7 Essential Wow Features for Mobile Apps in 2024

A search based on artificial intelligence (AI) is a game-changer when it comes to helping customers make purchase decisions. It goes beyond traditional methods by understanding the context of user searches. Instead of solely relying on keywords, AI-powered search algorithms can understand the intent behind user queries. This allows for more accurate and relevant search results.

Understanding customers’ intent helps when they are unsure of the exact item they need but can describe the occasion. For example, a customer might be looking for something to wear to a party. In this case, a search query “what to wear to a summer party outside” would be more relevant than a “party dress.” If the app can address this specific query, the customer will feel heard and find what she needs faster.

To implement an improved search, companies either partner with the organizations that provide large language models (LLM) or develop their own models. Instacart followed the first path and partnered with the AI research laboratory OpenAI. The result is an AI-powered search tool called Ask Instacart. The tool assists customers with grocery shopping questions, like “what to cook for dinner” or “products for weight loss.”

Expanding the app’s functionality beyond the main product has become one of the software development trends. Online clothing stores add chats with personal stylists to their apps, while home improvement stores provide their mobile users with AR measurement tools. To add a new service, a company may create a completely new app, but a better approach is to add a mini app to its existing m-commerce application.

A mini app is a small program that operates within the main app. It functions like a regular application but without the need to install it separately. This makes it convenient for customers because they can access extra features without having to download a new app.

There are two ways a company can benefit from mini apps—it can build its own super app with ancillary services, or join an existing super app and create a mini app inside it.

The first approach means that a company adds new services to the existing mobile app. For example, here’s how we helped a European neo-bank build a financial super app IZI. At its core, IZI is a mobile banking service, but it offers much more than money management—users can buy movie tickets, plan trips, book restaurants, and find beauty salons nearby without leaving IZI.

The introduction of Apple's visionOS for the Vision Pro AR headset is a huge milestone for developers. This release is expected to inspire a wave of app development that will show the full potential of this new platform. The main reason for this is that forward-looking companies are likely to try and surprise their customers with the new experience.

According to Apple, development for visionOS is not that different from other Apple platforms. It’s based on the existing APIs that have been around for a while—Swift UI, RealityKit, and ARKit. Hence, although visionOS will have its own app store, developers should get familiar with the new platform quickly, given that the software development kit should be available soon.

Tech giants say that passkeys are the beginning of the end of passwords. The reason for such a bold statement is that passkeys are a safer and easier way to sign in to apps and websites. Instead of remembering passwords, users hit one button and authenticate with fingerprints or facial recognition. That’s it—no need to enter a password or even a username.

Companies can add a passkey sign-in option to mobile apps on iOS and Android by using Apple’s and Google’s frameworks. Both tech giants have included a passkey section in their developer guides to encourage passkey adoption.

This has already brought results—Kayak and Instacart report that thanks to Apple’s underlying framework, implementing passkey functionality was “relatively smooth.”

Here is how passkey technology works. Users start by adding a passkey to their account settings. If it’s an iPhone, they will be asked to choose a passkey from their iCloud Keychain—Apple’s password manager.

Next time when a user tries to sign in to their account on another device, they’ll have the option to use a passkey. The sign-in will happen when they push the button “Continue” and use their fingerprint or face to authenticate.

Personalization has been among mobile app design trends for a long time, yet we see new forms of it appearing every year. One of them is a gender-inflected user interface—UI that is adapted to the user’s gender. Gender-inflected UI matters because a third of the world’s population speaks languages that use grammatical gender, and their devices should reflect that.

For example, “you are subscribed” in Spanish sounds different depending on gender—“estás suscrito” and “estás suscrita.” Some apps default to masculine grammatical gender, which can be offensive for non-male users. Another option to solve the problem is to rephrase the sentence, but it can be time-consuming to find the right words. Thus, the problem persists.

If a part of the app’s audience speaks Spanish, French, or other gender-inflected languages, it makes sense to use Grammatical Inflection API. It means that developers can make the UI user-centric without too much coding. Instead of building the feature from scratch, they use the API to dynamically adapt the app’s language. The API helps the app retrieve gender info from the user’s profile and generate grammatically correct phrases.

Machine learning (ML) opens up possibilities for features powered by AI. In the past, ML primarily ran on servers in the cloud. However, recent advancements allow for processing the data directly on the device within a mobile app. This means that the ML model processes images, text, or audio, directly on the device instead of sending the data to a server.

By leveraging on-device ML, companies will enhance the engagement, personalization, and utility of their iOS and Android apps. For example, a fitness company can use pose recognition in a fitness app to guide users toward proper posture during workouts. And an online store can include more search options in its app, like search by barcode or by image, quickly and easily.

To enhance an app with on-device ML, app developers can use APIs for vision, speech, natural language, and sound analysis. Google and Apple both have sets of these APIs. They apply algorithms to perform a variety of tasks on input data—images, text, video, and sound. It means that developers can embed features like text recognition, animal recognition, UI translation, or barcode detection in their apps without any machine learning experience.

App modularization is an approach to app development that involves breaking down a large app into smaller modules, or microservices. Each of these modules handles a specific feature or functionality. Modular architecture is the opposite of monolithic architecture, and the reason why it’s trending is reduced compile time.

When developers build an app, they write the source code and then convert it—or compile it—into a format that can be read by a mobile device.In a monolithic architecture, even if a small change is made to a source code, the entire app needs to be re-compiled. Thus, adding new features to such an app takes too much time. Modular app, however, doesn't require full recompilation.

“In a modular app, developers can make changes only to one module, and only that module needs to be re-compiled. This significantly speeds up app development, updates, and maintenance.”

Andrew

Project manager at HeyInnovations

One way to achieve a microservice architecture is by splitting an existing monolithic app into smaller, more manageable microservices. In the second approach, developers design a new app in microservices from the ground up.

When it comes to large apps, they are typically structured in a modular way. If a company is planning to create a large app, it makes sense to make it modular from scratch. For instance, Google has been using modularization to develop its most popular applications such as YouTube, Play Store, and Google News. We have also worked on a modular app project for one of our clients, Sportmaster.