sskates

Thanks Daniel! Sorry, I'm on it right now!

The short version is we saw a big gap in the product analytics market when we were building a consumer app. We were going to work on building a company no matter what and it was the best opportunity we found. B2B was much easier than consumer for us. All you have to do is build what your customers ask and then they’ll pay you money!

I just did a podcast on it if you’re curious: https://theboostvcpodcast.simplecast.com/episodes/ep98-the-e...

As an engineer turned founder, your instinct to jump in and start doing it is correct. It’s hard to learn from books. I never did, neither did the successful engineers turned sales people that I know. The key is learning to read each situation so you can apply the right approach. You also seem self aware which will help you learn faster.

My biggest advice is get a coach/mentor/consultant who you talk with once per week to get feedback. This is how professional sales people learn in practice (eg from a sales manager). This will accelerate you learning by a factor of 10 versus doing it yourself. They will help you read each situation and push you to focus on the right places. Otherwise it’s easy to flounder on the wrong ones.

RE metrics- closed business is the only one that matters! Do whatever gets you that as fast as possible.

I wasted a year when I first founded Amplitude trying to brute force it myself and closed a grand total of two contracts for $36k. After that I ended up working with a guy named Mitch Morando and got from $36k to $1M in ARR in less than a year. He cost me $5k a month and increased our market cap by $20M, it was well worth the investment. I’m happy to make an intro if you’d like.

Good luck on the journey ahead and I’m excited for you!

An interesting question for me would be if it had been all male co-founders. Would that have stood out?

100% agreed on this. Invention is a myth. We don't invent new things, we discovering them through deeper understanding of what's actually going on.

Yeah- the truth is always more nuanced. Both product market fit and doing things that don’t scale are required to get something off of the ground. It’s almost never you see a successful startup that didn’t have both of those pieces.

Agreed with all the above. Retention is the best long term predictor of success of every business I’ve seen. Growth can be fast or slow- what matters is do you keep your customers around.

The article made the distinction between criticism of an idea and criticism of the person behind the idea. "Of course we can and should say that ideas are mistaken, but we can’t just call the person a heretic. We need to debate the actual idea." It says right there that criticism of an idea is welcome.

As an interviewer, I’ve found that the ability to talk through the problem at multiple layers of abstraction to be one of the strongest indicators of mastery of a subject. This is independent of the topic as well- whether you’re interviewing for coding ability, sales skill, or good management practices. Glad to see it show up in these findings as a great way to interview people.

This is correct. I'm surprised at how much bad information there is in this thread. There hasn't been a clear mandate for a desire to become a state from Puerto Ricans and until that happens Congress has indicated it won't do anything. Both parties support the territory's right to self-determination. It has nothing to do with who Puerto Rico is likely to represent in Congress or the Electoral College: https://en.wikipedia.org/wiki/Statehood_movement_in_Puerto_R...

Agree with everything you're saying about data. Given how hard an analytics system is to set up properly, it's one of the last pieces you should be adding in to get an understanding of how to build your business.

That's definitely one of these things you have to learn as part of running a business. You tend to over-index on things you can measure and under-index on things that you can't. After a while you realize there's a lot more randomness in what happens than you might expect and so you can't weight any particular data point too highly. If you look at patio11's blogging of Bingo Card Creator, you'll notice he has little idea as to why his userbase grows or shrinks any particular year: http://www.kalzumeus.com/2012/12/29/bingo-card-creator-and-o... And he's one of the most sophisticated product analytics experts out there!

Firstly, I'm super biased as I'm the CEO of a product analytics company where one of the value props is getting the data in real time. I agree with this post that people will look at single data points out of context and weight the evidence much more strongly than they should be. Analytics should be one of many tools you use that informs your understanding of how customers are using your product. I also agree that I see a lot of early stage startups invest way too much in building out real-time analytics stores without thinking about what they value they get out of it. That's not something you should do until you're in the 100+ engineer range.

That said, this is a post-hoc justification of why having real-time analytics is bad. Delaying the data by 24 hours doesn't automatically make significance testing better or force people to incorporate more context when interpreting their data. If that's the issue, fix that problem, don't blame the tools.

There's a ton of positive value to having real time data. Just off the top of my head: 1) If you've instrumented something incorrectly you can see that and fix it right away 2) Even worse, if you've accidentally messed up a feature with a release you can know about it right away. This happened to one of our customers recently and without a real-time analytics system they wouldn't have caught it quickly (and this is a tech startup that's well regarded for their engineering that everyone here would know the name of). 3) You can observe significant changes to your user base right away, eg during a launch or if you're getting a lot of new users from a specific channel. 4) It allows you to have more confidence in deploying multiple times a day. It's a little crazy to me that the deployment of a product is faster than our ability to measure it.

I think the real issue is that we're in the early days of analytics and people don't have a great understanding of how to leverage their tools properly. It's like web search before Google or file sync before Dropbox. People will look at single data points and conclude totally crazy things. They won't have an understanding of basic things like the amount of fluctuation on a week to week basis. The largest analytics provider in the world (Google) gives away their product as an ancillary service to drive you to purchase more ads, not to have a better understanding of how your customers are using your product. I'm hopeful this will change over the next 5 years though (and for us to be a part of that!)

Absolutely agreed. I think the GP's viewpoint was widely shared by "The Elite" for the past 10 years and is what created the backlash that got Trump elected. We (and I use that loosely) have to care because the people who get displaced all care about their jobs. In fact, because this displacement is accelerating, we have to care even more than we would in the past.

This took me a year to really internalize- I wish I had read this a while back when we were 20 people. It wasn't until we passed 45 that I really took a thorough look at how I was spending my time. I intellectually understood the transition to delegation and leverage but a lot of the rest of the company didn't and it caused me to take longer than I should have to refocus on recruiting an exec team and defining the company strategy. Excellent writeup.

We've done it with food thanks to the Green Revolution in the 70's. The need to "not waste food" is an artifact from before food was abundant. I'm hopeful like you that we can do it for energy as well.

I remember one of the most mind blowing moments for me was the big reveal halfway through Knights of the Old Republic. Dunno if it counts as "changing my worldview" but it was the same feeling I got after watching The Matrix- I didn't know I could be so impacted by art.

Each individual still has a ~50% chance of being unable to find their name using the query sequence protocol. By agreeing to the same query sequence their success modes and failure modes are now linked. If there's a cycle of 51 or greater, all of those individuals in that cycle are guaranteed to fail, while if they're in a cycle of 50 or less, all of those individuals are guaranteed to succeed.

What this protocol does is make it so each individual failure mode is much more likely to overlap with each other failure mode. Correlating the performance of individuals when you have a one fail all fail scenario is a common solution to this type of problem.

This is awesome! I love the competition slide how more startups are mentioned than big companies. I remember back in 2010 a response investors (even YC!) had to almost any idea was "won't Google do that?" Now it's not strongly on people's radar.

CEO of Amplitude here, there hasn't been much in the way of how to use analytics to systematically improve your retention- hoping to change that today. Happy to answer any questions.

I think what was missed was that a lot of people feel inequality is inherently bad, independent of the cause. I think both sides are mostly talking past each other on this one. It's possible for the fact that an entrepreneur getting rich by founding a startup to be a good thing because of the wealth they create while the fact that it increases inequality to be bad. I think most people agree that entrepreneurs getting rich is on the whole net good. That doesn't make inequality inherently good though.

Not sure that giving liquidation preferences to common stockholders would be fair- the idea with a 1x liquidation preference is that money into the company at least first goes to repaying the principal on the investment first before rewarding any upside.

Once you get to 0.01% per employee it's not a strictly profit maximizing decision. It's more of a way to align people and make them feel they have ownership. Agreed on the second point.

Dilution is unpredictable and what's worse is you have the principal agent problem where employees who are affected don't have a seat at the negotiating table. You're definitely counting on upper management/the board not to do things like that. Not sure on the solution but agreed that it needs to be solved.

"Dead equity" is a tricky problem. On one hand, you've granted ownership and ownership is supposed to have significant upside for exactly the case where the company goes gangbusters like this. On the the other it still somehow feels unfair.

Equity has no intrinsic value and I'm glad you recognize you can't pay rent with it. Founders who try to claim otherwise are being deceptive and I wouldn't work for them either. Much worse if you get insulted and called an idiot for trying to negotiate.

However, equity is a significant form of compensation, not just at startups, but at large companies as well. You're missing out if you don't take some time to understand it in early stage startups.

The crazy thing to me is: 1) the fact that employees are granted options instead of shares is an artifact of tax law, and 2) the fact that there's a 90 day exercise window is also an artifact of tax law. Yet, companies constantly come up with post-hoc justifications of why only giving a 90 day window is fair. There is big resistance to change on this point. Even Ben Horowitz and Sam Altman don't think it's a clear decision! http://genius.com/B-horowitz-lecture-15-how-to-manage-annota...

If you were to derive how to think about employee ownership of a company as a form of compensation from first principles, you'd never come up with options and you'd never come up with a 90-day exercise window on top of that. Those are both artifacts from tax law yet it's become the standard form of compensation!

Agreed that it's mainly a function of employee number and secondarily a function of contribution. I'd much rather it be based on contribution. The trouble is that contribution is hard to tell up front but you have to be agreed on baseline compensation. Perhaps there's a way to fix that as well.

From the perspective of an employee, I completely agree this is the correct method of getting an idea of what equity is worth. I've had exactly 0 new hires ask me all those questions. Maybe 10% have asked me how many shares outstanding we have. The number of people with the experience to ask the right questions is really low, even for senior hires we've made with 10+ years of experience in startups. I think the onus is on startups to start proactively sharing this information with new hires- not just employees.

You make it sound so easy. Professionals at picking the right company (aka venture capitalists) get it wrong the vast majority of the time. Nobody has any guarantees about how things will end up.

You really think the 90 day exercise window is fair? It means an employee who just left a company has a huge burden with their vested options- either come up with a lot of cash and take a massive risk or have your equity compensation be worth nothing.