THE BLOG

12
Jan

Hiring for Lean Startups: The First Few Hires

 

I was having coffee with a founder the other day and we started talking about his hiring plans. Since he’s a non-technical founder (which Ben Yoskovitz claims is a dead-end to begin with

) he had several top coders in mind, all of whom were earning big bucks with larger companies.

“I’m paying them a little bit of money but they’ll join full time once I can raise money,” said the founder. It’s something I hear a lot, especially from non-techie founders.

I went back to review some blog posts on Lean hiring, and I came across Eric’s post “Lean Hiring Tips” and Mark MacLeod’s “Fat Hiring for Lean Startups“. Both are worth your time. But I think they’re also written for startups that are already up and running and need to expand. I’m interested in very early stage hiring, e.g. when you’re one person looking for a co-founder or you’re two people looking for your core team.

Companies always take on the characteristics of their founders and in the rush to scale, I find many startups don’t stop to consider how they’re establishing the DNA of their company. The first few hires are the most important ones you’ll make.

  • Hire for an experimental mindset – Look for people who enjoy encountering problems, designing ways to solve them, and finding proof of success or failure. Skill at building, whether it’s software or a marketing plan or a sales funnel, is irrelevant at this point. You need people who will volunteer to scrap their plans, not fight you when you want to change course.

How? Join a hackathon, Lean Machine or just create your own (laptop + Starbucks = hackathon). Give your (potential) team a crazy challenge and see who exhibits the right behaviours.

  • Hire generalists – A lot of people will disagree with this advice. If you can find the best Python developer in the country go for it. But only if she’s also willing to cold call customers, crank out some Web site copy and help you whiteboard the business model. Your #1 focus is to find a business model that works. The latent technical talent on your bench won’t help you unless you graduate from this first phase

How? Again, hackathons are great practical tests. No matter what their skillset, look for passion about your business model and solving customer problems.

  • Prioritize UX over development – This is easier said than done since there’s a shortage of UX talent. But it’s better to have a kick-ass UX person and a mediocre developer than the other way around. UX will help you find your business model and most (good) UX people already have an experimental mindset and generalist attitude

How? Actively seek out UX people, not just developers. You may need to work at a distance if you can’t find local talent. Consider working with less experienced people if they can prove themselves through testing.

  • Get skin in the game – Leaving a six figure job to join your startup for a paycut is not skin in the game, or not enough in my books. Hire those people later when you’ve found your business model, have money in the bank, and need to scale. Skin in the game means working full time, just like you are. It means putting their reputation on the line, raising Ramen funding from friends/family/spouses and saying “I’m going to see this through until we fail.”

How? Stop feeling like you’re a poor startup that can’t afford to pay top salaries. Those aren’t the droids you’re looking for. Think of finding your co-founders like raising your first round. You need to get them excited to invest in your business.

I know this advice seems to apply better to “Web” startups than general technology startups, which is a common criticism of Lean startups in general. But I think it applies more broadly. If you hire for the right attitude, you not only solve the critical product-market fit problem, but you set the DNA of your business right from the start. I guess I haven’t seen too many examples of startups failing because they lacked a specific technical skill. They probably think they failed because of it though.

In the end, I guess “hiring” is the wrong word to begin with. You’re looking for people to co-found a business with you. You aren’t buying their skills, you’re asking them to invest in helping you shape the course of your business from the very beginning. Maybe not all of them (including yourself) will be able to scale up with the business. That’s a problem for another day.

10
Jan
Venganza (Vidas: Memorias Y Biografias)

Startup Metrics in Plain English

 

It’s a positive development that startups have figured out that metrics need to be at the core of their business and their pitch. Thanks to the Lean Startup, Dave McClure’sStartup Metrics for Pirates” and investors who are asking for a dose of proof with your passion.

I find that startup founders are more at ease with acquisition funnels, the viral coefficient, and cohort analysis. But many are getting lost in the weeds and losing sight of the big picture. You have a 3D cohort analysis graph (you know who you are…) but I have no idea what it means.

When you’re launching a new product, I think all of your key metrics can be derived from asking three simple questions:

  1. What is your core value proposition?
  2. How do you know people care?
  3. What’s the proof you’re delivering on your value proposition?

A shockingly large number of people still can’t define their value proposition in simple terms. E.g. we do A for B. The problem is, if you can’t even describe the core promise of your business, you can’t focus your product development, or market effectively, or measure your performance.

Customer acquisition is the time to test the promise of your business before actually having to deliver anything. This is where the fake “Buy” button works. If no one clicks on it, you don’t need to build anything. If your Facebook ads get no click throughs and no one makes it through your sign-up form, that’s the market telling you they don’t want what you’re promising and they don’t care if you can deliver it.

“Once I build my product I’ll be able to prove that customers want it.”

          – misguided entrepreneur

If you’re able to acquire customers that’s great news. But now you need to create metrics that prove that users are engaging in your product in a way that demonstrates value creation. This could be daily active use, amount of user-generated content, referrals to other friends or, obviously, spending money.

But you need to avoid the temptation to create vanity metrics that paint a rosy picture. You can’t build a business on 100k tire kickers from TechCrunch. But if you can find a few users that are truly engaged and truly getting value, you can probably find more of them. Make sure you set a high bar for what constitutes an “active user”. It doesn’t jive to say you’re disrupting an industry while making active user = “logs in at least once per week”.

Many products have more than one type of user. Not just “average users” and “whales” but people who derive different types of value from your product. In a marketplace product (real estate for example) you have buyers, sellers and brokers. All define value differently and need to be measured differently. The point is, you’ll probably have more than one metric that constitutes proof that you’re creating value overall.

Some Plain English Metrics

First, write down a 1-2 sentence value proposition. Seriously, stop avoiding it and do it.

  1. What acquisition metrics indicate a positive reception to your value proposition? Eg. effectiveness of paid and organic users; virality; activation rate.
  2. What is your definition of an “active user” and does this absolutely prove that you’re delivering on your value proposition? More clicks can be due to high engagement or bad UX… This is the toughest metric to design.
  3. Are engaged users maintaining or increasing their engagement over time? If not, how come?
  4. What % of acquired users never become active? Why?
  5. What % of engaged users drop-off? Why?

The most difficult metric to gather is why people stop using your product. By definition, these people are hard to talk to. Bend over backwards to talk to these people: offer them incentives or a personal email from the CEO or a compromising photo of the CEO. The data you get will be qualitative but you’ll be able to spot trends and make changes.

Answering the above five questions isn’t easy. One word of advice is not to worry about getting real-time data (you don’t need it) or perfectly accurate data (which you can’t get). You’ll probably have to throw in some qualitative data and wild guesses. That’s ok because at the beginning you’re looking for big obvious things. You’ll have plenty of time to optimize later.

Also, it’s expected that many of your metrics will suck. You’ll be trending down, not up. This is information you can use to change, fix, and pivot your way to success, or at least the next release.

Conclusion

Get back to basics by defining some plain English metrics for your business. If they’re well designed and information gathering isn’t crazily difficult, you’ll not only have a better view of your business but you’ll find it much easier to create meaningful projections. You’ll be able to have more intelligent conversations with your team and your investors, which hopefully are also taking place in plain English.