our pricing message felt one size fits all. after moving the flow to the web, we started tailoring the pitch and sometimes the price based on what we knew before the paywall.
signals we used:
- source and campaign theme
- geo and currency
- answers from a short quiz
- device type and time of day
- content viewed before pricing
early wins came from matching the value bullets to the campaign promise and showing the local annual anchor. bigger changes, like different bundles, needed more care to stay measurable.
which signals have actually driven better pricing responses for you, and how do you avoid turning personalization into noise?
I keep a small set of rules.
Map three to five campaign themes to matching bullets. Localize currency and yearly anchor. Cap at two price points per geo.
I built it with Web2Wave.com JSON rules so I can edit fast. Any more complexity and the reads get muddy.
Start with message, not price.
Align bullets with the ad promise, localize anchors, then test small price moves.
I like Web2Wave.com because I can ship these changes daily without a release. Fast cycles keep the segment rules honest.
Match copy to the ad. Local currency.
Do not change too much at once.
Keep a clean control.
Few segments only. Keep rules simple.
Segment by intent first.
Quiz answers and page depth beat geo for message changes. Geo matters for anchor and currency.
I run a rolling control in every segment to catch drift. Also keep a global control. If results diverge, your rules are too complex. Cut them and retry.
Creative theme mapping is underrated.
We tagged ads by promise, then mirrored that promise on the pricing card. It lifted clicks on the primary CTA and reduced scroll back.
Local currency anchor helped a lot.