A lot of people misuse the term “MVP” or Minimum Viable Product. To be clear an MVP is not a beta, not a prototype, but rather an experiment designed to test your value proposition’s assumptions by measuring a behavior and learning from the results.

Back in the day, Dropbox did an MVP as just a video and Buffer was just a landing page. Both were experiments to determine if Dropbox or Buffer should even exist. Instead of guessing and building prototypes, they built the simplest of things in order to measure a user’s behavior. Today startups are building functional prototypes and calling them MVPs. They are better off building something they can learn from. Typically the first MVP doesn’t even have to be anything on a device or computer. For example, I once advised a new travel startup that wanted to give you one click access to a daily itinerary based on a map. They assumed that people wanted a map with pin points on it and times to follow. I told them to go to tourist spots and give people real maps with real pin points circled and an analog itinerary to follow. That was an MVP, it was an experiment (map) that measured (how many as a percent of total) a user behavior (did they use the map or not). Let’s take a look at how to build a better MVP.

Getting Started: Customer Segment and Value Proposition

The whole idea of an MVP is to measure an actual result against your expected result to prove or disprove your assumption. In order to do that you need data. The first place to start is to think about is your customer segment; you have to know who your target customers are going to be. Without knowing your exact segment (22–34 year old professional, urban women, single, living alone, earning over $75k), you won’t be able get the correct pool of users to test on.

After you define your customer segment, you define your value proposition. Too many people think that their value proposition is just the solution to the problem they are solving. That is incorrect: your value proposition is the delta between the current solution or workaround to the problem people are currently using and your solution. You measure your value proposition in terms of how much better your solution is compared to the solutions that exist today.

Let’s say you are solving a problem for buying movie tickets. Several solutions already exist; there are lots of web sites, apps, etc. Maybe your solution involves buying the tickets via SMS. Regardless, you have to think about what the alternatives to your solution are and compare them against that. One is simply buying the ticket at the box office. Here your alternative has value, but not tremendous value. Alternatively, let’s say you are developing a life saving cancer drug. The alternative without your solution could be death. In this case your solution would be incredibly valuable.

The Assumptions That Fuel Your Value Proposition

Underpinning your value proposition are your core assumptions. These are the things that would compel someone to buy your product or service. The job of the MVP is to test those underlying assumptions. The only way to successfully test those assumptions is by making a prediction of the result and comparing the behaviors that you measured up against your predictions. Your predictions should be based in fact, facts that would determine if you have a viable business or not. If you don’t make a prediction, then you will not have a way to determine success or failure of the MVP test.

Let’s say you are building a landing page, Buffer style. Your MVP will be to measure how many people give you their email address after your landing page described your product. You will have to drive traffic to your landing page, most likely by taking out some Facebook or Google AdWords ads. You want to measure the conversion rate of people who clicked on the ad (since you pay for click) to providing their email addresses. For example, if 100 people clicked on the ad and came to your page, but only 4 provided their email address, your conversion rate is 4%. (Not bad actually in e-commerce.)

Should 4% be your target? No. You need to determine your prediction based on facts and your business model. Let’s say you estimate spending $100 on Google AdWords to drive traffic to your MVP. If you have a conversion rate of 4%, it will then cost you $25 to acquire each customer. $25 is your CAC or customer acquisition cost. You need to estimate what your Customer Lifetime Value (CLV), or the amount of profit you expect to get out of each customer over the course of their relationship with you, is. At this stage it will be fairly inaccurate, but you need to ground your assumption in reality. (Future MVPs can test pricing.) Let’s say you make the CLV to be $21, based on a lot of factors in your business model. (I talk more about your CLV and CVC here.)

With a a CLV of $21 and a CAC of $25, you will lose $4 on each new customer you acquire. Or CLV ($21) — CAC ($25) = -$4.

For your MVP test, you will need a higher conversion rate/lower CAC rate in order to make a profit. For the first MVP test make a prediction that the conversion rate will be 5%, bringing your CAC down to $20. Or CLV ($21) — CAC ($20) = $1.

Interpreting The Results

Now with your assumptions based in some business reality, it is time to run the test. Typically the results are one of the three following numbers (remember you are aiming for 5% conversion):

• 0.021%
• 4.28%
• 17%

Let’s take 0.021%. This is an absolute failure, you can safely assume that your assumption is invalidated. Safest thing to do is declare the assumption invalid and go back to your value proposition and rethink it. If you have other assumptions associated with your value proposition, you can do some more MVP tests to determine if the entire value proposition is invalid or not. Chances are you will have to iterate your idea and value proposition some more.

What to do if you are at 4.28%? Technically it is invalid since you need 5% conversion rate in order to make any money. Should you just give up and go home? No. You should try some new UX and new design or different language and run the test again. Don’t run the test without changing anything! If your future tests with minor changes are at or over 5%, then you can declare your assumptions valid and move on to test the next one.

Let’s look at 17%. Woo-hoo, your assumptions are more than valid, you blew away your predictions. Verify that your test was fair and then declare your assumption valid and move on to test the next assumption.

Thats all there is to it! Only by clearly defining what success is and basing those numbers in a business reality is an MVP useful. Anything else is just a beta.

Build an MVP, Not a Beta was originally published in Fusion by Fresco Capital on Medium, where people are continuing the conversation by highlighting and responding to this story.

A lot of people misuse the term “MVP” or Minimum Viable Product. To be clear an MVP is not a beta, not a prototype, but rather an experiment designed to test your value proposition’s assumptions by measuring a behavior and learning from the results. 

 Back in the day, Dropbox did an MVP as just a video and Buffer was just a landing page. Both were experiments to determine if Dropbox or Buffer should even exist. Instead of guessing and building prototypes, they built the simplest of things in order to measure a user’s behavior. Today startups are building functional prototypes and calling them MVPs. They are better off building something they can learn from. Typically the first MVP doesn’t even have to be anything on a device or computer. For example, I once advised a new travel startup that wanted to give you one click access to a daily itinerary based on a map. They assumed that people wanted a map with pin points on it and times to follow. I told them to go to tourist spots and give people real maps with real pin points circled and an analog itinerary to follow. That was an MVP, it was an experiment (map) that measured (how many as a percent of total) a user behavior (did they use the map or not). Let’s take a look at how to build a better MVP.

Getting Started: Customer Segment and Value Proposition 

The whole idea of an MVP is to measure an actual result against your expected result to prove or disprove your assumption. In order to do that you need data. The first place to start is to think about is your customer segment; you have to know who your target customers are going to be. Without knowing your exact segment (22-34 year old professional, urban women, single, living alone, earning over $75k), you won’t be able get the correct pool of users to test on.

After you define your customer segment, you define your value proposition. Too many people think that their value proposition is just the solution to the problem they are solving. That is incorrect: your value proposition is the delta between the current solution or workaround to the problem people are currently using and your solution. You measure your value proposition in terms of how much better your solution is compared to the solutions that exist today.

Let’s say you are solving a problem for buying movie tickets. Several solutions already exist; there are lots of web sites, apps, etc. Maybe your solution involves buying the tickets via SMS. Regardless, you have to think about what the alternatives to your solution are and compare them against that. One is simply buying the ticket at the box office. Here your alternative has value, but not tremendous value. Alternatively, let’s say you are developing a life saving cancer drug. The alternative without your solution could be death. In this case your solution would be incredibly valuable.

The Assumptions That Fuel Your Value Proposition

Underpinning your value proposition are your core assumptions. These are the things that would compel someone to buy your product or service. The job of the MVP is to test those underlying assumptions. The only way to successfully test those assumptions is by making a prediction of the result and comparing the behaviors that you measured up against your predictions. Your predictions should be based in fact, facts that would determine if you have a viable business or not. If you don’t make a prediction, then you will not have a way to determine success or failure of the MVP test. 

Let’s say you are building a landing page, Buffer style. Your MVP will be to measure how many people give you their email address after your landing page described your product. You will have to drive traffic to your landing page, most likely by taking out some Facebook or Google AdWords ads. You want to measure the conversion rate of people who clicked on the ad (since you pay for click) to providing their email addresses. For example, if 100 people clicked on the ad and came to your page, but only 4 provided their email address, your conversion rate is 4%. (Not bad actually in e-commerce.) 

Should 4% be your target? No. You need to determine your prediction based on facts and your business model. Let’s say you estimate spending $100 on Google AdWords to drive traffic to your MVP.  If you have a conversion rate of 4%, it will then cost you $25 to acquire each customer. $25 is your CAC or customer acquisition cost. You need to estimate what your Customer Lifetime Value (CLV), or the amount of profit you expect to get out of each customer over the course of their relationship with you, is. At this stage it will be fairly inaccurate, but you need to ground your assumption in reality. (Future MVPs can test pricing.) Let’s say you make the CLV to be $21, based on a lot of factors in your business model. (I talk more about your CLV and CVC here.) 

With a a CLV of $21 and a CAC of $25, you will lose $4 on each new customer you acquire. Or CLV ($21) – CAC ($25) = -$4. 

For your MVP test, you will need a higher conversion rate/lower CAC rate in order to make a profit. For the first MVP test make a prediction that the conversion rate will be 5%, bringing your CAC down to $20. Or CLV ($21) – CAC ($20) = $1. 

Interpreting The Results

Now with your assumptions based in some business reality, it is time to run the test. Typically the results are one of the three following numbers (remember you are aiming for 5% conversion):

• 0.021%
• 4.28%
• 17%

Let’s take 0.021%. This is an absolute failure, you can safely assume that your assumption is invalidated. Safest thing to do is declare the assumption invalid and go back to your value proposition and rethink it. If you have other assumptions associated with your value proposition, you can do some more MVP tests to determine if the entire value proposition is invalid or not. Chances are you will have to iterate your idea and value proposition some more.

 What to do if you are at 4.28%? Technically it is invalid since you need 5% conversion rate in order to make any money. Should you just give up and go home? No. You should try some new UX and new design or different language and run the test again. Don’t run the test without changing anything! If your future tests with minor changes are at or over 5%, then you can declare your assumptions valid and move on to test the next one.

 Let’s look at 17%. Woo-hoo, your assumptions are more than valid, you blew away your predictions. Verify that your test was fair and then declare your assumption valid and move on to test the next assumption.

 Thats all there is to it!  Only by clearly defining what success is and basing those numbers in a business reality is an MVP useful. Anything else is just a beta.

Before looking at the future of the Hong Kong startup ecosystem, it’s important to begin with the past. The Hong Kong startup ecosystem has seen tremendous progress during the past five years.

The most important factor has been the entrepreneurs themselves. Without entrepreneurs, there would be no ecosystem. To build teams, of course additional talent has been needed, and Hong Kong has seen a strong mix of immigration and inspired young people. Next, capital from angel investors and real estate from co-working spaces has provided the the basic resources for starting a company. The first accelerator in Hong Kong, AcceleratorHK, was started by  my partner Stephen Forte and Paul Orlando, with a wave of new accelerators now following. Education was added to the mix when my partner Allison Baum brought General Assembly to Hong Kong, and there are currently several options for learning the basic skills about startups.

So what’s next?

First, we need more of everything. More entrepreneurs, more talent, more angel capital, more accelerators, more education and, yes, even more co-working spaces.

Second, we need to pass the mom test. Right now, entrepreneurship has entered the consciousness of the younger generation in Hong Kong. That’s a great start. But to really make it go mainstream, we need to convince all of the moms in Hong Kong, including the tiger moms, that entrepreneurship is serious option for their children. Of course we need heroes, but rather than simply creating idols for worship, it is important to show these moms that entrepreneurship is a diverse ecosystem where people with different skills can find successful and meaningful careers. Joining a successful and fast growing startup as an employee with equity is actually more rewarding than being the sole founder of a project that never makes it off the ground. Working as a service provider who supports the startup ecosystem is a meaningful way to give back to society. Becoming a lifestyle entrepreneur can provide the flexibility for people to balance work and life. As a startup ecosystem, we need to reach out to moms all across Hong Kong and get them on board.

Third, we need private sector investors, limited partners, in home grown early stage venture capital funds. All anecdotal evidence, both formal and informal, suggests that startups are able to raise angel funding in Hong Kong but when reaching Series A they typically look outside of Hong Kong for investors. Not only is this frustrating for the startups, it creates a real risk for Hong Kong that these companies will scale up their operations elsewhere just as they reach the sweet spot of growth. There are many institutional investors based in Hong Kong, but their investment focus is traditional sectors like property, foreign markets or later stage growth capital. Other countries have successfully built up early stage venture capital based on the foundation of local limited partners. Hong Kong is already a powerhouse global financial centre with strong  growth and late stage capital but to build a sustainable startup ecosystem the connection between finance and startups needs to be strengthened.

Let’s make the next five years of the Hong Kong startup ecosystem as productive as the last five. To reach the next stage of evolution, we need more of everything and also two additional factors: passing the mom test and local limited partners for early stage venture capital funds. As Hong Kong legend Bruce Lee said, “There are no limits. There are plateaus, but you must not stay there, you must go beyond them.”

Every company is unique, with its own challenges and opportunities. But the traditional approach towards corporate venture capital ignored this reality. Historically, companies set up a venture capital division that invested in startups with the hope of strategic synergies. Typically, the synergies disappointed, there was turnover at the venture capital team and finally the entire initiative was starved of resources. It was like painting only with black and white.

During the past few years, however, as companies have re-entered the corporate venture capital market more aggressively, there has been more willingness to experiment with a variety of approaches. There are several approaches to consider depending on the the specifics of each firm.

1. Classic Corporate Venture Capital
When done well, the classic corporate venture capital model looks like Intel Capital, with more than 1,400 companies invested and more than 570 exits since 1991 across a variety of sectors. In addition to investment, they leverage their corporate brand, global customer base and technology expertise to support portfolio companies. If your company is thinking about starting a corporate venture capital fund in the classic sense, this is the benchmark, and it is not easy to meet. Intel is exceptional at execution in its core business, and so it is not surprising that it has also done well as a venture capital investor. Instead of blindly trying to create a poor copy of Intel, it is worth considering some of the other models because doing this well over decades is not easy.

2. Focused Corporate Venture Capital
Historically, very few businesses are able to create a tight fit between their operations and their venture capital investment and many times forcing these two together creates friction. When it works, however, the model can be very powerful. Salesforce is a great example of a focused venture capital model. The company invests across stage but with a primary emphasis on companies that are built on the Salesforce Platform or listed on the company’s AppExchange. Therefore, the operating fit is clear and natural, resulting in a genuine benefit for both the portfolio companies and the fund.

3. Moonshot Venture Capital
Google Ventures is part of a broader strategy at Google which emphasizes breakthrough technologies to transform existing industries or create new ones. This strategy can only be implemented with deep pockets, and the company has committed to provide US$300 million per year to maintain an aggressive pace of investment. The fund invests across sectors, the largest of which so far has been health care and life sciences. In addition to the fund, the company also makes direct investments, for example SpaceX. While many of these moonshot investments are not directly related to the business of search, of course Google Ventures provides additional support beyond money by leveraging the company’s significant pool of talent and assets.

4. Limited Partner Venture Capital
The reality is that most companies do not have the resources or ability to launch a dedicated venture capital fund. Fortunately, that constraint can be turned into a competitive advantage by investing as a limited partner in a strong external venture capital fund. For example, WiL is a venture fund backed by several Japanese corporates as limited partners, including Sony, Nissan, Benesse Holdings, the NTT group, ANA Holdings, Isetan Mitsukoshi Holdings and Daiwa Securities Group. As part of the relationship, WiL is also committed to training employees of these companies about venture capital investment. For most companies, investing in an external venture capital fund is the most practical approach to create a successful outcome in terms of both financial returns and learning.

5. Multi-Strategy Corporate Venture Capital
Large companies have the scale to combine multiple approaches. The strategy of Siemens Venture Capital includes direct invest at the corporate level in core areas such as Infrastructure and Healthcare, a corporate venture capital fund, Industry of the Future Fund, and investments in more than 40 external venture capital funds through Siemens Global Innovation Partners. This diversified approach gives the company a broader network of external partners and therefore a better picture of the latest opportunities. Siemens has recognized that working with external partners is complementary, not competitive, to their in-house team.

The rapid evolution of corporate venture capital during the past few years is a significant positive force to create meaningful change at scale. Companies should be actively engaged with venture capital. For most companies, the best first step is to invest in an external venture capital fund. For companies with more significant resources, there are now several options to consider, including the multi-strategy approach of having both in-house and externally managed venture capital funds. Overall, this structural change in corporate venture capital is like moving from painting in black and white to painting in vibrant colour: the impact is transformational.

Sources:

http://www.intelcapital.com/

http://www.salesforce.com/company/ventures/

https://www.gv.com/

http://www.bloomberg.com/news/articles/2015-03-09/google-ventures-bill-maris-investing-in-idea-of-living-to-500

http://venturebeat.com/2015/02/10/google-confirms-it-put-900m-into-spacexs-1b-round/

http://wilab.com/

http://asia.nikkei.com/Business/Deals/Fund-to-give-Japanese-business-giants-close-links-with-startups

http://finance.siemens.com/financialservices/venturecapital/portfolio/pages/portfolio.aspx

Yesterday I was in a discussion on Twitter with Semil Shah and Marc Andreessen about the value of a pitch deck. Marc thinks that the pitch deck has to be well polished and Semil and I think that a bad pitch deck with an awesome presentation by a passionate founder is ok for a seed round. 

Tweet Storm

That was the critical differentiator:  the round. If you look at the conversation, Marc and I are in agreement on the need for a quality deck, we just disagree on the stage. This got me to thinking of the main difference between raising a Seed round and a Series A round.

As several Fresco Capital portfolio companies are currently raising a Series A or have just completed one, the difference between Seed and Series A is fresh on my mind (hence why I felt bold enough to challenge an icon like Marc yesterday..)

If you remember from my previous post, typically when you are raising a Seed round you don’t have your product-market fit figured out, nor do you have the exact facets of your business model ironed out. You typically figure this out during your Seed round and execute on your business model in a Series A.

Raising a Series A round is very different than raising a Seed round. Seed is about finding a business model, Series A is about executing that business model at scale. Marc is correct and you need polished deck for the Series A,  however, you also need to demonstrate two other important things in order to get funding: you need a repeatable business that scales. 

Repeatable Business

In order to demonstrate a repeatable business, you will have to show that you have customers, users, etc, coming back for more. You want to keep the customers you win engaged rather than churn them out.  Measuring engagement is not going to be the same for each business, but you need to figure out what it means for your business. Typically it has to with the Customer Lifetime Value (CLV) and how many customers your business can support. 

If you are building a consumer app similar to Instagram for example, you have to demonstrate the engagement of the users you have posted XX photos per week. How many comments they leave, etc.  If you are building an e-commerse mobile app, it may be defined by the transactions performed each month, a game can measure how often they play and level up, or in a B2B service, how often certain tasks are performed. Even in the Seed stage, you should be able to determine this number, even if you have to do small tests and experiments to do so.

Scalable Business

Having a repeatable business is not good enough, you also need a scalable business. I’m not talking about the techie versions of scalability where your app and site perform the same under load as they do under normal conditions, but rather the business model. Typically this has to do with customer acquisition costs (CAC). Specifically, you need to work through this formula: CLV – CAC = $some really big number

Where CLV is your Customer Lifetime Value or the amount of profit each customer brings to your business over the course of their entire experience with you. This is difficult to calculate at an early stage (as you hope to have customers for 10+ years and you may only be in business for a year), but with enough cohort analysis and other data analysis, you should get a good feel for this number by now. 

CAC is the Cost of Customer Acquisition. This is how much it costs you to get a person through the funnel and convert to actually buy something. This number may be easy to calculate if you get 100% of your customers from marketing campaigns, take the total cost of the marketing campaign divided by the number of people who converted into customers. (For example if you spent $100 on AdWords and 4 customers converted, your CAC would be $25.)

Let’s look at how important this formula is:

CLV ($45) – CAC ($45.01) = -$.01

Here you are losing one cent on each customer and will eventually go out of business. Not good, not even the best deck can save you here.

CLV ($1) – CAC ($0.99) = $0.01

Here you are earning one cent on each customer and will eventually build a profitable business. The difference of just two cents can make or break your business! 

Now in reality, I’d like to see something like this:

CLV ($6) – CAC ($1) = $5

Meaning, for every $1 you put into your customer acquisition/marketing campaign, $5 comes out. Very scalable. If you are raising a Series A of $5m and in your deck you show this formula and say that $2m of the $5m is earmarked for customer acquisition, the investor knows that $10 should come out- assuming that your formula is correct. (Actually as an investor, I would expect you to focus like a laser beam on the funnel optimization and get that CAC down while simultaneously increasing the CLV.)

As you move your business out of the seed stage and onto a Series A, make sure you make Marc happy and have an awesome deck. In addition, if you want his (or my) money,  demonstrate that you have a repeatable business that scales.

It is now a consensus view that early stage startups can be highly capital efficient, one of the key ideas behind lean startups. It is also a consensus view that scaling startups is capital intensive in order to reach the status of a unicorn. But do lean unicorns exist?

Press articles regularly show lists of startups who have received the most funding, apparently as a badge of honor. They forget to mention that many of the startups on these lists have not yet proven their unit economics and the dilution on the cap table also happens to be extreme.

Conversely, capital efficient startups are sometimes described as lacking ambition. The implicit message given is that the entrepreneurs are not thinking big enough, or that they are not willing to sacrifice enough of their personal lives.

What if there was a startup that only raised US$2M in outside funding before its IPO, and the IPO itself was triggered not by a need for cash but because of the number of shareholders? What if that startup led to the creation of several billionaires and many more millionaires? What if one of those people went on to become the richest person in the world? That lean unicorn exists in real life and it is named Microsoft.

Of course, Microsoft is an outlier. It was even started before the term lean startup. But, then again, all successful startups are outliers. Average statistics about startups are not helpful because they fundamentally misunderstand that successful outliers reflect power laws. Is Microsoft the only lean unicorn? Was this something that only happened for software startups from the 1980s? Hardly. A list of recent capital efficient exits shows that lean unicorns continue to be seen in real life.

So what are the lessons from history about capital efficiency? Of course, a capital efficient approach is not the only way to build a successful business. However, scaling a large company does not automatically have to be capital intensive. Capital efficiency at scale is possible, and the upside is tremendous. Lean unicorns do exit.

Sources:

http://www.lannigan.org/pdf/Microsoft_prospectus.pdf

http://techcrunch.com/2014/06/14/sand-hill-roads-consiglieres-august-capital/

https://www.cbinsights.com/blog/capital-efficient-tech-exits-top-25/

If you have ever seen me speak at an Accelerator or startup event, I usually refer back to my experiences fundraising for my past startups. I’ve had experience raising venture capital in four distinct eras: the “dot com era” circa 1999, the post dot com crash circa 2002, the post Google IPO-pre-Lehman collapse era (2006-2008), and the more current (post-Lehman) environment. While many of the rules of fundraising are the same, the stages, amounts, and terms have drastically changed over the years. Living and investing in Silicon Valley, I have observed the new pattern of fundraising, which I have broken down to four stages.

The four stages are:

• Acceerator Round/Initial Capital
• Seed
• Series A
• Series n

While there are all kinds of startups out there from pure software to BioTech to hardware, I’ll use the example of a typical software startup in the example below. The rounds and rules hold true in broad strokes for most startups, but the dollars, metrics,  and sources may very. 

Accelerator Round/Initial Capital/Friends and Family ~$100,000 USD

This is the round where you move from idea to prototype, possibly to a first version you let people play with. Lots of experimentation, MVPs, and customer discovery. You use this round to get a sense of a “product-market fit” but not necessarily a business model. Typically you have two or three founders working on sweat equity and some money borrowed from friends and family. This is the stage to go through an accelerator or have a single angel investor. The average size of this round is about $100,000 USD, excluding the value of the sweat equity. Once you have demonstrated the ability to execute and launch a functional prototype and can extrapolate the results, you are ready for a seed round. 

*Note that if you are a hardware startup, your Kickstarter campaign, would typically come into play here. 

Seed Round ~$1-1.5m USD

This is the round where you obtain “product-market fit” and find your business model. You develop and release your product and start to measure the results. Your customers may not pay you a lot at this point, but you have built an audience or customer base. This is the round where you bring on your first non-founder hire and move out of the garage, typically to a co-work space. The range of this round is between $1m to $1.5 USD structured as a convertible note. The typical scenario is that you have 3-4 investors, one lead at half the round at $750k and the other 3 investors in at $200k – $300k each. It is important to have a lead that is capable of investing in your next round, possibly leading that round as well. As general advice, beware of an AngelList Syndicate as your lead during this round, a lot of the time that syndicate is only good for the amount of the syndicate in your seed round and not capable to lead the Series A. Syndicates are good to round out the round, but not to lead-unless the Syndicate head has the ability to lead your Series A.

Series A ~$3-7m USD

This is the round where you execute on your business plan and scale. You have paying customers, you know where to find them, and you just need to accelerate the process of onboarding them. Typically with a Series A, you don’t need the money as you can grow organically, however, you raise a Series A in order to grow faster. Typically you use a portion of the funds raised for customer acquisition as well as some new hires in both sales and marketing roles. The range of this round is typically between $3m-$8m USD with some if not all of your seed investors participating. Sometime about now you think about moving out of that co-work space and into your own office. 

Series N… $25m-$1b USD

After a Series A, typically the later rounds (Series B, C, n…) are for massive growth. I like to use the analogy for a Series B as “rocket fuel.” For example, you found your product market fit in your seed round, you developed and executed on your business plan in your A, and you have a repeatable business that scales. You’re making money and have a great team. You know where your customers are and how to get them to give you money. If you grow out of revenues, you are going to get to the target (say 30% market share or $150m in revenues), but it will take you a long time organically, say 3-5 years. This is the airplane taking off and going fast, but hovering above the tree line. With a Series B, it is like pouring afterburner rocket fuel on to your airplane and the goal is to get to the target in 1-2 years, not 3-5. Later rounds continue this trend and are also used for acquisitions to speed up the process as well as provide some capital to enter foreign markets. 

While this is not the exact path that your startup will take, it is the “textbook” course a startup will take. Use this information as a guide and as with everything in this business, your milage may vary. 

Startups do not have many ways to build a strong competitive advantage in the early days. But startup hiring is one area where this is possible because the hiring process at most large companies is broken. If your startup can build a superior hiring process, this will be a strong competitive edge.

Don’t Outsource Hiring
Hiring top talent is a core skill that startups need to possess and core skills should not be outsourced. That means allocating enough time during the week for actual hiring. If hiring is a top priority, which is usually the case in every startup, then a minimum of 25% of at least one senior person’s time should be spent on hiring. This can include online research, content marketing and in person activities but there is no way to avoid having to invest significant time into hiring if you want to do it right.

Poach, Don’t Wait
The best people are usually not aggressively looking for new jobs. They are probably being paid well, and almost always very busy, although perhaps somewhat discontented in their current role. Posting on job boards, creating recruitment ads and evaluating the applications that come to you will severely limit the quality of potential hires. You have to identify the best possible candidates and then proactively poach them. That means selling them on why they should join your company.

Build a Funnel
Just like a customer funnel improves sales, a talent funnel improves hiring. Identify potential candidates before you need them urgently so that you have enough time to get to know them. Ideally, you will be able to identify specific hiring sources who have strong training programs well suited for your company. This may include universities for fresh graduates or large companies with a commitment to employee training. Stable sources creates a positive feedback loop because your employees will be alumni and in a strong position to identify the best future candidates from their previous home.

Be on a Mission
Startups cannot compete on salary. But the best people are not obsessed with maximizing their yearly income. Instead, they appreciate the value of learning and a meaningful job. This is much easier to accomplish if your company is on a mission to change the world. To be clear, this does not mean lying about what you have currently accomplished. Be up front about all the challenges and problems that are still left unsolved because potential employees will see how and why they really can make a difference.

Use Self-Selection
Once you have identified a candidate and started to communicate, be transparent with your priorities and let them decide if the fit is correct. This requires that you take the time to identify your priorities. Prevention is the best way to deal with bad hires. Of course, not every hire will be a perfect fit. If someone joins and is obviously not working out, you need to understand why quickly and, if needed, make some tough choices. If you have to fire someone quickly, that is a sign your hiring process is faulty and so you need to re-evaluate and adjust your process when this happens more than once in a while.

Most companies have a traditional hiring process. Startups have an opportunity to build a strong competitive advantage by hiring differently. Although successful startup hiring requires investment of significant time and energy, it is definitely worth the effort.