How does the Rule of 3s relate to business competition?
And what is the research to back that data up. We dig in below.
Rule of 3s – Business Competition
Fortune Favors the Bold
Why do we have such a tendency to favor average ideas that are easier to execute over big ideas that can transform industries?
Likely because the risks are so high and the chances of success much lower than executing on average ideas; nevertheless, the data shows that ‘category creators’ earn the lion’s share of market revenues. Fortune does truly favor the bold.
We analyzed data on U.S. venture capital–backed tech startups founded from 2000 to 2015 and found that category kings earned 76 percent of the market capitalization of their entire market categories
Newsweek
Even ignoring ‘the data,’ we know how many things in or related to markets revolve around the Rule of 3s and how the rewards are siphoned disproportionately to the top players. Over a longer time horizon, failing to be bold enough can mean being stuck in an über-competitive market fighting over the scraps from the Big 3.
That being said, these are concepts that apply to players in established, high-growth markets. Using something like the Business Opportunity Scorecard can help contextualize these opportunities relative to the stage of the market, especially as it pertains to ‘Capital Required.’ Startups can’t come in and create markets that don’t exist from the outset, the market itself has to evolve to a point where it is big enough to see high competition.
Rule of 3s in Markets
One of the most obvious places where the ‘Rule of 3s’ applies is in mature markets.
If there are many companies in an early-stage or heavily fragmented market, the rule of thumb is that 3 companies will eventually dominate from a profitability and market share perspective in the future:
- Company 1 will earn something like 40 – 50% of the market share
- Company 2 will earn something like 20 – 25% of the market share
- Company 3 will earn something like 10 – 12.5% of the market share
The rule of thumb – and it is not a scientifically, rigorously proven rule – is that the company below the leader will earn about half of the revenue as the company above it, and so on.
The Rule of Three applies (and renews itself) at every stage of a market’s geographic evolution from local to regional, regional to national, and national to global
Ivey Business Journal
So if 3 companies earn 80 – 90%+ in the market, the rest of the companies are competing for the final 10%. Sure there are exceptions (like everything), but this rule generally holds true across many major markets.
One exception is Google’s Search market share, which is more than 90%, as will be discussed below. Remember though, Google was not the first search engine.
Rule of 3 in Search
Google has more than 90% of the search market.
Google’s global search engine market share was at 91.88%, with Bing following at 3.19%, Yandex at 1.52%, Yahoo at 1.33%, Baidu at 0.76%, and DuckDuckGo at 0.64%.
Kinsta
(NB – Google’s search dominance is a rare example of what happens in a market when a company has a technological innovation to reach >70% and there is really no competitive #2).
When you pull up the organic search results for any search term, you typically see a page of 10 results. But from that Top 10 set of results you see, >50% of the traffic will be driven towards the Top 3, and more than 70% to the Top 5.
Not quite as profound of a Power Law distribution as the Markets above, but still nevertheless – fortune favors the bold (and the well-resourced) in Search as well.
Rule of 3s and Big Ideas
So what’s the relationship between the Rule of 3s and Big Ideas?
When we look at the study of both markets and innovations, there is a certain quote that comes to mind from a famous Wall Street movie about the 2008 Financial Crisis called “Margin Call.”
“Be First, Be Smarter, or Cheat”
Big companies are notoriously bad at creating innovations in hot new markets. But if they miss the opportunity, they deploy the M&A strategy and simply buy ’em up.
For the rest of us who don’t have the Balance Sheet to do M&A, missing the mark on certain moments in the market can be one of the biggest inflection points in a lifetime. Failing to crack the top tier in any market is usually the difference between making it big and just hanging on.
Big Ideas are inherently about being creative to create a customer base, new revenue stream, or sustainable competitive advantage. They don’t have to be about making ‘$Billions,’ but they have to be structured towards winning certain types of battles in markets.
Be First, Be Smarter, Don’t Cheat
Being First – as a pioneer, leading innovator, or ideator – can be hell. Being 5-10 years ahead of any market curve likely means lean dinners, taking the bus to work, and trying to stave off bankruptcy until the idea ‘clicks.’ The Streets of Markets are paved with those who had Big Ideas and bad timing.
Customer Validation is the key discipline in relation to testing new ideas.
But Being First in a newly forming market – with customers, competition, and capital – is a huge competitive advantage.
Being Smarter is a level on top of that where a company or brand can ‘Fast Follow’ or basically copycat it and plug something innovative into their existing infrastructure or customer base.
Cheating is never a recommended strategy at any point, despite it being relatively commonplace in many markets.
You don’t want to be is too far ahead of the curve or too far behind the curve. Timing is everything, so leveraging certain types of data is useful to help more clearly define the opportunity and appropriate strategy.
Customer Data, Search Data, Social Data
Usually there is a set of data points – somewhere – that give us an indication we are reaching certain inflection points in markets. There is obviously no absolute answer as to where, otherwise everybody would be doing it. But here are three possible places to look.
Customer Data
We have talked a lot about CBCV (Customer-Based Corporate Valuation) and the models created by ThetaCLV. Their models for public companies (mostly retail brands) have predictive dimensions to them.
Their models mostly revolve around four dimensions:
- Customer Acquisition
- Customer Retention
- Frequency of Purchases
- Average Basket Size (AOV)
From these, various data points can be extrapolated, particularly in relation to Lifetime Value (LTV). To develop frontier ideas from this type of data requires:
- data mining and analytics capabilities
- strategic framing of the data
- vision on market direction
Basically, if a small subsection of a company’s purchases or revenue is in something “obscure” or “niche,” certain customer data characteristics may highlight a bigger opportunity on the horizon.
Search Data
Search data can also be chalk full of insights about where certain markets may or may not be going. The basis for this is two major categories that is typically tied to search data:
- Keyword Difficulty (KD)
- Monthly Search Volume
If a market is well-established and highly competitive, KD will be high and search volume will be in the tens of thousands. That’s because thousands of people know what they want, broadly, and are searching for specifics.
The companies at the top of the results will typically be established players with a track record in the industry and a level of trust in their product/service.
The opposite is true with regards to those keywords with low KD and low search volume. These are ‘long-tail’ terms typically that a relatively low % of people are searching for, typically in the low 100s per month. There is, consequently, low competition to rank on those terms.
Patterns and signals can be ascertained from this data that relates to markets. It will depend on the specific industry or trend, but certain keyword data can be an indicator of an inflection point on the horizon, or project future demand for a certain product or service.
Social Data
Hedge Funds will buy and sell stocks based on what is being said on social networks and forums like Reddit. This is the ‘social data’ layer.
Sentiment Analysis can be performed to tap into this layer, even though some believe it to be one of the less ‘scientific’ types of data science relative to the above.
Naturally, by ‘listening in’ on what people are saying online (also called ‘social listening’) and applying some form of NLP (Natural Language Processing) to parse through what they are saying, a lot of insights into ‘what’s next’ can be unlocked.
This type of ‘unstructured data’ (or free text) can be harder to analyze because a lot of language on social networks or forums can be slang, emojis, or other difficult terms that can be hard to analyze at scale. But if hedge funds can use it to buy and sell stocks, tapping into different layers of social data can help source big ideas as well.
Evaluating New Ideas
One of the problems about ‘having ideas’ – even those with some kind of amazing data or insights to back them, is we usually have many ideas. Too many ideas.
Let’s say there are 10 Ideas on the Whiteboard.
First of all, break them down into a Top 3 based on a loose, qualitative criteria.
Then, with a Top 3 in place, develop a Criteria and Scoring process with more quantitative data to determine how to rank each one from 1 to 3. This is where some of the data from above (customer, search, and/or social) may come in handy.
The Business Opportunity Scorecard can also be used to supplement this data and come up with a more objective rubric for what might work and what won’t. Especially given that ‘Capital Required’ is always a consideration.
The Business Opportunity Scorecard
- Product Quality (A – F)
- Margins (A – F)
- Customer Acquisition Costs (A – F)
- Distribution Costs (A – F)
- Capital Required (A – F)
Add it up and ship it. Ideally, you want a niche to dominate and a vertical to scale into over time, but don’t overthink it.
Overall, there are many data points that suggest that being in the top tier of any market makes a huge difference, long-term, from both a market share and financial perspective. Big Ideas are meant to be creative, compelling, and create an advantage in highly-competitive markets.
Certain types of data can help to light the path towards better defining the timing and potential of ideas, but in the end, a decision-making criteria needs to be developed to determine which one is best to go for.
‘Rule of Three’ Case Studies Cited
Ivey Business Journal – Competitive Markets and the Rule of Three
BCG – The Rule of Three and Four
Backlinko – Google’s Organic CTR Analysis
More Rule of 3s Posts
Business Opportunity Scorecard
Instacart Business Model Analysis (Grocery Delivery)