# Instagram Active Hours & Best Time to Post Analyzer (`seemuapps/instagram-active-hours-analyzer`) Actor

Find the best time to post on Instagram for any public account — get a day-by-hour posting heatmap, peak engagement slots, and the account's likely time zone.

- **URL**: https://apify.com/seemuapps/instagram-active-hours-analyzer.md
- **Developed by:** [Andrew](https://apify.com/seemuapps) (community)
- **Categories:** SEO tools, Lead generation, Social media
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $100.00 / 1,000 active-hours reports

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Instagram Active Hours & Best Time to Post Analyzer

Find the **best time to post on Instagram** for any public account. Enter a username and get a day-by-hour heatmap of when the account posts, which time slots earn the most engagement, quiet (likely-asleep) hours, and an estimate of the account's time zone - no login or cookies required.

### What you get

- **Best times to post** - the day+hour slots where the account's posts earn the highest average engagement (likes + comments, plus plays for Reels)
- **Day-by-hour heatmap** - a 7×24 grid showing how many posts and Reels land in each hour of each weekday, in both the account's local time and UTC
- **Engagement heatmap** - average engagement per post for every day+hour slot
- **Most active day and hour** - the single peak weekday and hour
- **Quiet hours** - the hours with little or no activity (the account's likely offline/sleep window)
- **Estimated time zone** - auto-detected from the quietest posting window, with a confidence rating (or supply your own)
- **Weekday vs. weekend split** - what share of posting falls on weekdays vs. weekends
- Export to JSON, CSV, or Google Sheets directly from the Apify console

### Use cases

- **Best time to post** - schedule your own content for the slots where a top account in your niche gets the most engagement
- **Content calendar planning** - build a posting schedule backed by real engagement data, not generic "post at 9am" advice
- **Audience and competitor research** - understand a creator's or brand's posting rhythm and when their audience responds
- **Influencer vetting** - spot accounts that post on a flat, automated schedule vs. organic human activity
- **Time-zone inference** - estimate where in the world an account is based

### How it works

The analyzer samples the account's most recent posts and Reels and buckets every timestamp by weekday and hour. Posting time shows when the account is active; per-slot average engagement shows when its audience responds best. The time zone is inferred from the **circadian dip** - the multi-hour window when the account posts least (its local night) - and you can always override it.

> Note: this reflects *posting* activity, not real-time presence. Scheduled/automated posts can flatten the pattern - which itself shows up as a "low confidence" time-zone estimate.

### How to use

1. Enter the Instagram **username** (with or without @; profile URLs work too)
2. Set **Posts to Analyze** (default 500; more samples = a sharper pattern)
3. Optionally set a **Time Zone Offset** (e.g. `-5`, `1`, `5.5`) to skip auto-detection
4. Run the actor - the report appears in the **Dataset** tab

### Output format

A single record per run:

```json
{
  "username": "natgeo",
  "platform": "instagram",
  "postsAnalyzed": 500,
  "timeRange": { "earliest": "2025-08-01T...", "latest": "2026-06-09T...", "spanDays": 312 },
  "timezone": { "mode": "inferred", "offsetHours": -5, "label": "UTC-5", "confidence": "high", "note": "..." },
  "mostActiveDay": "Tuesday",
  "mostActiveHour": "13:00",
  "quietHours": ["02:00", "03:00", "04:00", "05:00"],
  "weekdayShare": 0.74,
  "weekendShare": 0.26,
  "engagementMetric": "likes + comments (+ Reel plays where exposed)",
  "avgEngagementPerPost": 48211,
  "bestTimesToPost": [{ "day": "Friday", "hour": "16:00", "posts": 9, "share": 0.018, "avgEngagement": 112480 }],
  "topSlotsByPosts": [{ "day": "Tuesday", "hour": "13:00", "posts": 14, "share": 0.028, "avgEngagement": 51730 }],
  "hourHistogram": [/* 24 counts, local */],
  "dayHistogram": [/* 7 counts, Monday-first */],
  "avgEngagementByHour": [/* 24 averages, local */],
  "avgEngagementByDay": [/* 7 averages, Monday-first */],
  "dayNames": ["Monday", "...", "Sunday"],
  "heatmap": { "Monday": [/* 24 */], "...": [] },
  "heatmapUtc": { "Monday": [/* 24 */], "...": [] },
  "engagementHeatmap": { "Monday": [/* 24 */], "...": [] }
}
```

Build a visual heatmap straight from `heatmap` or `engagementHeatmap`, or chart `hourHistogram` / `avgEngagementByHour` for a quick view.

# Actor input Schema

## `username` (type: `string`):

Instagram username, with or without leading @. Profile URLs (https://www.instagram.com/username) are also accepted.

## `maxPosts` (type: `integer`):

How many recent posts and Reels to sample for the heatmap (1-500). More samples = a sharper pattern.

## `timezoneOffset` (type: `number`):

The account's UTC offset in hours, e.g. -5 for US Eastern, 1 for Central Europe, 5.5 for India. Leave blank to auto-detect the time zone from the account's quietest posting window.

## Actor input object example

```json
{
  "username": "natgeo",
  "maxPosts": 500
}
```

# Actor output Schema

## `report` (type: `string`):

A single record: username, postsAnalyzed, timeRange, detected timezone (offset, label, confidence), mostActiveDay, mostActiveHour, quietHours, weekday/weekend split, bestTimesToPost (top slots by average engagement), topSlotsByPosts, hourHistogram (24), dayHistogram (7, Mon-first), avgEngagementByHour/Day, and full day-by-hour heatmaps for post counts (local + UTC) and average engagement.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "username": "natgeo"
};

// Run the Actor and wait for it to finish
const run = await client.actor("seemuapps/instagram-active-hours-analyzer").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "username": "natgeo" }

# Run the Actor and wait for it to finish
run = client.actor("seemuapps/instagram-active-hours-analyzer").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "username": "natgeo"
}' |
apify call seemuapps/instagram-active-hours-analyzer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=seemuapps/instagram-active-hours-analyzer",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/b0ll96tPVOn2TkuoG/builds/fgdwhbmiKZQEkmGUX/openapi.json