A/B Testing Process
A/B testing framework to process A/B Testing is given below;
- Data Collection: Provide data for webpages with low or high conversion rates while decreasing conversion rates to improve those pages.
- Goal Identification: Point out your conversion goals (such as increasing click rate, email signups or clicks to product purchases).
- Hypothesis Generation: Explain why you thnink they would be better than the current versions.
- Variation Creation: Make the desired changes on your website or mobile app (such as changing colors, elements on the page, revealing navigation elements or customizing).
- Conduct Experiment: Create your experiment and encourage your visitors to participate. These interactions will then be used to measure the performance of each page.
- Results Analysis: Look at the results presented by the A/B Testing software, and decide on whether a significant change is required.
![A/B Split Test Process Representation](png/65a77beefb5552d4273b931f_ab-testing-process-representation.png)
A/B Split Test Tools/Softwares
A/B Testing & SEO
A/B testing;
- Increases your ability to rank better in search engines, and
- Decreases the risk of cloaking.
If you run a split test with multiple URLs, use rel="canonical" to prevent Googlebot from getting confused by similar versions of the same page.
If you run a split test that redirects the original URL, use 302 (Temporary) Redirects rather than 301s (Permanent) to enable Google to keep the original URL.
You need to avoid conducting long and unnecessary experiments.
Instances for Variations of A/B Split Test
1. A media company might want to increase readership, increase the amount of time readers spend on their site, and amplify their articles with social sharing. To achieve these goals, they might test variations on:
- Email sign-up modals
- Recommended content
- Social sharing buttons
2. A travel company may want to increase the number of successful bookings completed on their website or mobile app, or may want to increase revenue from ancillary purchases. To improve these metrics, they may test variations of:
- Homepage search modals
- Search results page
- Ancillary product presentation
3. An e-commerce company might want to increase the number of completed checkouts, the average order value, or increase holiday sales. To accomplish this, they may A/B test:
- Homepage promotions
- Navigation elements
- Checkout funnel components
4. A technology company might want to increase the number of high-quality leads for their sales team, increase the number of free trial users, or attract a specific type of buyer. They might test:
- Lead form components
- Free trial signup flow
- Homepage messaging and call-to-action
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