The latest
Learning to recommend what agents should do
Are your ML models learning the right things? Here’s what we discovered when we took a closer look at what agents do vs. what they should do in one situation. Read more

Chris Fox
Staff Machine Learning Engineer
Why your care strategy must consider issue complexity and urgency
Does the customer need a live agent or is automation the right way to handle it? Many companies think it’s a binary question. The best answer is more nuanced. Read more

Rachel Knaster
Chief Product Officer, ASAPP
Modern CX orgs need to think about agent efficiency in a modern way
Are you measuring what matters in your contact center? AHT – or average handle time – can’t really measure agent efficiency in an asynchronous, digital world. Here’s thought on more modern metrics. Read more

Stephen Canterbury
Senior Customer Success Manager
How task-oriented dialog helps empower agents
Task-oriented dialog elevates AI for the contact center, providing a much richer view of what’s happening so agents can more efficiently serve customers’ needs. Watch now

Ryan McDonald, PhD
Chief Scientist at ASAPP
The danger of only using containment rate to measure success
Containment rate is not a good measure of success, used alone. A good metric will also consider if the customer’s need was met. Here’s how we measure. Read more

Bobby Kovalsky
Customer Experience Strategist at ASAPP
How do you know if ML-based features are really working?
How do you measure efficiency and effectiveness in your contact center—for individual agents and for the team as a whole? Gain insight from our CX pros working with large consumer brands. Read more

Jonathan Rossi
Senior Customer Success Manager at ASAPP
How do you find automation workflows for your contact center?
How do you identify the right workflows to automate in the contact center? And quickly implement them? ASAPP was awarded a patent for the technology to meet this challenge. Read more

Michael Griffiths
Data Scientist, ASAPP
Balancing customer expectations with efficiency
Are you meeting your customers where they are? Don’t get left behind as customer expectations evolve. Watch now

Judith Spitz, PhD
Advisor, ASAPP
Utilizing Pre-trained Language Model for Speech Sentiment Analysis
On the path to real-time speech sentiment analysis, new ASAPP research achieves training efficiency gains with transfer learning between spoken and written language domains. Read more

Suwon Shon, PhD
Senior Speech Scientist at ASAPP
Multi-mode ASR: Increasing Robustness with Dynamic Future Contexts
Rather than maintaining multiple ASR models that work under varying time constraints or conditions, new ASAPP research introduces a single multi-mode model that can dynamically adjust to different scenarios. Read more

Kwangyoun Kim
Senior Speech Scientist at ASAPP