[Series] 10 Weeks to open a 5-person startup office Paris — Chapter 1 — Spinning up Recruitment
If you’re looking at opening an office for your startup in Paris, this series will give you every tool, hack & workflow that I used to scale up from nothing to 5 people in 10 weeks. Each section has a bullet-point summary at the top, so feel free to scroll past the story-telling if you just want tips to hire/open an office. I’ll also talk about a few of the key decisions we made and how you can approach those decisions.
In early March, I hopped on a United flight from CDG to SFO — it’s a route I know well enough that I bought the domain SFOCDG.com — for my first days with MadKudu. I wrote about why I joined them already (here), so I’ll skip over that, but what I haven’t yet talked about is how I joined a startup without anything more than a handshake agreement (more than enough when you trust the founders), not wanting to waste any time.
For context, here’s how MadKudu sees itself today. MadKudu allows SaaS companies to deliver relevant customer journeys at scale. We do that by providing marketing & sales operations with an API that allows them to understand the next best step in the customer journey for a prospective customer. The most common way customers use us today is to do lead scoring, lead routing & lead prioritization to leverage their sales, because our product allows teams to leverage marketing, sales & product analytics data to build a predictive model of your ideal customer profile, delivering to you via API (1) how likely a given prospect is to convert to a paying customer, (2) the amount of money they are likely to pay, and (3) the necessary steps in the customer journey that they need in order to get there.
The timing for me joining MadKudu could not have been better — once I got started, as one of my first goals was to get an engineering team spun up in Paris, I quickly saw they had begun looking for someone ‘like me’ right around the time I reached out to say “if you’re looking for someone like me, I’m interested.” What makes it more fortuitous is that MadKudu had already decided to build their engineering team in France, so the fact that they could hire someone to own the brand and have that person open the Paris office was a bird:stone ratio that is too good to say no to.
Chapter 1: Spinning up Recruiting
Paris has great engineering talent, especially for big data, machine learning, AI. Engineers in France are motivated by the technological challenge and therefore more loyal, compared to the average 23 month churn rate of employees in the Valley.
Our founders Sam, Francis & Paul are all from France, and they have all been living & working in the Silicon Valley for a number of years (~8 on average). If you’re wondering how it is that I have worked for two different companies founded by French entrepreneurs based in the Silicon Valley, you should know that the ecosystem is small (especially when you filter by SaaS, developer tools, AI) — if you’re looking to live in Paris and work for a Silicon Valley startup with more than a sales office in Paris, you just need to get to know Front, Algolia, DataDog (NYC, but still) or anything coming out of eFounders.
For MadKudu, building the engineering team in Paris was a fairly natural decision. After initially interviewing engineering candidates in Mountain View, they found that the data engineer candidates initial interview questions were more around the cap table (our investors) and exit strategy than about the technical challenges and opportunities to build something that’s never been done, to product-ize something that is 99% done on a consulting basis and to build a real-time, in-production machine learning API. That’s a lot of buzzwords that we don’t often use to describe what we do, but when you’re the engineer that’s being interviewed to build it, we generally hope that this is what gets you out of bed in the morning. More importantly, we found it difficult to find engineers who matched our company culture, namely that they were eager to learn, eager to overcome a challenge at whatever the cost and valued personal & professional growth.
Some may think that we chose Paris simply because our founders were French, they knew the market & the culture was familiar — and you’d be absolutely right. Never forget that opening an office is not an ecosystem competition. Opening an office is about making the best decision for your company based on your needs, and for MadKudu, Paris was the best solution to our needs.
Going from 0 to 1 when recruiting in Paris
When I returned from Mountain View to Paris, I had one goal: get three signed offer letters from data engineers before July 1st. This is core to our 2018 company goals, as the work our data engineering team does is core to our product, specifically in streamlining our implementation process and allowing us to extend MadKudu into more and more parts of the customer journey.
Needless to say, the pressure was on.
Step 1: cold outreach, talk to everyone!
Here are the tools I used to hack together a fully autonomous cold outreach stack:
- LinkedIn Premium (~$72/month) for employer branding & infinite search results.
- Rebump (~$3/month) for automating follow-up emails 3-days & 10-days after initial outreach (significant increase in response rate)
- Hunter.io (free) for finding email patterns that aren’t intuitive (lastname.f@company.com, l.f.name@company.com, and other crazy combos)
- Github (free) for identifying engineers by programming language/commits, and also for finding personal email addresses.
A great way to spin up recruitment in any new ecosystem is to grab a LinkedIn Premium account and search “data engineer” and start looking at people who self-identify for the position you’re looking to fill. You’ll very quickly establish which companies hire that role as well, as well as how the top 1% of the most visible candidates position themselves professionally.
What stack do they build on? What other terms do they use to describe what they do?
Especially for engineers, a lot of roles have fluid names and functions — people with “data engineer” titles can either be engineers who build data pipelines, work on data integration & focus on ETL (Extract, Transform, Load), or they can be what formerly was called database administrators. The same way the system administrators became devops, the inherent nature of using frameworks like hadoop means you might be more on the engineering side — leveraging & manipulating big data — or you might be on the database side.
Getting your bearings straight and figuring out your core message that you want to cold-send to candidates is key, and it was a great way for me to ramp up on the technology-side of our product as well as our employer brand.
If you’re committed to building a significant presence in any city, then you need to commit to creating a great candidate experience, even when people say “no” to your first email.
Three important rules to building your employer brand while recruiting your first engineers:
- Only reach out to people with relevant skill sets for the post you’re looking to fill.
- Create a compelling first outreach email (they’re being read, even if they’re not responded to)
- Send earnest, enthusiastic responses to people who say no right away
Remember that the people who say “no” to you today may very well be the people you want to reach out to tomorrow, just like the candidates you ultimately pass on because they’re underqualified might be qualified tomorrow. I had candidates decline because they had just accepted a new job, just changed cities, and who were just happy with where they were working (95%+ of the people we reached out to were currently employed, at least according to their public-facing profiles).
Cold outreach is a great way to get started, and as long as you approach it from an authentic place, then you’ll be fine. Sam & I split the role of sending the emails in order to see if there was a difference in terms of response rate if it came from the CEO or the Head of Brand Strategy — we didn’t see much of a difference (this may be because I have a relatively big LinkedIn network in Paris), so I quickly took over 100% of the outreach & follow-up.
By the end of the first half of April, I had reached out to 100+ data engineers, and I realized that sourcing + outreach + candidate experience = exhausting.
Send your in-house recruitment team some love if you’re reading this now and have one, because that job is a grind and a half. I knew that down the road I was going to need to hire a recruiter, but until that made enough sense (more on that later, the next step was to automate inbound and create a process to be a one-man recruitment machine.
I’ll be publishing Chapter 2: Automation & Process are your friend tomorrow at 2PM and the rest of the chapters throughout this week.
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