Marketing paradoxes

A lot of credit to for these (i’ve made my own changes to better reflect what i agree with). Check out his content too.

The Paradox of Tribes

To be loved, you must be hated. The binding force of a tribe is typically what they stand against. Crypto communities thrive in part because of what they oppose. ex: Decentralized Finance vs. Wall Street.

The Paradox of Focus

Start small to go big. Do one thing extraordinarily well and your value compounds. Do many things and you dilute impact across all of them. The iPod relaunched Apple. Amazon started by selling books.

The Paradox of (Over-)Selling

The more you feel sold to the less you buy. A purchase is an expression of autonomy. People want to feel like they’re making their own decisions. No one wants to be manipulated into parting with their money. A good salesman guides a customer through the process, not pushes.

Marketing Strategy Course.jpg
SRC: Createx

The Paradox of Popularity
Some brands are victims of their own success. When aspirational products become too commonplace, they lose their appeal. Be exclusive or popular, but you can’t be both.

The Paradox of Price

To sell more, increase your prices. People associate price with value for many physical goods like jewelry and clothing.
Increase desire by raising prices and watch sales rise with it.

The Paradox of Choice

Too much choice paralyzes consumers. Anchor your target price between high and low options to make the middle option most appealing.
Simplify decisions for your customers and they’ll thank you for it.

The Paradox of Scale
To find product-market fit, do things that don’t scale. Talk to every customer. Handle every complaint.
You won’t have something scalable until you find something that a few people LOVE.
A lot of people talk about product scaling being a REQUIREMENT to even start, but generally more niche products are far easier to start with. If you only focus on scalability you will probably never have enough customers for it to become an actual problem.

If you only focus on scalability you will probably never have enough customers for it to become an actual problem.

Statistics basic: stddev and z-score

I’ve been trying to wrap my head around some statistics/data science used for dissecting ddos attacks, and came across a couple of new topics that are quite important but rarely explained.


Standard deviation

Standard deviation is a property of a set that describes the spread around the mean.

Sx = σ = de standard deviation of the set
Xi = The number i in the set.
Xgem = the mean of the set
Nx = the total number of elements in the set

σ = Sx = √( ∑ ( (xi – xgem)2 / nx) )



z-score: easy normalized way of seeing if something is above the average or below, and if it is an outlier (z-score >3 | <3 is often seen as a outlier)

 Z = frac{X - mu}{sigma}.
SRC: statistiekbegleider

mean = average
Z-score = (Measurement – mean) / stddev

In python:

df['zscore'] = ((df['count'] - df['count'].mean()) / df['count'].std(ddof=0)).round().fillna(NONE)