Pega seizes to enrich Pega Customer Service offers real-time natural language processing (NLP) functionalities, more specifically based on Speech To Text, adapted to the needs of customer services. The solution must help agents in real time to determine the best actions to take to solve the problems of their recipients. The startup is developing Whipnote, a tool with automatic text transcription, key word extraction, interlocutor detection, and emotion (via volume and tone of voice analysis). The start-up founded in 2016, which has raised a total of $1.7 million, intends to offer its solution at a minimal cost (1 cent of dollars per minute).

This same technology should allow chatbots to better understand what a customer is saying and make self-service products more efficient. is the second company Pegasystems has acquired in two years to enhance Pega Customer Service. In 2019, the publisher got its hands on In The Chat in order to add support for messaging channels.

“Qurious gives them NLP capabilities that they [les responsables de PegaSystems] didn’t have,” said Predrag Jakovljevic, senior analyst at TEC.

The new features resulting from this operation should integrate with Pega Customer Service shortly before PegaWorld, the company’s user event planned for May, warns Don Schuerman, chief technical officer of Pegasystems and vice president of strategy and product marketing. .

In itself, has thought of its Whipnote product as such: it integrates by API with all systems capable of supporting Rest APIs. It could also become a brick available from Pega’s BPM platform.

“Pegasystems acquired rather than partnering with another company or building its own solution. brings us its expertise in voice recognition based on AI”, assures Don Schuerman. fills some of the technology gaps in the Pega Customer Service suite, including self-service and phone channels, with its agent support tools.

The health crisis is transforming contact centers

Prior to the health crisis, Pegasystems planned to bolster its Pega Customer Service agent support features and add emotion detection – also known as sentiment analysis – to learn the state of mind of a customer. a customer. This is what’s technology brings.

When social distancing rules forced customer service workers to work remotely, it became even more important, Schuerman says, because contact centers lacked experienced agents who could properly mentor newcomers. For many sectors, the volume of contacts has also increased, which has required tools that promote efficiency.

Technologies that contact center managers thought they would be years away from suddenly became requirements that needed to be implemented quickly.

“Sentiment analysis is important for detecting escalation, and for knowing when exactly to transfer an irate caller to a flesh-and-blood operator. »

Pedrag JakovljevicPrincipal Analyst, TEC

“The volume of requests that an agent has to deal with has increased a lot, and I think that customers anticipate the growth of this phenomenon over several years”, considers Don Schuerman. He adds that long after the pandemic is over, call centers will continue to rely on remote workers.

“The more a robot can relieve humans, the better,” says Pedrag Jakovljevic. “But there comes a time when we all want to talk to a human being. Sentiment analysis is important for detecting escalation, and for knowing when exactly to transfer a furious caller to a flesh-and-blood operator.”

Don Schuerman also says that AI-only customer service is still far from a reality. But sentiment analysis and agent support tools can make handling customer issues more efficient for humans — who deal with the tricky questions that chatbots can’t.

Voice analysis is unanimous among publishers

These two major trends, Pega is not the only one to follow them. In reality, the publisher finds itself in competition with a famous CRM player, Salesforce. The group led by Marc Benioff offers Service Cloud Voice, a solution that also allows real-time analysis of the words of customers in contact with agents. Presented at Dreamforce 2019, Service Cloud Voice has been available since July 2020. And while Salesforce touts the merits of Einstein’s artificial intelligence, it largely relies on its partner AWS and its Amazon Connect service.

The cloud giant integrates several NLP services, including Contact Lens for Amazon Connect, also designed to detect problems during calls through voice analysis. Google offers the Google Contact Center AI offering with similar capabilities. Other players like Avaya or Voicebase (partner of Tableau, before the acquisition by Salesforce, and of ToughSpot) are following the same path. But this is only one of the uses of voice analysis in the call center. Pindrop is starting to make a name for itself in voice recognition and sound signal processing to detect potential identity theft, for example.

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