Synthetic demonstration — not a real Instagram account

A transparent sample follower analysis

Every username and number below is fictional. This page demonstrates what one export can show, how relationship formulas work, and why two dated snapshots are required to identify new or lost followers.

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Snapshot B · July 15

Current relationship summary

Fictional account: @harbor_stories

Followers

Unique usernames in followers

Following

Unique usernames in following

Mutuals

Present in both sets

Follow-back rate

71.4%

5 mutuals ÷ 7 following

Mutual followers

Followers ∩ Following

@cedar_notes
@luna_sketches
@maple_frames
@orbit_bakes
@quiet_cactus

Not following back

Following − Followers

@river_archive
@sunroom_press

Followers not followed

Followers − Following

@alpine_postcard
@mossy_window
@paper_kite_lab

Two-snapshot demonstration

New and lost followers require a before and after

A single export cannot reveal who unfollowed. Compare the followers set from Snapshot A with Snapshot B to see which fictional usernames entered or left between those dates.

Snapshot A

July 1 · 7 followers

@cedar_notes
@luna_sketches
@maple_frames
@orbit_bakes
@quiet_cactus
@velvet_morning
@willow_type

Snapshot B

July 15 · 8 followers

@alpine_postcard
@cedar_notes
@luna_sketches
@maple_frames
@mossy_window
@orbit_bakes
@paper_kite_lab
@quiet_cactus

New followers

Snapshot B − Snapshot A

@alpine_postcard
@mossy_window
@paper_kite_lab

Lost followers

−2

Snapshot A − Snapshot B

@velvet_morning
@willow_type

Net change: 8 − 7 = +1 follower. Net change alone hides the three additions and two losses, which is why username-level set comparison is useful.

Formulas used

Mutuals: Followers ∩ Following
Not following back: Following − Followers
Followers not followed: Followers − Following
New followers: New snapshot − Old snapshot
Lost followers: Old snapshot − New snapshot
Follow-back rate: Mutuals ÷ Following × 100

Methodology

Read the follower and following JSON records included in the selected ZIP.
Normalise usernames for comparison and remove duplicate records within a set.
Apply set intersection and difference formulas for current relationships.
For change analysis, compare two dated follower sets in chronological order.
Present the categories and counts for review; do not infer motives or engagement from a relationship alone.

Limitations to understand

Snapshot, not event log. A difference shows that a username left a set between dates; it does not explain why.

Input-dependent. Missing files, export options, format changes, and incomplete data can affect results.

Account changes. Deletion, deactivation, or username changes may look like a lost account in a simple set comparison.

No engagement score. Following relationships do not reveal reach, views, saves, or the quality of a connection.

No historical reconstruction. The tracker cannot determine past followers unless an older snapshot is available.

Review before acting. Treat lists as analytical aids, not proof of intent or a reason for automated decisions.

Privacy and storage in the real tracker

Guest analysis

The ZIP is parsed in your browser and the result stays in sessionStorage. A guest result is not uploaded and normally disappears when that browser session ends.

Optional saved history

A signed-in user may explicitly save derived usernames, profile details, categories, counts, relationships, and timestamps. The raw ZIP is not uploaded. Saved history remains until the session or account is deleted.

A separate optional OAuth connection applies only to eligible Instagram professional-account features, not ZIP analysis. See the Privacy Policy for analytics, advertising, email, logs, and other service details.

Ready to analyse your own export?

Start with one export for current relationships. Keep or explicitly save a snapshot, then compare it with a later one for new and lost followers.

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