Server Density is a hosted server and website monitoring service. They monitor websites from locations around the world combined with internal server metrics so you know when your site is down and have the server metrics to figure out why. After reading this account of how increasing prices increased overall revenues, David from Server Density wanted to try something similar. He used Visual Website Optimizer, the world’s easiest A/B testing software to setup and run this test.
There were two hypotheses:
- Increasing the price of their service will reduce free signups
- The increased price will increase revenue in spite of the reduced signups.
The test had two goals:
- Free trial signup (Goal 1)
- Upgrade (Goal 2)
Goal 1 was completed when visitors signed up for a free trial and Goal 2 when they upgraded to a paid account. Server Density’s initial pricing page looked like this:
The control was configurable pricing where customers paid based on the number of servers and websites they wanted monitored. It simply assumed that there is a direct correlation between entities monitored and value provided. Though the majority of their customers have 7 servers, they had this pricing structure to cater to first time, single-server users in the hope of increasing their customer base. Also, most of their customers complained about their prices.
In spite of the complaints, they decided to A/B test a new “packaged” pricing structure where the lowest package started from US$99 per month. Here’s the variation screenshot:
As you’ll notice, 10 servers and 10 websites according to the old plan would cost US$130 per month, so they have dropped prices but increased the Average Order Value (AOV).
Goal 1: Free signup
Control (per unit pricing): 1950 visitors, 135 conversions, 6.92% conversion rate
Variation (packaged pricing): 1925 visitors, 100 conversions, 5.19% conversion rate
Result: Free signups dropped by 24.96%
Goal 2: Paid upgrade
Control (per unit pricing): 1950 visitors, 20 conversions, US$19.70 AOV, total revenue US$394
Variation (packaged pricing): 1925 visitors, 15 conversions, $55.53 AOV, total revenue $833
Result: 114% increase in total revenue
The key insights generated from this test are:
- Pricing is important to get right and the best way to do that is to test hypothesis with real data.
- Most of your customers care more about the value your product provides them rather than how much it costs you to operate.
- Therefore, you should base your prices on what your product is worth to your customers and not on how much it costs you or the profit you want to make per sale.
- Always be testing; you don’t know where you’re leaving money on the table.
Other articles on pricing
A/B testing of prices, promotional offers, pricing packages and price display come up quite often in our interactions with Visual Website Optimizer customers. Here are some of our other articles that should be of interest:
- Stop guessing! Use A/B testing to determine ideal price for your product
- How pricing plans evolved over time for a SaaS startup
- Coaxing out every possible dollar: a “Pricing Page” test you can launch today
- Ecommerce website? Bring price and add-to-cart button closer to increase sales
- 107% increase in sales shows that customers care more for authenticity than low prices
Your views please
What are your thoughts on this test? Have you conducted any similar tests and if yes, what was the result? If you have any views or would like to contribute a similar case study for our readers, please email us at email@example.com.