why aren't all 15 resolved? a statement only gets an assessment when the public
record can support or contradict it. opinions and what-ifs never can, and 0 checkable
ones are still open, waiting for their date. predictions held up or didn't;
assertions are supported or contradicted. on every card:
▮▮▮▮▮ certainty ·
▮▮▮▮▮ debate potential. speakers are clickable
Insight
Essas: Restaurants often perceive themselves differently than how diners view them
“The way restaurants talk about themselves is not always how diners view them. And many times it's actually it's actually interesting that restaurants not even thinking about certain things, that diners who go there express themselves kind of on social media an…”
Assertion Supported
Joseph Essas: OpenTable only allows reviews from verified diners
“Every review that a person leaves, they only allow to leave if they, we know for a fact that they actually dined in that restaurant.”
Assertion Not checkable as stated
Essas: OpenTable data shows diners have grown far more specific and demanding
“People used to be very generic. People used to say in our reviews, and that's the beauty of the fact that we have 15 years worth of them, people used to say, I just want a booth sorry, people used to say, I just want to be a romantic setting, or I want to have…”
Insight
Essas: Power user dining patterns cannot easily predict general consumer choices
“From what we looked at so far, it's pretty hard to make that, that extrapolation from that power diner population into the general population, which much more picky about when they would go and why would they go to certain places.”
Assertion Supported
OpenTable operates in about 32,000 restaurants as of June 2015
“It's about 32,000 restaurants, so we provide software that sits inside those restaurants, and allows restaurants to manage their inventory.”
Assertion Supported
OpenTable seats about 16 million diners per month as of June 2015
“We sit about sixteen million diners a month”
Assertion Not checkable as stated
Essas: OpenTable has 30 million reviews in its database
“We have thirty million reviews in, in our, kind of, in our database.”
Assertion Not checkable as stated
Diners in SF, NYC, and Chicago prioritize different restaurant scenery
“In San Francisco, people talk a lot about the view of the Bay, the view of the bridge. In New York, people talk about, ah, a view of the river, or view of the Hudson, ah, while in Chicago, ah, people talk about the city and the lake.”
Disclosure
OpenTable uses review topic modeling to advise restaurants on marketing strategies
“We also can teach our restaurants how to market on, on themselves on using words and descriptions that they wouldn't think about otherwise.”
Assertion Not checkable as stated
Essas: Valentine's Day generates OpenTable's most polarized restaurant reviews
“So, our, literally, it's our most polarizing day on reviews basis, based on one-star review versus five-star reviews.”
Assertion Not checkable as stated
Essas: OpenTable review data shows a major cauliflower trend in NYC
“For example, New York City, just looked, looked it up before I came to speak here there's a huge trend in cauliflower.”
Assertion Not checkable as stated
Essas: OpenTable's model learned 'crispy' and 'moist' carry positive sentiment
“The model started to get smarter, so the model started to understand things like to die for, crispy, and moist are all positive words, which wouldn't, you wouldn't necessarily understand otherwise.”
Assertion Supported
OpenTable CTO Says Majority of Revenue Comes From Per-Diner Fees
“And so, so that's majority of our revenue comes from the dollar per person, which is, that's how we like it because that is per performance.”
Disclosure
Essas: OpenTable routes event streams through Kafka, Cassandra, and Spark
“All of our events flowing through Kafka, they've been populated into Cassandra, which then we run Spark instances that kind of model on top of the data.”
Assertion Not checkable as stated
Essas: OpenTable used non-negative matrix factorization to find review topics
“Non-negative matrix factorization allowed us to break things into just make them much simpler and find topics easier.”