Digital Superfecta Leg 2: E-Commerce Conversion
Last week, I introduced the concept of the “Digital Superfecta.” These are the four things companies need to be great at to take full advantage of the digital world. We focused on the first leg of the Superfecta: qualified lead generation.
This week, we shift gears toward e-commerce conversion, which we define as “the percentage of your traffic that completes a defined objective.”
Usually, conversion means “sale,” but in the digital world it can also include actions such as providing an email address, reading an article, filling out a customer lead form, and so on.
Conversion is a broad topic, and a lot has been written on the subject. Here’s a brief overview of our philosophy to set the stage.
Optimizing Conversion is a Three Part Cycle
Excelling at conversion entails mastering a three-part cycle: setting objectives, measuring results, and correcting course.
For example, we might set an objective of selling our membership program to 2% of traffic that reads an article. We measure the percentage of people that convert from an article to a paid membership. If we fall short of our 2% goal, we analyze and modify our site accordingly. Perhaps the value proposition was not explained well enough, or too many clicks were needed to get through the checkout process, or customers needed to engage with three articles before becoming primed to buy. In any case, we use the results to change our user experience, then re-run the experiment and re-measure the results.
I have found three common mistakes companies make when trying to optimize conversions.
Mistake #1: Too Many Objectives Per Page
“Hey, read these eight articles!”
“You over there – sign up for our newsletter!”
“Mister, Mister, sign up for a free trial subscription!”
“Ma’am – be sure visit our sponsor’s website!”Disciplined companies have one clear objective per page. Sometimes you’ll need to have two— or maybe even three—different call to actions, but if you have more than that, you’re probably confusing your visitor and hurting conversion.The Paradox of Choice, author Barry Schwartz explains why too much choice has proven to be detrimentalto our psychological well-being. He says eliminating choices can greatly reduce stress. Here is a summary of one experiment Schwartz described to illustrate his point:
Researchers set up a display of “exotic, high-quality jams” in a gourmet food store. “Customers who came by could taste samples, and they were given a coupon for a dollar off if they bought a jar. In one condition of the study, 6 varieties of the jam were available for tasting. In another, 24 varieties were available. In either case, the entire set of 24 varieties was available for purchase. The large array of jams attracted more people to the table than the small array, though in both cases people tasted about the same number of jams on average. When it came to buying, however, a huge difference became evident. Thirty percent of the people exposed to the small array of jams actually bought a jar; only 3 percent of those exposed to the large array of jams did so.”
How can you limit yourself to one to three goals? Your objectives should be context-specific. For example, if the page is where cold traffic arrives, your goal should be to get the consumer to read a piece of content. If you’re page is for warm leads (consumers who have spent some time with your brand), you probably want the goal to be around lead capture (e.g., provide an email address in exchange for a whitepaper). If it’s a place where hot leads will visit, that’s when you should ask for the sale.
Mistake #2: Asking for the Sale Too Soon
Sorry, Glengarry Glen Ross fans, you shouldn’t “Always Be Closing.” (For those familiar with the play/movie: Coffee is also for lead nurtures in the digital world.)
Don’t get me wrong – you have to ask for the sale at some point. Mistake #2A is not asking for the sale at all. But it needs to come at the right moment.
I’ve seen a few websites that use an interstitial (pop-up ad) to ask for a sale way too soon. If I land on your page as a result of a Google search, and within three seconds you ask for my credit card, chances are I will go away. You’ve lost your chance to nurture me.
If, instead, after I engage with your valuable content, you offer me a related how-to guide in exchange for my email address, I am much more inclined to gift you such information.
You can continue to provide valuable, useful information to me via email. Then, once you see I am engaging with your emails, you can send me a hard offer and go for the close.
Mistake #3: Jumping Quickly to Conclusions from A/B Tests
A key tool to conversion optimization is A/B split testing, i.e., creating two different user experiences and seeing which version (Version A or Version B) leads to higher conversions.
This is an extremely powerful tool, but I’ve seen it abused. I’ve seen too many companies get overly-excited because the yellow box led to a 20% lift in sales over the green box. They jump to the conclusion that sales are going to skyrocket as a result.
Usually there are two root cause problems associated with this over-exuberance: 1. The variable being tested was not meaningful, and 2. The sample size was not sufficient.
To derive actionable insights from A/B tests, companies should strive to understand the why behind the results. What specifically about the variation likely led to the higher conversion rate? This will help you make better guesses in the future when setting up the next A/B split test.
Furthermore, you need to have a statistically significant sample size to draw conclusions. I like this tool for determining the number of visitors you need to have a valid test. Try it out – you’ll probably realize your existing samples sizes are too small.
This is particularly a problem for price tests, because the number of people who actually convert is much smaller than the total number of visitors. You need really long time periods to have enough data to declare a winner in a price test. While we still recommend A/B price tests, we recommend starting with other types of analyses, like the Van Westendorp Price Sensitivity Meter, since we know that it will take a long time to run a statistically meaningful A/B price test.
The beauty of the digital world is that tools and techniques are available to avoid these three common mistakes. Next week we will move on to the third leg of the Digital Superfecta and discuss digital product management.