Understand Customer Intent with Best of Breed Conversational AI

Scale conversational AI in your contact center and across your customer touchpoints using conversational AI middleware
Jacada’s product development and go-to-market strategy is focused on automating customer service operations. It is a pioneer in delivering unified RPA and conversational AI capabilities and has a differentiated value proposition for organizations looking to automate and optimize processes across the customer service value chain.
Amardeep Modi
Practice Director

Why Conversational AI Matters Now?

The #1 reason why contact center leaders purchase speech analytics, is to gain conversation intelligence that helps identify broken processes.Collecting customer insights is a close #2 reason.

It shouldn’t be surprising that Gartner has used speech analytics to recommend a blueprint for contact center automation and effortless customer experience in this research report.

Gartner Research:
Call Center Automation Strategy Based on
Conversation Intelligence

Conversational AI Meets
Real-time Assistance

While post-call analytics has been very helpful in reducing churn and improving agent performance for a long-time, much of the excitement and promise of conversational AI is in using the technology in real-time to automate conversations with customers and employees, as well as to assist employees in real-time even as they engage in complex interactions with customers.

5 Ways Real-time Assistance is Eating the Contact Center

Challenges With Conversational AI

Choosing which conversational AI to use can be a daunting task. Further harnessing the power of conversational AI across your customer operation for a variety of use cases can be even more challenging, and many times, require significant investment in money, time, and effort without direct control over business outcomes. So, here are a couple of insightful articles on the topic.

Top 3 Challenges with Scaling Conversational AI in the Contact Center

6 Ways to Maximize the Impact of Conversational AI

Conversational AI is one of the most promising developments that have influenced the customer experience space over the last few years. Coupled with the right automation technology, you can harness conversational AI to improve customer experience and business outcomes.
Besides availing best of breed conversational AI, here are the top 6 ways in which conversational middleware complements conversational AI and helps organizations minimize time to value and the total cost of ownership.

#1 Make Real-time Speech Analytics Actionable

59.9% of contact centers are already using or planning to use speech analytics soon. If existing speech analytics vendors don’t step up to deliver insights in real-time, there are several start-ups and big tech platforms that are vying to deliver conversation intelligence in real-time.

Jacada integrates with real-time speech analytics services to personalize the agent experience and the customer experience in real-time using intent flows designed in our no-code designer.

Empower Your Business with Google Contact Center AI

Webinar on the topic of scaling conversational AI in the contact center, featuring Google Dialogflow and Google Contact Center AI

#2 Speech Transcription + RPA Based Auto Notes

With advances in the responsiveness and accuracy levels of various speech to text transcription services, there is growing excitement in the contact center to automate after call work, particularly in terms of generating an automated summary of the conversation and accelerating the creation of notes with the business case of saving around 60 seconds per call.
Besides leveraging real-time speech transcription services, Jacada’s RPA bots track agent desktop events and contribute to the automated notes and call summaries as well. Clients, therefore, have a variety of options (speech transcription, RPA based notes generation or a combination) to fulfill their automation needs.

#3 Understand Intent With Conversational AI & More

Clients need to select the best conversational AI in the context of the languages and modalities (speech, messaging) that matter.

Jacada’s best of breed approach to conversational AI, and the inbuilt connectors to various conversational AI services come in handy to scale the benefits of intent recognition across customer-facing and agent-facing use cases.

While it’s great to understand customer intent based on their own words, there are many scenarios in which their interaction with other systems and interfaces can also tell a great story about their intent. Great conversational AI middleware combines conversation intelligence with insights from a variety of other sources to zero in on customer intent and personalize the agent experience and the customer experience.

Crack the Code on Contact Center Automation:
Top 5 Agent Assist Tools for 2021

Webinar featuring a demo of Jacada Agent Assist

#4 Test the Quality and Reliability of Entity Extraction

Great conversational AI services provide exceptional capabilities to capture the data elements a user might provide in a natural language utterance. When these data elements are of the same type and can be easily misunderstood by a machine, more sophisticated systems provide various mechanisms to fall back and gather the required context without tiring out the user. This might be a reasonable approach when a virtual agent, engaged in a travel planning conversation, needs to understand the time of departure and the time of arrival without getting tripped up.
However, when conversational AI is used to extract data elements from a conversation between the customer and the agent, there is hardly any room for error or fallback. The human agent is already listening to the customer speak. The only value of entity extraction is in automating the work that otherwise may need to be done manually by the agent. If the AI isn’t capable of reliably capturing the spoken data elements the opportunity to automate tasks by virtue of conversational AI is simply lost.

While Jacada’s automation platform and its intent flows stand by to personalize the agent experience and the customer experience using the extracted entities, we recommend that clients first test the ability to reliably extract entities before proceeding headlong into a business case and a project based on this capability.

#5 Personalize Based on Your Customer's Emotions

59.8% of contact centers are either already measuring or are planning to measure customer emotion during live interactions. There’s certainly excitement in the contact center to personalize the agent experience with real-time coaching based on the real-time insights from the customer’s tone and spoken words.
Jacada’s intent flows pick up on the emotions and sentiments detected during the interaction and use these signals to drive personalized next best actions and automations for the agent. The result is that Jacada’s agent assist serves as a player coach instead of just a coach, as it can automate actions for the agent and enable the agent to focus on the customer interaction.

#6 Find Hidden Customer Needs With Dialog Design

Dialog management is a great help while discovering what the user really needs. In many scenarios, when customers reach out for help, they tend to narrate their stories rather than articulating what exactly they need, as if they were talking to a virtual agent. This often trips up virtual agents that are solely relying on natural language understanding to discover customer intent.
Dialog design provides the constructs to advance the conversation one step at a time to zero in on the customer intent that the virtual agent or the human agent needs to execute on.

With Jacada’s intent flows, a dialog designer can construct choices at every step of the conversation to either go deeper down a certain path or offer tangents that enable sidebar conversations that make intent discovery effortless and deliver more personalized experiences.

Continue to the Next Page

Let AI Make the Difference by Connecting AI with Contact Center Automation