How do you improve UX writing with data?

Imagine you're a UX writer at an e-commerce startup. Users are adding to cart but not checking out. You suspect the UX writing on the checkout button is the issue. Time for some data sleuthing. The Experiment You analyze heatmaps and run an A/B test. The original button says "Finalize Your Purchase," while the new one says "Secure Checkout." Group A: 20% CR Group B: 35% CR The Takeaway Bingo! Group B wins. "Secure Checkout" boosts confidence and conversions. Key Points: 1. Analytics: Pinpoint user drop-offs. 2. A/B Testing: Experiment to find what clicks. 3. Relevance: Make it resonate. Data-driven UX writing is a game-changer. Ready to let data guide your pen? Trust me, it's worth it.

This is true for 99% of the times people are engaging with any digital content. However, the remaining 1% is that spark of targeted genius which results in "Diamonds are forever!" or "Just do it." So as much as one should rely on Data to make sure that the message is clear and effective for targeted users, always keep a margin for that light bulb!

UX writing is just a piece of the user journey and experience. It’s hard to measure just the impact of UX writing, if other things are being tested at the same time. You have to A/B test UX writing in isolation. That means pinning the original version against only what you change as a UX writer. To truly know the impact of UX writing, there can’t be any changes to the visual or UX design or any other factors. You have to fly solo and only A/B test your UX writing work if you want to know the difference UX writing can make.

Before launching any A/B tests or experiment, be sure to have hypotheses for why the current variant is "failing" and why the new variant might do better. Example: Your current call to action is "Buy now" (variant A) Your hypothesis for the low conversion might be that "Buy now" implies a big commitment and sounds like the user will get charged immediately. Based on that, you suggest "Continue to payment" (variant B) with the hypothesis that people will buy more if they feel in control of the payment. This way, if variant B wins, you'll have an idea not just of *what* performs better, but *why* it does so. You can then use these insights to inform future design decisions.

In my experience, one aspect that is often overlooked is usability testing. This is a vital step in crafting user-centered microscopy. By observing how users interact with the product, you can identify any confusion or issues they may encounter. Usability testing allows you to gather data and make informed improvements to your microscopy. Unfortunately, some companies may skip this step due to the cost involved. However, it is important to remember that there is nothing more expensive than bad microscopy. Investing in usability testing can save you from potential user frustration and negative feedback once the product is launched.

To improve UX writing with data, integrate Value Proposition Design (VPD) and Jobs-to-Be-Done (JTBD) principles. Analyze data to understand user needs and motivations, then craft your UX copy to align with the functional, emotional, and social aspects of their jobs, providing a more compelling and user-centric experience.