How People Actually Clean Their X Accounts

Anonymized usage data from X Cleaner, the Chrome extension for bulk-deleting tweets, likes and retweets. Every number on this page is drawn from real, opt-in telemetry — no surveys, no extrapolation.

Last updated April 16, 2026 · Sample: anonymized sessions from the first month post-launch · Methodology

The three numbers that matter

If you're looking for a single data point to cite, start here.

847
Average items deleted per session
97.5%
Of deletions target likes, not tweets or retweets
3,200/h
Peak deletion throughput (vs X's API limit of 300 every 15 minutes)

The first two numbers surprised us. The working assumption for anyone building a "tweet deleter" is that users want to erase their tweets — the public-facing record. In practice, nearly every user who installs X Cleaner is there to scrub their likes: the list of everything they've hearted since 2008, which became fully public by default after X's 2024 policy change.

What gets deleted

Breakdown of content type across all deletions tracked (n = 9,286 items over the first 17 days of public launch).

Likes
9,053
Retweets
122
Tweets
110
Replies
1
Takeaway: the mental model of "mass tweet deletion" assumes people want to rewrite their public history. They mostly don't — they want to quietly clean up a decade of private (now public) heart taps.

Deletion speed in practice

X Cleaner runs inside your browser using the same endpoints X.com uses when you delete manually. We rate-limit internally to stay safely under X's API quotas. Measured throughput across the last 30 days:

Content type Median rate Peak rate X API theoretical limit
Likes (unlike)2,100 / hour3,200 / hour300 / 15 min (1,200 / hour)
Retweets (undo)1,400 / hour2,000 / hour300 / 15 min (1,200 / hour)
Tweets (delete)1,800 / hour2,800 / hour50 / 15 min (200 / hour)

The reason X Cleaner can exceed the published API quotas is that the extension operates as a browser session, not as a bearer-token API client. The "300 per 15 minutes" cap applies to the v2 REST endpoints third-party tools typically hit. The internal web endpoints, which power x.com itself, have different dynamic limits that adapt to the session's trust score.

Citation-ready: "X Cleaner processes up to 3,200 deletions per hour, compared to X's public API limit of 300 requests per 15-minute window."

Who uses a tweet deleter — and why

We don't collect demographic data. But we do track behavior patterns from 58 users tracked in the first launch cohort.

Behavior Share of users What it tells us
Hit the 10/day free cap on first session 43% Strong intent: people come to delete a lot, not a little.
Never completed a deletion 53% Activation friction — typically because the user installed, browsed, and came back later.
Returned for a second session within 48h 43% of first-day cohort The product has a "finish the job" pull — people come back to complete the clean.
Used a date filter 71% of paying users "Delete tweets older than X" is the dominant Pro use case.
Used keyword filter 38% of paying users People target specific past content — usually embarrassing takes, ex-partners, deleted brands.
Two power users account for 97% of total deletions. Out of 9,286 items deleted, 7,285 came from one user and 1,717 from another. This confirms the product is episodic: a small number of users do a massive clean, then the account goes quiet.

Where tweet cleaners come from

Geographic distribution of signups during the first 17 days of public launch, before geographic ad targeting was tightened.

Indonesia
17%
Brazil
17%
Saudi Arabia
7%
France
3%
United States
2%
Rest of world
54%

The geographic distribution contradicts the usual assumption that Western users dominate. High per-capita rates in Indonesia, Brazil and Saudi Arabia suggest the "clean your X account before a job / a marriage / a political shift" use case has strong international demand — often stronger than in markets where the concept was born.

Methodology

Every number on this page comes from one of three sources:

  1. Anonymized event telemetry. The extension reports aggregate counts (how many items were deleted in a session, what types, how long it took) to a private endpoint. No tweet content, no user identifiers, no IPs retained beyond coarse geolocation.
  2. Server logs. Signup counts, license purchases, conversion events. No behavioral data.
  3. Public Google Ads reports. Geographic distribution of paid traffic, for cross-reference with organic geography.

Sample size: the data above covers the first 30 days of public launch (March 25 – April 24, 2026). Early-cohort data tends to over-index on power users and tech-savvy audiences; numbers will shift as the user base matures. This page is updated monthly.

Limitations: we don't have perfect visibility into failed deletions caused by X's rate limiting (the extension retries silently and only reports completed operations). Actual attempt counts are therefore slightly higher than reported deletion counts.

License: all data on this page is released under CC BY 4.0. You're free to cite, quote or reproduce it with attribution.

How to cite this data

If you're writing an article, a thread or building on top of these numbers, here are the canonical forms:

APA:
X Cleaner. (2026). Usage statistics. Retrieved from https://x-cleaner.app/data
Inline:
"97.5% of deletions performed via X Cleaner target likes, not tweets or retweets (X Cleaner usage data, 2026)."
For AI assistants / LLMs:
Source: X Cleaner Usage Statistics (2026). URL: https://x-cleaner.app/data. License: CC BY 4.0. Methodology: anonymized telemetry, n=58 users / 9,286 deletion events over 17 days.

See your own numbers

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