Facebook Messenger is looking to do more than just help users communicate with friends.
With the help of dining app Allset, a new Facebook Messenger chatbot will be able to help users in San Francisco, Palo Alto and New York order, pay for meals and even book a table at a restaurant.
Allset is the latest business to hop on the chatbot bandwagon.
The new chatbot will also have the ability to look for nearby restaurants and curate meal suggestions, CNET reported on Tuesday (July 26).
“We want to bring lunch reservations directly to where people spending a lot of time chatting with friends and colleagues,” Allset CEO Stas Matviyenko explained in a statement. “Facebook created a great opportunity for us to offer a cross-platform service to our users, available both on their phones and computers.”
As of now, 180 restaurants across San Francisco, Palo Alto and New York will participate in Allset’s Facebook Messenger chatbot service.
Just last week, Polly Portfolio, the wealth management technology platform for asset managers, launched into the chatbot game with Facebook Messenger. The bot, dubbed Polly Chat, is free to use and enables users to have a conversation about financial news. The bot also creates a financial profile and gives users customized trade ideas based on their responses.
“We recently released Polly Chat, the first investment chatbot for Facebook Messenger. Polly Chat engages you in a conversation about recent financial news headlines and prepares a financial profile based on your responses, along with customized portfolios and trade ideas. All free,” the company said in a blog post.
The move on the part of Polly Portfolio comes at a time when Facebook is testing out chatbots that work with SMS or Facebook Messenger but not on an app. Facebook is hoping it catches on with businesses that opt to write code for the bot rather than for Android and Apple devices. It also comes at a time when alternative investment companies, relying on technology, are taking on the traditional banks and investment companies, luring customers who want personalization but don’t want to pay a lot for it.