- Mobile

Teach Your Apps, Not Your Users: AI Intervention

The demand for applications is more than ever today. Applications have become a handy tool for enterprises to take their businesses to customers’ pocket. The revenue models are redefined with applications. It is expected that by 2020, mobile apps will generate around 189 billion US dollars. (Forrester forecast) And, 71 percent of marketers believe mobile marketing is essential for business. (Salesforce)

In this landscape, the way your application performs plays a crucial role in determining your success. A user looks into the app to find relevant information. When relevant details are not available on the applications or do not find what the users are looking for, they are likely to uninstall the app. For instance, for e-commerce apps, 74 percent of online shoppers get frustrated when content is not relevant to their interests”.

With the most advanced technology interventions, it is possible for businesses apps to recommend the right information to its users (customers).

So, how do you teach your apps? 

Before, we focus on “how” to teach your apps, let’s understand what do we mean by “teach” here.

With cognitive technologies coming into picture across industries, the apps can learn from the user-behavior. Cognitive technologies such as Artificial Intelligence, Machine Learning, and Deep Learning enabled the systems to learn from information, patterns observed or even from experience like humans.

Intelligence is embedded in the devices to understand human actions and allow the devices to perform tasks that are most specific an individual. They have the ability to understand human speech to identify. They are capable of perceiving simulations and acting upon.

Algorithms are derived in this process to analyze unstructured and complex data and perform data processing and automate logical tasks.  It turns ordinary systems into intelligent systems to make accurate decisions.

When it comes to apps, the development process must integrate the features which meet your customers’ requirements. The development doesn’t end once the apps are deployed. It is continuous. The apps evolve with time and become a ‘self-learning system’. This where cognitive technologies play their part to permit personalization of app. It is two-fold:

  • User Interface
  • User Experience

User Interface (UI) includes a series of visual elements such as color, pages, icons which are most often used to interact.

Whereas, User Experience (UX) is mostly the internal experience of products and services. It includes features such as a dialogue box, search recommendation based on location, preferences or offers.

However, these two components use the same strategy in acquiring favorable results. The strategy involves

  • Acquiring Data:  In this process, the app collects different samples from several sources such as account details (Sign in details), user-search preferences, location, gender, age group and all the information that define the user persona. This information is usually unstructured.
  • Data Structuring: The information in the first step is gathered and use Machine Learning and Deep Learning tools to organize the acquire information of a specific individual or a group. This often involves categorization, manipulation and sorting of details in multiple ways.
  • Identifying Hidden Patterns:  In this step, algorithms are used to streamline the data to recognize the patterns that are relevant to the target group or individual. These algorithms identify the format or the nature of content across several parameters taking categorization to next level. Algorithms used here are mostly derived based on specific requirement. Depending on the algorithm, the process of automating data classification can be either partial or complete. In order to save time and strenuous effort, the patterns can be established without human intervention.

Teach Your Apps, Not Your Users: AI Intervention

  • Form a Robust Knowledge-base: The output of the earlier step is structured information which contains a set of facts, notable features of the user which can solve multiple issues of the application.
  • The AI Intervention: Artificial Intelligence techniques are used to take major decisions and help a user get the best of apps and available content whether it is product recommendations or search recommendations that reduce the tasks of the user. Hence, the user need not make endeavors to find what’s specific to him or her. The search process is simplified. From a UI perspective, the icons or menu is modified based on the user-behavior and what is most comfortable to the user.

For instance, the advanced technology enables the apps to identify the user is left-handed or right-handed and change the menu according to the user convenience.

  • Integrate into Apps: The definite features are integrated with the apps to allow enhanced UI and UX.

With the above process you don’t teach your users how to use the apps, rather the apps learn how the user uses the app. These personalization techniques have become the norm of the day. One of the key properties of AI is that it is dynamic in nature. It is constantly upgrading to enhance the app performance and experience. However, it is invariably dependent on the algorithms derived to employ while automating the process.

Today, the native app development is intertwined with AI platform to allow personalization of app to an individual level and deliver better experiences to the user.

Teach Your Apps, Not Your Users: AI Intervention

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