This post walks through how I get that data without writing a scraper and without giving a password to a stranger, then what I do with it in ten minutes of spreadsheet work.

Step 1: Get the data out

There are three realistic sources, and I usually combine two of them.

1. Instagram's own export. In the app go to Settings, then Accounts Center, then Your information and permissions, then Download your information. Pick your profile, choose JSON (easier to convert than HTML), and select the data types you need: followers and following, plus content if you want post history. It is free, official and complete for accounts you own. The catch is that it is slow, it only works for your own account, and the output is nested JSON rather than a tidy table.

2. Instagram Insights. Professional accounts get in-app numbers for reach, impressions and audience demographics. Meta Business Suite can export some of these as CSV. Good for your own paid-reach questions, but limited to your own account and a fixed history window.

3. A public-data tool for any public profile. When I need to benchmark a competitor or look at a prospect's account before a pitch, I use igtrackr, a free follower tracker that works from a public handle with no login and offers CSV/JSON export on its data. It only sees what any visitor sees, so treat it as a comparison and tracking tool, not a replacement for the official export on your own account.

Step 2: Flatten the JSON

If you went the official route, the followers file looks roughly like a list of objects, each with a username and a timestamp. A few lines of Python turn that into a CSV:

import json, csv

with open("followers_1.json", encoding="utf-8") as f:
    data = json.load(f)

rows = []
for item in data:
    entry = item["string_list_data"][0]
    rows.append({"username": entry["value"], "followed_at": entry["timestamp"]})

with open("followers.csv", "w", newline="", encoding="utf-8") as out:
    w = csv.DictWriter(out, fieldnames=["username", "followed_at"])
    w.writeheader()
    w.writerows(rows)

The exact structure can differ slightly between export versions, so print one item first and adjust the keys. The timestamp is a Unix epoch value; in a spreadsheet, =A2/86400+DATE(1970,1,1) converts it to a date.

Step 3: Ten minutes of analysis

With a clean CSV you can answer real questions.

Growth by week. Convert the timestamps to dates, then build a pivot table counting new followers per week. Spikes usually line up with a Reel, a collab or a giveaway. Flat stretches tell you what a quiet month looks like.

Follower quality signals. Sort usernames and skim. Long strings of digits, empty-looking handles and runs of near-identical names are often bot or giveaway traffic. You do not need a fancy classifier; a quick manual look at fifty rows tells you whether you have a problem.

Churn. Export again next month and compare the two lists. A COUNTIF or a simple VLOOKUP on usernames shows who is missing. Keep one export per month in a folder and you get history that Instagram will not give you.

Content vs. growth. If you also have a posts CSV with dates and like or comment counts, put post dates next to your weekly follower gains. Look at which formats precede the best weeks. Correlation is not causation, but it is a far better starting point than guessing.

Step 4: Add engagement rate

A simple and honest metric is average engagement per post divided by follower count. Take the last twelve posts, add likes and comments, divide by twelve, then divide by followers. Compare against peers of a similar size rather than against a universal benchmark, because rates vary a lot by niche and account size.

Caveats worth knowing

• Public-data tools cannot see private accounts, and they cannot see anything that Instagram does not show to logged-out visitors.
• Numbers from different sources can disagree by a small amount because of timing. Compare like with like.
• Respect privacy. Follower lists contain real people. Keep exports in a private folder, do not publish usernames, and delete data you no longer need.
• Check the terms of any tool you use and never enter your Instagram password into a site that is not Instagram.

A routine you can reuse

Once a month: request the export, convert to CSV, append to your archive, build the weekly pivot, note two or three observations in a running document. After a quarter you will know more about your audience than most people who pay for expensive suites, and the whole process costs nothing but a little spreadsheet time. If you want a second opinion on a competitor in the meantime, a public tracker plus the official export covers nearly every case a small creator or agency will run into.