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A +B Testing

A/B testing, also known as split testing, is a method used in marketing and web development to compare two versions of an APP, webpage or marketing campaign to determine which one performs better. The purpose of A/B testing is to understand how changes in variables can impact user behavior and optimize conversion rates.

Here’s how I implement the A/B testing:

  1. Hypothesis: First, I start with a hypothesis or a question I want to answer. For example, I might wonder if changing the color of a call-to-action button on your website will lead to more conversions.
  2. Variations: Next, you create two versions of the APP, webpage, or marketing campaign: Version A (often called the control group) and Version B (the variation). The only difference between the two versions is the specific element you want to test, such as the color of the button.
  3. Randomization: Users are randomly divided into two groups: Group A sees Version A, while Group B sees Version B. It’s crucial to ensure that the groups are representative of your target audience to obtain accurate results.
  4. Data collection: As users interact with the webpage or campaign, relevant data is collected, such as click-through rates, conversion rates, or engagement metrics. This data is usually gathered through analytics tools or specialized A/B testing platforms.
  5. Analysis: After sufficient data is collected, statistical analysis is performed to determine which version, A or B, performed better based on the predefined metrics. The statistical significance of the results is considered to ensure reliable conclusions.
  6. Conclusion: Based on the analysis, I can draw conclusions about which version performed better and whether it supports your initial hypothesis. If Version B outperforms Version A, you may choose to implement the changes permanently. If not, you can go back to the drawing board and generate new ideas for testing.

A/B testing allows me to make data-driven decisions and optimize various aspects of your website and marketing campaigns to improve user experience and achieve your desired goals. It’s an iterative process, as you can continue testing and refining different elements to continuously enhance performance.

A + B Testing image of two different pictures of an medical APP to make test to see which one works better.
A +B testing image of 3 pictures of a medical APP. Some text explaining that number 3 was the final decision after testing users of the app. The decision to change the app design to a Tab Menu. Meaning Menu below, so it is reachable to the thumb to the handy only with one hand. Instead of the typical hamburger menu.
See the complete “A +B Section” in the Case Study page here.

Task 1:
Search for a doctor and book an appointment.

Issue: Testers get confused by the doctor’s picture in order to book a doctor’s appointment and click on it rather than clicking the loupe to search for a doctor. Severity mayor

Suggested Change:  Change the images to a more precise one.

Results show that the updated image of the button “For My Doctors” which shows clearly an envelope and a person/doctor makes it more intuitive to them that this is where they can add information about their doctor.

ITERATION

Till now, I iterated the design of the interface three times. To streamline the user experience and improve accessibility, I eliminated the hamburger menu and replaced it with a tab bar that only contains five icons or buttons.

I found that users were struggling to locate the appropriate button in the main menu, as all six buttons were grouped together. To address this issue, I placed the most relevant buttons in the center of the screen and the less relevant ones in the top right corner.

Ultimately, I decided to incorporate the tab bar to ensure that the menu was easily accessible at all times and within reach of the user’s thumb. This change not only simplifies the user interface, but also increases the convenience and usability of the app.

By reducing the workload and making the app more user-friendly, I hope to enhance the overall user experience and satisfaction with the product.