There’s a silent shift taking place that could change the way mobile and Web applications are developed in the coming years. Not only do consumers want fewer applications, but they want the applications they’re using to be more interactive, and they want new ways to engage with them. Many companies that empathize with these consumer requests have become early adopters of AI assistants and chatbot technology to address the app development shift. As a matter of fact, billions of dollars have already been poured into enhancing AI, machine learning, and Natural Language Processing (NLP) for future chatbots. So if your company hasn’t adopted a plan to implement chatbots in your products, where does that leave you?
Understanding the Current App Development Shift
Gartner estimates that by 2021, more than 50% of enterprises will spend more on developing bots and chatbots than traditional mobile and Web applications. Chatbots are expected to become the face of app development as companies look for new ways for bots to support their current applications.
Consumers are abandoning traditional applications faster than ever before. A 2017 report by Localytics reveals that almost 25% of all downloaded apps are deleted after just one use. Consumers are becoming tired of having to bounce in between applications just to send a message, check an email, see the delivery status of their package, and more. It can also be cumbersome to a user if they have to constantly learn new interfaces for each new application.
Consumers don’t necessarily want new apps, they just want the applications they’re currently using to be more interactive. If a user has to download a new application or search the Web for a service, this may inhibit the overall user experience. By understanding this shift, companies are not only looking towards chatbots to become smarter and more interactive, but to become an integral part of the user experience in their current applications.
Think of future chatbots as virtual assistants, being able to bridge requests from the user so seamlessly, that we’ll hardly know they’re even there. Imagine being able order a pizza, check your email, text a friend, purchase a plane ticket, and book a hotel all on a single platform. Better yet, imagine being able to do all of this within minutes. This will eventually be possible as the technology behind chatbots becomes more robust.
So where will this change take place? Results from a recent comScore survey shows that among mobile users, many spend almost 85% of their time using email or messaging apps like Facebook Messenger, Snapchat, Kik, WhatsApp, and more. As a matter of fact, BI Intelligence estimates that the most common messaging apps will have 1.4 billion users by 2019. These messaging apps prove to be great platforms for chatbots because of their easy-to-use interfaces, and familiarity amongst many users.
Niki.ai – The Intelligent Personal Assistant
A current chatbot that utilizes a messenger interface is Niki.ai; which was initially developed for Android, but has now expanded on the Facebook Messenger and Apple iOS platforms. Niki.ai’s core functionality is serving as a digital assistant which helps with scheduling and payments for more than 100 thousand users in India.
Booking a cab through Niki.ai is fast and simple, as it will automatically connect to GPS and find the closest Uber or Ola for the user with a single click. Pay your water, gas, electricity, or even insurance premiums through Niki.ai by connecting the bot to your Paytm wallet in chat. Users can also “top-up” their phone plan talk-time or data through Niki.ai’s in-chat Paytm feature by just typing in their phone numbers.
Niki.ai functions so well, that as of January of 2018, the company behind the chabot has been asked by Kerala-headquartered Federal Bank to launch a chatbot-based virtual assistant on the lender’s smartphone application, FedMobile.
Being able to offer these helpful services through a single messenger platform provides a great user experience. Even though Niki.ai is only available to users in India, it still serves as a model for future chatbots.
The Technological Next Steps to Advance Chatbots
Most chatbots available right now operate within a set of rules and parameters, being able to provide basic responses to basic questions. Other chatbots harness the power of AI and machine learning, which can provide a richer user experience, but can be more difficult to develop. These types of chatbots can be helpful to a user, especially in a customer service setting, but they’re not quite ready to replace traditional mobile and Web applications just yet.
There are a few technological barriers that developers will need to overcome in order for chatbots to make their way in the mainstream market:
The evolution of Natural Language Processing (NLP) and Natural Language Understanding (NLU)
NLP is a critical human-facing part of artificial intelligence, because it’s how machines and people interact with each other. NLP allows a machine to take in information, digest it, and develop a proper response that a person will be able to understand. Our current understanding of NLP is very limited, so this is where many companies are investing in.
NLU is actually a subset of the broader term NLP, and refers to the more complex challenges of machine learning — like being able to actually understand and respond to a poor or unclear request from a human. It’s important to remember that not every request is perfect, and humans are usually able to decipher mispronounced words, slang, and other quirks. Machines, however, have an extremely difficult time doing this. NLU will be the next step towards building a better chatbot.
Mastering voice interface for chatbots
One could argue that the best interface is an interface that requires the fewest amounts of taps, swipes, and clicks. This is why the market of AI assistants like Amazon’s Echo, Microsoft’s Cortana, and Apple’s HomePod have exploded in the past few years. There is currently no hotter trending way for users to interact with their technology than through a voice interface — and the research supports it.
By 2020, comScore estimates that 50% of all searches on the Web will be vocally prompted. Additionally, 30% of all searches will be done without even looking at a screen. The average person can speak up to three times faster than they can type, which can allow a chatbot to provide quicker results through a voice interface. Lastly, a voice interface requires the least amount of time to learn, and can be implemented on a single messenger app.
Knowledge-base enrichment and minimizing the data in which chatbots require to learn
The current leading chatbot algorithms require a ton of data to train a chatbot. The more data a chatbot has to process, the slower its response. This is in part to a lack of knowledge-base enrichment, which not only stores valuable information for a chatbot, but also determines its quality of learning. When the information is stored correctly with the right rules and data structures, it can greatly enhance a chatbot’s ability to learn.
Can Mobile and Web Applications Compete with Future Chatbots?
The phrase “there’s an app for that” may soon become irrelevant as more users conclude that they don’t want to constantly load their devices with new applications. But companies that don’t have chatbot development in their scope shouldn’t look at it as a “competition,” but as a way to understand the growing wants and needs of consumers.
Chatbots still have a while to go before the technology behind them has reached a point that will outpace Web and mobile application development. Also, chatbots aren’t currently being developed with the sole purpose of replacing Web and mobile applications. Many of them are meant to serve as an extension of an existing application — like a messenger application as we have mentioned before. The purpose behind this is to evolve the overall user experience, and minimize the total amount of applications a user has to navigate through in order to complete a task.
As more money and research is poured into chatbot development, it will ultimately transform the way future applications are built. But this won’t inhibit the traditional app development industry, it will evolve it. Advancements in chatbot technology may also provide breakthroughs for completely voice-based operating systems, but only time will tell.
