How Facebook is planning to bring businesses and ads to Messenger with the help of AI-enabled chatbots and its own virtual assistant M
Ainsley Harris / Fast Company : Tweets: @noahr . Thanks: @hellomountfuji Tweets: Noah Robischon / @noahr : “It's one thing to be selling a product at the exact right time,” says Robyn Caplan, a researcher at the Data & Society think tank, of Facebook's ad targeting. “It's another thing to start selling ideas at the exact right time.” http://www.fastcompany.com/... Thanks: @hellomountfuji
Context & Ripple Effects
This piece lands at the end of a two-year build-out: Facebook first tested M, its human-supervised virtual assistant inside Messenger, then opened the door to commerce with developer access to a chat SDK for shopping and travel bots, launched the full Messenger platform with chatbots alongside the Bot Engine built on Wit.ai, and began testing sponsored messages from businesses. What Fast Company adds is the synthesis: chatbots plus M are the mechanism for turning Messenger from a messaging utility into an ads-and-commerce surface.
First-order effects
- Businesses gain a direct conversational channel into Messenger — bots handle inquiries and transactions while M completes purchases on users' behalf, moving commerce into the chat thread itself.
- Robyn Caplan of Data & Society flags the sharper edge: the same targeting machinery that sells products at the right moment can start 'selling ideas' at the right moment, extending ad targeting from purchase intent to persuasion.
Second-order effects
- Developers building on the Bot Engine and chat SDK become the supply side of the ecosystem — their bot quality determines whether businesses actually shift spend from feeds into threads.
- Rival messaging platforms face pressure to open equivalent commerce and sponsored-message APIs, since advertisers will follow whichever chat network can close a transaction inline.
Third-order effects
- If the pattern holds, messaging apps consolidate into AI-mediated commerce layers where the assistant sits between buyer and seller — concentrating both transaction flow and the intent data that powers targeting in one platform.
- Caplan's product-versus-ideas distinction points toward the scrutiny that follows: when conversational ads are indistinguishable from assistance, regulators and researchers will treat chat-targeting as a persuasion problem, not just an advertising one.
The trend: Messaging platforms are being rebuilt from communication utilities into AI-assistant-mediated commerce and advertising channels, with the assistant as the new transactional interface.