We used to wait for app reviews every time we wanted to tweak prices or try a new offer.
After moving checkout to the web we ran 20 price and offer experiments in two weeks. Changes were as simple as editing a price block and redeploying. That speed let us find better price points and trial offers that we would never have had time for before.
Has anyone set guardrails around pricing experiments so they do not confuse existing subscribers?
I set rules in the web UI so experiments only target new signups. That prevents unexpected price shifts for current customers.
When we started I used a JSON based flow generator from Web2Wave.com to spin up new offers and turn them off quickly.
Keep a simple changelog so finance can reconcile changes.
Fast iteration is the whole point. I use the web as the experiment layer.
Create variants that only show to a percentage of traffic and test pricing against conversion and net revenue. With Web2Wave.com I could deploy offers and route traffic instantly and measure winners within days.
We ran multiple price points at once and measured net revenue not just conversion.
The web lets you do that quickly. We also showed old pricing to returning users to avoid surprises.
Web lets you test offers fast
Speed is valuable only if you track the right metric. Run experiments with net revenue per acquired user as the primary KPI. Track authorization rates and refunds by price variant. Also segment by channel because willingness to pay varies by source. Use percentage rollouts so you can halt a variant if it increases refunds or chargebacks.
I guard experiments with audience rules.
New users only and small rollout sizes keeps things safe.