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I Automated 2,700 Twitter Accounts. They Generated $160,000.

$160,000 in cumulative revenue from an experiment I started in 2019. How a few manual accounts became a publishing system, and the work it took to run it.

Editorial paper-cut illustration of blue social posts passing through an automation machine toward a small stack of coins.
Table of Contents

In 2019, I started testing an affiliate campaign with two or three Twitter accounts. I posted manually, changed the timing and copy, and watched what happened. Once the concept worked, I began automating it.

As of 12 September 2026, the experiment has generated $160,000 in cumulative revenue. That is the total before costs, accumulated since the project began.

When I first wrote about it in October 2021, the figure was close to $85,000. This is the updated story: how the system worked, what took the most effort, and why maintaining it became a project of its own.

The numbers, with their dates attached

MeasureWhat it covers
2019The year I started the campaign
2–3 accountsThe initial manual test
About 2,700 accountsAll accounts created over the project
At most 900 accountsThe largest number running together
1–1.5 million tweetsPosting volume during a twelve-month period
Close to $85,000Cumulative revenue reported in October 2021
$160,000Updated cumulative revenue as of 12 September 2026

The tweet count covers twelve months; the revenue total covers the life of the project.

I tested the boring part manually

Before building the automation, I needed to see whether the campaign worked on a small scale. With two or three accounts, I could test posting schedules, different kinds of tweets, links and frequency without having to manage hundreds of moving parts.

That stage was basic, but it gave me something concrete to automate. I had a working process before I started trying to multiply it. A script can repeat an action thousands of times; it cannot tell you whether the original idea was worth repeating.

The engine was an RSS feed and IFTTT

The core setup was simple: an RSS feed produced a new item, IFTTT detected it, and a connected Twitter account published a tweet.

I wrote the RSS generator in PHP. Each account had its own feed, and the feed supplied the text that would become the tweet. The original system used variations of prewritten copy, affiliate links and hashtags. IFTTT handled the connection between the feed and Twitter.

Historical diagram showing an RSS feed connected to IFTTT and then Twitter.
The RSS → IFTTT → Twitter workflow from my original 2021 article.

Splitting the system this way made its parts easier to understand. The generator decided what to publish. The automation service passed it along. The Twitter account was the distribution channel.

I also described WordPress’s built-in RSS feeds as a possible alternative in the original article. The campaign itself used my custom PHP generator.

Setting up the accounts took the most time

Publishing a tweet automatically was only one part of the job. Creating an account, preparing its profile, connecting it to IFTTT and checking the result was repetitive work. At the time, I estimated ten to fifteen minutes for each setup. Verification requests could interrupt the process too.

The pictures from that period show some of the hardware I discussed alongside account setup: a prepaid SIM listing and a multi-SIM adapter.

Historical listing for a prepaid Lycamobile SIM card, with a price of €1.90.
A prepaid SIM listing included in my 2021 write-up. The displayed price is historical.
A multi-SIM adapter with twelve SIM card slots.
The multi-SIM adapter pictured in my 2021 write-up.

I eventually outsourced that work. In my experience then, an account created and connected to IFTTT cost around $2.50 to $3.00. Those are historical prices from this project. They do not tell you what the entire campaign cost: development, supervision and ongoing maintenance were separate concerns.

Delegating also meant documenting the process clearly. Someone else had to understand what a finished setup looked like and where a connection might fail. The instructions and the checks became part of the system alongside the code.

Redacted historical account-tracking spreadsheet showing its column headings and setup status.
A redacted view of my historical account-tracking spreadsheet. Account details are hidden for privacy.

At 900 accounts, management became its own problem

With hundreds of accounts active, keeping track of everything became difficult. Accounts could be banned or lose visibility. I built a custom dashboard to follow the accounts and the problems I was encountering.

Historical Twitter account-management dashboard showing follower counts, posting activity and account status, with usernames blurred.
My custom dashboard from the original experiment. Usernames were already blurred in this screenshot.

Back in 2019, an account might last only a few days, while others lasted six to eight months. Some were still active when I first published this story in 2021.

Automation reduced the repetitive posting work. It still left me with a changing collection of accounts and a need to know what was working. The dashboard was a response to that practical problem.

The setup belongs to its time

Even the 2021 version of this story said the method needed changes because Twitter had altered its anti-bot measures. Treating that article as a current installation guide would miss that context.

There are concrete differences today. IFTTT’s current documentation says affiliate URLs are not supported in the text of its Twitter posting actions. X’s automation rules prohibit duplicate or substantially similar posts across multiple accounts, as well as automated accounts serving duplicative purposes. These points were checked on 12 September 2026. See IFTTT’s Twitter integration and X’s automation rules.

The old interface walkthrough, free-plan limits and account-creation tactics would therefore make a poor set of instructions for a new project. The useful part of this account is the actual experiment: a small manual test, a simple publishing system, a large increase in volume, and the maintenance that followed.

The updated result: $160,000

Updating the figure from roughly $85,000 to $160,000 puts a new number on an old experiment. The mechanics were simple; maintaining hundreds of accounts was where it became real work.

If you have questions about the experiment, leave a comment below. I will do my best to answer.

This case study was first written in October 2021. Revenue updated on 12 September 2026.

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