--- title: Why a Genetics Product's Error States Were Rewritten Before They Could Appear description: How a genetics app stopped users thinking correct results were broken, by rewriting screens before anyone saw them using plain, trust-building language. image: https://weareaffective.com/hubfs/learning-centre-images/why-a-genetics-products-error-states-were-rewritten-before-they-could-appear.webp --- [Skip to content](https://weareaffective.com/learning-centre/why-a-genetics-products-error-states-were-rewritten-before-they-could-appear#main-content) [![we\_are\_affective\_logo\_200](https://weareaffective.com/hs-fs/hubfs/we_are_affective_logo_200.png?width=175&height=48&name=we_are_affective_logo_200.png "we_are_affective_logo_200")](https://weareaffective.com) - [Home](https://weareaffective.com) - About Us - [Our Story](https://weareaffective.com/about) - [How We Work](https://weareaffective.com/how-we-work) - Our Services - [App Planning & Strategy](https://weareaffective.com/app-planning-strategy) - [App Design](https://weareaffective.com/app-design-agency) - [App UX Design](https://weareaffective.com/app-ux-design) - [App UI Design](https://weareaffective.com/app-ui-design) - [App Technical Architecture](https://weareaffective.com/app-architecture) - [Existing App Audits](https://weareaffective.com/app-audit) - [Case Studies](https://weareaffective.com/case-studies) - [Pricing](https://weareaffective.com/pricing) - [Learning Centre](https://weareaffective.com/learning-centre) - [Get Started](https://weareaffective.com/get-started) Expert Guide Series # Why a Genetics Product's Error States Were Rewritten Before They Could Appear Table of Contents We worked on a genetics wellness app where the data was correct and people still thought it was broken. Someone opens their results, reads a line about how their body processes caffeine, and thinks that doesn't ring true for me. In their head, the report has made a mistake. Nothing has actually failed. No field rejected an entry, no server timed out, no red warning text appeared anywhere on the screen. > The data was never wrong, and users still read it as a fault in the report. The product was working exactly as built. The user had [quietly decided it was not to be trusted](https://weareaffective.com/user-psychology-app-design). That is an error state, and it is the hardest kind to design for, because it never reaches a log file and no amount of better error messaging will catch it. So we rewrote the copy that came before the results rather than the copy that came after the problem. The aim was to make variation feel expected by the time people reached it, so the thought that doesn't ring true never formed in the first place. This article walks through how that decision was made on the project, what the brand audit turned up, how we tested the rewrite with focus groups and five-second tests, and where pre-framing stops being useful and real error handling has to take over. ## What Counts as an Error When the Data Is Correct Genetic results are built on variation. The whole point of the product is that your body is different from the next person's. Yet a user reading a result that contradicts how they see themselves has no way to tell the difference between unusual and incorrect. If someone has never burned in the sun and the report flags higher sun sensitivity, the sensible reaction is to doubt the report. On the project we inherited, the product carried a huge amount of content and let people fall straight into that doubt with no framing around it. The result sat on the screen as a bare statement. Nothing in the copy acknowledged that surprise was normal, so surprise got read as failure. Error handling in product design usually means the opposite problem, where something genuinely breaks and the message is vague. Baymard Institute found that [98% of sites](https://baymard.com/guidelines/722-using-adaptive-error-messages) do not use specific, adaptive error messages that say exactly what is wrong and how to fix it. Their work looks at checkout forms, and the thinking carries. A generic message leaves people guessing. What we had was the inverse. The message was precise, the science behind it was sound, and the user still filed it under broken. ## The Gap Between the Brand Promise and the App The brand side of this product was lovely. Packaging, website, photography, all of it luxurious and aspirational, built around transformation and becoming a better version of yourself and reaching your full potential. People bought into that story, paid for a kit, waited, posted a sample off, and waited again. Then they opened the app. What they found was cold and clinical, functional in its copy and functional in its design, with none of the warmth that had persuaded them to buy. The journey broke down entirely at the product touchpoint, and it was a jarring experience for anyone who had come through the marketing first. That gap matters for error states more than it looks like it should. Tone sets expectations about care. A brand that has spent weeks speaking to you warmly, and then hands you a clinical screen of markers with no explanation, has signalled that you are now on your own. People read ambiguity generously when they feel looked after. They read it suspiciously when they feel handed off, and a surprising result lands in that second frame of mind. So the mismatch was quietly manufacturing distrust at the exact moment the product needed the most of it. ## UX/UI design built around *real* psychology We design app interfaces around how people actually think and behave. User research, psychology-driven UX/UI design and technical specs delivered as one complete package. [See how we work](https://weareaffective.com/how-we-work) [Get started](https://weareaffective.com/get-started) No commitment ## Why the Narrative Had Been Engineered Out Our audit found something that surprised the client. The brand promise itself was sound. The narrative of giving you a real inside look at how your body works, how it is ageing, and what you can do about it was compelling and well constructed. Nobody needed to rewrite the positioning. The product had been built largely by a developer team, and in building it they had stripped out the storytelling in favour of functional delivery. Every screen worked. Every number appeared where it should. What had gone was any sense of a person moving through a story about their own body, which meant users were not connecting emotionally with their data, and retention suffered directly as a result. > The promise was right all along, and the build had quietly removed the story that made the data mean anything. That audit forced a decision. Rather than redesign the brand promise, we reintroduced [narrative into the product and gave people](https://weareaffective.com/learning-centre/why-a-wellness-genetics-product-needed-a-rewrite-before-it-needed-a-redesign) a sense of identity inside it. The data stayed the same. The order it arrived in, the voice it arrived in, and the framing around it all changed. Once narrative came back, pre-framing became possible. You cannot warn someone about what is coming next if your product has no sense of a next. ## Rewriting Results Before Users Reached Them The single most effective change we made was [pre-framing potential error states rather than](https://weareaffective.com/learning-centre/how-to-structure-progressive-disclosure-around-a-users-anxiety-not-your-data-mod) designing better responses to them. Instead of letting someone see an unexpected result and judge it alone, we wrote the lead-in copy to contextualise variation ahead of time, with lines like this is to be expected and everyone is different and that's fine. It sounds almost too simple. The effect is that the error state never forms in the user's mind, which is far more powerful than catching it afterwards with a help link or a tooltip. | Moment | Before the rewrite | After the rewrite | | --- | --- | --- | | Opening the results | Straight into data | A line on what you are about to see | | A surprising result | Left for the user to judge | Framed as expected variation | | Scientific detail | Full medical depth by default | One layer deeper, on request | | Tone | Clinical and functional | Narrative, matching the brand | List the three results most likely to contradict how a user sees themselves, then write the framing copy for those three first. They do the heavy work of the whole rewrite. None of this hides anything. The same markers, confidence levels and sources sit in the product. They arrive after people have a frame to put them in. ## Plain Language First, Science on Request There is a narrow band of information density that works in medical and wellness products, and both edges of it are dangerous. Simon put it plainly on this project. If you have too simplistic language, people don't trust it, because they suspect there is no real science behind the thing. Go too far the other way and you're too technical, too medical, and people switch off completely. So [plain language became the primary layer](https://weareaffective.com/learning-centre/10-micro-interactions-that-will-transform-your-apps-user-experience), carried by real-world analogies about how the body works, with medical and scientific depth sitting underneath for anyone who wanted it. Scientific rigour lends credibility by being there. Reading it is not a condition of using the product. This runs against how the category tends to write. A content analysis of 29 direct-to-consumer genetic testing websites published in [PMC, 2010](https://pmc.ncbi.nlm.nih.gov/articles/PMC2997043/table/T4/) found a mean SMOG readability level of 14.7, which is post-secondary reading level, with only 7% mostly using common language and explaining their technical terms. Writing at that level is a sign that nobody decided who the reader was. The science earns its place by being available, not by being first. ## Sequencing Disclosure Around Anxiety, Not Product Logic Progressive disclosure usually gets built around product logic, where the structure follows how the data is organised. On this product we [built it around anxiety instead](https://weareaffective.com/learning-centre/how-to-structure-progressive-disclosure-around-a-users-anxiety-not-your-data-mod). People arriving at a genetics result already carry a degree of worry, and the job of the first layer is to bring that down rather than add to it. The sequence we landed on ran roughly like this. 1. Tell people what is about to happen and where they are. 2. Explain the part of the body in a simple, everyday way. 3. Give the result in plain terms, framed as normal variation. 4. Explain why people differ on this marker. 5. Offer the science, the markers and the confidence levels. 6. Say what, if anything, is worth doing next. Ask permission before each heavier layer. A simple "ready to see the detail?" hands people ownership of their own progress and lowers the stakes of every screen after it. Each step reduces the anxiety load of the one after it. Educating people about what is coming is the most reliable way we have found to calm a product down, and it changes how people feel about the whole thing, not just the screen in front of them. ## Why Too Much Science Too Early Damages Credibility We went into the user testing on this product expecting science to build trust. The opposite happened. Going science-heavy early lost us credibility, because people felt they could not trust something they did not understand. Confusion reads as evasion, even when every word on the screen is accurate. Bringing the science in slowly, after people had grasped the key result, pushed credibility back up. The detail now confirmed something they already held, and confirmation feels like proof in a way that a wall of terminology never does. > People do not trust what they cannot understand, so early depth costs credibility rather than building it. A usability study of personal genomics reports published in [PMC, 2015](https://pmc.ncbi.nlm.nih.gov/articles/PMC4526936/) found that about half of participants commented on technical jargon and found it hard to understand. That is half an audience spending its attention decoding vocabulary rather than absorbing what their results mean for them. The order is what does the work here. Same science, same sources, same markers, placed after comprehension rather than in front of it, and the product reads as more rigorous rather than less. ## Testing the Rewrite: Five-Second Tests and Focus Groups We measured the rewrite rather than argued for it. Focus groups and five-second tests ran before and after the copy and narrative changes, scoring comprehension, clarity and sense of purpose. A five-second test is exactly what it sounds like. Someone sees a screen for five seconds, the screen goes away, and they tell you what the product is for and what that screen was telling them. It is unforgiving, and it is the closest thing to how people actually skim a results page. The first round scored badly. The product held a great deal of content, people fell into error states, and comprehension was low across the board. We then made the changes already described, reintroducing narrative and pre-framing the results most likely to be read as mistakes. The second round of focus groups and testing came back much higher on clarity, on purpose and on retention. Subtle changes to copy, quite profound changes to how the product felt. Testing also settled a disagreement. The client's preference had been full medical detail as the default. The testing pointed clearly back to our original plan, which was to strip it back, give people enough to understand the principle, and let them explore the depth if they wanted it. ## Handling Stakeholders Who Want the Data Up Front In health and wellness products there is always a pull from the people who know the science best to go straight in and show the results, show the data, show the information. The instinct is honest. They understand the material, they are proud of its quality, and holding it back feels like hiding something. What that does to a user is raise anxiety at the exact moment it needs to drop. Stress levels are already high for anyone opening a health result. Emotional framing first gets people into the content in a state where they can take it in, and the data lands better for having waited. We have found three things help that conversation along. - Show the detail is still in the product, one layer down, with nothing removed. - Put the testing in front of them rather than the opinion. - Frame the sequencing as a comprehension problem, which it is. Record a five-second test session and play it back in the meeting. Watching one person fail to say what a screen was for ends the debate faster than any deck. On this project the testing did the persuading. Nobody had to win an argument about taste. ## Where Pre-Framing Stops and Real Error Handling Begins Pre-framing works on perceived errors. It has no business anywhere near a real one, and the two get confused surprisingly easily once a team gets comfortable with soft, reassuring copy. A sample that failed in the lab is a real error. A kit lost in the post, an upload that did not complete, a login that will not accept a password, an account where results are genuinely delayed. Telling someone this is to be expected in any of those moments is dishonest, and people spot it immediately. Real failures need the opposite treatment. Say what has happened, say why, say what happens next and who is doing it. Baymard's finding that 98% of sites fall back on generic error messaging is a reminder of how rare that specificity is. So we kept a clean line on this product. Variation in the results gets framed before it arrives. Anything that has genuinely gone wrong gets named, explained and given an owner. The test is simple enough to apply in a review. If the user is right to be concerned, do not soften it. If the user has misread normal variation as a fault, you had the chance to prevent that several screens earlier. ## Applying Pre-Framing Beyond Genetics The same gap shows up anywhere a product hands someone information about themselves. In a meditation app teardown we ran, the app promised calm in under a minute and then immediately asked the user to define their goals, as though they had arrived rational and relaxed. Nobody opens a meditation app for the first time because they are already calm and curious. They open it because they are stressed and want help. Building management and concierge apps do a version of this too. The norm is to hand over the full directory of information at onboarding, to someone who has just moved home and is in no state to absorb a directory. On the product we worked on, we treated the timing and sequencing of that information as an emotional design question rather than an information architecture one. > Timing is an emotional design decision, and most products treat it as an information architecture one. Skincare diagnostics, supplement quizzes, fitness assessments, sleep tracking. All of them deliver a verdict about a person's body to a person who has an opinion about their own body already. Wherever those two can disagree, the framing has to arrive first. ## Conclusion The genetics product taught us something we now bring to every project where results are handed to a user. The error state you most need to design for is the one that exists only in someone's head, where nothing has broken and the person has stopped believing you anyway. You fix it upstream. Plain language carries the main path, analogies do the explaining, the science sits a layer deeper for anyone who wants it, and the surprising results get contextualised before people reach them. Narrative holds all of it together, which is why reintroducing storytelling into a developer-built product changed comprehension so much more than any individual screen redesign. Testing is what makes the case. Our focus groups and five-second tests moved the conversation away from whose instinct was better and onto what people actually understood, and the second round came back higher on clarity, purpose and retention. If you are building something that tells people about their own body, their own money or their own home, the order of information is doing as much work as the information itself. We are always happy to look at where a product is losing people and why. [Let's talk about your results experience](https://weareaffective.com/get-started). ## Frequently Asked Questions What does it mean to call something an error state when nothing has actually failed? It means the user has decided the product is wrong, even though no field rejected an entry, no server timed out and no warning appeared. In a genetics app, a result that contradicts how someone sees themselves gets filed as a fault in the report. Nothing reaches a log file, so this kind of error is invisible to the usual monitoring. Why can't better error messaging solve this problem? Error messaging only fires when something breaks, and in this case nothing breaks. The copy is precise and the science is sound, so there is no failure for a message to attach itself to. The fix has to happen before the result is read, not after a problem is detected. What is pre-framing and how was it applied here? Pre-framing means rewriting the copy that comes before the results rather than the copy that comes after a problem. The aim was to make variation feel expected by the time people reached their results, so the thought that doesn't ring true never formed. It shifts surprise from a signal of failure to a signal of something normal. Why does a mismatch between brand tone and app tone create distrust? Tone sets expectations about care. If a brand speaks warmly through packaging, website and photography and then hands over a cold, clinical screen of markers, it signals that the user is now on their own. People read ambiguity generously when they feel looked after and suspiciously when they feel handed off. What did the brand audit reveal about the product journey? The brand side was luxurious and aspirational, built around transformation and reaching your full potential, and people bought into that story before sending off a sample. The app itself was functional in both copy and design, with none of that warmth. The journey broke down entirely at the product touchpoint, which was jarring for anyone who had come through the marketing first. How was the rewrite tested? The rewrite was put through focus groups and five-second tests. Focus groups surface how people interpret and react to the framing, while five-second tests check what registers from a screen almost immediately. Together they show whether the framing lands before a user has time to form a doubt. What does the Baymard research about error messages add to this? Baymard Institute found that 98% of sites do not use specific, adaptive error messages that explain exactly what is wrong and how to fix it. Their work looks at checkout forms, but the thinking carries, because a generic message leaves people guessing. The genetics project was the inverse problem, a precise message that users still read as broken. When does pre-framing stop being enough? Pre-framing handles perceived errors, where the data is correct and the user simply doubts it. It does nothing for genuine failures such as a rejected input, a timeout or a processing fault. Those still need real error handling with specific, actionable messages that say what went wrong and what to do next. ## Related Articles [![Why a Wellness Product's Education Layer Has to Be Designed Around Anxiety, Not Around Information](https://weareaffective.com/hubfs/learning-centre-images/why-a-wellness-products-education-layer-has-to-be-designed-around-anxiety-not-around-information.webp)](https://weareaffective.com/learning-centre/why-a-wellness-products-education-layer-has-to-be-designed-around-anxiety-not-ar) ### [Why a Wellness Product's Education Layer Has to Be Designed Around Anxiety, Not Around Information](https://weareaffective.com/learning-centre/why-a-wellness-products-education-layer-has-to-be-designed-around-anxiety-not-ar) People do not arrive at a wellness product in a calm, curious frame of mind. 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