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Zendesk introduces new ML driven Customer Sentiment and Intent Functionality

Zendesk introduces new ML driven Customer Sentiment and Intent Functionality
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Zendesk has introduced Intelligent Triage and Smart Assist, two new AI technologies that enable companies to intelligently prioritize customer support calls and gain access to priceless data on a large scale. Companies can quickly realize the value of these solutions by interpreting intent and sentiment using account-specific, information models that are tailored for specific use cases and result in speedier answers.

Lesser than a third of businesses are now utilizing artificial intelligence (AI) to boost the productivity of their customer service staff, despite industry analysts\’ predictions that it could soon affect the majority of client interactions. This is in part because the software providers are still marketing pricey AI solutions that require a lot of setup time, even though AI technology has advanced quickly over the past five years.

The development of Intelligent Triage and Smart Assist represents the next phase in Zendesk\’s goal to develop usable customer experience (CX) AI for businesses of all sizes. The technology utilizes a vertical view and draws insights from a multitude of consumer data points as well as exclusive industry knowledge. This produces models that are unique to each company and can recognize the intention, language, and sentiment of every client encounter.

To better serve clients, our innovative machine learning application provides interactions that are more knowledgeable and personalized. For instance, specific questions like \”I\’m having payment problems\” can be automatically routed to an agent who is trained to handle the payment for a quicker resolution, whereas questions crafted in all upper case letters or a sarcastic manner will imply a highly negative sentiment and be sent to the front of the queue.

“With this technology, we’re delivering AI tools that can be set up in under a minute to streamline business operations without needing dedicated developers or an expensive implementation,” chief technology officer of Zendesk, Adrian McDermott commented. “Our approach is designed to take the burden off customer experience teams through pre-trained machine learning tools that do more, faster, and with less guesswork involved. These models come ready to use instantly, and continue to learn over time and become customized to each company’s operations by continuously incorporating feedback.”

The updated abilities:

  1. Ensure that agents are focused on business-critical inquiries by immediately routing and prioritizing revenue drivers.
  2. Analyze the distribution of requests to enable improved operational planning, cross-departmental collaboration, and the identification of improvement possibilities for CX operations.
  3. Automatically instruct employees on how to effectively address a customer\’s concern at a moment, comprehend the situation, offer answers, and enhance coaching and training using insightful data.
  4. progressively improve the accuracy of the AI solutions by receiving a report on estimates and suggestions.
  5. To meet security and compliance requirements, sensitive information can be automatically detected. Confidential data can also be extracted for use in workflows, including names, phone numbers, addresses, usernames, and financial information.

The Zendesk Suite Enterprise Edition comes with all of these features pre-installed, eliminating the need for extensive training or expensive development assistance. According to a Zendesk analysis, 20 issues can be used to resolve 80% of inquiries. This information is quite useful when trying to simplify and enhance CX procedures.

“Instead of putting bots that aren’t fully trained in front of customers, causing frustration and many times lost business, Zendesk’s fundamentally different approach takes the burden and complexity off of customers, allowing companies to build powerful applications on top of a strong foundation,” said vice president of product at Zendesk, Cristina Fonseca.


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