The idea
With 200,000 units at Rp 35,000 contribution and a cross-price elasticity of 0.5, doing nothing loses Rp 0.7 billion a month, a blanket match loses Rp 2.0 billion, and a targeted match for 40,000 at-risk customers loses Rp 0.4 billion, if the churn model finds the right customers. A blanket match also signals that you will follow every cut.
Use it thoughtfully
- Check whether the cut is permanent before reacting.
- Use cross-price elasticity to size the threat.
- Target the match at customers likely to leave.
An example
ILLUSTRATIVE EXAMPLE: An Indonesian competitor cuts a 10 GB pack 20%. A targeted match for 40,000 at-risk customers loses Rp 0.4 billion a month, against Rp 2.0 billion for a blanket match.
A question to try
How accurate was your churn model the last time you used it to target a match?
A useful framework is a starting point, not a guarantee. Effects vary with the audience, product and situation. Use truthful evidence, respect customer choice, and test the result.