Use competitor analysis in CRO
Use competitor analysis in CRO
1. Create a spreadsheet with a column for each competitor.
In the first row, add the URL of their website. In the next row, list the type of page you want to analyze (landing page, category page, product display page, cart, etc). Create a new row to catalog a screenshot of the page or use a ready-made spreadsheet.
2. Open Facebook Business Manager > Audience to measure your audience overlap with competitors.
If your competitors are not on Facebook or it does not show enough data on them, choose the two or three competitors you believe are the most important, pick one of them for now and skip to the website steps. Import your list of audiences into Facebook and name them. For example, your newsletter subscribers or registered users. Create a draft of an ad. Scroll to Detailed Targeting and type the name of your competitor in the search bar. Choose your competitor from the list. Enter the competitor’s total audience number in your spreadsheet, found on the right side of the Ad Manager. Scroll up to Custom Audiences and add the audience that you target. Enter the potential reach number, found under Audience Definition, in your spreadsheet.
3. Calculate the audience overlap percentage using the formula: (Custom Audience/Competitor Audience)*100.
The percentage number is the overlapping audience. Identify competitors with at least 10% audience overlap. Use these for your competitor analysis.
4. Identify pages on your competitor’s website that are similar to pages on your website.
5. Identify elements on their page that you could test on your own website.
Catalog the count and characteristics of their buttons, other interactable elements (sliders, links, tab navigation, etc), the count and choice of words, the amount of forms and form fields, images and videos, content blocks and their structure, CTAs, emotional and rational drivers, themes and styles of their images. Make a list of which of these elements you believe could work better than the equivalent solutions you currently have on your website, listing the reasons why.
6. Run an A/B test to compare the new design, incorporating changes from competitors, with your current design.
Group the changes in the new design into hypotheses that address issues found through research conducted with your website’s audience. Use the list of “why’s” you created in the previous step to help you write your test hypothesis.
7. Run tests with more variations containing adjustments on other pages of your sales funnel based on the highlights from the analysis.
Test more variations and calibrate the amount of changes in each variation according to your traffic and conversion rate. General guidelines (these can change according to your website’s conversion rate and the expected effect of the changes you are promoting): Up to 300,000 users per month: group all changes into a single variant. Your tests will probably still have to run for a full month to reach statistical significance. Around 500,000 up to 1M users per month: run large changes as individual tests. Group multiple smaller changes together into bigger tests. Effects caused by standalone small changes can still be hard to detect in this traffic range. More than 1M users per month: run tests containing only one change at a time to perfectly isolate the effects obtained by each individual change. This will still require planning and time that could be used to test other, potentially more promising changes. Evaluate the cost-benefit of proceeding this way.
8. Create a report that analyzes all your test variations to identify which change was more successful.
Compare each test variant and identify which changes were most successful. Use the findings to better optimize your pages based on what your target audience is receptive to.
9. Create a new spreadsheet and compare more than one competitor.
Analyze up to 4 direct competitors that have similar audiences. Repeat the testing process.