Re:How we de-risked our SaaS pricing strategy
by gingerlime on Wednesday March 01, 2017 @09:36AM
(#13763897)
We did very limited experiments so far, mainly due to the fact that we feel it's unfair to offer different prices at the same time on the website. (And even if we didn't, some users might figure it out and/or complain).
We did a few experiments via email, where we offered a different discount to different cohorts. For example, some people will get an offer for 20% discount, and others for 40%. We tried to extrapolate pricing elasticity from that, but it's still hard... We have a few ideas for other experiments, but didn't get round to it yet. It's one of the areas we need to be more careful.
I'd be happy to talk to you and try to understand what you have in mind. (I didn't quite). Hope it's ok to contact via the contact details on your profile? (Or feel free to reach out to me.).
It would look something like:
1. Use historical price data to determine the optimal price for each customer given what we know about them. 2. For a small number of customers (<10%), randomly adjust prices slightly to find additional data.
Once we have the data, we could find the price elasticity for customers (elasticity = % price increase / % change in purchases; so if elasticity is > 1, it makes sense to increase prices, if elasticity is < 1, you should decrease it), and use that to increase prices.