Artificial Intelligence, or AI, is everywhere these days. From once being a futuristic concept in Hollywood movies, to now touching our lives everyday, the advent has been really swift and revolutionary. What started with digital assistants such as Siri, is now the magic working behind the scenes for almost all of our major apps in this mobile-first market.
AI has also transformed how we interact with our smartphones. Thanks to the advances in the fields of Natural Language Processing, Deep Learning and Machine Learning, we have been able to make chatbot interfaces, which are much more natural and convenient. The digital assistants can now not only understand our commands in our natural conversational languages but only also help us make smart choices and complete the orders. This field, called conversational commerce, is so full of potential that it is being hailed as the next big revolution to happen after the ‘app revolution’.
This AI-powered ‘app revolution’ has the potential to impact how we use mobile and mobile apps, as well as mobile advertising, as we know it. Mobile has undergone a change from being a mere device to make calls, to being a personal experience. And, with AI, it has become more personal than we could have ever imagined.
We are at the cusp of another revolution in the world of mobile technology. And it might be the biggest one yet. Here are some innovations that we can see soon using the concept of AI and Machine Learning:
App User Interfaces
From WeChat becoming a mobile OS to Facebook Messenger becoming a platform for customers to interact with businesses, apps are fast evolving. The traditional tap interface is becoming restricted in terms of what it can achieve, and experts say will be replaced by the chat interface in the very near future. Shifting from a tap interface, now users can make use of chatbots for a smoother experience such as calling a cab, making a hotel booking and even making payments.
The chatbots can unleash the potential of AI to improve the user experience manifold. In recent trends, chatbots are becoming more prevalent. We are already seeing that in how chatbots are being integrated. Facebook, for example, has integrated chatbots into its Messenger app for seamless interactions for businesses, while others such as Google have a new AI-powered voice-activated digital helper that is built into their new lines of phones. Chatbots are the future, and the future is almost here.
Improve the User Experience
One of the biggest applications of AI is automated reasoning. We can program our apps so that they can make decisions really fast after taking various different parameters into consideration. AI and Machine Learning have made apps, as the name suggests, ‘intelligent’ in that now they can think on their own with minimum human intervention. The algorithms which make this capability possible take in millions of data points provided by analysing the actions of the users on the app.
Automated reasoning helps us make apps much more personalized, rather than a ‘one size fit all’ experience. It provides an improved user experience for the users and a better product, backed by data and numbers. Uber uses this technology to provide the best route to its driver by learning from previous trips along the same route taken by their drivers.
Sentiment Analysis to Understand the User
AI is being powered to study our habits and better serve us. App marketers can now begin to better understand a user’s behavior on the app through their actions, likes and preferences. With AI and Machine Learning, app advertisers can do sentiment analysis, which is the process of determining the emotional tone conveyed by sentences of natural English. It can be used to gain an understanding of the attitudes, opinions (positive, negative or neutral) and emotions expressed by customers. This understanding of the customer will allow advertisers to recommend and suggest items or content that is relevant to each user. It will also allow them to learn a user’s behavior patterns in order to make the future sessions personalized and seamless.
This is already used by YouTube to recommend you similar music. Amazon uses it for product recommendations. In the near future, app advertisers would also be able to push the right product based on the emotions of a user. For example, on the Niki App, users get relevant recommendations from the chatbot that helps users make the right purchase for each service. For example, if a user asks for hotels in Manali (a town in India) which have a swimming pool, we will be able to recommend the relevant options.
Ad Targeting
Any mobile marketer will tell you that the art of targeting is a process of trial & error, tweak and repeat. You build a hypothesis about your target, run the ads, analyze the conversion and then retarget again. Machine Learning can help in this regard by ‘learning’ the user behavior to all ads, comparing it to the user’s behavior to your ad, and then helping you define your target demographics with a better focus.
Similar to a lot of other AI application on marketing, Deep Learning is behind how to do the right ad targeting. Deep Learning is the science to ‘teach’ the machines, recognize patterns and then apply these ‘learnings’ to solve various complex queries. Andrew Ng, Chief Scientist at Baidu Research, recently told the Wired magazine, “Deep learning [is] able to handle more signal for better detection of trends in user behavior. Serving ads is basically running a recommendation engine, which deep learning does well.”
Cross Selling on the App
Acquiring new users for your app is tough, time consuming & expensive. But selling more to existing customers and gaining the maximum revenue from your mutually beneficial relationship with them, is one of the main driver of growth for any firm.
The analysis of past transactions, views and actions can help you classify users into various “similar” groups of customers. You can then use the behavior of these groups as data points, and use predictive analytics to push immediate, real-time suggestions in your app about other products and services in the catalogue effectively to the customer. At Niki.ai, we make informed and extremely cautious decisions of ‘who’ to sell ‘what’ and ‘when’ backed by past data and user behavior.
Look Ahead
While we have seen many advancements in AI in the year 2016, many experts believe that 2017 will be the year when AI really start majorly impacting the everyday lives of millions around the world. The market for AI is ripe and research estimates put it at around $5 billion by 2020, as the adoption of Machine Learning and natural language processing technologies increase. It will be interesting to see how we move from a mobile-first world to an AI-first world that will change the mobile apps, as we know them today.
