Diane
Chang

Making Chatbot Magic

Intuit

Diane Chang

Diane
Chang

Key Notes – Making Chatbot Magic

Intuit

Diane Chang

Bio

Diane Chang is a Distinguished Data Scientist at Intuit, where she powers the prosperity of consumers and small businesses with machine learning, behavioral analysis, and risk prediction.

Diane initially worked on TurboTax, looking at the effectiveness of our digital marketing campaigns, understanding user behavior in the product, and analyzing how customers get help when they need it. She also helped launch QuickBooks Capital, predicting outcomes for loan applicants. She is currently applying AI/ML techniques to customer care.

Diane has a PhD in Operations Research from Stanford. She previously worked for a small mathematical consulting firm, and a start-up in the online advertising space. Prior to joining Intuit, Diane was a stay-at-home mom for 6 years.

Bio

Diane Chang is a Distinguished Data Scientist at Intuit, where she powers the prosperity of consumers and small businesses with machine learning, behavioral analysis, and risk prediction.

Diane initially worked on TurboTax, looking at the effectiveness of our digital marketing campaigns, understanding user behavior in the product, and analyzing how customers get help when they need it. She also helped launch QuickBooks Capital, predicting outcomes for loan applicants. She is currently applying AI/ML techniques to customer care.

Diane has a PhD in Operations Research from Stanford. She previously worked for a small mathematical consulting firm, and a start-up in the online advertising space. Prior to joining Intuit, Diane was a stay-at-home mom for 6 years.

Abstract

The magic of a chatbot happens when a customer asks a question using the customer’s own words, and the chatbot understands those words and answers the question correctly. But how does that magic happen? Determining that two questions mean the same thing, even if completely different words are used, is part of the challenge of building a chatbot.

In this talk, I will describe how we developed a tool to support our chatbot designers’ need for training data in our customers’ own words, and how we designed a method of having our customers label data for us, while improving the customer experience at the same time.

Abstract

The magic of a chatbot happens when a customer asks a question using the customer’s own words, and the chatbot understands those words and answers the question correctly. But how does that magic happen? Determining that two questions mean the same thing, even if completely different words are used, is part of the challenge of building a chatbot.

In this talk, I will describe how we developed a tool to support our chatbot designers’ need for training data in our customers’ own words, and how we designed a method of having our customers label data for us, while improving the customer experience at the same time.

Planned Agenda

8:45 Reception
9:30 Opening words
9:45 Talk
10:15 Talk
10:45 Break
11:00 Lightning talks
12:30 Lunch & Poster session
13:30 Roundtable session & Poster session
14:30 Roundtable closure
14:45 Talk
15:15 Talk
15:45 Closing remarks

Planned Agenda

8:45 Reception
9:30 Opening words
9:45 Talk
10:15 Talk
10:45 Break
11:00 Lightning talks
12:30 Lunch & Poster session
13:30 Roundtable session & Poster session
14:30 Roundtable closure
14:45 Talk
15:15 Talk
15:45 Closing remarks