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SaaS

A pricing page that answered the only question people had

Usage-based pricing that nobody could estimate. Support tickets told us exactly which number people were trying to work out.

Primary result

+18.9%

pricing to signup rate

ControlVariant

Overview

Where we came in

A developer tool billing on API calls with three tiers and an overage rate. Traffic to pricing was healthy and intent was high, but the page was the last thing a large share of visitors ever saw. The support inbox held the answer: the same question, phrased forty different ways, all of them asking what a normal month would actually cost.

The baseline problem

  • Pricing was expressed per 1,000 calls, but customers thought in requests per second and monthly active users.
  • 31% of support tickets originating from the pricing page were cost-estimation questions.
  • Session replay showed repeated scrolling between the tier table and the overage footnote, a pattern of people trying to do arithmetic on the page.
  • Exit rate on pricing was 58%, well above the site average.

Hypothesis

What we expected, and why

Written before the test was built. Because we observed X, we expect Y, measured by Z.

Because visitors cannot convert usage they understand into a monthly bill they can approve, we expect that an interactive estimator that outputs a single monthly figure will increase signups from the pricing page and reduce cost-related support contacts.

Experiment plan

How the test was set up

Sample size and stop date were both fixed before launch, so no result here was called early.

Two-arm split test on the pricing page. Control kept the static three-tier table with the overage footnote. Variant added an estimator above the table: a request-volume slider that named a monthly figure and highlighted the matching tier as the slider moved.

Primary metric
Signup rate among pricing page visitors
Traffic
~9,700 visitors per arm
Duration
28 days
Guardrails
  • Average contracted tier value, to catch the estimator talking people down into cheaper plans
  • Pricing page load time, since the widget adds JavaScript
  • Trial-to-paid conversion downstream

Results

What actually moved

Control and variant values for each measured metric, with the change between them
MetricControlVariantChange
Pricing to signup rate11.15%13.26%+18.9%
Pricing page exit rate58.0%49.4%-8.6pp
Cost-question support tickets84 / mo39 / mo-53.6%
Average contracted tier value$318$326+2.5%
Trial-to-paid conversion22.4%23.1%+0.7pp

The worry going in was that an honest calculator would talk people onto cheaper plans. It did not. Visitors who could predict the bill picked slightly larger tiers, which is the usual pattern when uncertainty is what was capping commitment.

What changed

Shipped to production

  • Interactive estimator added above the tier table, defaulting to the median customer volume rather than to zero.
  • Overage rate moved out of a footnote and into the estimator output, where it changes a number people can see.
  • Tier names rewritten from Starter, Growth and Scale into the volume bands they actually represent.
  • A worked example for the three most common integration patterns added below the table.

Next experiments

Already in the queue

  1. 01Test an annual toggle with the saving stated in dollars rather than a percentage.
  2. 02Test surfacing the estimator on the docs pages where evaluation actually happens.
  3. 03Test a self-serve enterprise path against the current contact-sales gate.
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