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Analyzing data from Silicon Valley ventures and founders prosecuted for fraud

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Re: Analyzing data from Silicon Valley ventures and founders prosecuted for fraud

#11
post #3

A lot of 'numbers' startups cite are basically fake I think. Like if someone says we have this many users as a statement to TechCrunch you have no idea what they are actually calculating But there is a clear line that gets crossed if you start actually making a database of millions of synthetic users and that's what happened with 'Frank' that sold to JP Morgan and eventually the founder was prosecuted

> Like if someone says we have this many users as a statement you have no idea what they are actually calculating I think that's BS. User metrics are usually very explicitly defined (e.g. monthly or daily active users have always been clearly defined wherever I've worked, even if just for the sole reason that people collecting those numbers need to know what to count). User quality is definitely a gray area and estim…

Right I'm not saying that Zuck's staff doesn't know how to calculate MAU or ARR. I'm saying I'm not sure we can trust the 'median' (median on a scale of super-scrupulous to outright-dishonest) CEO is not counting things like inactive cohorts, newsletter subscribers, website hits when counting 'users'... or being very optimistic about whether a customer will renew when calculating 'recurring revenue'

I may be wrong! But I am definitely giving such claims the side-eye

Re: Analyzing data from Silicon Valley ventures and founders prosecuted for fraud

#12
post #3

A lot of 'numbers' startups cite are basically fake I think. Like if someone says we have this many users as a statement to TechCrunch you have no idea what they are actually calculating But there is a clear line that gets crossed if you start actually making a database of millions of synthetic users and that's what happened with 'Frank' that sold to JP Morgan and eventually the founder was prosecuted

> Like if someone says we have this many users as a statement you have no idea what they are actually calculating I think that's BS. User metrics are usually very explicitly defined (e.g. monthly or daily active users have always been clearly defined wherever I've worked, even if just for the sole reason that people collecting those numbers need to know what to count). User quality is definitely a gray area and estim…

if someone says they have a billion users because they are connected to the doubleclick exchange... they aren't lying, they might be deceptive or simply foolish.

As part of due diligence, the buyer/investor should ask how these numbers are calculated and make their own judgement. Unfortunately I believe startups select for those who dance the border of deceptive and foolish.

Re: Analyzing data from Silicon Valley ventures and founders prosecuted for fraud

#13
post #3

A lot of 'numbers' startups cite are basically fake I think. Like if someone says we have this many users as a statement to TechCrunch you have no idea what they are actually calculating But there is a clear line that gets crossed if you start actually making a database of millions of synthetic users and that's what happened with 'Frank' that sold to JP Morgan and eventually the founder was prosecuted

> Like if someone says we have this many users as a statement you have no idea what they are actually calculating I think that's BS. User metrics are usually very explicitly defined (e.g. monthly or daily active users have always been clearly defined wherever I've worked, even if just for the sole reason that people collecting those numbers need to know what to count). User quality is definitely a gray area and estim…

This is an area where deception is possible. For example, if the metric is background API calls, you can fake that too. What matters is how you define 'active users.' In fact, this is a common technique used in well known scam apps in Korea, often called 'vanity metrics.' Generating abusive users and background traffic that create no real business value, then packaging it as user growth. There are even people who specialize in this.

Re: Analyzing data from Silicon Valley ventures and founders prosecuted for fraud

#14
post #10

I'm surprised there was no mention of Elizabeth Holmes. Whenever there is mention of criminal deception of any sort, she's like the poster child for it in my eyes. And I remember her accomplice who instead of admitting he was on the wrong side, kept blaming the journalist who tried to uncover the fraud, instead. He said (something along the lines of) "He (the journalist) kept coming at her.." as if she would've been…

Seems they use the nickname 'ScaleX' to discuss Theranos

Re: Analyzing data from Silicon Valley ventures and founders prosecuted for fraud

#15
post #8
post #3

A lot of 'numbers' startups cite are basically fake I think. Like if someone says we have this many users as a statement to TechCrunch you have no idea what they are actually calculating But there is a clear line that gets crossed if you start actually making a database of millions of synthetic users and that's what happened with 'Frank' that sold to JP Morgan and eventually the founder was prosecuted

In the current environment I doubt Elizabeth Holmes would go to prison. She would be saying the machine would work by early next year. After all a drop of blood is just a smaller quantity. Making the machine work is just an engineering problem. If she were really clever she would recruit a social media army of all the weird conspiracy theorists who think "medbeds" are real. Of course now we know that a drop of capill…

The big difference was that she was in the medical field. She used her machines that worked unreliability on patients and caused actual damage to humans. Then she noticed that this could be a problem and switched to blood analyzer from Siemens. But she still continued to say that the machines do work. She lied to investors. I still feel her case is a lot different to what musk is doing. I think you can definitely say “coming next year” and actually needing 5 years. You cannot blatantly lie and harm people along the way

Re: Analyzing data from Silicon Valley ventures and founders prosecuted for fraud

#16
post #8

Earlier quoted context omitted.

In the current environment I doubt Elizabeth Holmes would go to prison. She would be saying the machine would work by early next year. After all a drop of blood is just a smaller quantity. Making the machine work is just an engineering problem. If she were really clever she would recruit a social media army of all the weird conspiracy theorists who think "medbeds" are real. Of course now we know that a drop of capill…

The big difference was that she was in the medical field. She used her machines that worked unreliability on patients and caused actual damage to humans. Then she noticed that this could be a problem and switched to blood analyzer from Siemens. But she still continued to say that the machines do work. She lied to investors. I still feel her case is a lot different to what musk is doing. I think you can definitely say…

Are you a biochemist? Would the Theranos machine have worked with new tests using new reagents? Is the needed blood volume not similar to, for example, payload capacity? Are we discriminating against people who affect an unusual voice?

Re: Analyzing data from Silicon Valley ventures and founders prosecuted for fraud

#17
post #11

Earlier quoted context omitted.

> Like if someone says we have this many users as a statement you have no idea what they are actually calculating I think that's BS. User metrics are usually very explicitly defined (e.g. monthly or daily active users have always been clearly defined wherever I've worked, even if just for the sole reason that people collecting those numbers need to know what to count). User quality is definitely a gray area and estim…

Right I'm not saying that Zuck's staff doesn't know how to calculate MAU or ARR. I'm saying I'm not sure we can trust the 'median' (median on a scale of super-scrupulous to outright-dishonest) CEO is not counting things like inactive cohorts, newsletter subscribers, website hits when counting 'users'... or being very optimistic about whether a customer will renew when calculating 'recurring revenue' I may be wrong! B…

The “Active” part of “Monthly Active Users” can mean an awful lot of things

Re: Analyzing data from Silicon Valley ventures and founders prosecuted for fraud

#18
post #12

Earlier quoted context omitted.

> Like if someone says we have this many users as a statement you have no idea what they are actually calculating I think that's BS. User metrics are usually very explicitly defined (e.g. monthly or daily active users have always been clearly defined wherever I've worked, even if just for the sole reason that people collecting those numbers need to know what to count). User quality is definitely a gray area and estim…

if someone says they have a billion users because they are connected to the doubleclick exchange... they aren't lying, they might be deceptive or simply foolish. As part of due diligence, the buyer/investor should ask how these numbers are calculated and make their own judgement. Unfortunately I believe startups select for those who dance the border of deceptive and foolish.

> they aren't lying, they might be deceptive

I think that’s well within the bounds of what most people would consider to be a “lie”. The legal system has more specific definitions, though.

Re: Analyzing data from Silicon Valley ventures and founders prosecuted for fraud

#19
“Our theoretical framework captures how entrepreneurs facing minor, wide, and extreme expectation-reality gaps engage in evermore sophisticated efforts to detach the venture’s externally projected appearance from its actual operational reality.”

Look, I’m not promoting fraud at all, but having been doing seed raising for the last eight months, there have been many times where I thought the only way to compete was by fudging the numbers (because everyone else is, basically). It’s one of several reasons I left this game and am pursuing non-traditional means of funding now.

Re: Analyzing data from Silicon Valley ventures and founders prosecuted for fraud

#20

“Our theoretical framework captures how entrepreneurs facing minor, wide, and extreme expectation-reality gaps engage in evermore sophisticated efforts to detach the venture’s externally projected appearance from its actual operational reality.” Look, I’m not promoting fraud at all, but having been doing seed raising for the last eight months, there have been many times where I thought the only way to compete was by…

Good on you for saying no to committing fraud! It really sucks that this is unusual enough that it warrants a bit of positive feedback!
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