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Kieran Snyder

VP of Product, AI, Microsoft · 1 appearance on the record.

computed by AI from the episodes · how this works → · full disclaimer →

founderexecutiveacademicauthor@KieranSnyder ↗LinkedIn ↗nerdprocessor.com ↗

After product leadership stints at Microsoft and Amazon, Snyder co-founded Textio in 2014, serving as CEO for nearly a decade while developing AI-driven writing and bias-detection tools. Holding a PhD in linguistics, she conducts empirical research on workplace gender bias and publishes data-driven analyses through her newsletter nerd processor.

14statements → 10claims → 2claims resolved → 4.07/5average certainty → 2.29/5average debate potential → 4.3/5argument clarity · the sources →

2 supported 0 partly supported 0 contradicted 1 not yet assessed 7 not checkable as stated how the 10 claims stand · each chip opens the sources

10 assertions · 4 insights · every statement was checked. The predictions and assertions are the 10 claims: statements the public record can support or contradict. 2 are resolved, 1 is not yet assessed, and 7 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Kieran argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable supported claim

Assertion Supported
Snyder: 'Abrasive' appeared in 17 female performance reviews, zero male reviews
“The word abrasive, which has been talked about since then ended up, you know, being used in 17 out of a couple hundred women's reviews and zero times in, in men's reviews, right?”
Kieran Snyder Jan 2, 2019 ▶ 27:51 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data

Argument clarity: do they answer the question? how? →

4.3 / 5 directness 4.4 · coherence 4.9 · precision 4.4 · compression 3.9

redirected or did not address 1 of 8 assessed questions (13%). Watch them ▸

This is a score against a rubric. It is not a rank. Every host question → answer exchange is scored with names hidden on directness, coherence, precision and compression, 1–5 each, on meaning alone: disfluencies are ignored, and only raw unedited episodes count. This is the score that measures thought. Every scored exchange, scores shown → · The rubric and its checks →

How they sound: speaking style how? →

238 words/min while actually speaking · 23.2 um and uh per 1k words · 9 false starts per 1k · 26.2% of pauses land inside a clause

Measured by listening to the audio itself: 4,576 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →

Everything Kieran Snyder said on the a16z Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Insight
Snyder: Kickstarter success depends on text structure rather than idea quality
“The quality of your idea doesn't matter just looking at the content aspects we could predict.”
Kieran Snyder Jan 2, 2019 ▶ 4:12 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Assertion Supported
Snyder: 'Abrasive' appeared in 17 female performance reviews, zero male reviews
“The word abrasive, which has been talked about since then ended up, you know, being used in 17 out of a couple hundred women's reviews and zero times in, in men's reviews, right?”
Kieran Snyder Jan 2, 2019 ▶ 27:51 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Assertion Not checkable as stated
Snyder: Textio predicted Kickstarter fundraising success with over 90% accuracy
“We got over 90% predictive on minute zero of a project as to whether it was going to hit its fundraising goal based solely on things like how long is the text and what kind of fonts are you using and how many headings do you have.”
Kieran Snyder Jan 2, 2019 ▶ 2:59 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Assertion Not publicly verifiable
Snyder: "Fast-paced environment" in job listings statistically reduces female applicants
“So the difference between fast-paced environment and rapidly moving environment, it's almost head-scratchingly tiny, but statistically, one of them draws many fewer women to apply.”
Kieran Snyder Jan 2, 2019 ▶ 25:44 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Insight
Snyder: Kickstarter campaigns succeed when formatted like a "ransom note"
“You want it to look like a ransom note, so you want to mix and match types. You want lots and lots of headings.”
Kieran Snyder Jan 2, 2019 ▶ 3:48 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Insight
Snyder: Longer project descriptions perform better on Kickstarter
“Longer is better where Kickstarter is is concerned kind of counterintuitive.”
Kieran Snyder Jan 2, 2019 ▶ 3:29 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Assertion Not checkable as stated
Snyder: Mentioning off-street parking harms higher-priced home listings
“So we saw when we were prototyping out the real estate stuff that if you say off street parking that really moves the needle for low income homes, but for high income homes in terms of the number of people who go to your open house and then the eventual sale p…”
Kieran Snyder Jan 2, 2019 ▶ 7:15 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Assertion Not checkable as stated
Snyder: Textio identified 25,000 job description phrases affecting recruiting outcomes
“In jobs, it matters hugely. You know, we, we've identified at this point over 25,000 unique phrases that move the needle on how many people will apply for your job, what demographics, how qualified they are.”
Kieran Snyder Jan 2, 2019 ▶ 7:43 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Assertion Not checkable as stated
Snyder: "Big data" in job posts lost its positive impact by 2015
“So my favorite example of this is the phrase big data. So a year and a half ago, if you use the phrase big data in a tech job listing, it was positive. You know, it was seen as compelling and cutting edge. In June of 2015, it's not negative, but it's totally n…”
Kieran Snyder Jan 2, 2019 ▶ 8:58 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Assertion Not checkable as stated
Snyder: The word "synergy" torpedoes job listing candidate response rates
“The biggest, you know, the, one of the very common, we call it a gateway term that kind of torpedoes your listing is the word synergy. But it's a gateway term because when people include synergy, they're also significantly more likely to include, you know, val…”
Kieran Snyder Jan 2, 2019 ▶ 11:04 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Assertion Not checkable as stated
Snyder: Text is the single largest output produced by any business
“In businesses, whatever your business is, text is actually the thing you produce the most of.”
Kieran Snyder Jan 2, 2019 ▶ 18:36 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Assertion Supported
Snyder: Tech Resumes Show Systematic Gender Differences in Formatting
“Women's resumes tended to tell a story. They were written in prose. They didn't use bullets nearly as much. They included executive summaries. They included detailed statements of their Personal interests that were twice as long as what men tended to include. …”
Kieran Snyder Jan 2, 2019 ▶ 28:55 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Insight
Snyder: Overused language optimization patterns lose effectiveness, forcing marketing innovation
“If everybody tries to glom onto the same patterns, they're no longer effective. Someone is gonna figure out, as with any marketer, someone is gonna figure out how to do it better, and they're gonna introduce the next Pattern for success.”
Kieran Snyder Jan 2, 2019 ▶ 31:27 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data
Assertion Not checkable as stated
Snyder: 'People analytics' has replaced 'workforce analytics' in effective job postings
“Turns out workforce analytics is no longer a good phrase to use. You want to use people analytics.”
Kieran Snyder Jan 2, 2019 ▶ 13:11 a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data

Appearances (1)

EpisodeDateSpeaking time
a16z Podcast | It's Not What You Say, It's How You Say It -- When Language Meets Big Data Jan 2, 2019 22m
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