Skip to main content

Analyzing Your Inbox & Engagement

Use Obie to analyze comments, DMs, emails, sentiment, ad performance, and trending topics across all channels.

Written by Alec Corum
Updated today

Obie has full access to your inbox data across every channel. Ask questions in plain English and Obie will query your data, analyze patterns, and surface insights.

Channels & Data

  • Comments — organic posts, ad posts, Reels, Stories (Facebook, Instagram, TikTok)

  • DMs — Instagram, Facebook, and TikTok direct messages

  • Emails — all email inbox threads

  • Live Chat — website chat conversations

  • Meta Ad Data — campaign names, adset names, ad names and IDs for every ad comment

Filters You Can Use

Obie can filter your data by:

  • Date range (e.g. "last 7 days", "past month")

  • Smart Label (e.g. "all messages labeled Product Complaint")

  • Channel (comments, DMs, emails, live chat)

  • Platform (Facebook, Instagram, TikTok)

  • Status (unread, seen, resolved)

  • Ad vs. organic content

Sentiment Analysis

Obie can analyze the tone and sentiment of your messages — across a single ad, an entire campaign, or your full inbox. It breaks down positive, negative, and neutral sentiment and highlights specific messages driving each.

Trending Topics & Clustering

Ask Obie to group similar messages together to find recurring themes, common questions, or emerging issues across any channel.

Ad Campaign Analysis

Since Obie has access to your full Meta ad hierarchy (campaigns → adsets → ads), you can ask it to compare engagement across campaigns, identify your best and worst performers, or drill into a specific ad's comments.

Example Prompts

  • "Analyze the sentiment of all incoming messages across comments, DMs, and emails over the last 7 days. Break it down by channel and highlight any spikes in negative sentiment."

  • "Which ads have gotten the most comments in the last 30 days?"

  • "Cluster all ad comments from the last 30 days into themes. Show me the top recurring topics and flag any themes that suggest product confusion."

  • "Find all comments with the 'Product Complaint' Smart Label and identify the top 3 reasons people have complaints."

  • "Review all comments, DMs, and emails from the past 7 days and identify the 10 most frequently asked questions."

Did this answer your question?