Experiment Library
10 Pricing Page Tests That Affect Revenue, Not Just Clicks
Pricing pages sit at the bottom of the funnel, so even small improvements compound into real revenue. Each experiment below includes a hypothesis, the change, the metric to track, and what can go wrong.
Toggle & Default Behaviour
1. Default to annual billing
Hypothesis: Pre-selecting the annual toggle will increase the share of annual plans chosen because most visitors accept the default, and the lower per-month price shown will reduce sticker shock.
Change: Set the monthly/annual toggle to "Annual" on page load.
Primary metric: Percentage of new subscriptions on annual plans.
What could go wrong: Some visitors may feel tricked if the switch is not obvious. Make the toggle large and clearly labelled.
2. Show per-month price on annual plans vs. total annual price
Hypothesis: Displaying "$29/mo billed annually" instead of "$348/year" will increase annual plan selection because the monthly frame feels smaller and is easier to compare against monthly pricing.
Change: Reformat the price label. No pricing changes.
Primary metric: Annual plan selection rate.
What could go wrong: Almost nothing. This is a framing change, not a pricing change.
Plan Emphasis & Anchoring
3. Highlight the middle plan vs. the cheapest plan
Hypothesis: Adding a "Most Popular" badge and subtle border highlight to the mid-tier plan will shift plan distribution upward because the visual emphasis acts as a recommendation signal.
Change: Add a badge and slight background change to the mid-tier column.
Primary metric: Plan distribution (share of mid-tier signups).
What could go wrong: If the mid-tier price is much higher than the lowest tier, the badge alone will not bridge the gap. Ensure the value gap between tiers is clearly explained.
4. Add a high-priced enterprise column
Hypothesis: Showing a visibly expensive enterprise tier (even as "Contact Us") will make the mid-tier plan feel more reasonable by contrast, increasing mid-tier conversion.
Change: Add a fourth column with enterprise features and a "Contact Sales" CTA.
Primary metric: Mid-tier plan conversion rate.
What could go wrong: An enterprise column that looks empty or poorly defined can reduce trust. Only add it if you can list real enterprise features.
Trust & Objection Handling
5. Add a money-back guarantee badge
Hypothesis: Showing a "30-day money-back guarantee" badge near the CTA will increase paid conversions because it reduces perceived financial risk.
Change: Add a small badge or text line beneath each plan's CTA button.
Primary metric: Checkout initiation rate.
What could go wrong: If you do not actually honour refunds easily, this creates a support burden. Only add if refund policy is real and simple.
6. FAQ position: below pricing table vs. inline accordion
Hypothesis: Moving the top 3-4 pricing FAQs into a compact accordion directly beside or below the pricing table will reduce drop-off because visitors get answers without scrolling away from the decision point.
Change: Place an accordion FAQ section immediately beneath the pricing columns. Keep it to 4 questions max: billing cycle, cancellation, what happens after trial, and upgrade/downgrade policy.
Primary metric: Pricing page exit rate; secondary: checkout starts.
What could go wrong: Too many questions can clutter the layout. Limit to objection-focused questions only.
Feature Comparison
7. Expandable feature table vs. full table always visible
Hypothesis: Collapsing the full feature comparison table behind a "Compare all features" link will increase CTA clicks because the table currently pushes the CTA below the fold and overwhelms visitors who do not need granular detail.
Change: Show the top 5 differentiating features. Hide the rest behind an expand link.
Primary metric: CTA click rate on pricing cards.
What could go wrong: Power users who need the full table may miss it. Make the expand link prominent.
8. Checkmarks vs. descriptive feature labels
Hypothesis: Replacing generic checkmarks with short benefit-oriented descriptions (e.g., "Unlimited A/B tests" instead of a check under "Testing") will increase plan selection because visitors understand what they get without cross-referencing a legend.
Change: Rewrite feature row labels to be self-explanatory. Remove the check/cross icons where possible.
Primary metric: Plan CTA clicks.
What could go wrong: Longer labels can make the table wider on mobile. Test on small screens first.
CTA & Urgency
9. "Start free trial" vs. "Start my [Plan Name] trial"
Hypothesis: Personalising the CTA text to include the plan name (e.g., "Start my Pro trial") will increase clicks because it reinforces the visitor's choice and creates a micro-commitment.
Change: Update each plan's CTA button text to include the plan name.
Primary metric: Per-plan CTA click rate.
What could go wrong: Very little. This is a copy-only change.
10. Limited-time discount banner vs. no discount
Hypothesis: Showing a genuine time-limited discount (e.g., "20% off annual plans this month") will increase paid conversions because urgency accelerates decision-making.
Change: Add a banner or strikethrough price on the annual toggle.
Primary metric: Paid conversion rate; secondary: refund/churn rate in first 30 days.
What could go wrong: Fake urgency erodes trust fast. Only run this if the discount is real and expires on a real date. Watch churn: discount-motivated signups may churn more.
When to Run These
Pricing page tests affect revenue directly, so you need reliable traffic volume to reach significance. Use the sample-size calculator to check. Start with low-risk tests (1, 2, 5, 6, 8, 9) and only run urgency-based tests (10) when you have strong data showing that price is the primary objection.