---
title: "YouTube comment analysis for ad research"
description: "Review videos in your niche hold thousands of pre-purchase comments. How to analyze YouTube comments for the objections and desires that shape converting ads."
canonical: https://tryadlicio.com/scrapers/guides/youtube-comment-analysis-for-ads
---

# YouTube comment analysis for ad research

By Daniel, founder of Adlicio

Review videos in your niche hold thousands of pre-purchase comments. How to analyze YouTube comments for the objections and desires that shape converting ads.

The comments under a 'is X worth it' video are pre-purchase conversations happening in public: people on the edge of buying, saying exactly what is stopping them. That makes YouTube comment analysis less like social listening and more like sitting in on **a thousand sales calls**.

The method below turns those threads into the **two things ad research actually needs**: ranked objections to answer and verbatim desire language to lead with.

## Choose videos by intent, not size

A 2M-view entertainment video gives you jokes. A **80k-view review of your competitor** gives you buyers. Prioritize review videos, comparisons ('X vs Y'), roundups ('best X in 2026'), and tutorial content where your product category is the tool. The commenters there have their wallets half-open, and their questions are your objection list.

## What to count

Analysis means counting patterns, not collecting impressions. Across a few videos, tally **four things**:

- **Repeated questions**: the same 'but does it work with/for X' asked across videos is a top-of-funnel objection your ads should pre-answer.
- **Deal-breakers**: 'I was going to buy until' comments name the exact friction in your funnel.
- **Owner testimony**: comments from people who already bought carry the credible phrasing your ad copy should borrow.
- **Timestamp reactions**: when comments cluster around one moment of a review, that feature or flaw is what the market actually cares about.

## Compress the counting to 60 seconds

Adlicio does the tally for you: paste a video URL, the comment thread is scraped in **about 60 seconds**, and the analysis comes back as ranked angles, recurring objections, desires, and sub-audiences, each backed by the verbatim comments. Scrape three or four videos in your category and the recurring clusters across all of them are your validated angle list.

From there the workflow is direct: the **top objection becomes a retargeting ad** that answers it, the top desire becomes the cold-traffic hook, and the owner-testimony quotes become your proof lines.

## How to do it with Adlicio

1. **Scrape 3-4 high-intent videos** - Reviews and comparisons featuring your product or competitors. Paste each URL into Adlicio; each takes about a minute.
2. **Merge the patterns across videos** - An objection that appears under every video is real. One that appears under one video might just be that reviewer's framing.
3. **Map angles to funnel stages** - Desire clusters feed cold-traffic hooks, objection clusters feed retargeting, and buyer testimony feeds landing-page proof.

## FAQ

### Why YouTube over other platforms for ad research?

Intent. Review and comparison videos attract people actively deciding, so the comments read like pre-purchase questions rather than casual reactions. Pair it with Reddit for depth and TikTok for hook phrasing.

### How many videos should I analyze?

Three or four per product question. Enough that patterns repeat across different creators' audiences, which filters out any single reviewer's bias.

### Can Adlicio analyze a competitor's video comments?

Yes, any public video. Competitor reviews are usually the highest-yield source because the objections in them are the reasons people did not buy from them, which is your opening.

## Links

- This guide: https://tryadlicio.com/scrapers/guides/youtube-comment-analysis-for-ads
- Scraper: https://tryadlicio.com/scrapers/youtube-comment-scraper
- Pricing: https://tryadlicio.com/pricing
- Start free: https://tryadlicio.com/signup