How to find content ideas with a social media competitor analysis (90 days of real Instagram data from 3 brands)
▲ 5 r/SocialMediaManagers+1 crossposts

How to find content ideas with a social media competitor analysis (90 days of real Instagram data from 3 brands)

I've stopped brainstorming content ideas and started pulling competitor data instead, then scoring every post against that account's own engagement rate median rather than raw likes. Tried it on 3 UK banks this week on the theory that if it works in banking it works anywhere.

Follower count and posting volume were both dead ends. Barclays UK has 86k followers and hit my 50 post ceiling in 75 days, Lloyds Business has 9.4k and posted 15 times, and their medians finished half a point apart.

86k followers or 9.4k, barely mattered. All 3 medians landed inside half a point.

Scoring each post against its own account baseline is where it got fun. Lloyds got 10.6x their median from one founder telling one story, and the strongest organic post Barclays managed in 90 days was a nail art reel captioned "Is this too niche? 💅". No product content anywhere in the top 5.

Same posts, ranked against their own account baseline instead of each other. Nothing in the top 5 is product content.

Lloyds is the one that stuck with me. Their Making Tax Digital posts are useful to exactly the right people and sat between 0.11% and 0.77%, while founder stories on the same account cleared 8%. Nobody wants the deadline explained to them, they want to watch someone else survive it.

Barclays also ran the identical Wimbledon reel 3 times in a week, so you can watch a repost die in real time.

One reel, 3 runs, 1 week. Run 2 kept about a fifth of run 1 and run 3 barely registered.

The 5 briefs I actually took out of it:

Content idea What the data said Format
Turn every product announcement into a customer telling the story Lloyds founder reel hit 10.6x their median, their own deadline posts sat at 0.11% to 0.77% Reel or carousel, one named person
Explain the boring history of your category Barclays' notes, contactless and "pound of silver" posts all beat their median with zero product mention Static or 15 second reel
Post something deliberately off-topic once a fortnight The nail art reel was their single strongest organic post in 90 days at 2.74% Reel, low production
Rebuild the winner instead of reposting it Same reel 3 times went 0.98%, then 0.20%, then 0.12% New cut, same idea
Split content by job, reach or response NatWest reels pull 1,800 to 2,600 views at 0.16% to 0.41%, their photos sit at 1.1% to 1.5% Reels for reach, carousel plus question for replies

Two things make the method work. Pull the whole 90 days rather than a top posts list, because top post rankings are survivorship bias in a nicer interface. Then score against each account's own median, since 100 likes at 9k followers is a different animal to 100 likes at 86k.

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u/berfin-cezim — 1 day ago
▲ 2 r/SocialMediaManagers+1 crossposts

AI was useless for post ideas until I plugged it into my actual data with an MCP

Every time I talk with my social media manager friends the conversation drifts to the same complaint, and none of us can crack it.

AI is great at describing what already happened and useless the second you ask what to do next.

I can open analytics any time and see what worked. That half's been solved for years. What I actually want is the thing that comes right after: "given all that, what's the smartest move next week?" And every AI tool fell apart at that moment, because for ages ChatGPT just fed me the same recycled loop:

  • post more carousels
  • use trending audio
  • hook them in the first line
  • be consistent

Advice-shaped noise, basically, because it couldn't see a single one of my numbers.

I connected my analytics straight to the AI, so it reads my real performance before it answers. I used Sociality MCP since that's what we're already on, but the idea matters more than the tool. One demanding prompt, told it to skip the generic stuff, and this came back:

Sociality MCP

Sociality MCP

The first line stopped me. It flagged that my text posts pull ~2x the engagement of my photo roundups, and yet 10 of my last 12 posts were those roundups. That number had been in my dashboard the whole time and I'd never joined the dots. The AI did it in one reply because it was finally looking at something real.

So now the suggestions are actually mine, hook already written out. That's the layer I could never reach no matter how I worded the prompt.

Curious if anyone else hit this same wall: is AI actually helping your content decisions yet, or still handing you the same generic advice?

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u/berfin-cezim — 17 days ago

Is it really AI reporting if you still have to clean the data?

We’ve all been using AI for summaries, captions, first drafts, and reporting help.

But the second you want actual social media reporting, the workflow usually still includes exporting dashboards, cleaning data, and explaining what the numbers mean to AI.

So the question is: can we really call that automation?

This is where social media MCP gets interesting. It connects your AI tool to the social media data behind the workflow, so you don’t have to manually feed it every metric first.

For this example, we used Sociality MCP.

After connecting it, you can ask something like:

“Create last month’s LinkedIn performance report.”

Then AI can use connected reporting data to generate a report with key metrics, top-performing posts, performance changes, analysis, and recommendations.

Sociality MCP

Sociality MCP

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u/berfin-cezim — 22 days ago
▲ 1 r/SocialMediaManagers+1 crossposts

The Claude + MCP combo cut my Instagram competitor analysis down to 1 minute

Competitor research is one of those tasks I always put off. Not because it’s hard, but because exporting data and comparing everything in spreadsheets is painfully boring.

I connected the Instagram competitors I already track in Sociality.io to Claude through Sociality MCP. Now I can ask one question and get the analysis back in about a minute.

For example, I asked Claude to compare six weeks of posts from four brands and rank them by median engagement per post:

Brand Posts Median engagement/post
Nike 19 ~194,000
Converse 21 ~7,500
Hepsiburada 94 ~2,600
Trendyol 105 ~1,900

Nike posted the least but performed far better per post. Claude also found that one creator collaboration generated 77% of Converse’s total engagement.

https://preview.redd.it/kdztwo2reeeh1.png?width=1544&format=png&auto=webp&s=66cca1f49fb34d59026c06b1029232206ea7ed84

Across all four brands, the top posts featured athletes, collaborations, or cultural moments. Regular product shots barely moved.

The biggest win for me is the workflow. I can now run the same competitor check every Monday in the time it takes to type one sentence.

Public data and boosted posts make the numbers directional rather than exact, but it’s still useful for spotting patterns quickly.

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u/berfin-cezim — 1 month ago
▲ 8 r/DigitalMarketingHack+1 crossposts

I used Ahrefs MCP + Sociality MCP on Claude to audit our blog and plan the social distribution.

I spent 15 minutes this Monday morning using Claude with two MCPs to audit our blog and plan the social distribution. Here's what I did and what came out.

I work at Sociality.io and I update articles regularly, but deciding which ones to prioritize is always the stressful part with GSC, Ahrefs, Cloudflare, back and forth, never feels conclusive. So, I connected all of it to Claude at once and let it run.

What I fed it 👉 Ahrefs MCP for live rankings and traffic data (no exports), three weeks of Cloudflare data showing which pages AI crawlers were actually hitting, our blog sitemap, and Sociality MCP to pull LinkedIn post performance for the distribution part.

Ahrefs MCP

Ahrefs MCP

The most AI-crawled pages were our plain analytics guides. LLMs are already citing us for analytics queries constantly, but none of those pages mention our MCP product. That's the whole insight.

Scoring

I shared a rubric, each article rated 1–5 on CF bot activity, SEO opportunity, AI/MCP relevance, business relevance, and effort. Total out of 20. Claude applied it across 23 articles.

The skip list was honestly the most useful part for me. Articles I'd been meaning to update for months got cut in seconds. The "social listening" post I was convinced had strong AI bot traffic? Actually 2 requests/week.

Then I asked it to look at our LinkedIn too.

Connected Sociality MCP to pull our last 3 months of LinkedIn posts and asked Claude what had actually worked.

Sociality MCP

Uncomfortable finding 👉 Text-only posts averaged 249 impressions and 13.9% engagement. Photo roundups averaged 80 impressions and 8.1% engagement.

From there, it mapped each blog update to a post format with suggested hook copy and a 4-week schedule.

Sociality MCP

Sociality MCP

Sociality MCP

Stack if anyone wants to replicate:

Claude (regular claude.ai, no code), Ahrefs MCP, Sociality MCP (free trial available), and the Cloudflare data.

That last one is massively underused. It shows you which pages LLMs are actively pulling as sources, as direct a GEO signal as you can get without being inside the model.

Happy to answer questions if you have any especially about Sociality MCP.

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u/berfin-cezim — 2 months ago

I tried using AI/social media MCP to figure out how we can beat competitors

I tested a competitor analysis workflow with Sociality MCP because checking competitors manually always turns into a bigger task than I expect.

As the marketing person at Sociality.io, I usually open each competitor page, look through recent posts, compare formats, check engagement, read comments, note down hooks and CTAs, and then try to turn all of that into something useful for next month. This time I asked AI to do the first research pass with our social data and competitor data already connected.

The prompt was basically this.

Compare us with our tracked competitors for the last 60 days. Show where they are doing better, where we are stronger, what we should test, what we should avoid copying, and give us post ideas for next month.

I did not need to export reports or paste screenshots, which was already a big improvement because that is usually where this kind of work gets slow.

Our stronger posts were mostly simple and specific. The MCP launch post had 8.5% ER, the MCP teaser had 11.3% ER, and one weekly roundup reached 13.9% ER. The weaker posts were mostly the repeated roundup format with low impressions, generic hooks, and not much reason for people to comment.

https://preview.redd.it/0cpj7j2xon6h1.png?width=1534&format=png&auto=webp&s=98317b7fafe3c8a4f20657b9f004e036745ca625

Competitors were doing better with posting frequency, format variety, question-based CTAs, comments, and opinion-led posts. But copying them directly would not make sense for us because our more differentiated angle is the MCP and AI workflow side.

https://preview.redd.it/38dv4w5zon6h1.png?width=1534&format=png&auto=webp&s=622991a5c0dea7c67ea6a5befbde733322c2fefa

The ideas that made sense were to post 3 to 4 times a week, make roundups more about what each update means, test carousels and short videos, ask more direct questions, and use more real AI workflow examples instead of generic social media tips.

https://preview.redd.it/3nyr89kyon6h1.png?width=1534&format=png&auto=webp&s=67cf2539a9df7ad407b9e8372b5b6fd53f1dce11

I would still check the actual posts and comments manually before using the ideas, because numbers do not always explain brand fit or audience quality. But for the first pass, this saved a lot of profile-by-profile checking and made the next steps easier to see.

How do you usually do competitor analysis for social? Do you have a real process, or is it mostly manual checking and gut feeling?

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u/berfin-cezim — 2 months ago

I used AI/MCP to analyze & shortlist YouTube creators for influencer outreach

I tested a workflow recently that felt useful enough to share.

I was trying to answer a pretty normal marketing question: Which YouTube creator would be the best fit to mention Sociality MCP? (I work at Sociality.io as a content marketer, and I used Sociality.io's social media MCP as I really needed to analyze those YouTube creators.)

I already had a shortlist of channels. Some covered AI, MCPs, automation, developer tools, social media APIs, and tool reviews. At first glance, several looked relevant, but choosing a creator for a product mention is not just about topic overlap.

I’d go through this manually. Open each channel, check subscriber count, review recent videos, compare views and engagement, understand the creator’s usual angle, and make a decision from scattered notes.

This time, I used Sociality MCP to analyze the shortlisted YouTube channels side by side as potential influencer partners.

Then I asked it to compare the channels, review key YouTube metrics, and help identify which creator looked like the strongest fit for a potential product mention.

The useful part was the follow-up questions:

Which channel has the strongest engagement rate?
Which creator talks about MCPs most directly?
Which audience would understand the product fastest? Which mention would feel natural instead of forced?

Option 1 came out as the strongest fit, even though it was one of the smaller channels in the shortlist, with around 670 subscribers. The reason was relevance. The channel had a strong overlap with social media APIs, tool comparisons, WhatsApp API, scheduling tools, and similar workflows. It also had the highest amount of tool review-style content in the group.

Option 2 was the strongest backup. It had a much larger audience, around 13.9k subscribers, and much higher average views per video, around 10k, compared with Option 1’s roughly 260. It also had strong MCP relevance, with 18 MCP-related videos and 10 AI tool-related videos in the dataset.

The difference was mostly about campaign fit.

Option 2 had stronger reach and clearer MCP credibility. Option 1 had a more natural connection to social media APIs and tool comparison content, which made the product mention feel less forced.

That distinction mattered because more reach does not always mean better fit.

I still would not fully automate creator selection. Before outreach, I’d still manually check recent video quality, comments, audience tone, brand fit, and whether the creator’s style actually matches the campaign.

But as a first research pass, this was much faster than checking every channel one tab at a time.

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u/berfin-cezim — 3 months ago