Three Ways to Build a Profitable Business With The Revenue Rainbow

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Many entrepreneurs dream of building a business with a certain revenue, like “$10 million a year”, or a certain profit, like “$10 thousand a month”.

But what does a $10 million company look like? How much profit does that generate, and how many employees will it require?

The “revenue rainbow” is a simple way to visualize the possibilities.



Red: $1 MM /mo profit. With annual revenue of 24 to 120 million dollars, this company may be a candidate for public trading.

Orange: $100,000 /mo profit. This profit could support a fairly large founding team.

Blue: $10,000 /mo profit. This would be a nice single-founder “lifestyle business” with under 10 employees.

How to use the rainbow

  1. Decide how much monthly personal income you want to make from your business (your choices are $10k, $100k, or $1 million)
  2. Look at the corresponding color band. The top of the color band shows conditions for a 10% net profit margin business, and the bottom for 50% (so the middle is for 30%).
  3. Build the company!

What are the animals for?

Christoph Janz did a great job of outlining 5 ways to build a $100 million Business, giving each customer type names, like Elephant ($100,000 Average Revenue Per Account clients), Deer ($10,000 ARPA), and Rabbit ($1,000 ARPA). So if most of your sales are in the $100 range, you’re hunting rabbits.

The main assumption is that “employees” account for half of company expenses, and each is paid $5000/mo. That’s roughly true for many businesses, whether the labor goes to making sales, maintaining code, or flipping burgers.

I’ll follow this post up with example profit margins, employee expense statistics, and profit-per-employee numbers from some businesses we all know.

Is Pokémon Go Just a Fad? How Millions Are Getting Hooked

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[Update October 2016: Yes it was. ]

Pokémon Go is phenomenal. Just two weeks past launch, it’s the highest grossing app in all 33 countries that it’s launched in, with 21 million active users in the US alone (1/3 of US citizens ages 15-29, if we assume those usage demographics).

US Google Search VolumeUS Google Search Volume

Is Pokémon Go a Fad?

Pokémon Go’s incredible rise can be explained by several factors, and the debate has now turned to “is Pokémon Go just a fad?” It’s longevity will depend on how “addictive” it is: the strength of the habits formed by its users.

The 4-Step Pokémon Go Habit Loop

The “Hooked” model was developed by Nir Eyal to explain the habit formation for products, and Pokémon Go follows it like a blueprint. The more times a user goes through the 4-step loop, the stronger the habit becomes.

Step 1: Trigger

Pokémon’s trigger is very powerful: walking. Having used Pokémon Go only lightly for one week, I now find myself asking “I wonder if there are Pokémon around here?” whenever I start walking. Worse yet, there’s a feeling of “missing out” on a virtual world of treasure that may be surrounding me at any moment. And if I should forget to check, the app’s vibrate notification will get me back in the loop. Players will also become conditioned to think of the game whenever passing a known PokéStop or gym, making real-life landmarks powerful game triggers.

Step 2: Action

The trigger must lead to an action, and for Pokémon Go that’s as easy as looking at your phone.

Step 3: Variable Reward

Predictable feedback loops don’t create desire, according to Eyal. Casino slot machines wouldn’t be very addictive if after every pull of the handle (the action) you received 95 cents for every dollar bet (the statistically expected outcome on typical slots). There are three types of rewards, and Pokémon Go hits them all:

A) Rewards of the Hunt. Pokémon clearly invokes the primal urges and rewards of hunting.

B) Rewards of the Self. People desire a sense of competency, progress, and accomplishment. Pokémon easily feeds that need through experience levels, experience points (XP), winning battles, and collecting items.

C) Rewards of the Tribe. Players can join the red, blue, or yellow team, instantly connecting them with a global tribe and providing feelings on belonging, camaraderie, and contribution.

Step 4: Investment

The final step for building a strong habit is investment: not wanting to quit because of sunk time or costs. Clearly people are sinking plenty of both time and money into this game, and the massive, near-simultaneous launch in each country means that even slowing down usage would put you far behind your friends. With each time it’s played, the user finds themselves more heavily invested in continuing.

Like all modern mobile games, Pokémon Go’s habit formation loop is strong. It has especially strong Triggers and a simple Action, which should make the game easy to pick up, and hard to put down for good.

Estimating Startup Complexity by Assumption Count

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Questions addressed in this post:

  • How do I choose between startup alternatives?
  • How long before startups reach profitability?
  • Which startup idea is best?

All of these questions require a second question: “how complex is each startup idea?”

In “Lean Startup“, Eric Ries defines “runway” as the number of pivots a startup has remaining before it runs out of cash. This implies you could calculate a startup’s funding requirements by estimating the number of required pivots (provided the cost per pivot can be estimated, possibly from burn rate and frequency of “pivot or persevere” meetings).

A startup would only need to pivot when it realizes one of its key assumptions is wrong; for example, if the value hypothesis is invalid and nobody wants to pay. This is realized when the actual metrics don’t reach the target metrics, despite optimization attempts.

Ideally, a startup would pivot along until it finds the nearest viable model (which may no longer be an innovative one), but as Ries suggested, every pivot might be a startup’s last as it eats runway.

Since these costly pivots are caused by assumptions, it follows that the risk, complexity, and cost of a startup must be largely determined by the number of founding assumptions:

First-order startup complexity  ∝   # of founding assumptions

A zero-assumption startup would be purely replicative: selling the same product to the same market under the same conditions as an existing successful business. Each additional assumption — such as those related to problem, product value, growth, or competition — creates a potential pivot, which increases expected startup risk, complexity, and cost.

Since every key assumption must be correct to successfully implement the founding vision, the probability of success is proportional to the power of the number assumptions:

Probability of success  ∝  c(# of key assumptions)

Effect of Key Assumptions on Probability of Startup Success

The chart illustrates a simple example. The chance of a startup eventually succeeding is higher than shown because it can pivot around a wrong assumption.

Since the reality of business requires selecting from among competing opportunities, carefully counting founding assumptions may be a useful evaluation tool.

How NOT to launch a new product: A $4 Billion lesson in 2 minutes

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When is a product launch a “sure thing”? How about when you’re the market leader, employ an army of marketers and designers, enchant the media, and invest four billion dollars?

Ford had every advantage, and the result was disaster. What went so wrong?

It was the mid-1950s, and Ford needed a new medium-priced model to round-out their line. They invested heavily in marketing research to determine what consumers wanted in a new car. They meticulously analyzed the competitive landscape. They designed genuine innovations that would later be copied by other manufacturers. In short, they did everything one would think sensible and prudent.

Yet the launch was a complete flop. Manufacturing was halted within three years — long before reaching break-even sales — and the “Edsel” name became synonymous with monumental failure.

If they did such excellent planning, where did it go wrong? How can we avoid making similar mistakes with our own product launches?

1. Ford paid lip-service to their customer’s preferences, but disregarded them on key points. For example, they produced an incredible list of 6,000 name ideas ranked by consumer reactions and expert opinion, but top executives couldn’t pick a winner. The puzzling “Edsel” brand (a low-ranked name in their research) was chosen by the chairman of the board to break the debate. As John Brooks’s concluded in his 1969 essay on the topic,

“Although the Edsel was supposed to be advertised, and otherwise promoted, strictly on the basis of preferences expressed in polls, some old-fashioned snake-oil selling methods, intuitive rather than scientific, crept in.”

2. It’s hard to believe that in a $3 billion development budget ($250 million in mid-50’s), basic test marketing was never conducted. This can be done from a very early stage in the form of concept testing: showing a finished concept to the target market and getting feedback. Done quantitatively, several concept variations can be compared to determine the best one. In a later stage, consumers can try prototypes. Ford took the opposite approach: keeping their Edsels literally “under wraps” and hidden from public view until the grand unveiling.

Edsel Carrier

3. Watch people shop for as much as a toaster, and it becomes obvious that pricing is crucial. The Edsel’s pricing was confusing, overlapping with other product lines so consumers didn’t know where it was supposed to stand. Furthermore, the positioning was unclear: highlighting innovative features that could only be considered “premium”, while lacking features common to other premium cars.

4. For over a year the Edsel was slowly revealed to the public in what some called and “automotive striptease”. It was hyped through stunts and ads like no other car had been, so expectations were naturally high. But after release, the only sensible media story remaining was “does it live up to the hype?” With such an intense spotlight, minor problems typical of any new model became headlines, fueling a devastating negative news cycle.

Key takeaways:

  1. Apply your marketing research at each stage of development and marketing.
  2. Test market early and often to avoid launching an “Edsel”.
  3. The consumers’ purchasing decisions consider the competition, so you should too: position clearly.
  4. Don’t build unrealistic expectations or over-hype your product: it invites piercing scrutiny.