover how voice intelligence can help handle different types of outbound calls

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Outbound Calls Made Intelligent with Voice Intelligence
Speech AnalyticsInsights

Published: June 13, 2022

Sandra Radlovački

Sandra Radlovački

Outbound calls are customer calls initiated by agents with many different goals, such as sales, lead generation, or simply marketing.

Whether a company is following up on a particular product or service with the customer or looking to close a sale, outbound calls tend to get repetitive as agents often read from a script.

Outbound calls can also be automated using a pre-recorded voice to save time and costs of hiring more agents.

Yet, it’s important to track and analyze both agent and automated conversations to better understand the customer success rate.

With agent conversations, companies need to be able to see if the agent followed the protocol, for example, whether they were polite enough or empathetic enough, used the right words and mentioned the right products.

Meanwhile, automated outbound calls can reach an answering machine on the other end and fail to detect that there is no real human being answering the call.

This is where voice intelligence comes into play.

The Benefits of Voice Intelligence

Firstly, voice intelligence helps with cutting down costs in the contact center. Using specific algorithms, voice intelligence can help create automated outbound calls that are able to immediately ‘recognise’ an answering machine and disconnect the call.

Rajath D.M., API Solutions Manager, Symbl.ai, said: “Not all humans’ greetings on answering machines follow the same patterns and voice signals. Usually, answering machines have specific kindness or begin with a message that says the person called is unavailable. In most cases, there is a phrase that says you can leave a message after the beep. While tones and signals are the same, the context of the message remains the same.”

“Augmenting existing answering machine detection with context understanding of the conversation content can drastically increase the accuracy of detection thus enabling an action or routing to be done in seconds rather than minutes – saving massive dollars on these outbound calls.”

Symbl.ai has developed this intelligence capability that can help track contextually similar phrases. Common phrases like ‘leave a message’ or ‘drop a message’ will be detected with their Tracker API, making it easier to identify humans, machines and other intents on the call for AI-enabled call routing.

In the scenario of outbound calls made by a human which are usually scripted or unscripted, voice intelligence can help businesses understand the customer better. It can also show script effectiveness, listening skills, and empathy that are critical to the brand. Rajath says:

“The moment in which a customer mentions a competitor offering a product they are looking for at a better price, Symbl’s Tracker API can be used to customize the action recommendation to the agent in real-time: whether it is recommending an answer, adding their manager or giving them a discount. The programmability of the platform enables customization that can differentiate business logic and different your brand experience. “

Changing the Future of Conversations

Looking to the future, Symbl.ai is continuously innovating the voice intelligence space. Apart from contextual analytics, sentiments and various speaker metrics, Symbl.ai has recently introduced an aggregation feature which lets users aggregate data like hot topics, and questions at an agent level and at a business unit level.

Rajath explains: “In order to do this, users need group economization IDs, like different conversations from a specific business group for a particular agent or issue.

“When you aggregate all of this information, they can identify things like the topics that came up in a particular business unit, or the topics with bad sentiment that came up with a particular issue.”

The company has also worked on expanding their AI platform to add other dimensions of context like tone, and voice signals along with the content of the conversation, making their understanding and intelligence superior and highly accurate.

When asked about the long-term goals, Rajath says: “We believe that our Symbl has the potential to be the dominant cloud platform for conversations that enables businesses to monitor, analyze, act and learn from conversations – truly unlocking the potential of this new stream of data that is still under-utilized. The key to adoption lies in the ease of customization, constant learning and scalable price point – all of which puts Symbl in a unique spot.”

“Outbound calling has so much potential to be disrupted with machine learning and we are excited to have customers and partners that are both saving costs and growing revenues with their specific implementations across verticals”

Find out how Symbl.ai can help you make the most out of your conversations here.

 

 

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