An Introduction to the British Invalid Carriage (Abandoned History Series)

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Not running a test methodically can also be one of the reasons your test fails. To ensure your mobile app testing efforts are going in the right direction and are fruitful for business growth, be sure to test systematically and strategically, and avoid the following:. Successfully conducting any kind of test requires patience, and mobile app testing is no different. You need to give your tests enough time before you can begin analyzing results and devising the way forward. Therefore, the primary pitfall to avoid here is the tendency to conclude tests prematurely, before reaching statistical significance.

Before commencing any test, always have a pre-calculated duration for that test as well as the sample size, and ensure that the test is run on the entire sample size so that you have enough data maximum true positives to safely draw conclusions. Declaring tests done before this pre-decided time duration can negatively impact the intended purpose of running them. Run the test for the same amount of time as was pre-decided until the set number of visitors have been tested on.

Therefore, mobile app testing is considered a viable option only when you have a large enough sample size that can drive substantial results and help you take better decisions in a reasonable amount of time. Whether it is the testing environment, the control and variation design, traffic allocation, sample size, or the experiment goals, the key parameters of your test need to be locked before you get started.

By altering any parameter mid-test, such as changing the traffic split between the variations, you could skew your test results and in worst cases, invalidate them — all without having achieved the intended purpose of making the modification. In such a case, it is essential to run controlled tests rather than running multiple of them simultaneously. Also, if the traffic for multiple tests overlaps, you need to ensure that the traffic from each version of a test is split equally between the next, and so on.

But, could skipping the hypothesis render your test results useless? Also, yes. A hypothesis is a statement that offers a definitive starting point to run a test and can be substantiated based on research and analysis. It clearly states the problem being tackled, the element being tested, the reason behind testing it, and the expected result. While it could later be validated or disproved, the hypothesis defines the rationale behind running the experiment. You might argue that testing with fewer variations limits the scope of your test and keeps you from discovering solutions you never thought existed.

And these are valid points. First, you are likely to end up with way more false positives as the significance level of your test will decrease with an increase in the number of variations. Technically referred to as the multiple comparison problem, this could drastically impact the accuracy of your test results. The other issue it causes is commonly known as sample pollution. Since you will be running your test for longer than usual, one of the repercussions might be the high probability of users returning to your app after deleting their app cache and becoming a part of the test again, which would negatively affect the accuracy of your sample size.

The conversion rates for the variations could turn out to be skewed because of the polluted samples, and you will notice little difference in the numbers for different variations. All of these critical factors add up to conclude that increasing variations just for the sake of it or doing so and expecting better test results is not going to work in your favor. You should only consider increasing the number of variations if your experimentation and resource bandwidth permits, you have the required number of app users and sample size to run long tests on, and if it is absolutely necessary for a particular test.

Mobile app testing empowers you to experiment with ideas beyond the scope of client-side testing and optimize your entire stack by testing on the server-side. All of this apart from helping you test and make quick, UI-based fixes to your app. Due to this enhanced scope, the requirement of an SDK installation and the involvement of developers becomes imperative to successfully run and conclude tests on mobile apps. It might also lead to an increase in the effective time required for end-to-end implementation of tests on mobile apps due to dependencies on multiple teams.

Unlike web or mobile sites, the user experience, app flow, and conversion funnel in mobile apps are not linear. Users seldom navigate unidirectionally through the app and almost never follow the classic conversion funnel model. In a gaming app, for instance, gamers are more often than not found switching levels, engaging in chat rooms, and making in-app purchases, all at once. Hence, testing on mobile apps demands a much more sophisticated and comprehensive approach.

Therefore, instead of merely testing standalone elements, it would be more fruitful to first understand how your app user journeys intersect with one another and then accordingly define your testing roadmap to optimize user flows, in-app experiences, and features that holistically uplift your app performance. For every app update, you need to wait for app store approvals and for users to update their apps to be able to finally view the winning variation. Therefore, building and maintaining a culture of continuous experimentation becomes tough in case of mobile apps, as probable delays caused in universally deploying winning variations post tests, and launching app updates post approvals could negatively impact the time-to-market of app updates, feature release cycles, and testing schedule.

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You can work your way around this by initiating the testing process better prepared. You can use test calculators to estimate test durations beforehand so that you can schedule and your app updates, feature releases, and experimentation roadmap accordingly, so that continually running tests and updating your app does not slow down your app or business. And then there are apps that you open determined to make a purchase, add your favorite items to the cart, but somehow end up losing interest and dropping off. Friction in checkout flows can lead to frustrated users and a significant increase in the cart abandonment rate.

More so because mobile users have even shorter attention spans, and hence demand a checkout flow that is absolutely seamless. Due to the obvious space constraint on mobile screens, it becomes all the more essential to ensure that your search algorithm works effectively to fetch and display the most relevant items on the top to get users hooked from the moment they hit the search button. To test how successful your search algorithm is in doing so, you can simply test it.

You can experiment with multiple search algorithms that use different ways to categorize products and several criteria to decide their relevance to a search query to finally narrow down on the one that proves to be the most effective. Whatever the results of experimentation, there are a few things you can incorporate to ensure your users always find something that interests them or at least never leave disappointed.

Another one could be to provide autocomplete for quicker searches. It is, in fact, even advisable to ensure that misspellings also have results.

All these impactful steps will work together with an effective algorithm to create a delightfully seamless shopping experience for your users. Your customers are on-the-go shoppers who thrive in a mobile-first world, where personalization is king and thankfully, even more effective on mobile.

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Therefore, meticulously offering personalized, relevant, and intelligent product recommendations is as customary as it is an urgency, to unlock a whole new bunch of conversion opportunities. However, how successfully you are able to do so depends on the efficacy of your product recommendation algorithm. And mobile app testing allows you to put that to test.

You can experiment with multiple algorithms based on the diverse criteria of selection of the products to be recommended.

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The most common criteria you can test with include bestsellers from the category, trending products, new arrivals, top-rated products, etc. The search results page is where users are first introduced to your products. This will ensure your customers are given all the relevant information on the search results page that makes them take the desired action. How do you decide on the right amount of free credits in-game currency to offer that ensures the ideal balance between happy and hopefully, returning users and increased profitability?

Similarly, you can test to find out the ideal number of unlocked levels you should offer to ensure minimal drop-offs, maximum retention, and optimal monetization. An effective and almost indispensable strategy for monetization, in-game ads need to be seamlessly integrated within the app environment so they enhance the gaming experience rather than causing an unwelcome and annoying distraction.

At this unbelievable pace of growth, relentless innovation, and cut-throat competition in the mobile gaming industry, gaming app developers are now forced to constantly outdo their gaming experience to make the cut. Since mobile app testing allows you to experiment with even the dynamic elements of your app, you can alter different features for various user segments to tailor experiences for all gamers basis their level in the game, behavior, and demographic factors.

For instance, you could test whether dynamically changing gaming levels for certain dormant users can get them to return, level-up easily, and re-engage. This will not only deliver better, more delightful gaming experiences, but also help you figure out the critical pain points you can optimize to get users hooked. Pricing is another element that can be dynamically altered to strategically target various user segments to boost profitability while keeping users engaged.

Seamlessly onboarding a user on a mobile banking app can be challenging due to the obvious hesitation people have when it comes to sharing sensitive information online.

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Therefore, the onboarding process should be created so as to instill a sense of confidence within the users to shift their financial lives to their mobile phones. Continually testing your onboarding flow will empower you to optimize it for the most seamless, user-friendly experience to ensure your customers are not intimidated or hesitant to sign-up and use your app for all their banking needs.

Mobile app testing comes to the rescue here. So, mobile app testing becomes the obvious choice for optimizing mobile apps where data security is paramount. If you are just getting started with mobile app testing, you can take up simple tests to optimize your FinTech app. By highlighting how far users have come, you can eliminate roadblocks with regards to time constraints and confusion on the way ahead by clearly showcasing how close they are to the finish line.

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Another hypothesis you can test for is postponing inessential bits of the onboarding process until after the user has successfully registered. For instance, instead of providing the onboarding tutorial upfront during the registration process itself, go for the in-app contextual and interactive tours layered on top of UI elements, wherein hints are triggered, and tips are provided whenever users reach the relevant sections of the app or perform the relevant action for the first time. Also, when it comes to asking for permissions and personal information, you can test if giving more context as to why you need it can help you get the information or permission quickly.

For a food delivery business, the target audience, in all likelihood, ranges from white-collar folks looking to order organic or gourmet food to university goers looking for the cheapest late-night pizza place in town. By not using segmentation to target these two segments and all the others that lie in between separately, you are probably missing out on quite significant business opportunities.

By using analytics to better understand your users basis their demographic, behavioral, or geographic attributes, you can categorically target them. With the advent and huge success of on-demand economy, effortless and promising experiences can be instrumental in driving users to your app. And this is primarily why in-app personalization has taken center stage in the hyperlocal delivery landscape. The app allows users to place orders and select their desired pickup location for the same.

It was created with an aim to cut down on the long wait time their customers were experiencing at the restaurants. The product team at Chick-fil-A created a hypothesis that suggested better highlighting the credit card payment option would positively impact their mobile app payments and reduce customer complaints directed at their checkout flow. While the teams at Chick-fil-A were expecting the test results to be in their favor, even they were surprised by the outcome. Therefore, they were able to resolve a huge customer pain point and successfully optimize one of the most challenging sections of the app — the payment page.

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The challenge at hand for RunKeeper was to reposition the brand as the go-to destination for tracking all health and fitness-related goals as opposed to just being the leader in the running category. They decided to go about it by revamping their app design to one that highlights how the app can be used for various activities and at the same time, encourages people to inculcate those activities in their daily routine and notice the difference.

While the control allowed users to select the activity type from the drop-down menu on the start screen, the variation showcased different activities in an icon-based format that users could simply tap on to select. The result? The variation was declared the winner as it was 10X more successful in driving users to track their non-running activities on the app. As of June , The Sandbox had over 40M downloads and more than one million monthly active users.

Why Should You Use Mobile App Testing?

Pixowl initially struggled with a lower-than-average retention rate and often found it challenging to entice players back to the game and retain them. They tested to see if they could leverage push notifications to re-engage with dormant players. They created and ran a push notification campaign wherein inactive players were targeted after three, seven, and 14 days of inactivity with a push notification that persuaded them to return to the game.

The result was measured in terms of the percentage of users interacting with a notification and returning to the game. After running the experiment for 28 days on over , users, the results derived validated their hypothesis and how!

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The teams at VEVO discovered that even though tutorials are meant to help users understand how to use the app, the added steps can be frustrating and might lead to increased drop-offs. An online travel app that offers discounted, last-minute hotel accommodations across 36 countries, HotelTonight has been known for its virtually seamless user experience.