Automate OnlyFans Messages with the API
Your chatters are sending the same $15 PPV to the subscriber who has spent $2,000 and the one who spent $15. Same price. Same message. Same timing. That is not messaging automation — it is noise delivery. The API gives you LTV, purchase history, and activity timestamps for every subscriber. Wire that data into your sends and the difference is not incremental — it is 3.2x higher PPV conversion. Scale from 1 creator to 60+ without adding headcount.
PPV Conversion
3.2x higher
conversion rate vs. manual mass DMs
Scale
60+ creators
managed simultaneously from a single integration
The problem: agencies flying blind on every send
Messaging drives 40 to 70% of total earnings in a well-managed creator account. PPV campaigns, re-engagement sequences, and personalized DMs are where revenue is actually made. But the manual process does not scale — and worse, it does not optimize.
A skilled chatter managing 2 to 3 accounts sends the same $15 PPV to the subscriber who has spent $2,000 and the subscriber who has spent $15. They send at whatever time they happen to be at their desk, not when each fan is most likely to open and purchase. They miss the re-engagement window for the subscriber who went quiet 11 days ago because nobody is tracking it. Every manual send is a blind send.
Scale the roster to 15, 30, or 50 creators and the problem compounds. You hire more chatters, but headcount does not solve the intelligence gap. You still have no subscriber-level data informing who gets what message at what price point — you just have more people making uninformed decisions faster.
Other tools offer mass messaging features, but without the data layer they are noise delivery systems. Sending the same message to every subscriber is not automation. It is spam. Real messaging automation requires knowing your subscribers: LTV, purchase history, last active timestamp, engagement pattern. That data is what the API gives you.
The solution: subscriber intelligence wired directly into your sends
The /stats/fans/top endpoint returns each subscriber's total spend, purchase history, last active timestamp, and engagement data. That is the targeting layer. The /messages/send and /messages/queue endpoints are the delivery layer. Wire them together and you have a messaging system that treats a $2,000 subscriber and a $15 subscriber the way they deserve to be treated: differently.
The mechanism is LTV-based segmentation. Pull subscriber spend data, bucket into tiers — whales, regulars, casuals — and assign each tier its own PPV price, message template, and media. The high-spend subscriber gets the $25 exclusive. The casual fan gets the $8 promotional offer. Both receive something appropriate. Neither feels like they are on a broadcast list.
Timing is the second optimization. Activity timestamps in the fan data let you calculate peak engagement windows per subscriber. Queue campaigns to fire when each fan is most likely online and purchasing — not when a chatter happens to be free. That alone moves conversion rates measurably.
For agencies, the compounding effect is significant. One integration runs targeted PPV campaigns across 60+ creators simultaneously. Chatters stop being manual senders and start being campaign strategists — designing the logic once, letting the API execute across the entire roster.
API endpoints used
/messages/send Send a direct message to a specific subscriber. Supports text, media attachments, and PPV pricing. Returns message ID and delivery status.
/messages/queue Queue messages for scheduled delivery. Specify send time, recipient list, and message content. Messages are delivered at the specified time with retry logic.
/stats/fans/top Top subscribers ranked by spending, with LTV, last active timestamp, purchase history, and engagement data. The foundation for intelligent message targeting.
Code example
A targeted PPV campaign that segments subscribers by LTV and sends different pricing tiers to each group.
import requests import time API_BASE = "https://api.ofapi.dev/v1" HEADERS = {"Authorization": "Bearer your_api_key"} # PPV pricing tiers based on subscriber LTV TIERS = { "whale": {"min_ltv": 500, "price": 25.00, "text": "Exclusive drop just for my top fans..."}, "regular": {"min_ltv": 100, "price": 15.00, "text": "New content you won't want to miss..."}, "casual": {"min_ltv": 0, "price": 8.00, "text": "Special offer just for you..."}, } def run_ppv_campaign(creator_id, media_id): # Get all subscribers with spending data subs = requests.get( f"{API_BASE}/onlyfans/models/{creator_id}/stats/fans/top", headers=HEADERS ).json()["data"] sent = {"whale": 0, "regular": 0, "casual": 0} for sub in subs: # Determine tier from LTV ltv = sub["totalSpent"] if ltv >= TIERS["whale"]["min_ltv"]: tier = "whale" elif ltv >= TIERS["regular"]["min_ltv"]: tier = "regular" else: tier = "casual" config = TIERS[tier] # Send PPV message with tier-specific pricing requests.post( f"{API_BASE}/onlyfans/models/{creator_id}/messages/send", headers=HEADERS, json={ "subscriberId": sub["id"], "text": config["text"], "mediaId": media_id, "price": config["price"], } ) sent[tier] += 1 time.sleep(0.1) # Rate limiting return sent # Run campaign results = run_ppv_campaign("creator_001", "media_abc123") print(f"Campaign sent: {results}") # {"whale": 23, "regular": 187, "casual": 412}
Outcomes
3.2x PPV conversion
LTV-segmented pricing converts 3.2x better than sending the same price to every subscriber.
60+ creators simultaneously
Run campaigns across your entire roster from a single API integration. No per-account logins.
Optimal send timing
Messages queued for each subscriber's peak activity window, not whenever a chatter is available.
Chatter efficiency
Chatters shift from manual message senders to campaign strategists designing targeting logic.
Every blind send is money left on the table
Agencies managing 60+ creators with LTV-segmented campaigns consistently outperform those doing manual sends. The gap is not effort — it is data. Pull your first subscriber intelligence endpoint and you will immediately see the targeting your current process cannot do.