E-Commerce conversion rate optimization statistics are rarely helpful. According to optimization expert, Andrew Anderson, “Real world data distribution, especially over any short period of time, rarely resembles
Simply put: it’s hard to find reliable statistics about conversion rate optimization. But if you understand why it is so challenging, you’ll have a better lense to view the few reputable sources out there.
Part 1 - Challenges with E-Commerce Conversion Rate Optimization Statistics
A few important factors make it difficult to either determine or make use of e-commerce conversion rate optimization statistics.
1. Sample Size
The first issue is in sample size. At the core of it, if you don’t have a large enough sample size, any single conversion can skew the numbers. If you’re looking at optimization statistics, be aware of how many sessions, visitors, or other factors were included in the study.
There’s bound to be a difference between two test groups. The probability that two groups will behave the exact same way is very low. The danger is that any behavior looks big in a small test group. A “spike” in conversions could be influenced by many factors. If your sample size is large enough, you’ll be able to see if the factor you are interested in consistently affects conversions.
2. Test Time and Duration
Another issue to look at when reading conversion optimization statistics is the time and duration of the test. Shopping behavior changes throughout a cycle, whatever cycle that may be. If only part of a cycle is captured, only part of the story is told in the resulting statistics.
The test time and duration ought to be considered when you analyze conversion rate optimization statistics.
3. Representative Sample
Closely related to time and duration, pay attention to the representative sample. Your weekend and weekday shoppers might be entirely different groups of shoppers with differing motivations and concerns. Segmenting this data to compare types of shoppers, shoppers from difference sources, etc., is well worth the effort.
At Granify, we can easily see statistically significant differences in the conversion rates of shoppers from different sources. We’ve come to understand that
Understanding the representative sample is crucial if you want to use your conversion rate optimization statistics to provide a more personalized experience for your shoppers.
Part 2 - Quality Sources for Conversion Rate Optimization Statistics
The tricky part is trusting your sources. In a data-driven market, quality data is essential. The following list of publications, blogs, and case studies are good sources to review conversion rate optimization statistics.
Adobe Digital Insights (ADI) regularly publishes reports on retail trends. Their stats come from looking at “aggregated and anonymized consumer data from online retailer websites. It analyzes over 50+ billion visits since January 2015.”This is just one example of a great source of information from ADI. Check out their SlideShare page for even more.
BEHAVE’s content is well vetted and researched. They publish the results of A/B tests from a number of different verticals including e-commerce and retail.
For each test, the reader is given the option to vote if they variant A or B won. After voting, the reader is taken to a page that shows and explains the results.
The value here is that you can test your hunches and learn at the same time.
Kissmetrics has compiled an extensive 100 item list of conversion case studies. Each one has a screenshot, a summary of the results, and a link to the full case study.
Use this to get a quick glimpse of the topic to see if it is relevant before diving in.
This report was commissioned by FedEx with original research conducted by Internet Retailer. The report speaks more to what retailers and e-commerce stores are doing to increase their conversion rates, more so than what consumer wants. But despite this, retailers can find value in knowing the industry best practices.