How to Use AI in Mobile Applications?
Mobile Applications remain the prime focus for enterprises, be it for internal customers or external. Whereas big tech companies like Google, Baidu, Microsoft, IBM and others are getting engrossed in the newer emerging technologies like Artificial Intelligence (AI), Blockchain, AR/ VR etc. AI especially is taking the world by storm in almost all spheres of business be it retail or healthcare or automobiles.
Some enterprises have started pondering on whether they should adopt AI first or the mobile apps. Today, I have tried to point some ways in which AI can be used to make mobile apps intelligent which also has been mentioned in Gartner’s Top 10 Strategic Technology Trends for 2017, more than just digital assistants that make it easy to complete common tasks such as prioritizing emails.
Why add AI to your mobile app?
Applying AI technology to your mobile app personalizes and streamlines the user’s experience at a level in-achievable by a ‘one size fits all’ interface. AI can be used for many purposes, but within the context of mobile, it can be embedded using chatbots or in context-aware sensors. Many companies in the western world are beginning to adopt AI as a tool to deeply engage and ultimately retain their users.
What makes mobile an ideal platform for AI apps is the varying array of personalization capabilities. Smartphones are aware of user location and the outside world beyond the home, so integrating AI makes apps even more relevant and personalized. AI capabilities are being built into mobile apps of all kinds, making them contextually aware of user behavior through actions, likes, preferences, purchases and more. These technologies can be used to learn users’ behavioral patterns to make each app session more valuable than the last, increasing overall retention rates.
Problem areas in which AI can be used in mobile apps:
* Facial recognition – Think Facebook’s automatic tagging suggestions when you upload a photo.
* Artificial creativity – For example, AI generated apparel designs. Tried currently by likes of Myntra
* Speech recognition – Adobe’s new ‘Photoshop for audio’ platform, VoCo, lets you edit speech as easily as text.
* Learning behavior pattern – fraud detection for online payments. Pattern-detecting algorithms go through your credit card statements and purchases as they happen, and can detect if you’ve made a recent purchase out of the norm of your behavior.
* Email spam filtering – Online grocer Ocado uses AI to prioritize customer service inquiries over busy periods, such as Christmas or during freak weather events. The technology reduces email overload on the customer service team by assessing the urgency and nature of each query using natural language processing and cloud computing.
* Recommendation services – The reason why most apps fail within a year of launch is that they fail to provide relevant content to continuously engage users. You may be providing fresh content regularly, but if it isn’t something that is interesting to the end user than it isn’t worth the time you spend creating it. This is a powerful source of revenue for such entertainment app like Netflix. Yet any business that up-sells or cross-sells content can utilize this type of AI. Every time you click, the algorithm grows smarter and delivers you more and more relevant content.
* Automated reasoning — it is the art and science of getting computers to apply logical reasoning to solve problems. This way AI machines beat humans at chess, stock trading, poker etc. Uber uses automated reasoning to optimize routes and get the riders to their destinations faster. The algorithm takes millions of bits of data from Uber Drivers who have traveled similar routes and learns from their trips.
* Purchase predictions – Online retailers like Amazon make a lot of money from accurately predicting your purchase behaviors. Amazon is currently working on rolling out anticipatory shipping, a technology that sends you items before you need them, removing the need for you to make last-minute visits to the website. With enough data on your purchase history for certain products, Amazon can prompt you to purchase more toothpaste, for example, when its algorithm predicts you are about to run out.
The above examples illustrate how AI can solve problems as a standalone technology.
70% of applications are deleted by users after the first week. This implies the initial 1-5 sessions are significant for retaining new customers.
Enterprises are much more likely to make these sessions memorable if they use AI technology to learn customer’s behavior and make each app session more valuable than the last.
Would you like to explore how AI can benefit your application/s? Comment here or contact me.