Psychometrics works well and can be ethically used but when fools are added to the equation, things go very bad.

Recent headlines have put many of us in a reflective move. We are collectively retracting our steps, discovering the power of data and how it can be used for us and against us.

When you write on Facebook, you should not be surprised when they use it to sell better ads to a targeted audience. But you should be surprised when they allow the machine to hand it off to others. An election is a lot bigger than advertising a clothes.

Marketers have to segment. If they did not, they would be marketing shotguns to nuns. Marketers have to segment to cut the possible audience down to a small ‘tribe’ of people. Since 1890, this has been done by the punched card system method. Almost everything sitting in your house today was bought by a company using the foundations of this system. Now, marketing needs to reflect on the mess it made.

A map of German ancestry in 1890. The American 1890 census was the first to be machine-tabulated. Because of this, the bureau was able to add new, detailed questions and observe micro-trends in the American population.

A Brief History of Machine Personalities The Character & Ephemera From a Century of Machine Thinking.

What should be in place starts with ownership and control of our data. You choosing to provide it or not. If you provide it, it should come at a cost. Maybe building an blockchain enabled technology would allow for 1:1 marketing and a fair exchange of value.

Sadly, Facebook is struggling right now. They made poor decisions that many marketers and publishers before avoided. It’s a bad situation to be in. The market and world will now decide its fate.

Modern psychometrics at scale - the United States by State.

When I decided to invent my version of psychometric analytics, I chose to live by a few rules:

  1. Never use it to make people poor, hurt, or do anything evil.
  2. Psychoanalytics must give better choices to business and consumers. It’s not about manipulation of one side but balance. Providing better choices helps people. It limits the bad buys, the unhappy results when you bought something that does not fit who you are. Since almost all our buying decisions are 'emotion', why not match what fits.
  3. Never market to anyone under 18 years old.
  4. Be non-invasive. Never ask people to give up information. What we did is create theories of people and how those activities could bridge to personality traits. There is no need for cookies or surveys. You can create a great tribe with very little data. Having too much data, weak in value, is a bad crunch.
  5. All sources of data are publicly available sources. Example: a list of people who scuba dive, own horses, like art, etc. By creating a bridge between these activities, we found a way to calculate what likely traits are associated with people. Then we re-cluster the data into meaningful tribes that help business describe products, reach the right people. The goal is to create multiples of higher value than using ‘data from the past’ methods (cookies, browser history, etc).
  6. Combining theories of people with business data, you have a solid picture of the business, that helps create macro-economic business predictions. For a business to function well, it needs to have a reasonable prediction of its own future.
  7. Avoid cookie data, browser history and mobile location data to be a better marketer. Invasive data has limited value if you adopt predictive systems, based on sources of truth. Too much data leads to indecision and bad decisions.

Ethical use of data can be used to help consumers choose products wisely, but when data is used to manipulate people, trust is violated and we get to where we are now.