Rule-based auto reply
Route different interaction types to different actions, such as thanking positive comments, answering support requests, or skipping low-priority items. Rules can be scoped by platform, sentiment, and intent.
Yuma Social AI automates ecommerce comments, DMs, and review workflows across social channels. It helps teams moderate conversations, respond in brand voice, and move customer questions into private messages when needed.
Yuma Social AI is an ecommerce automation product for managing comments, direct messages, and reviews across social channels. It is designed to monitor incoming interactions in real time, classify them by intent and sentiment, and take configured actions such as replying, hiding, flagging, or moving the conversation to a private DM.
The product is positioned for teams that need to keep social support, moderation, and brand responses consistent without manually scrolling through every thread. The page emphasizes configurable brand voice, safety checks, gradual rollout, and analytics so teams can automate routine interactions while keeping control over sensitive cases.
Route different interaction types to different actions, such as thanking positive comments, answering support requests, or skipping low-priority items. Rules can be scoped by platform, sentiment, and intent.
Automatically flag or hide spam, phishing links, bot comments, and other unwanted content so teams spend less time on manual cleanup and public threads stay focused.
Turn comments that need a private exchange into DMs, while posting a brief public response first. This supports purchase questions, account issues, and other conversations that should not stay in public view.
Define the persona, tone, verbosity, emoji usage, and written guidelines the AI should follow so replies stay aligned with the brand voice across channels.
Review comments in a single feed that shows the original post, customer profile, intent classification, sentiment, and the action the AI took. This helps teams monitor what the automation is doing.
Track automation coverage, sentiment trends, response speed, engagement lift, revenue from AI-assisted threads, and errors to monitor performance over time.
Use Social AI to monitor public comments on posts and ads, answer simple questions, and hide spam or harmful content before it distracts from the conversation.
Route questions about availability, sizing, order status, or account details into DMs so support can continue privately with more context and less clutter in the comment thread.
Keep review and praise management consistent by automatically thanking positive commenters and surfacing helpful feedback for follow-up.
Watch for spam, misleading links, insults, and other negative content across social channels so the team can respond quickly and protect the brand presence.
Use the analytics and review feed to see which automations are working, where sentiment is changing, and which interactions need manual review or rule changes.
Yuma’s Social AI is set up by connecting Facebook and Instagram pages, defining automation rules, and then letting the system classify and act on comments and DMs based on the rules you choose. The page also describes a lightweight one-click setup and a snippet for going live quickly.
The source specifically shows Instagram DMs, Instagram comments including ad comments and mentions, Facebook Messenger, and Facebook comments. The broader site also says Yuma covers 25+ support channels and includes a native Chat AI widget, but this Social AI page focuses on social channels.
It can reply publicly, like or flag interactions, hide or move comments to DM, and use brand guidelines, tone, verbosity, and safety checks to shape responses. The page also says every reply goes through quality checks before posting.
Yes. The page says a public comment can receive a brief reply and then be moved into a private DM when the topic needs a one-to-one conversation, such as order details or account issues.
The page describes Social AI as useful for comment moderation, review replies, social listening, and DM conversion flows. It is positioned for ecommerce teams that want to manage real-time customer interactions without manually monitoring every thread.
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