AI-MC for Effective CX

CX in AI/ML Use Case Frequency 2021

According to Statista, improving customer experience represents the top artificial intelligence and machine learning use cases, for 2021 with 57%

AI and ML use case frequency 2021

AI-MC for Great Conversation Flow

AI-Mediated Conversations(AI-MC) is an automated call routing solution that uses emotion AI and voice data to match the customer to the best-suited agent to handle a specific conversation. This match is based on profile data and our superior algorithms developed from years of research and experience in natural language processing(NLP) and Behavioral Signal Processing.

What makes conversations arranged via AI-MC so special? Well, they all have in common something called conversation flow. Conversation flow happens when the conversation is comfortable, effortless, and smooth. It’s the way conversations are supposed to work.

According to research, experiencing conversational flow in social interactions is a significant determinant of customers’ experiential quality and service quality perceptions. Furthermore, the social flow state indirectly influences customer satisfaction through experiential quality and service quality perceptions.

Measuring customer experience involves focus groups, surveys, or follow-up calls, and each Behavioral Signals’ client uses different methodologies to garner customer insights. According to our data, we have monitored an impact on CSAT ranging from 4.7 – 19.2% for Sales, and 3.0 – 15.1% for DBAs and Customer Service agencies.

Use our calculator below to see the predicted CSAT impact on your own business:

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RESULTS

– 4.74 – 19.84% CSAT IN SALES

– 3.07% – 15.18% CSAT INCREASE IN DBA

– 3.04% – 15.03% CSAT INCREASE IN CUSTOMER SERVICE

– 95% IMPROVEMENT in CALL SUCCESS, ACROSS ALL AGENTS

IMPLEMENTATION

– Virtual appliance on-premise
– No external access, in compliance with the corporation’s strict security protocols
– Initial POV

TESTIMONIAL

“Apart from achieving ROI, it was surprising how most agents did better. They seemed more motivated, and all that, because they were matched to customers that fit their own personality traits”.

— Senior Call-Center Executive