How to Benchmark Your Instagram Against Competitors Using ChatGPT

Your own Instagram Insights data tells you how you’re performing. To know whether that performance is actually good, you need a benchmark, and the most relevant one is what’s working for accounts in your space. Once you’ve connected your own Instagram Insights to ChatGPT (see: How to Connect Instagram to ChatGPT), you can add a second data source and compare both in the same conversation.

Setting up Instagram Public Data

Windsor’s Instagram Public Data connector pulls publicly visible metrics from any public Instagram profile, competitor brands, industry leaders, and influencers you’re vetting, without needing admin access. Just the handle.

Go to onboard.windsor.ai/app/instagram_public and connect it as a second data source, entering the handles you want to track. Windsor pulls their public post data, follower counts, and posting frequency in real time, and both sources become queryable together in the same ChatGPT conversation.

Engagement rate benchmark: how do you stack up?

Using my Instagram Insights data and public data for [@competitor_1] and [@competitor_2]:

For each account, calculate average engagement rate over the last 30 days.
For my account, include saves and shares (media_engagement / media_reach × 100).

1. How does my engagement rate compare to each competitor?
2. Is the gap in follower count explained by higher engagement, or are they growing on both dimensions?
3. For the competitor with the highest engagement rate, what media_type do they post most?

Content format strategy: what are competitors betting on?

Using public Instagram data for [@competitor_1], [@competitor_2], and [@competitor_3]:

For each account, analyse the last 30 posts: format breakdown, average
likes/comments per format, posting frequency.

1. Which format and topic does each competitor post most often?
2. Which gets the most engagement for each?
3. Is there a format a competitor uses heavily with strong results that I'm underinvesting in?
4. How does their posting frequency compare to mine, and does engagement suggest it's helping or hurting them?

Follower growth trajectory: who is growing and why?

Using Instagram Public Data for [@competitor_1] and [@competitor_2], track
followers_count over the last 60 days: net gain/loss, any spike weeks and
what was posted, growth rate %.

Compare against my own followers_count growth over the same period.

1. Who grew fastest?
2. What content coincided with the growth spikes?
3. Is there a campaign moment worth learning from?

Content pillar and competitive SWOT

Using public Instagram data for [@competitor_1], [@competitor_2], and [@competitor_3],
identify each account's strongest content pillar (the topic or format that
consistently outperforms their other posts) and note whether any of them
recently gained a notable engagement or follower spike that looks like a
campaign or collaboration. What does this suggest I should test?

Influencer vetting: before you commit to a partnership

Using Instagram Public Data for [@influencer_handle], show:
followers_count, media_count, average likes/comments over their last 20
posts, engagement rate, posting frequency, Reels-to-static ratio.

1. Is their engagement rate consistent with their follower size?
(A 500k account with 0.3% engagement is a red flag; 1.5%+ is strong at that scale.)
2. Has their follower count grown or declined in the last 30 days?
3. Do their comments look genuine, or generic ("great post!", emoji-only)?

💡 The short rule: Organic for your own free content, Public for everyone else’s, Meta Ads for anything you paid for. Connect all three and ChatGPT can answer across them in one conversation.

Related reading

Want to turn a competitive insight into action? If benchmarking reveals a format or angle you’re underusing, ‘How to manage Instagram ad campaigns from ChatGPT‘ covers how to test it as a paid campaign. Or go back to ‘ChatGPT prompts for Instagram content strategy‘ to mine your own top posts before comparing them.