Talk of conversion rate optimization is everywhere. From ecommerce to landing pages, social media to email and webinars, everybody’s hunting for those most elusive of digital big-game beasts: more clicks, more money, more growth.
The problem is most CRO guides come off sounding something like this:
Step 1: Change the color of your call-to-action button during checkout.
Step 2: Run an A/B test.
Step 3: Get a major lift in clicks, strike it rich, and retire to St. Barts.
Easy, right? Well, not so much.
Misconceptions about CRO abound, even when it comes to something as basic as defining success and failure. To help you separate CRO myth from CRO fact, we’ve put together this list of common mistakes made by CRO practitioners—and what to do to get your strategy right.
Nine common CRO mistakes to avoid
- Slow loading times
- Deprioritizing experimentation
- Vague hypotheses
- Lack of segmentation
- Optimizing for a single device
- Inadequate sample sizes and statistical significance
- Neglecting the post-purchase user experience
- Customizing the checkout page too much
- Overlooking micro conversions
1. Slow loading times
Online shoppers have become accustomed to getting everything they need, fast—and they’re not willing to compromise on those expectations. Our report found that just half of a second can have positive gains on conversion.
The issue is that most ecommerce leaders take their ecommerce platform at face value. They make changes to individual pages in a bid to improve site speed, not recognizing that the ecommerce platform powering their online store has a major impact on how fast the site loads.
Take a big-picture look at your technology infrastructure before making any page-level site speed optimizations. Shared website hosting plans, for example, have a trade-off: they’re cheaper than private servers, but resources are spread across all sites in the group. Should another site on the same shared server get a sudden spike in traffic, your site speed will be compromised.
You’re not alone if your current experience with your existing infrastructure is subpar. The same report found that 57% of CIOs would replace half or more of their company’s current technology to start from scratch if they were given the chance. A quarter said they’d replace most or all of it.
At Shopify, we’ve made huge investments in our technology to help businesses meet their customers’ ever-increasing expectations. All plans are fully hosted by our fleet of servers, which have been proven to be fast and reliable enough for some of the world’s biggest retailers—so much so that Shopify has the fastest server speed in ecommerce. We process site requests up to 3.9 times faster than competing ecommerce platforms.
Site speed isn’t just critical to conversion, it can influence your reputation and a customer’s likelihood of returning to your store. Benchmark your current site speed score amongst competitors in your industry with our free Site Speed Audit.
2. Deprioritizing experimentation
Optimization is about adopting a holistic process to growth driven by one of the least sexy words in business: science. While it might sound strange, this means starting your CRO endeavors at the macro level with corporate culture.
In large companies, getting optimization off the ground can be tough. Testing takes investment, and when that investment returns a negative result, it’s all too easy to chalk the whole thing up as a failure and start pointing fingers. Don’t. With optimization, there’s no such thing as a failed test.
The entire point of good science is to find out what’s not true and what doesn’t work. That’s profoundly counterintuitive to our humanity. We’re accustomed to thinking in terms of right versus wrong, good versus bad, winner versus loser.
Without educating your company culture beforehand and championing the CRO process internally—with a high degree of empathy and patience for those who don’t “get it”—what turns out to be a “losing” test can not only hurt your reputation but easily derail your entire CRO approach.
Adopting a process of optimization means being willing to set aside both and instead embrace whatever road the data points to. And it means being wide-eyed about that from the very start, even in the case of failed tests that don’t turn out how you expected.
“People in Hawaii and people in Texas will react differently to a brand based on the macroeconomics, based on politics, based on so many factors,” says Jeremiah Curvers, cofounder and CEO of Polysleep. “There's a bit of a trap here thinking that because you've got a persona and because you've got a great product, it's gonna work everywhere and anywhere. Don't try to oversimplify, don't create complexity when it's not necessary, but don't think a persona is the same everywhere.”
3. Vague hypotheses
Initially, both split-testing as well as its more advanced counterpart multi-variant testing were designed as a way to determine a target audience’s preferences. But those preferences were never meant to be relegated to the shallow webpage elements many tests now revolve around: big button versus small button or short headline versus long headline.
Rather, these on-page elements were only a representation of deeper underlying thoughts and views about how people behave. In other words, you should start with a big-picture hypothesis and only then proceed to nitty-gritty tests.
Thankfully, it doesn’t need to be complicated. Just follow this simple formula: “I think that changing [element A] to [element B] will produce [qualitative result] and therefore [quantitative result].”
Let’s take a look at what this big-picture hypothesis looks like in action. We’re testing impersonal language in the headline (“Receive a free bumper sticker”) and personal language (“I’ll send you a bumper sticker”).
Your hypothesis needs to go beyond that. A better version would be: “I think that changing the headline from (A) impersonal language to (B) personal language will produce a far more direct and engaging user experience, and therefore increase form completion.”
This way, you can attribute the change in conversion rate to the psychological trigger behind the test. It’s a cheat code that acts as preliminary research for future experiments—you have some prior evidence to show the reasoning behind why previous tests succeeded or failed.
4. Lack of segmentation
Given the fact that not every website visitor shares the same goals, challenges, and pre-purchase anxieties, it doesn’t make sense to run blanket one-size-fits-all CRO campaigns. Instead, run smaller-scale experiments and segment your sample size based on your buyer personas. These are smaller groups of potential customers who share similar characteristics.
Segmentation helps you understand the distinct behaviors, preferences, and pain points of different groups, too. Say you’re optimizing a product page. You narrow down your sample size to only display the control and variant pages to people who’ve already visited your website.
Returning visitors likely already know about your brand and what you sell, and they’ve thought about how the product would slot into their lives. Lack of social proof or trust in your site might be the reason for their first exited session, so you run an A/B test that only targets this segment. The control group sees the existing page, while the variant group sees an additional section that showcases your awards and accolades. Your hypothesis was correct, so you roll out the new element on all product pages for returning visitors.
This approach to segmentation solves the age-old issue of asking stakeholders for more budget. You can identify the highest value segments and prioritize them for experimentation, giving you a higher return on investment—a powerful chess piece that you can use when pitching for budget increases and showcasing the need for CRO.
5. Optimizing for a single device
Many business owners and CRO practitioners design their website and user experience on a desktop, which makes it easy to overlook how the site looks on mobile. It’s an expensive oversight to make. Studies estimate that by 2028, some 63% of all ecommerce sales will happen through mobile devices. Your ecommerce analytics will likely show this trend already coming into fruition.
Furniture retailer Monte Design did exactly that. “Before switching to Shopify Plus, we didn't have a broken-down numbers comparison of our traffic between desktop and mobile,” says their digital marketing and social media specialist Danielle Ott. “Shopify Plus reminded us to check the stats on our mobile version”—and the results made the investment in mobile optimization a clear priority. Some 70% of the brand’s overall traffic was coming from mobile.
Shopify made it easier for Monte Design to optimize their site for mobile. “With our previous ecommerce provider, we had to create the whole mobile site,” says founder Ralph Montemurro. “Shopify Plus is optimized for mobile, which really let us fine-tune our user experience.”
6. Inadequate sample sizes and statistical significance
Say you ran an A/B test, and it concluded that people think you’re the best florist in the world. What you haven’t told them is that the sample size is two: your mom and your sister. While the verdict is true (that 100% of the people you surveyed place high value on your floristry skills), it’s not entirely believable. You can’t assume most people have the same belief.
The same concept applies to A/B testing your conversion rate optimization strategy. You need a big enough sample size for your experiment to be accurate. A larger sample size is more likely to be representative of the entire population, making sure that the test results are generalizable and not just applicable to a specific subset.
Of course, sample size is related to how much traffic your site receives. A store with 100,000 daily visitors will have much more data to monitor user behavior on. One with just 200 daily visitors will need longer experimentation periods to gather enough data to form statistically significant decisions. It will confirm that accurate results observed from the test are due to the changes implemented (such as a new design or feature) rather than random chance or bias.
7. Neglecting post-purchase user experience
Concentrating solely on acquiring new site users rather than optimizing the entire customer journey puts a ceiling on your CRO strategy. While you might excel in turning first-time visitors into paying customers, sustainable revenue lifts come from repeat customers. It’s been proven that despite only accounting for 21% of a brand’s customer base, loyal customers account for 44% of total revenue.
Your CRO campaign needs to encompass this by optimizing for post-conversion actions, such as upselling, cross-selling, and customer support—all of which occur after someone has crossed the milestone of making their first purchase.
Post-purchase optimization is all about creating positive experiences and encouraging shoppers to make another purchase. That might involve:
- Testing whether people respond best to post-purchase emails within one, three, or seven days after their first purchase
- Experimenting with loyalty rewards, like the value of accumulated points
- Using social media advertising to recommend products related to their last purchase
Again, the ecommerce platform that’s powering your interactions with your existing customer base plays a major role in how easy it is to run post-purchase tests. The Shopify App Store is home to hundreds of approved apps that specialize in loyalty and retention, and you can manage them all from the same dashboard you already know and love.
“As a Shopify Plus customer, we have access to the tools, apps and integrations needed to succeed in a multi-channel world,” says Kerri Economopoulos, managing director of Titan AV. “Allowing us to put the customer first and deliver a seamless experience across all channels that builds trust and loyalty in our brand whilst driving growth for our business.”
8. Customizing the checkout page too much
The sheer volume of customization options often creates a debate between optimization and marketing teams. Marketers want apps to improve customer loyalty, promote upsells, and highlight special offers. But CRO teams know that too many apps can have a detrimental effect on page load times and site speed.
Deciding where to cut back can help both teams meet in the middle. Product and landing pages can have more freedom when it comes to customization and third-party apps, such as those from the Shopify App Store.
But the checkout is the final stage in a customer’s purchase process. And considering more than 70% of online carts are abandoned, it’s no surprise why it ranks high on the priority list for A/B testing.
That’s not to say you should rule out checkout optimization entirely. Best practice is to consider the reasons for cart abandonment (such as too many form fields and lack of diversity in payment methods) and work around them—rather than go full force into above-and-beyond customizations that ultimately slow down page load times and lengthen the checkout process.
Businesses running on Shopify already have an advantage in this area. At our base, Shopify has the best performing checkout on the market. We outperform the competition by up to 36%—and when Shop Pay is in the mix, you can increase lower funnel conversion rates by 5%.
As Mani Fazeli, VP of product at Shopify concludes, “At Shopify, we have more engineers working just on making checkout high-converting and performant, than some other companies have working on their entire commerce solution.”
9. Overlooking micro-conversions
Purchases are widely considered to be the holy grail in conversion rate optimization. Revenue is the number one objective of ecommerce stores, so this metric should take priority over others in your CRO campaign, right? Not necessarily.
The unfortunate reality is that ecommerce conversion rates are notoriously difficult to increase. Studies estimate that not even 2 out of every 100 website visitors end up converting into paying customers—but the majority of whom will still complete micro conversions that you might not be tracking.
Monitor how your CRO experiments drive people toward the end goal of a purchase by monitoring these micro-conversions. That could include:
- Newsletter sign up
- Free trial sign ups
- Account registration
- Add to cart
- Specific category, product, or landing page visit
High conversion rates for these smaller events indicates how effective your sales funnel is, and anxieties that people might have prior to converting. For example, if you’re optimizing a product page and 57% of people add a product to their cart yet just 0.5% of them buy the product, it could be your checkout process that needs optimization.
Make CRO a breeze with Shopify’s enterprise ecommerce platform
Conversion rate optimization is an ongoing process for any retailer. But when you build on Shopify, you can rest assured knowing that the foundation of your website is the result of years of experimentation.
And with our enterprise ecommerce platform, you’ll never need to migrate in search of a more customizable platform with a lower total cost of ownership. Our TCO is 33% better than other competitors, on average, and you have the ability to customize your site on the fly—no developers required.
“It took us one week with a developer to create specific templates [on Shopify],” says Vincent Arrouet, CEO and cofounder of Sunology. “I'm not talking about off-the-shelf ready-made pages because there are plenty of those with Shopify. Here, in just five days of development, our customized platform was ready.”
No matter how you sell, we have the solutions for you. Learn more about how we’re powering enterprise commerce now and long into the future.
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Common CRO mistakes FAQ
What are the 6 primary elements of conversion rate optimization?
- Research
- Segmentation
- Experimentation
- Design
- User experience
- Personalization
Is conversion rate optimization worth it?
Conversion rate optimization eases the pressure on marketing teams to consistently drive new people to your site, and instead squeezes more revenue out of the traffic you’re already driving to your site. It’s a much more cost-effective way to generate paying customers.
What is the area that is often overlooked in conversion rate optimization?
Personalization is often overlooked in CRO. A lack of segmentation means that all site visitors get the same on-site experience, but they likely have different pain points, goals, or challenges that they need to overcome before converting.
What are the challenges of conversion?
Slow page load times Lack of buy-in for experimentation Vague hypothesis for testing Lack of segmentation Inconsistent messaging Failure to reach statistical significance Inadequate sample sizes Too much test variation Neglecting existing customers
