ASAPP—Why you want conversation summarization designed specifically for CX

Why you want conversation summarization designed specifically for CX

Here’s the data science behind getting the best conversation summaries (call notes) for your contact center.

The latest

ASAPP - Modern CX orgs need to think about agent efficiency in a modern way

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
Stephen Canterbury

Senior Customer Success Manager

ASAPP - Modern CX orgs need to think about agent efficiency in a modern way
ASAPP—Ryan McDonald

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
Ryan McDonald, PhD

Chief Scientist at ASAPP

ASAPP—Ryan McDonald
ASAPP—The danger of only using containment rate to measure success

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
Bobby Kovalsky

Customer Experience Strategist at ASAPP

ASAPP—The danger of only using containment rate to measure success
ASAPP—How do you know if ML-based features are really working?

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
Jonathan Rossi

Senior Customer Success Manager at ASAPP

ASAPP—How do you know if ML-based features are really working?
ASAPP—How do you find automation workflows for your contact center?

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
Michael Griffiths

Data Scientist, ASAPP

ASAPP—How do you find automation workflows for your contact center?

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
Judith Spitz, PhD

Advisor, ASAPP

ASAPP—Utilizing Pre-trained Language Model for Speech Sentiment Analysis

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
Suwon Shon, PhD

Senior Speech Scientist at ASAPP

ASAPP—Utilizing Pre-trained Language Model for Speech Sentiment Analysis
ASAPP—Multi-mode ASR: Increasing Robustness with Dynamic Future Contexts

Multi-mode ASR: Increasing Robustness with Dynamic Future Contexts

Rather than developing and maintaining multiple ASR models that work under varying levels of time constraints or conditions, new ASAPP research introduces a single multi-mode model that can dynamically adjust to various environments and scenarios. Read more

Kwangyoun Kim
Kwangyoun Kim

Senior Speech Scientist at ASAPP

ASAPP—Multi-mode ASR: Increasing Robustness with Dynamic Future Contexts
ASAPP—Why you want conversation summarization designed specifically for CX

Why you want conversation summarization designed specifically for CX

Here’s the data science behind getting the best conversation summaries (call notes) for your contact center. Read more

Will Wolf
Will Wolf

Staff Machine Learning Engineer at ASAPP

ASAPP—Why you want conversation summarization designed specifically for CX
ASAPP—Introducing CLIP: A Dataset to Improve Continuity of Patient Care with Unsupervised NLP

Introducing CLIP: A Dataset to Improve Continuity of Patient Care with Unsupervised NLP

In pursuit of ASAPP’s mission of augmenting human activity and automating the world’s workflows, we are releasing one of the largest annotated datasets for clinical NLP. Read more

James Mullenbach
James Mullenbach

Research Engineer at ASAPP

ASAPP—Introducing CLIP: A Dataset to Improve Continuity of Patient Care with Unsupervised NLP