You're scrolling through 200 comments on your latest video. Most are praise, some are feedback, a few are spam. But somewhere in there, someone asked a question — and you missed it.
Not because you weren't paying attention. Not because you don't care. But because the question didn't look like a question.
Here's the thing: not all questions use question marks.
The Hidden Question Problem
When we started building Engage Suite, we noticed something: creators were missing questions constantly. Not the obvious ones like "What camera do you use?" — those are easy to spot. But the subtle ones. The ones that look like statements but are actually asking for help.
Real examples we see every day:
Example 1: The Confusion Statement
"I'm confused about the part where you mentioned the settings. I tried following along but something isn't working."
This looks like feedback. It's actually a question. They're asking for clarification, but they phrased it as a statement about their confusion.
Example 2: The Implied Request
"Would love to see how you set up the lighting for this shot."
This sounds like a compliment. It's actually a question disguised as a request. They're asking you to explain or show something, just phrased politely.
Example 3: The Uncertainty
"Not sure if I'm doing this right. The results look different than yours."
This reads like a simple observation. But it's someone asking for validation, help, or clarification — they just didn't phrase it as a direct question.
Example 4: The Rhetorical Question
"Why would anyone do it that way?"
This has a question mark, but it's rhetorical. However, in context, it might actually be someone genuinely asking for an explanation. The challenge is understanding the intent.
How We Approach Question Detection
We didn't build this feature by looking for question marks. We built it by understanding what questions actually are — and how people actually ask them.
Understanding Intent, Not Just Syntax
A question isn't defined by punctuation. It's defined by intent. Someone asking for help, clarification, or information is asking a question — regardless of how they phrase it.
So we built our detection around understanding intent, not just pattern matching.
Context Matters
Here's what makes this hard: the same words can mean different things in different contexts.
"I'm confused" could be:
- A genuine question asking for help
- A statement expressing frustration
- A rhetorical comment
We can't tell which it is without understanding the video's context. What was the video about? What topic is the comment referring to? What's the overall sentiment?
That's why we analyze comments with full video context — not in isolation. We understand what the video covers, what the commenter is referring to, and what they're likely trying to accomplish.
Our Detection Process
When we analyze a comment, we look for several signals:
1. Direct Questions
- Obvious question words (what, how, when, where, why, who)
- Question marks
- Direct requests for information
2. Implied Questions
- Statements expressing confusion or uncertainty
- Requests phrased as compliments or suggestions
- Comments seeking validation or confirmation
3. Contextual Questions
- Comments that reference specific parts of the video
- Statements that suggest the commenter tried something and needs help
- Observations that indicate a gap in understanding
4. Rhetorical vs. Genuine
- Understanding when a question mark indicates a real question vs. rhetorical expression
- Recognizing when someone is genuinely asking vs. making a point
We use AI to help with this analysis, but the real work is in our decision framework — understanding what makes something a question worth answering, not just a pattern to match.
Why This Matters
When you miss a question, you miss an opportunity:
- To help someone who needs it
- To build a relationship with a viewer
- To show you're engaged and listening
- To create content that addresses real needs
Questions are engagement signals. They show someone is:
- Actively watching your content
- Trying to apply what you're teaching
- Invested enough to ask for help
- Potentially becoming a loyal viewer
Missing questions means missing these opportunities.
How It Works in Practice
When you use Engage Suite, we automatically analyze every comment and identify questions — even the ones that don't look like questions.
You can:
- Filter to see only questions — instantly find what needs answers
- See questions highlighted — never miss one in a long comment thread
- Understand the context — see what part of your video the question relates to
You don't have to scroll through 200 comments looking for question marks. We find the questions — obvious and hidden — so you can focus on answering them.
The Real Value
This isn't about technology. It's about understanding how people actually communicate.
People don't always phrase questions as questions. They express confusion, make requests, share uncertainty. But they're still asking for help — and they deserve answers.
We built our question detection to understand that. To see questions the way people actually ask them, not just the way grammar textbooks say they should be phrased.
Conclusion
Questions come in many forms. Some are obvious. Some are hidden. All of them deserve answers.
We detect questions by understanding intent, context, and how people actually communicate — not just by looking for question marks. Because the best questions are often the ones that don't look like questions at all.
Want to never miss a question from your audience? Engage Suite automatically detects questions in your YouTube comments — even when they don't look like questions — so you can focus on answering them instead of finding them.