I’m reading “The Psychology of Judgment and Decision Making” by Scott Plous. It’s a really interesting book.

Plous explains:

“As the amount of detail in a scenario increases, its probability can only decrease steadily, but its representativeness and hence its apparent likelihood to subjects may increase”

The more detailed the description is, the more likely we are able to imagine it. Imagining a situation helps increase the situation’s perceived likelihood vs. a situation we find difficult to imagine.

Plous describes an experiment by Tversky & Kahneman in 1982:

“Linda is 31 year old, single, outspoken, and very bright. She majored in philosophy. As a student she was deeply concerned with issues of discrimination and social justice, and also participated in antinuclear demonstrations. Please check off the most likely alternative:

A] Linda is a bank teller
B] Linda is a bank teller and is active in the feminist movement”

When this scenario was presented to 86 subjects, nearly 9 out of 10 selected “B”. The study authors found similar results with “Bill”, who was thought more likely to be an accountant and a jazz player than simply a jazz player.

Keep in mind that there is nothing in the description to indicate that Linda is a bank teller, but apparently enough to indicate that she is a bank teller *and* a feminist?!?

Some OSS vendors currently converting ~0.01% of their user downloads base into paying customers would love to increase their conversion rates. Some vendors do so with proprietary extensions or product versions, or by providing ‘enterprise’ binaries for paying customers.

Could more detailed descriptions of situations where paid support would be beneficial help raise the conversion rate?