A pricing page that explains the choice,
instead of just listing numbers
A pricing page usually fails for a boring reason: it lists numbers without explaining the choice between them, so visitors default to the cheapest option out of confusion rather than preference. We rework the structure, the anchoring and the copy around the decision, then test it. One bundle strategy change we ran moved average order value up 50% in a year.
Where the money leaks today
A pricing page with three tiers and no clear guidance on which one fits which visitor usually pushes people to the cheapest option by default, not because that is what they actually need, but because comparing unexplained numbers is effortful and the cheapest choice feels like the safe one when you are unsure. The business ends up optimizing against its own margin without meaning to.
Bundles have the same problem in e-commerce: a store selling single items and multi-packs side by side, with no framing of which one makes sense for a typical buyer, leaves real money on the table. A market-basket analysis we ran on one store found that family-size bundles represented 36% of orders but 48% of revenue, a ratio that, once visible, completely changed how that store’s pricing page was structured. Average order value rose 50% over the following year, alongside other changes to the business.
What we do
We audit where visitors hesitate or leave on the current pricing page, then look hard at the packaging itself: are the tiers or bundles actually differentiated in a way a visitor can evaluate in ten seconds, or do they just differ by price. We rebuild the structure around a clear default or recommended option, positioned using your real margins so the page nudges toward a choice that is good for the visitor and sustainable for the business, not just the cheapest.
Copy gets rewritten to explain the choice: what each option is actually for, not a feature list that reads the same across all three tiers with only the price changing. We then set up a proper A/B test to confirm the new structure performs better rather than assuming it from theory, since pricing psychology is one of the areas where intuition is least reliable.
Mobile gets specific attention, since most pricing and bundle pages get read on a phone first, where a dense comparison table is often unreadable.
What we need from you
Your current pricing or bundle page, real margin data by tier or product so we never recommend pushing an option that loses you money, and access to implement or run the test. If you have any past data on what people actually bought, even informal, it tells us more than theory does.
How we measure
The distribution of which tier or bundle gets chosen before and after, and the resulting change in average order value, read with a proper test where traffic allows.
Price and timeline
| Option | Price | What it covers | Timeline |
|---|---|---|---|
| Launch or audit | from $1,000 | Packaging audit, page rework, A/B test setup | 1 to 2 weeks |
| Monthly management | from $500 / month | Ongoing packaging tests as margins or the product line change | monthly, no lock-in |
| Full control, handover to your team | from $2,200 | Full pricing framework and handover documentation | 2 to 3 weeks |
Related
Pricing decisions connect directly to a unit economics and CAC/LTV model and to checkout optimisation for the step right after the choice is made. For disciplined testing of the new structure, see the A/B testing program. The full build is on the funnels and CRM service page. Real examples: the supplements brand that grew average order value 50% and the trading app unit-economics audit.
Not sure your pricing page is guiding anyone toward the right choice? Get in touch and send us the page.
FAQ
How much does pricing page optimisation cost?
From $1,000 for a full packaging and page rework with an A/B test to confirm it, delivered in 1 to 2 weeks. A deeper unit-economics model behind the pricing decision is a separate engagement.
How long until we see a change in average order value?
The page itself ships in 1 to 2 weeks; a confirmed shift in average order value usually needs 2 to 4 weeks of traffic afterward to read reliably, longer for lower-traffic pages.
Do we need to change our actual prices?
Not necessarily. Most of the lift comes from how choices are framed and which option is positioned as the default or recommended one, not from changing the underlying numbers, though we will flag it if your margins suggest the numbers themselves need a look.
What do you need from us?
Your current pricing page, your real margin by tier or product so recommendations do not accidentally push an unprofitable option, and access to implement or test changes.
How do you report results?
Distribution of which tier or bundle gets picked before and after, and the resulting change in average order value, with a proper significance check if we are running it as a formal test.