Scrape Comments From Posts

Scrape Comments From Posts extracts comment threads from Instagram posts, returning commenter usernames, comment text, like counts, reply counts, and timestamps. Comments on Instagram posts represent direct audience engagement and provide rich qualitative data about how people perceive a brand, product, or piece of content. For GTM teams, comment data is a social signal goldmine that reveals customer sentiment, common questions, purchase intent, and competitive mentions.

Brands use comment scraping to monitor their own posts for customer feedback, product questions, and support issues that need attention. Competitive intelligence teams extract comments from competitor posts to identify customer complaints, feature requests, and switching triggers. Influencer marketing teams analyze comment quality on potential partners' posts to ensure genuine engagement rather than bot activity. E-commerce teams look for purchase-intent comments like 'where can I buy this?' or 'is this available in my country?' to identify demand signals.

Each run costs 1 credit and returns all comments from a specified Instagram post URL. The output includes the commenter's username, full comment text, comment like count, number of replies, and timestamp. This data feeds into SyncGTM enrichment pipelines where you can attempt to match Instagram usernames to professional profiles, email addresses, or other contact data for outreach.

Once your data is in SyncGTM, you can run it through waterfall enrichment to fill in missing emails, phone numbers, and firmographics from 75+ data providers. Pair this lead source with SyncGTM's enrichment actions and push clean, enriched records directly to your connected CRM or outreach tool. Learn more about how waterfall enrichment works.