Windsor MCP for Organic Content Strategy: Better Topics, Content Planning, and Posting Times

Planning organic content means deciding which topics to cover, which formats to make, when to post and where to spend the team’s time. When you publish on several platforms, the answers sit in separate analytics apps: Instagram Insights, TikTok, YouTube Studio, LinkedIn and Search Console each report their own metrics for their own content.

Windsor MCP connects that content data to Claude, ChatGPT and other AI assistants. You can analyze one platform at a time or several together. Ask which Instagram posts earned the most saves, which YouTube videos brought the most subscribers, which Search Console queries are growing or which themes perform best across all channels.

This guide has ten use cases with ready-to-copy prompts for social media managers, content strategists, creators and marketing teams.

🚀 Start for free with Windsor MCP. The free forever plan connects one data source with no credit card. Cross-platform analysis uses more than one source: the first 30 days include up to 10 sources, and after that paid plans start at $19/month for 3 sources or $99/month for 7.

How Windsor connects your content data to AI

1. Connect your channels to Windsor

Connect Instagram, TikTok, YouTube, Facebook Pages, LinkedIn Pages, Google Search Console, WordPress and the other platforms you publish on. No code is needed. Windsor pulls current and historical data from each platform in a consistent format.

2. Add Windsor to your AI assistant

In Claude, open Customize, then Connectors, search for “Windsor” and click Add. In ChatGPT, open Plugins in the sidebar, search for “Windsor” and click Install plugin. Then sign in to Windsor.ai. Setup guides: Claude, ChatGPT and other AI clients.

3. Ask your content strategy questions

Ask the assistant to find your top topics, compare formats, suggest posting times, describe your audience, find content gaps and draft the next content plan from your own performance data. The prompts below cover each of these.

10 ways to use AI for content strategy, with prompts

Replace the values in square brackets with your own platforms and topics. The prompts work in Claude, ChatGPT and any other AI client connected to Windsor MCP.

1. Top content review: find out why your best posts worked

The challenge:

Most teams know which posts did well, but not why. Format, topic, hook, length, timing and audience response all play a part, and judging by likes alone misses most of them.

This use case finds what your top posts have in common, so the next content plan is based on engagement data.

Best for:

• Content strategists
• Social media managers
• Creative teams

Prompt: Find what your top posts have in common

Analyze my Instagram data for the last 90 days.

Identify my top 10 posts by engagement rate, calculated as likes + comments + saves divided by reach.

For each top post, include:
- Post type
- Estimated topic or theme (from the caption)
- Posting day and time
- Engagement rate

Then analyze the patterns across those posts.

Answer:
- What formats perform best?
- Which topics appear most often?
- Are there common posting days or times?
- What makes these posts different from the bottom 10 posts by engagement rate?

Finish with a 10-point summary of the factors driving high engagement on this account.

Prompt: Compare saves and shares with likes

Analyze my Instagram data for the last 90 days.

Compare posts based on:
- Saves per 1,000 reach
- Shares per 1,000 reach
- Comments per 1,000 reach
- Likes per 1,000 reach

Identify posts that rank highly on saves or shares but not on likes.

Then explain:
- Which content topics generate the strongest interest
- Which posts people keep to come back to later
- Which content starts conversations
- Which posts may be more valuable than their like count suggests

Prompt: TikTok video retention analysis

Analyze my TikTok Organic data for the last 60 days and include all videos with more than 200 views.

For each video, include:
- Views
- Likes
- Video duration
- Average watch time
- Full video watched rate
- Shares
- New followers

Then identify:
- Which videos have the highest full watched rates
- What those videos have in common in length, opening hook (from the caption), or topic
- Which videos got high views but a low full watched rate
- Which videos may have had a strong hook but weak content after it (high views, low average watch time)

Then use these patterns to create a plan for the next 10 videos, including suggested topics, hook ideas, and video length.

What you get:

A list of the topics, formats, posting patterns and video lengths behind your best content, so you can make more of what works.

Example from our own account: we ran the TikTok retention prompt on the windsor.ai TikTok account: 15 videos published between 22 July and 7 August 2026, with 2,769 views in total.

• Every video was 57 to 72 seconds long. Viewers watched 2.9 seconds on average, which is 4.5% of the average video length.
• No video was watched to the end by more than 1.4% of its viewers.
• The 15 videos brought 3 new followers, about 1 per 1,000 views.

With almost every viewer leaving in the first three seconds, topic and length made little difference between the videos. The recommendation was to open each video with the result instead of the setup and to test versions under 30 seconds.

2. Audience insights: understand who engages with your content

The challenge:

Most brands have a target audience in mind, but the people who follow and watch can be different. Your TikTok followers may be younger than expected, your LinkedIn followers may be more junior than your buyers, and your Instagram followers may live in different countries from the people you sell to.

This use case shows who your followers are on each platform, so you can choose topics, hooks and posting times for that audience.

Best for:

• Brand managers
• Content strategists
• Marketing directors

Prompt: Audience profile across platforms

Build an audience profile using my connected social media data.

Use these data sources:
- TikTok Organic
- Instagram
- YouTube

Show for each platform:
- Audience age breakdown
- Gender split
- Top countries and cities of followers (TikTok and Instagram)

Then analyze:
- Where these audiences overlap
- Where they differ significantly
- Whether my content reaches a consistent audience across platforms
- Which platforms attract different audience segments

Prompt: Are you reaching the right people on LinkedIn?

Analyze my LinkedIn Pages follower data.

Break down my followers by:
- Seniority
- Job function
- Industry

Our intended audience is [describe it, e.g. marketing directors at e-commerce companies].

Then answer:
- What share of my followers matches the intended audience?
- Which seniority levels, functions, and industries are over- or under-represented?
- Which topics from my posts in the last 90 days earned the most comments and likes per impression?
- What content changes could attract more of the intended audience?

Prompt: Find the best posting times

Find the best times to post on TikTok and Instagram.

From TikTok Organic, show:
- The hours of the day when the most followers are online

From Instagram, use my posts from the last 90 days:
- Group posts by day of week and hour published
- Calculate the average engagement rate (likes + comments + saves divided by reach) for each group
- Mark groups with fewer than 3 posts as low confidence

Then answer:
- What are the best times to post on each platform?
- Do the best time windows overlap across the two platforms?
- Am I currently posting at those times?
- Which posting slots should I test next?

What you get:

A clear picture of who follows you on each platform, which groups each platform reaches and when your posts get the most engagement.

3. Build next month’s content calendar from performance data

The challenge:

Content calendars are often built from deadlines and whatever ideas the team has that week. Your past performance already shows which topics, formats, posting times and posting frequency get engagement.

This use case turns that history into next month’s plan.

Best for:

• Social media managers
• Content teams
• Editors planning monthly content

Prompt: Generate a 30-day content plan

Based on my Instagram and TikTok Organic performance data from the last 90 days:

1. Identify the 5 content themes that generate the highest average engagement rate across both platforms.
2. Identify the 2 content formats that consistently perform best on each platform.
3. Identify the best days and times to post, based on when my past posts earned the highest engagement and when my TikTok followers are online.

Then use these insights to create a 30-day content calendar for next month.

For each week, suggest:
- 3 Instagram post ideas with format and theme
- 5 Instagram Reels ideas
- 3 TikTok video ideas with topic and hook direction
- Cross-platform repurposing opportunities
- Recommended posting days and times (as an editorial calendar)

Prompt: Find content gaps and underused topics

Analyze my Instagram and LinkedIn Pages posts from the last 3 months.

Identify:
- Which content topics I post about most often
- Which topics related to my brand I have rarely covered
- Which rarely covered topics performed well above average

Then find 5 underused topics where I have posted fewer than 3 times, but the content performed better than my average engagement rate.

Explain why these topics may deserve more attention in future content plans and suggest 5 post ideas based on them.

Prompt: Find the best posting frequency

Analyze my Facebook Page and Instagram performance data for the last 90 days.

Look at the relationship between posting frequency and engagement rate per post.

Then answer:
- Does posting more often increase or reduce engagement per post?
- Is there a point where engagement per post starts to decline?
- What is the best number of posts per week for each platform?

Finish with a recommended posting schedule for these platforms based on the data.

What you get:

A content calendar for next month based on your own data: topics, formats, posting times and how often to post.

4. Format strategy: which content types perform best

The challenge:

Each platform offers different formats: carousels, Reels, Stories, image posts, Shorts, long videos and text posts. General benchmarks do not tell you what your own audience responds to.

This use case compares the reach, engagement, saves, shares, watch time and followers each format brings on your accounts.

Best for:

• Content teams
• Brand managers
• Teams deciding where to put creative effort

Prompt: Compare Instagram content formats

Analyze my Instagram data for the last 3 months.

Compare performance across these content formats:
- Image posts
- Carousel posts
- Reels

For each format, calculate:
- Average reach per post
- Average engagement rate
- Average saves per post
- Average shares per post

Then answer:
- Which format delivers the most reach?
- Which format drives the most saves and shares?
- Which format has the highest engagement rate?
- Which format should I produce more often based on its performance?

Prompt: Compare YouTube Shorts with long-form videos

Analyze my YouTube data for the last 3 months.

Separate my videos into Shorts and long-form videos using the content type.

For each group, compare:
- Average engaged views per video
- Average view percentage
- Average watch time per video
- Subscribers gained per 1,000 views

Then answer:
- Which format is growing my channel faster?
- Which format holds viewers better?
- Which format brings more subscribers?
- Should I put more effort into Shorts or long-form videos?

Since March 2025, YouTube counts a Shorts view on every play or replay. Engaged views use the older counting method, so they compare Shorts and long-form videos on the same basis.

Prompt: Compare Facebook Reels, videos and images

Analyze my Facebook Page data for the last 90 days.

Group my posts by post type (for example photo, video, and Reels).

For each type, include:
- Total reach
- Engagement rate (engagements divided by reach)
- Shares
- Average watch time for Reels

Then answer:
- Do Reels reach more people than other post types?
- What percentage of my total reach comes from Reels?
- Which post type performs best overall?
- Which post types should I publish more often?

What you get:

A comparison of the formats that bring the best results on your accounts, so you can put more time and budget into them.

Example from our own accounts: we ran the Instagram and YouTube format prompts on windsor.ai’s accounts.

Instagram, posts published in the 90 days to 6 October 2026:

Format	Posts	Average reach per post	Engagements per 1,000 reach
Reels	18	94	12
Image posts	5	41	59
Carousel	1	80	50 (one post, low confidence)

Reels reached more than twice as many accounts per post, while image posts got five times more engagement per account reached. Instagram returned no follows data for the Reels, so follower growth could not be compared across formats.

YouTube, 1 July to 30 September 2026 (81,115 views in total):

	Shorts	Long-form videos
Share of channel views	30%	70%
Average view percentage	62%	40%
Seconds watched per view	26	40
Subscribers gained per 1,000 engaged views	2.4	3.1

Shorts were watched further through, but long-form videos held viewers for longer in seconds and brought about 30% more subscribers per 1,000 engaged views.

5. YouTube channel growth audit

The challenge:

Publishing more videos does not always grow a channel. Viewers may leave early, a few strong topics may never become a series, or most views may come from one traffic source.

This use case finds what is helping and what is holding back the channel, so you know what to work on first.

Best for:

• YouTube creators
• Video content leads
• Brand teams with YouTube channels

Prompt: YouTube channel health audit

Analyze my YouTube data for the last 90 days.

Show me:
1. Average view percentage across my videos
2. Subscribers gained vs. subscribers lost
3. Views and watch time by traffic source
4. The 10 videos with the most watch time

Then answer:
- Which of these looks weakest?
- What is most likely limiting channel growth?
- What should I improve first?

Prompt: Find videos where views and retention do not match

Analyze my YouTube data for the last 6 months for all videos with more than 500 views.

Identify:
- Videos with above-average views but below-average average view percentage
- Videos with below-average views but above-average average view percentage

Then explain:
- Which videos may have strong titles or thumbnails but content that does not hold viewers
- Which videos hold viewers well but may need better titles or thumbnails to get more views
- Which videos may need stronger openings or faster pacing

Prompt: Find the best YouTube traffic sources

Analyze my YouTube data for the last 90 days.

Break down views and watch time by traffic source, including YouTube search, suggested videos, browse features, and external sources.

Then answer:
- Which traffic source brings the most watch time per view?
- Is my channel growing more from search, recommendations, or external traffic?
- Should I focus more on search-based topics or on content that gets recommended and shared?

Prompt: Identify topics worth turning into a series

Analyze my YouTube video performance over the last 6 months based on video titles and topics.

Identify:
- Which topic groups generate the most watch time
- Which topics have the highest average view percentage
- Which topics consistently bring subscribers
- Which successful topics have only one or two videos and could become a longer series

Then recommend the top 3 topic groups I should turn into a regular YouTube series.

What you get:

A list of what helps and what holds back channel growth, with specific next steps for retention, traffic sources and future video topics.

Example from our own account: the traffic source prompt on the windsor.ai YouTube channel, 1 July to 30 September 2026:

Traffic source	Share of views	Seconds watched per view
YouTube search	68%	29
External websites and links	17%	53
All other sources (channel page, subscriptions, Shorts feed, playlists, ads)	14%	43
Suggested videos	0.6%	109

The channel grows mostly from search, which suits how-to videos. Viewers who arrive from external websites and links watch almost twice as long per view as viewers from search. Suggested videos send very few views but the longest watch time, so end screens and playlists that lead viewers to the next video are the clearest opening.

6. SEO and blog content strategy from search data

The challenge:

Content teams have three kinds of SEO work competing for time: new articles, refreshes of older posts and small fixes on pages that rank just below the top results. It is hard to decide which to do first.

When you combine Google Search Console with your blog data, for example from WordPress, the assistant can rank these opportunities for you.

Best for:

• SEO strategists
• Content writers
• Blog editors
• In-house content teams

Prompt: Find high-opportunity keywords

Analyze my Google Search Console data for the last 90 days.

Show all search queries where:
- Average position is between 4 and 15
- Impressions are above 20

Sort the results by impressions in descending order.

Then identify:
- Which queries have the most impressions
- Which queries have a lower click-through rate than expected for their position
- Which pages may need a stronger title tag or meta description
- Which queries are closest to reaching the top 3 positions

Prompt: Find old content worth refreshing

Compare my Google Search Console performance for the last 90 days with the same period 12 months ago.

Identify pages that have lost more than 30% of their clicks year over year.

For each page, include:
- Current average position
- Current click-through rate
- Main search query driving traffic
- Change in clicks compared to last year

Then explain:
- Which pages are likely declining because the content is out of date
- Which pages should be refreshed first
- Which pages may need stronger titles, internal links, or new sections

Prompt: Compare blog posts with search performance

Combine my WordPress data with my Google Search Console data.

For each blog post published in the last 12 months, identify:
- Whether it appears in Google Search Console
- Whether it is receiving impressions or clicks
- Whether it has gained impressions after 60 days

Then answer:
- Which posts have no search visibility and may target topics with low demand
- Which posts may have indexing or internal linking issues
- Which older posts still receive strong impressions and should be refreshed
- Which topics deserve more supporting content

Prompt: Generate a content brief from search demand

Analyze my Google Search Console data for all search queries related to "[keyword topic]".

For each query, include:
- Impressions
- Clicks
- Click-through rate
- Average position

Then group related queries into topic clusters.

Based on the strongest cluster where I do not currently rank above position 15, generate a blog content brief that includes:
- Suggested article title
- Primary keyword
- Secondary keywords
- Suggested H2 structure
- The questions the article should answer

What you get:

A list of which queries to target, which posts to refresh and which new articles have the most search demand behind them.

💡 Search Console shows the searches where you already get impressions. WordPress shows what you have published. Combining the two shows the searches with no matching content and the existing posts worth updating.

7. Follower growth: which content brings new followers

The challenge:

Some posts get many views and likes but few new followers. Others bring followers steadily because they show expertise, personality or a reason to come back.

This use case finds the content that turns viewers into followers.

Best for:

• Creators and bloggers
• Brand accounts focused on audience growth
• Community managers

Prompt: Find the TikTok videos that bring the most followers

Analyze my TikTok Organic data for the last 90 days.

For each video, include:
- Views
- New followers
- New followers per 1,000 views

Rank the videos by new followers per 1,000 views.

Then identify:
- Which topics bring the most new followers
- Which video lengths work best for follower growth
- Which hook styles (from the captions) appear most often in these videos
- Whether the most-viewed videos are also the best for follower growth
- Which content patterns are most likely to turn viewers into followers

Prompt: Find the Instagram posts that bring followers

Analyze my Instagram feed posts and carousels from the last 90 days.

For each post, include:
- Reach
- Follows from the post
- Follows per 1,000 reach
- Profile visits from the post

Rank the posts by follows per 1,000 reach.

Then identify:
- Which topics and formats bring the most follows
- Whether the posts with the most reach also bring the most follows
- Which posts get profile visits but few follows (the profile may need work)

Instagram reports follows and profile visits per post for feed posts and carousels, not for Reels. To check Reels, compare their reach and shares with your daily follower growth.

Prompt: Find the YouTube videos that bring subscribers

Analyze my YouTube data for the last 6 months.

Rank my videos by subscribers gained per 1,000 views.

Then identify:
- Which videos are best at turning viewers into subscribers
- Which topics bring the most subscribers per view
- Whether subscriber growth is linked to a high average view percentage
- Whether some videos bring subscribers despite average retention
- What these patterns suggest about why new viewers subscribe

What you get:

A list of the topics, formats and hooks that turn viewers into followers, so you can grow your audience with more of them.

8. Cross-platform content repurposing

The challenge:

A post that works on one platform can often work on another. An Instagram carousel can become a YouTube video, a TikTok can become a LinkedIn post, and a blog article can become a series of short videos. The hard part is choosing which content to repurpose and how to adapt it.

This use case finds your strongest content and suggests where else to use it.

Best for:

• Content teams managing several platforms
• Social media managers
• Solo creators

Prompt: Find cross-platform repurposing opportunities

Analyze my content performance across all connected channels for the last 30 days.

For each platform, identify the top 3 posts by engagement rate.

For each top post, include:
- Content format
- Main topic
- Main reason it performed well
- Whether it did well on reach, saves, shares, watch time, or comments

Then identify:
- Which top posts could be adapted to another platform
- Which content formats have equivalents on other channels
- Which posts could become a video, carousel, blog article, LinkedIn post, or email

Finish with 5 specific repurposing recommendations, including:
- Original platform
- Original content type
- New platform
- Suggested new format
- Why the content should work there

Prompt: Find evergreen content worth repeating

Analyze my Instagram and LinkedIn Pages data.

Identify posts that were published more than 3 months ago and still have strong engagement relative to their reach or impressions.

For each evergreen post, include:
- Topic
- Format
- Engagement rate
- Date published

Then answer:
- Which topics continue to perform well over time
- Which evergreen posts could be reposted or refreshed
- Which posts could be turned into other formats or adapted for other platforms
- Which evergreen themes could become a regular content series

What you get:

A repeatable way to turn your best content into more posts, videos and articles across platforms.

9. LinkedIn thought leadership

The challenge:

LinkedIn rewards different content from most social platforms. Posts that do well are usually specific, take a position and are useful to the reader, and they get comments and discussion as well as likes.

This use case shows which topics and angles get the most engagement on your company page.

Best for:

• B2B marketing teams
• Brand managers
• Company page managers

Prompt: Analyze your best LinkedIn posts

Analyze my LinkedIn Pages data for the last 6 months.

Rank all posts by engagement rate, calculated as likes + comments + shares divided by impressions.

For the top 10 posts, identify:
- Main topic or angle (from the post text)
- Number of comments
- Number of shares
- Engagement rate

Then answer:
- Which topics perform best?
- Which posts generate the most comments and discussion?
- What separates posts with many comments from posts that only get likes?
- Which angles appear most often in the best posts?

Prompt: Build a LinkedIn content plan for next month

Based on my LinkedIn Pages performance data from the last 90 days:
1. Identify the 3 topic groups with the highest average engagement rate.
2. Identify the days of the week when my posts earn the most impressions and engagement.

Then create a LinkedIn content plan for next month with:
- 3 posts per week
- Topic for each post
- Recommended format
- Suggested hook or angle

What you get:

A list of the topics and angles that work on your LinkedIn page and a plan for the next month.

10. Organic and paid: is paid adding reach or replacing it?

The challenge:

Brands that run organic content and paid campaigns need to know whether paid helps strong content reach more people or makes up for weak organic performance. If organic engagement is flat or falling, paid spend can hide the problem.

This use case compares the two, so you can decide where to invest.

Best for:

• Marketing managers running organic and paid campaigns
• Social media managers

Prompt: Compare promoted posts with organic-only posts

Combine my Instagram data with my Meta Ads data for the last 90 days.

Identify the Instagram posts that were boosted or used as ad creatives.

Compare promoted posts with organic-only posts on:
- Organic likes and comments
- Saves and shares
- Reach

Then answer:
- Did the promoted posts already perform above average before paid support?
- Which organic-only posts performed well enough to be worth promoting?
- Which promoted posts had weak organic results and may not deserve more budget?

Instagram reports organic likes and comments per post separately from the totals that include boosted engagement, so the assistant can compare the organic part on its own.

Prompt: Compare your LinkedIn followers with your ad audience

Combine my LinkedIn Pages data with my LinkedIn Ads data for the last 90 days.

Compare:
- My page followers by seniority and job function
- Impressions and clicks from my LinkedIn Ads by seniority and job function

Then answer:
- How much do my followers and my ad audience overlap?
- Am I paying to reach the kind of people who already follow my page?
- Does paid reach seniority levels or job functions that my followers do not include?
- Which groups respond best to ads, and how could organic content reach them too?

What you get:

A view of whether your paid campaigns add new reach and audiences or mostly cover gaps in organic performance.

Tips for content analysis with AI

Ask for the output format your workflow needs

Add an instruction like one of these to the end of any prompt:

...Present this as a content calendar table with columns:
Week | Platform | Format | Topic | Hook direction | Goal (engagement / reach / followers)

...Format this as a creative brief I can share with a designer or video editor.

...Give me the top 5 insights as a bullet list I can paste into a Slack message to my team.

...Write the analysis as a 3-paragraph narrative for a strategy presentation.

Ask follow-up questions

When you get a performance table, ask the assistant to explain it:

• “Why do you think carousels outperform video on this account?”
• “What does the gap between reach and engagement suggest about who sees these posts?”
• “If I could change only one thing in my content strategy based on this data, what should it be?”

Ask questions across channels

Most use cases above look at one platform at a time. With two or more channels connected to Windsor.ai, you can ask questions that no single platform’s analytics can answer:

• “Does a rise in TikTok reach go with an increase in Search Console impressions for my brand name the following week?”
• “In weeks when my LinkedIn posts get high engagement, does traffic from social sources in GA4 also increase?”
• “Which blog posts get the most social traffic in GA4, and do the same posts rank well in Search Console?”

Conclusion

Windsor MCP with Claude, ChatGPT or another AI assistant turns your content performance data into topics, posting schedules, audience profiles and content plans. You ask in plain English, and the answer is based on your own accounts.

Start with one channel and one prompt from this guide. When the first answers are useful, add more channels and more of the prompts above.

🚀 Start for free at Windsor.ai and connect Instagram, TikTok, YouTube, LinkedIn or another platform to your AI assistant in about a minute. No credit card needed.

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