Decision Tree — Test Market Before a National Launch
The value-of-information classic: a regional test with Bayes-consistent posteriors (0.694 after a favourable read, 0.118 after an unfavourable one) is worth $4,421k against $3,600k for launching blind, so the $800k test pays for itself and the tree abandons after a bad read. Illustrative values.
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title "Run a regional test market before the national launch?"
subtitle "Contribution NPV, US$ thousands — posterior probabilities by Bayes' rule"
currency $
unit k
risk-profile compare
note "Prior P(success) = 0.40. The test reads favourable for 85% of eventual successes and 25% of failures, so P(favourable) = 0.49, P(success | favourable) = 0.694 and P(success | unfavourable) = 0.118."
note "Illustrative values for a fictional consumer-goods launch."
decision "Test first?"
"Run a 12-week test market" cost 800 -> chance "Test result"
"Favourable" p 0.49
decision "After a favourable read"
"Launch nationally" -> chance "National outcome"
"Success" p 0.694 -> 18,000
"Failure" p rest -> -6,000
"Abandon" -> 0
"Unfavourable" p rest
decision "After an unfavourable read"
"Launch nationally" -> chance "National outcome"
"Success" p 0.118 -> 18,000
"Failure" p rest -> -6,000
"Abandon" -> 0
"Launch nationally now" -> chance "National outcome"
"Success" p 0.40 -> 18,000
"Failure" p rest -> -6,000
"Abandon the product" -> 0