Monetization Strategies: How Will Bots Become Profitable?
Interest in chatbots is surging. Currently, traditional mobile apps and games have hit a wall; usership is lagging with no sign of growth anytime soon. Messaging services, however, are showing steady growth, and have already eclipsed social media usage.
According to Business Insider, Millennials and Gen Xer’s are already comfortable with chatbots, with an estimated 60% of both generations having interacted with them before. Investing in chatbot tech seems like the next logical step for those looking to tap into the mobile market’s true potential.
Big companies are already paying attention to the profitable potential of bots. Facebook launched Messenger Platform, a platform that allows for the creating of chatbots for Facebook Messenger, last year. Zuckerberg predicted at the time of launch that it was going to be the “next big platform” for connecting business and customers to all sorts of services.
“We think you should just be able to message a business in the same way you’d message a friend. You should get a quick response and it shouldn’t take your full attention, like a phone call would, and you shouldn’t have to install a new app,” Zuckerberg explained at the F8 conference last April.
“It’s a simple platform. It’s powered by artificial intelligence, so you can build natural language services to communicate directly with people.” Zuckerberg showcased some of Messenger’s chatbot chops, such as ordering a bouquet from 1–800-Flowers with a few simple chat commands without the hassle of entering in credit card information. “I find it pretty ironic,” Zuckerberg joked, “because now to order from 1–800-Flowers, you never have to call 1–800-Flowers again.”
The Messenger Platform is only the beginning. Developments in artificial intelligence and in natural language processing (NLP) have made chatbots not only smarter, but much better conversationalists. Gone are the days of having to input incredibly precise commands. Current chatbots have the ability to extract meaning from context, much in the way that humans do.
While we’re a long way from AI being able to replace human representatives in every capacity, recent strides in AI technology have enabled chatbots to handle a great deal of the drudgery of everything from online shopping, scheduling important meetings to fetching data about today’s weather forecast. This leads us to an important question: now that chatbots have proved themselves to be useful workers, how do we generate revenue from their labor? How do we make it so when a user queries a chatbot about current traffic conditions, the response generates some sort of profit?
In Facebook’s demo of their platform, the example of 1–800-Flowers seems like an obvious application of bots. A retail company, like 1–800-Flowers, would develop its own chatbot, which would allow users to place orders, and immediately convert. But what about a chatbot that simply retrieves data, in which no product is being sold? This is when things become less obvious. There are a few business models that may prove useful to chatbot companies, like those employed by SaaS companies, in these cases.
Chatbots, like SaaS, could be available to users at a subscription. Many chatbots could offer introductory features for no fee, then introduce premium tiers. For example, a traffic-focused chatbot may give a user one free traffic report a day, but lock more extensive traffic analysis and recommendations for paying subscribers. Of course, there are drawbacks to this model: there’s no guarantee that users will be willing to pay for chatbots as readily as they do for other SaaS products. Luckily, there are other models; models that do not require payment from users, but from advertisers. This is especially attractive to consumers.
Native and sponsored advertisements have proved successful for many ventures. Tencent Holdings reported massive growth last March, largely due to the success of the ad revenue they generated from their messaging app WeChat, which offers chatbot services in addition to instant messaging.
Affiliate marketing could be integrated even more seamlessly. For example, when interacting with a chatbot, certain sponsored brands could be shown preference when providing answers. When a user asks for a book by Ernest Hemingway, the bot could direct them to Amazon’s ebook store. The chatbot when then be credited as a referrer and receive a small kickback from Amazon if the user completes the purchase. Both native advertising and affiliate marketing reduce the burden on your consumer. Still, quality chatbots that dispense valuable information may find more luck with a subscription model. It all depends on the abilities of the chatbot and the spending habits of its target market.
Maximizing profit from bots will certainly be a learning process. At present, we’re able to look a previously successful monetization strategies. We can apply those strategies in new ways to address the unique challenges of the chatbot market. There will be bumps along the road, but eventually an optimal strategy will emerge, whether it be one replicating SaaS or one utilizing affiliate marketing. In the meantime, developers and business leaders need to work together to properly assess the potential of chatbots to determine which strategies are best suited.
