Julian has been viewing property listings for three weeks and eventually managed to find one of his desired homes, a 2-bedroom apartment in an ideal area. Rent was affordable, and it met his expectations of a home quite accurately. Julian tapped on the “Enquire” button on his phone, filled in his personal information into the form, and submitted it. However, nothing happened.
He tried again. Still, nothing happened. When he refreshed the page, the form became empty, with all his submitted particulars lost. Julian quickly opened another app and managed to book another apartment within 2 minutes. Eventually, after a few days, a few other customers also quit the app. Such failures happen everywhere, unnoticed and unknown, especially in complex platforms.
These silent failures rarely generate error reports but directly impact user trust and conversions. Modern platforms today use AI-based software testing methods to detect errors in user flows before they reach real users. This goes a long way in avoiding such issues.
Property and lifestyle apps (such as real estate platforms, home service apps, or multi-service mobile applications) include many user workflows happening every day. For instance, searching for a house to rent, viewing new properties, using home services, recharging a mobile, or reading the latest property news. Each service has multiple stages, such as search filters, forms, payment gateways, and confirmation screens.
Even if a minor glitch occurs at one of these stages, users usually don’t bother to complain. They will instead switch to another app.
The most serious factor is that such failures are not immediately noticeable from the outside. For example, the filters on a property search page may look fine, but an API inside may be broken, resulting in no results. Similarly, a mobile top-up button may appear to be active, but after an update, it may not be able to connect to the payment gateway.
These types of Application Logic Failures are extremely difficult to detect through manual testing alone.
Most product teams do manual testing before releasing a new update. The software testing team opens the app and checks a few screens to make sure everything looks good. This helps to find visible and common issues. But such tests often don’t reveal what’s going on inside after a button is clicked.
● Is the form getting submitted correctly?
● Is the search information we provide reaching the right server?
● Are we redirected to the confirmation page immediately after payment?
● Does the feature load properly on a typical Android phone?
It’s not practical to manually test these scenarios on every phone, every browser, and every screen size after every update. Teams are small, but updates need to be delivered frequently. The truth is, time is not enough to cover everything.
This is where automated testing comes in. Traditionally, implementing automation required significant coding effort and maintenance, which limited its accessibility to technical teams.
As said, manual testing can’t cover every scenario, and scripted automation is not always flexible. A growing trend in modern testing is the use of AI-driven and natural language-based automation, where test steps can be written in plain English instead of complex code.
Instead of writing scripts, teams can describe test scenarios in simple instructions, and the system interprets and executes them across different browsers and devices.
The flexibility of this testing method is that everyone on the team can be a part of the testing. For example, a property operations manager can simply describe how a booking should be done. Similarly, a customer support lead can prepare tests to check whether the confirmation screen appears after a mobile top-up. This does not require coding knowledge.
Let’s look at a real-world example. A user visits a property platform and wants to send an inquiry.
Example Scenario:
● User searches for a 2-bedroom apartment
● Selects a property from the results
● Opens the property details page
● Clicks on the “Send Message” or “Enquire” button
● Submits the required details
● Expects a confirmation message or login prompt
This type of scenario can be translated into automated test cases in simple English commands that validate whether each step in the user journey functions correctly.
As the test steps will be written in the same way we usually explain something to someone, a developer or a non-technical person can read and make changes to it.
There are many no-code test automation tools available. Based on the tool you choose, you can write the test cases without scripting.
The test case above is to check whether a user is able to search for a property and get the option to enquire about the property details. Say, if the “Send Message” button is missing on the property page, the test case will fail, and you will get an alert. Therefore, you can easily identify the issue and resolve it immediately before your users experience the same issue. Manual testing might not always help to catch every issue.
In addition, automated tests can capture logs, screenshots, and failure points, making it easier to debug issues quickly.
Most property searches happen on mobile phones. Therefore, mobile testing is not an option but a must.
A common problem with mobile phones is interface overlap. That is, some buttons might be hidden behind navigation bars or footers on the phone. This prevents customers from clicking on those buttons. Such errors cannot be found when testing on computers (desktops). To identify such issues, we need to execute mobile viewport tests.
Modern testing approaches allow the same test scenarios to be executed across multiple devices and screen sizes, helping teams detect layout and usability issues early.
When a test passes on desktop but fails on mobile, the team can quickly identify a design (layout) issue and fix the error before it affects customers.
If you look at the way these apps are built, you will see that more bugs occur in certain areas. They can be mainly divided into the following categories:
● Search and Filter Logic: The search filters are the most affected when new updates come. For example, if a new property type is added to the database and it is not correctly linked to the filter in the app, then no results will be displayed when searching.
● Form Submission: Form submission is likely to be interrupted when changes are made to the backend services. If the front-end development team forgets to handle the error scenario and fails to display the error message, we will never get an idea about the issue just by viewing the UI.
● Payment and Top-up Confirmation: These rely on third-party services (third-party integrations). If payment providers make any changes on their side, the redirect URL may not work, and the confirmation screen may not be displayed.
● Login Process (Authentication): Login systems, whether through social media accounts or otherwise, may experience issues after updates. If session tokens are not handled properly, customers may not be able to log in.
The main advantage of automated testing using plain English is that developers or testers don’t have to rely solely on themselves to write and maintain tests.
When a product manager can read and understand a test case, they can check if something is missing and add new scenarios. Similarly, if they notice a particular complaint being repeated by customers, the customer support team can describe the problem in plain English and pass it directly to the team as a test case. This kind of collaboration helps in finding and fixing bugs quickly.
This shared ownership of quality reduces dependency on individual roles and improves overall product reliability.
Julian’s experience, which we discussed at the beginning of this article, is not that uncommon. Even on the best platforms that provide regular updates, inquiry forms don’t work, or payment confirmations fail. This doesn’t happen because of anyone’s negligence. It happens because of the complexity of the apps.
Today’s apps have so many layers of functionality that any one of them can silently fail at any time.
The real question we should be asking is not “Do we get more traffic into our application?” but rather, does every key step: searching for a home, booking a room, paying for a service, and getting a confirmation work properly on every phone and every browser after every update?
When core user journeys fail silently, the impact is immediate: lost users, lost revenue, and reduced trust.
The only way to reliably answer this question is through automated testing. With tools that help teams define test scenarios in simple, understandable ways, this responsibility can be shared not just by developers, but by everyone on the team.
Have you experienced similar issues while using property or lifestyle apps? Observing these patterns is often the first step toward improving product quality and user experience.
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