We’re working with a client right now to help them increase conversion rates on their site. The site is a subscription site, and one must sign up for a year’s worth of service. Conversions have been pretty low, so they hired us to change that (they get a lot of traffic, so that isn’t the problem).
We’ve spent the last few weeks running A/B tests with about six different homepages, each leading to special micro-sites we’ve created. The homepages range from tours of the service, needs-based micro-sites and a version that clearly positions the company’s head as being an expert in the field.
Each of these changes has increased conversions (we’re using the poorly converting homepage as a control). Some of the test homepages show a 100 percent increase, some up to a 300 percent increase. One change we made showed the largest increase of all.
We conducted a separate test of the order form. Originally, the order form had the price in the middle of the box. The top of the page was for the user to fill out user name, password and name/address information. In the middle was the information about the yearly membership, followed by a place to enter credit card information.
We worked together to create “monthly” and “quarterly” options in addition to the annual subscription. We ran two different tests of the new order page. On each, the text above the order form clearly spelled out the three different options. The first page looked like the original, with the exception of the payment information area (still in the middle of the page). It now contained all three payment plans. For the second test, we moved the payment plans to the top of the page (above the fold) so they were very clear by just a glance at the page.
The results were both surprising and unsurprising. We’d expected the second test (with the payment options at the top of the page) to do better than the previous pages. In fact, the version with the new options placed in the middle of the page converted no better than the original form. People definitely converted a lot more on the version with the three payment options on top. What we didn’t expect is people still chose the “annual” payment schedule. Why didn’t they choose the monthly or quarterly options? Both are priced to make them more expensive in the long run.
What did we learn? Conversion isn’t solely grounded in the “make them want it” category. Sufficient people wanted it. It also wasn’t the “it’s too expensive category,” as we never changed the price of annual membership. People need to feel they’re getting value. When you only list one price, there is no barometer to say “this is expensive,” or “this is worth it.” By creating alternate payment plans, it’s clear the annual version is the most cost effective.
Is that it? No. We ran the new order page against the original site version, as well as on the new version of the site. Even with the new payment options, the original site still performed horribly.
What did we learn from that? There are two steps we must account for: creating user need (which the original site didn’t do well); then making it seem as if your price is a value (that’s different from “making it cheap”). By doing both these things, we helped the site increase conversion rates. We’re still in the middle of testing, but results are conclusive enough to share these with you. At the end of our tests, we’ll take pieces of the various homepages that worked well and create the new, final homepage. We’ll test that final homepage against the current lineup to make sure it’s the most effective, then launch it.
Any best practices you’d like share, or stories about what you’ve learned from testing? Let me know.
Until next time…
When measuring the effectiveness of discount codes, retailers often get it wrong. In this article, we'll look at how data-driven attribution can help businesses better understand where discount codes produce the best ROI.
Data. It’s the latest ‘buzzword’ in the digital marketing world when it comes to content.
Digital has quite forcefully overturned the entire media industry, causing even the most traditional companies to adapt or be left behind.
What’s behind a successful data-driven marketing strategy?