Think about the bold ideas that have the potential to move the needle enough to make a bigger splash.
Most marketers don’t have the luxury of millions of pageviews on their sites each month. As a result, it can take weeks or months for an A/B test to reach statistical significance for these sites. Testing ideas often becomes time consuming and costly, driving marketers to create long backlogs of ideas they want to test and debating how to prioritize those lists. Worse, marketers may end up giving up on data-driven testing altogether, costing them potential conversions on their website.
What can you do to test, learn, and grow quickly on 1,000 pageviews a day? We have three suggestions:
Focus on incremental conversions
If you are only testing a handful of ideas every year with a typical site’s traffic, waiting for statistical significance may work for you. However, if your marketing strategy would benefit from dozens of tests a year, A/B testing will usually not yield results fast enough for you to meet your goals.
We suggest asking yourself why statistical significance is important. We believe most marketers want significance so that you can generate incremental conversions from your website and know the conversions aren’t due to chance.
If incremental conversions are the point, then we suggest focusing on them. More conversions means more revenue, customers, etc.
We further suggest keeping a holdback group, often also called the control group. This group will see your existing website rather than the tests you’re running, enabling you to measure apples-to-apples lift of your ideas over time.
Test your biggest ideas and spread your bets
If your daily pageviews are in the hundreds of thousands, a fraction-of-a-percent improvement can mean significant growth. However, if you’re working with smaller numbers, any individual small win has less value. For example, if you drive a 0.15% increase in conversion rate by changing a button color and your site has 2,000 visitors a day, that means 3 more conversions per day. For most companies that won’t move the needle.
So test your biggest ideas now. Think about the bold ideas that have the potential to move the needle enough to make a bigger splash. A bunch of small ideas can also add up to something big, and we suggest starting with the bigger ideas.
Then spread your bets. Instead of trying ten variations of a single page element (such as 10 different headlines), try a couple variations for five different elements on your page (such as two headlines, two call to action texts, two hero images, two layouts, and two abandon modal ideas). Your site visitors will tell you which elements to invest more in through their behavior. Once you see lift by changing one element of the page, create similar, derivative variations of those high performers to drive even more lift.
Use predictive personalization to automate and accelerate your testing
Predictive personalization enables marketers to test more ideas with less work. Marketers with low traffic often test many ideas at once and see results in days rather than months. This is possible because predictive personalization automates the process of allocating traffic to your best performing ideas.
One client working with Intellimize was able to test 39 ideas (which yield a total of 633K possible versions of the page) on less than 2,000 daily pageviews and saw a 70% lift in referrals overall, with a 27% lift in conversions within the first month alone. With a traditional A/B test this would have taken 11 months to reach statistical significance and they would have lost out on conversions while waiting for their tests to end.
Even without a large volume of traffic, marketers can use data driven approaches to optimize their conversion rate quickly. We suggest:
- Focusing on incremental conversions to optimize for what matters
- Testing big ideas to improve the likelihood that your tests will have a material impact
- Using predictive personalization to test more, learn what works more quickly, and automatically allocate more traffic to your best ideas
Instead of trying to fit your company to a testing model that doesn’t suit it, focus on these three ideas to drive better performance more quickly.