Instagram Analytics Data in Ayrshare: A Product Manager’s Guide

If you’re a product manager building on top of Ayrshare, you’ve probably bumped into this question: “What data do we get back from Instagram, and where does it live?”

With post-level metrics, account analytics, history logs, and brand profile data, it’s easy for the overall picture to become blurry. Engineers see JSON, customers see charts, and you’re somewhere in the middle trying to design features, prioritize tasks, and explain what’s possible.

This guide breaks down the main types of Instagram data available in Ayrshare, where each one comes from, and how to think about it in product terms. The goal is not just to list fields, but to give you a clearer map of what each endpoint is actually useful for. While the focus is on Instagram, the same general principles apply to other social networks within Ayrshare as well.

What Instagram Data Ayrshare Actually Provides

Before getting into endpoints and field names, it helps to zoom out. Instagram data in Ayrshare falls into a few distinct buckets, each answering a different product question. At a high level, product managers can think about Instagram data in Ayrshare like this:

• Post analytics tells you how an individual post performed.
  
• Account analytics shows how the overall Instagram profile is doing.
  
• History data records what was published and what happened to it.
  
• Brand profile data provides public account and identity information.
  
• Followers online data shows when the audience is active.
  

Once those categories are clear, the rest of the data becomes much easier to work with.

Field names and availability can change over time as Meta updates their APIs. Always treat this as a convenient map and cross-check the raw JSON if something looks different.

Field names and availability can change over time as Meta updates their APIs. Always treat this as a convenient map and cross-check the raw JSON if something looks different.

Instagram Post Analytics (Analytics on a Post)

Post analytics is the layer product teams use to understand how individual pieces of content perform. In Ayrshare, this data comes from POST /analytics/post endpoint, where Instagram metrics are returned under the relevant instagram key for each post.

For each Instagram post, you’ll see:

• id: Instagram social post ID.
  
• postUrl: public URL to the Instagram post.
  
• analytics: object containing metrics (varies by media type).
  
• lastUpdated, nextUpdate: timestamps indicating when Ayrshare last refreshed and when it will next refresh the analytics.
  

1. Feed Posts (mediaProductType: “FEED”)

Feed post analytics is best for standard post-performance reporting. This is where you’ll find metrics such as likes, comments, saves, shares, reach, profile visits, and engagement totals, along with media metadata such as captions, media types, and media URLs.

For PMs, this is typically the most familiar reporting layer because it closely aligns with the performance summaries users expect in dashboards.

Inside analytics for a feed post:

• caption: caption text.
  
• commentsCount: number of comments on the post.
  
• created: UTC timestamp when the post was created.
  
• engagementCount: total engagement (likes + comments + saves + shares, where available).
  
• followsCount: number of follows attributed to this content (when provided by Instagram).
  
• likeCount: number of likes.
  
• mediaProductType: “FEED”.
  
• mediaType: “IMAGE”, “VIDEO”, or “CAROUSEL_ALBUM”.
  
• mediaUrls: array of attached media:
  
• mediaUrl: URL to the image or video.
  
• profileActivityCount: total profile actions (e.g., visits, taps) attributed to the post.
  
• profileVisitsCount: profile visits driven by the post.
  
• reachCount: unique accounts reached by the post.
  
• savedCount: saves/bookmarks.
  
• sharesCount: shares of the post.
  
• username: Instagram username.
  
• viewsCount: views (primarily relevant for video content; replaces older videoViews behavior).
  

Meta does deprecate metrics over time, so not all fields may always be present for every account or post.

Meta does deprecate metrics over time, so not all fields may always be present for every account or post.

2. Reels (mediaProductType: “REELS”)

Reels include additional video-oriented metrics such as plays, replays, watch time, and total viewing time. That makes them especially useful when you’re designing features around video engagement rather than just static post interaction.

This includes:

• clipsReplaysCount: number of replays of the Reel.
  
• igReelsAggregatedAllPlaysCount: aggregate plays for the Reel.
  
• igReelsAvgWatchTimeCount: average watch time.
  
• igReelsVideoViewTotalTimeCount: total watch time across all views.
  
• mediaProductType: “REELS”
  
• mediaType: typically “VIDEO”.
  
• playsCount: plays for the Reel.
  

Some Reel fields may change over time as Meta adjusts its API, so it makes sense to treat certain video-specific metrics as helpful enhancements rather than permanent product guarantees.

3. Stories (mediaProductType: “STORY”)

Stories work differently from feed posts and Reels. Instead of focusing only on likes or reach, Story analytics is more useful for understanding navigation and drop-off behavior:

• mediaProductType: “STORY”.
  
• mediaType: e.g., “IMAGE” or “VIDEO”.
  
• notEnoughViews: flag indicating Instagram didn’t provide full stats due to low view counts.
  
• navigationCount: total navigation interactions with the Story.
  
• repliesCount: direct replies to the Story.
  
• swipeForwardCount: swipes forward from this Story.
  
• tapBackCount: taps back to the previous Story.
  
• tapForwardCount: taps forward to the next Story.
  
• tapExitCount: exits from the Story.
  

Metrics such as tap forward, tap back, exits, replies, and navigation counts can help product teams understand how far people moved through a Story and where engagement started to fade. In product terms, this makes Story data especially useful for retention-style content insights rather than simple performance summaries.

Instagram Account Analytics in Ayrshare

Account analytics looks beyond a single post and shows how the Instagram profile is performing overall. This is the layer product teams use for account health dashboards, audience insights, trend reporting, and profile-level performance views.

In Ayrshare, this data comes from Endpoint POST /analytics/social, where Instagram account data lives under “instagram.analytics” for the connected profile.

At a high level, Instagram account analytics includes:

• Account summary.
  
• Basic profile info (name, username, biography).
  
• Follower and following counts.
  
• Media counts (number of posts).
  
• Performance totals.
  
• Reach and impressions totals (various time windows, depending on Instagram’s API).
  
• Profile visits and actions attributed to the profile.
  
• Audience demographics.
  
• Age distribution buckets (e.g., 13–17, 18–24, etc.).
  
• Other demographic breakdowns (such as location and gender), for which Instagram provides a sufficient sample size; if a bucket has too few people, Instagram omits that demographic data.
  

Because the account analytics payload is sizable and subject to change, the easiest way to work with it as a PM is to think in layers:

1. Profile Layer

This is the “who is this account?” layer. It includes profile-level details such as username, name, biography, follower counts, following counts, and media totals.

2. Performance Layer

This is the “how is this account performing over time?” layer. It includes profile-level metrics such as reach, impressions, profile visits, and related totals, depending on what Instagram makes available.

3. Audience Layer

This is the “who is this account talking to?” layer. It may include demographic data such as age ranges, location, gender, and other audience breakdowns, subject to Instagram’s availability rules and minimum sample sizes.

Everything in the JSON falls into one of those buckets.

Instagram History Data in Ayrshare

History data is operational data. It helps product teams understand what was published, where it went, and whether it succeeded, rather than how it performed afterward.

That distinction is important. If post analytics is about performance, history is about publishing records and workflow visibility.

In Ayrshare, this comes from:

• GET /history for unified history across platforms by Ayrshare post ID.
  
• GET /history/instagram for Instagram-specific history, including Instagram posts not sent via Ayrshare.
  

For Instagram in GET /history/instagram, you’ll see posts under posts[], with each entry containing fields like:

• id: Instagram social post ID.
  
• post: post caption text.
  
• created: UTC creation time.
  
• mediaProductType: “FEED”, “STORY”, “REELS”, or “AD” (where applicable).
  
• mediaType: “IMAGE”, “VIDEO”, or “CAROUSEL_ALBUM”.
  
• mediaUrl: primary media URL (if available; may be omitted in copyright-restricted cases).
  
• thumbnailUrl: thumbnail image URL.
  
• permalink/postUrl: canonical Instagram URL for the post.
  
• username: Instagram username.
  
• commentsCount: comment count at capture time.
  
• likeCount: like count at capture time.
  

From the generic history response (GET /history), you also get Ayrshare-level fields that apply to Instagram posts as well as other platforms:

• platforms: array of platforms the post was sent to (includes “instagram” when relevant).
  
• postIds[]: per-platform status objects (platform, id, status, postUrl).
  
• status: Ayrshare posting status (success, deleted, awaiting approval, etc.).
  
• type: “now”, “schedule”, etc.
  
• scheduleDate: scheduled publish time.
  
• notes, errors[], mediaUrls[], refId, profileTitle, etc.
  

How to Think About History as a PM

• Use History when you care about what was sent and whether it succeeded, not deep performance.
  
• Use Post Analytics when you care about how that post performed over time.
  
• Use Social Analytics when you care about the account’s overall health.
  

Instagram Brand Profile Data (Get Brand Data)

Brand profile data is identity data. It tells you what an Instagram account is, not how it performs.

In Ayrshare, this comes from GET /brand/byUser, which returns public profile information for usernames across supported social networks, including Instagram.

For Instagram, that can include fields like:

• biography: bio text from the Instagram profile.
  
• followersCount: number of followers.
  
• followsCount: number of accounts the profile follows.
  
• id: Instagram business account ID.
  
• igId: numeric Instagram user ID.
  
• mediaCount: total number of posts on the profile.
  
• name: display name.
  
• profilePictureUrl: URL to the profile picture.
  
• username: Instagram handle.
  
• website: Website URL configured in the profile.
  

From a product perspective, this data is most useful for lightweight account context. It works well for account header UI, connection verification, profile previews, and simple side-by-side comparisons between brands or creators.

This is usually not the right data source for dynamic reporting or charts that change every day. It’s better suited to identity, setup, and context.

Instagram Followers Online Data (Hourly Distribution)

Followers online data helps product teams understand when an Instagram audience is active. That makes it especially useful for scheduling recommendations, audience activity heatmaps, and other timing-related product features.

In Ayrshare, this comes from GET /analytics/getInstagramOnlineFollowers?date=YYYY-MM-DD, which returns follower activity by hour for a given day.

Key fields:

• status: “success” or error state.
  
• onlineFollowersByHour: object keyed by hour “0”–”23″:
  
• Each value is the number of followers online during that hour (in UTC, within the given date window).
  
• startTime / endTime: the measurement window.
  

The main value here is not complexity, but usability. At the raw JSON level, the data is fairly simple: an hourly distribution of online followers plus the relevant time window. But once product teams wrap that data in the right UX, it becomes much more valuable.

How Product Teams Can Use Followers Online Data

Once you have onlineFollowersByHour, you can support features such as:

• Suggest the best times to post per brand.
  
• Render a heatmap of your users’ audience activity.
  
• Compare activity patterns across networks (e.g., Instagram vs TikTok).
  

There are also some important constraints. This endpoint is only available for Instagram accounts with at least 100 followers; the history window is limited, and the day boundary follows Instagram’s reporting logic rather than a simple local calendar day.

For PMs, the important thing is to treat this as timing data, not as a complete picture of performance. It helps answer when an audience is active, not necessarily why content performed well.

How to Actually Use Instagram Data in Ayrshare as a PM

The easiest way to make sense of Instagram data in Ayrshare is to stop thinking of it as one thing.

What looks like “Instagram analytics” is actually a set of different data types, each designed for a specific product job.

• Use post analytics for content-level performance.
  
• Use account analytics for profile health and audience insights.
  
• Use history data for publishing visibility and workflow tracking.
  
• Use brand data for account identity and setup context.
  
• Use followers online data for timing and scheduling decisions.
  

Once that model is clear, product decisions become much easier. You can map features to the right data source, avoid misusing endpoints, and design reporting experiences that actually reflect how the data works.

If you apply the same structure across other social networks, you end up with a consistent, product-friendly way to reason about all your social data, not just Instagram.

Ready to start building with Instagram analytics in Ayrshare? Explore the analytics API documentation to see available endpoints in more detail, or review the full API overview with your engineering team to map the right data to the features you want to build.