All Latest 502 A/B Tests

In this experiment, a pricing plan selector was shifted from the very bottom of a long product page towards (almost) the top. Impact on any transactions or sales was measured.

In this experiment, a single focus signup was transformed into a pricing comparison table. Impact on signups was measured.

In this experiment, the variation added a second total price at the bottom of the checkout screen just above the checkout button. The impact on sales was measured.

This experiment tested the order of purchase plans. The control version sorted the purchase options by the least expensive while the variation sorted them by the most expensive first. Impact on sales and revenue was measured.

In this experiment, a 3 plan vs 2 plan pricing page was shown to potential customers. Impact on sales and revenue were measured.

In this experiment, the only change was an added message at the top of the pricing screen, clarifying that there is an active discount on a yearly plan. The discount was already communicated with a strike-through price on the control version as well. The variation simply emphasized this aggressively. 

In this experiment, the B variation property prices were framed using higher and crossed out price points from 12 months ago - achieving a relative discount. A tooltip was also shown which explained the higher price point on hover. The example in the screenshot translates to "2% less compared to 12 months ago". This high-power experiment measured the number of leads that were generated on property (product) screens.

In this experiment on a casting call site, pricing information was shown beside the application button. This change shows the effect of setting a price expectation and being more clear that the application process is not free.

The core hypothesis of this experiment was that by showing clear availabiltiy (in green text) beside each casting call, more users would apply and become premium members. The experiment reports on two metrics: application starts (the first progression metric), and premium membership sales (merasured a few steps further in the funnel).

In this experiment, the order of pricing plans was rearranged as to show the most expensive one first.

In this experiment, all three prices of each plan were shifted higher for greater visibility.

In this experiment, the three pricing plans were condensed into a single recommended plan (annual), with a secondary option to choose the monthly plan.

In this experiment, the $69 payment was explained as $6 per month over 1 year, and the $89 was explained as $4 per month over 2 years. 

In this experiment, 4 things were adjusted in the variation: the highest pricing plan was shifted to the left, it was set as the default one, the recommendation was also adjusted to point to the highest plan, and one benefit from the lowest plan was removed (customer support).

In this experiment, two pricing plans were inverted to show the most expensive plan first (in the variation).

This test deprioritized the free option (kostenlos) of cancelling a contract. It did so by placing it under the paid options as small text link / radio option.

The idea is that, if the customer has an active discount code for that session (either by landing on a particular page, or entering a code somewhere), instead of just showing the discount in the basket, we show it further (earlier) up the funnel and automatically discount on the product page.

The effectiveness of this depends on the discount level, I've tested it at 30% and 50%.

With a 50% Discount:
Add to Cart rate +33%
Sales rate + 24%

With a 30% Discount:
Add to Cart rate +11.6%
Sales rate + 10.2%

Olark's homepage was directing users towards a free forever trial - with followup nudges to upgrade some days later. The variation B of the experiment tested a more aggressive push to a pricing page page - with options to select a paid plan, as well as provide a credit card (getting the payment conversation out of the way sooner).