- Use more advanced analytics data to supplement your results data
- Use analytics to generate hypotheses for experimentation and Personalization campaigns
Analytics reports are powerful tools in your arsenal when you are generating ideas for experimentation. They help you focus your testing on important opportunities. After your first test, your Optimizely Experimentation Results will help provide key insights; but your analytics tools can provide important parts of this picture as well.
This article walks through a few ways to use more in-depth reporting for hypothesis generation. You can also check out our other article on how to use more basic reports to decide what to test. The examples below are from Google Analytics, but you can apply the same principles to other platforms. Many of these platforms integrate with Optimizely Experimentation, so you can build a robust picture of your visitors’ behaviors.
The advanced reports discussed in this article generally provide granular data about the friction points that visitors in different pathways. Use these reports to brainstorm how you can push the boundaries of your visitors’ expectations.
Pathing and funnel reports
The funnel report is one of the most important pieces of data from your analytics platform. It shows you the different steps in your conversion funnel and how visitors navigate between each:
Where do visitors enter the funnel?
What pages do visitors leave your site from?
How do visitors navigate between pages?
On what pages do visitors fail to take the action you’d like them to?
Bottlenecks in your funnel are opportunities for optimization.
Consider the example above. A large number of visitors left the site during account login and creation. Is the login process overly complicated? Do they abandon the funnel after being taken to a different page? Test ways to ease friction points in your login process, or experiment with ways to connect account creation with the funnel experience better.
You can also use your pathing report to calculate opportunity based on bounce rate:
total visitors X bounce rate = opportunity
For example, if 15,000 visitors visit your homepage, but 40% of them bounce from the site, you have an opportunity to optimize this page for 6,000 visitors.
15,000 visitors X 0.40 bounce rate = 6,000 visitors
If you have 7,000 visitors on your request-a-demo page, with a 90% bounce rate, you have a 6,300 visitor opportunity. Even though the request-a-demo page sees less traffic, the size of the opportunity for optimization is comparable. Use the concept of opportunity to help prioritize test ideas that target different pages on your site.
Create a stacked bar chart
A stacked bar chart helps you visualize how visitors progress down the funnel. This chart is one of the most impactful dashboards that a conversion rate optimization team can use. Put it in a visible place.
When you run a test on a particular page, reference this chart to gauge whether you’re devoting resources to the right opportunities.
Visualize the following three behaviors for each step:
Visitors who exited the website
Visitors who left the funnel to go to a different page
Visitors who continued to the next step in the funnel
High exit rates at unexpected points in the funnel suggest that customers are frustrated; consider prioritizing ideas that test these pages in your roadmap.
The example above tracks visitors from the Homepage all the way to a 3% final conversion. Where should you focus your efforts?
Your attention may have been drawn to the 8% conversion from the product page to the shopping basket. While this is an important metric to note, further research might show you that 6-8% conversion on this step is in line with industry standards. But the 48% exit rate from the product page is unusually high. Why is this happening?
Perhaps visitors are not finding relevant products. Do you see visitors spending a long time on the search results listings? Is the ratio of viewed products to purchases unusually high? If so, you may have identified an inventory or discoverability problem. Pass this information to the relevant team; if the experience of finding a product is too difficult, visitors may exit the site permanently.
Landing and exit pages
Your top landing and exit pages show how visitors enter and leave the site.
Some pages with high exit rates may align with expected behavior. For example, a logout page is quite likely to have a high exit rate. Other pages with high exit rates are opportunities for optimization. For example, if a high percentage of visitors exit immediately after reading one article, try showing related content to encourage visitors to spend more time on the site.
You can also use the landing and exit pages report to find product pages that are underperforming. Use the report to show you all product pages on the site. Then, sort them by exit rate and filter to identify the pages with the highest exit rates. Is this content hurting your brand? Try testing an experience that aligns better with your visitors’ expectations.
Heat maps, click maps, and scroll depth
Heat maps, click maps, and scroll depth visualize your visitors’ behaviors on your site. Platforms such as CrazyEgg, Clicktale, and GA tell you not only which parts of your site receive the most attention, but also what is being ignored.
Use them to:
Visualize how much of the page visitors see on initial page-load and how far they actively scroll
See where visitors click on the page
Consider whether to prioritize high-value content
Consider whether different styles, colors or animations draw attention to the most important elements on the page
What is the best way to use the most impactful spaces on your site?
In the example above, 20% of visitors clicked the Google Store icon. This suggests that these visitors come to the page but don't see any products of interest displayed, so they leave. How can you highlight value propositions or display new inventory to appeal to these visitors?
Notice the key real estate in the center of the page above. It features an inexpensive product that results in a very low clickthrough rate, compared to the higher-priced products that surround it. Consider rearranging the page to highlight the valuable products that more visitors engage with.
For many web-based businesses, site search is one of the most impactful functions to optimize. Search is a behavior that most visitors are familiar with. It’s a low-friction way to find the exact product you’re looking for.
Compare the metrics for visitors who used the search bar against visitors who didn’t. In the example above, only 10% of visitors used the search function but they converted at 3-4 times the rate of those who didn’t. They also generated 33% of total revenue and spent significantly more time on the site.
If you find that visitors who search perform far better than those who don’t, consider making your search bar a prominent visual element on your site. Try centering it, re-sizing it, or drawing attention to the search to encourage visitors to use it to find the products they’re interested in.
Time to purchase
Time-to-purchase tells you how long visitors take to convert. Some visitors are quick to make a decision; others may spend time performing additional research, looking at competitive offerings, and obtaining approval for a purchase.
How many days do visitors take to complete a purchase?
What’s the best way to segment visitors by time-to-purchase: same day, within a week, within a month, or more?
Consider the motivations of your visitor segments. If customers take long periods to research and deliberate, you might experiment with showing a star-rating system or social validation to encourage the purchase. Or, if you’d like to streamline the process for those who make purchase decisions quickly, try surfacing key product details or highlighting the purchase button.
You have improved the percentage of visitors who complete your check-out funnel, or you have received a certain number of visitors to click on your CTA. That’s great! But what does it mean to your business?
Attach a value to your experiments to better understand how to optimize your site and increase ROI.
Revenue metrics to look for:
What is the revenue per visitor? (RPV)
What is the average order value? (AOV)
Are visitors purchasing a few high-priced items or several lower-priced items?
Are there up-sell opportunities in the cart or on the pricing page or do those distract and lower conversion rates?
What is the value of a new lead and how much do new leads decrease your average acquisition costs?
Analytics by industry
Now that you have an overview of analytics to consider when testing, you may have noticed that some that aren’t applicable to your business. Depending on the industry, some metrics may be more valuable or insightful than others. In the table below we’ve provided a list of commonly used metrics by industry, and examples of where they are tested.
For a deeper dive into industry-specific testing ideas, check out these test ideas by industry vertical: