Any successful business finds that analytics is a key point to stay on track with your goals. Today we’d like to share the best practices of applying analytics for decision-making by our partner – Web 2 Market.
The company provides data-driven Magento digital marketing, custom development, and hosting. Being data-driven means to them using the vast array of analytics information and tools from vendors like HiConversion. They believe that proper use of these tools can provide deep insights into your clients, how to generate more traffic and convert that traffic into sales.
- Case Study: why new and returning visitors require different approaches?
- Best Practices: what to consider when conducting any experiment?
- Take the next step and learn how to optimize your site for returning visitors
Case Study: why new and returning visitors require different approaches?
Intuitively we all know that new visitors and returning visitors behave differently on e-commerce sites.
Returning visitors are fewer, their purchase intent is higher and they have substantially higher revenue per visitor (RPV).
In this post, we’ll explore how customizing the user experience for these different groups can lead to dramatic sales increases with minimal changes to the website.
We’ll provide specific examples of the tests run on client sites and how they increased RPV.
A recent study by Barilliance found return visitors:
- added items to carts 65.16% more than first-time visitors;
- converted 73.72% more than first-time visitors;
- spent 16.15% more per transaction.
Indeed, personalization is a hot topic in e-commerce, and for good reason. But how do you know what changes work and how well do they work?
As part of the Mobile Optimization Initiative, we’ve been using powerful HiConversion analytic tools to study how changes to customer interface impact RPV. One of the ways we’ve been looking at the data is by comparing new vs. returning visitors. In client after client, we find returning visitors are looking for different site elements and information than new customers.
Let’s look at an example. One of our clients, whom we’ll call FragranceCo, sells commercial fragrances. Clients are small businesses and individuals using their scents to create products like candles and soaps. The majority of their customers order regularly.
For FragranceCo, we ran 4 tests. In the results below, you’ll see that new and returning customers think differently. And by making small modifications to what they see, RPV increases dramatically.
In this test, we simply added the word ‘Secure’ to the button.
By reinforcing the safety of the purchase and calling attention to the button, customers are more likely to continue the purchase.
This clearly worked better for returning visitors. Specifically desktop users. In general, desktop users are older and more risk-averse than mobile device users. Returning desktop users in this test had a dramatically higher lift in conversion rate and RPV.
Test #2. We numbered the checkout steps
In this test, we simply added a number to each step of the checkout process.
Customers are encouraged knowing they are making progress as they enter their shipping and order information.
Again, a dramatic difference between new and returning visitors. RPV was more than triple the rate of new visitors to the site.
This isn’t unique to this client. We’ve identified this trend across a range of clients. So we’ve begun slicing the data, comparing new vs returning visitor results for all our clients.
Best Practices: what to consider when conducting any experiment?
Tip #1. Sample size does matter
A caveat to this way of slicing the data, or any other kind of segmentation, is that each time the data is segmented the sample size decreases.
Tests with smaller sample sizes are more sensitive to random noise that may give false negatives or positives for RPV lift.
For the tests that we have done this segmentation for, we always make sure there are at least 100 conversions for each segment before we draw any conclusions from them.
Tip #2. Keep it simple
Even though you can capture some amazing lifts through small changes specifically targeted to your different customer groups, this may not hold for larger changes. Remember that new visitors become returning visitors and returning visitors were once new visitors, and cookies aren’t stored across different devices or browsers. Showing your customers a drastically different site between one visit and the next can be a jarring user experience that may leave your customers frustrated.
But small changes mean that you and the developers don’t have to worry about spending a ton of time and resources to capture more value from your customers. Small changes to the website can be tested and implemented rapidly to keep up with your customers’ wants and expectations. This is how you can pursue continuous improvement on your website and know that you aren’t taking two steps back whenever you take one step forward.
Take the next step and learn how to optimize your site for returning visitors
Merchants should be analyzing and testing their site for user experience improvements.
How? Join the Mobile Optimization Initiative. By joining us, your site will be thoroughly analyzed for problems in the sales funnel. You’ll get several months of A/B testing and recommendations for permanent improvements. Merchants get a sales lift of 8.56% based on recommendations.
Special thanks to Graham Howell for taking part in writing the article. He’s recently completed his MBA. Graham focuses on helping companies grow sales by using analytics.