TikTok Device Farming Operations
Budget: $30 – $250 USD
I need help standing up and running a live device farm—roughly 2,000 TikTok accounts split across a bank of smartphones and tablets. The remit is very specific: the profiles don’t have to read like handcrafted influencers; instead they can rely heavily on automated workflows, as long as they stay alive and functional.
Geo lacation needs to be targeted and must use gps mock app
Core workflow
– Provision new accounts in bulk, bind them to rotating residential or mobile proxies, and keep device fingerprints clean so TikTok’s risk flags stay low.
– Push mostly automated likes and comments at scale; these two metrics matter most because they feed the viral-loop signals we are measuring.
– Capture and warehouse performance data (engagement rates, retention time, shadow-ban incidents). I’ll be iterating strategy every few days, so I need neat CSV/JSON exports or a lightweight dashboard.
– Continuously refine the automation logic to mirror TikTok’s latest behavioural patterns while remaining within the ToS grey-zone.
Deliverables
• A functioning farm (≈1,000 live accounts) distributed over smartphones and tablets, ready to run 24/7.
• Scripted or GUI-based tooling for bulk account creation, login rotation and human-like like/comment actions.
• Daily heartbeat report and a weekly roll-up that includes engagement numbers, account health, and suggestions for tweaks.
• Full hand-off documentation: device layout, proxy list, and the scripts/workflow so another operator can step in without downtime.
Acceptance criteria
1. At least 95 % of accounts remain unflagged after a seven-day stress test.
2. Target volume of likes/comments per account achieved with <5 % action errors.
3. Data exports arrive on schedule and match TikTok back-end numbers within a 2 % margin.
If you already have experience juggling large fleets with ADB, MDM suites, or custom Python/Node automation, let’s talk; I’m ready to move quickly.
Geo lacation needs to be targeted and must use gps mock app
Core workflow
– Provision new accounts in bulk, bind them to rotating residential or mobile proxies, and keep device fingerprints clean so TikTok’s risk flags stay low.
– Push mostly automated likes and comments at scale; these two metrics matter most because they feed the viral-loop signals we are measuring.
– Capture and warehouse performance data (engagement rates, retention time, shadow-ban incidents). I’ll be iterating strategy every few days, so I need neat CSV/JSON exports or a lightweight dashboard.
– Continuously refine the automation logic to mirror TikTok’s latest behavioural patterns while remaining within the ToS grey-zone.
Deliverables
• A functioning farm (≈1,000 live accounts) distributed over smartphones and tablets, ready to run 24/7.
• Scripted or GUI-based tooling for bulk account creation, login rotation and human-like like/comment actions.
• Daily heartbeat report and a weekly roll-up that includes engagement numbers, account health, and suggestions for tweaks.
• Full hand-off documentation: device layout, proxy list, and the scripts/workflow so another operator can step in without downtime.
Acceptance criteria
1. At least 95 % of accounts remain unflagged after a seven-day stress test.
2. Target volume of likes/comments per account achieved with <5 % action errors.
3. Data exports arrive on schedule and match TikTok back-end numbers within a 2 % margin.
If you already have experience juggling large fleets with ADB, MDM suites, or custom Python/Node automation, let’s talk; I’m ready to move quickly.
Related categories:
PHP
Python
Mobile App Development
Android
Software Architecture
Node.js
JSON
Data Analysis
Automation