They had always relied on WhatsApp broadcasts to drive conversions. The ones where you send promotional messages for a sale or a new launch to every phone number in your CRM.
For long, these messages were crucial for their sales. More than 90% folks would open these messages and a fair number would click website links in those messages and transact. But suddenly, those same campaigns started falling flat.
Turns out their delivery rates had tanked to just 52.73%.
Nearly half their messages weren’t reaching users.
They were baffled.
They tried everything marketers usually do:
✓ Toned down the copy
✓ Changed send times
✓ Cleaned the list and removed folks who were not opening messages
Still no improvement.
The campaigns looked fine. But something was breaking under the hood.
That’s when they came to QuickReply.ai.
It took just one look at their dashboard to see that the killer was not the message, but the infrastructure.
Their software did not reveal any error codes
There was no system to track numbers with failed messages
The software did not attempt a resend when delivery failed
But beyond all this, there was a delivery killer that they weren’t aware of.
Meta had recently tightened the frequency at which brands can send messages to users — a policy called frequency capping. In simple terms, this means there’s now a limit on how frequently you can message a user within a specific time frame.
And this brand did not configure its campaigns to account for this change.
So we helped them build a fail-safe system, one that could:
✅ Detect why a message didn’t go through by tracking each delivery attempt and flagging issues like frequency cap hit, user blocked, or number inactive.
✅ Automatically retry sending the same message after gradual intervals — say, once after 6 hours, then again after 12. This increases your chances of delivery without overwhelming the user or triggering Meta’s limits.
✅ Do all of it automatically. QuickReply systems do this on autopilot. Humans don’t need to handle the system, hence no errors.
In plain terms: the message didn’t just disappear.
It waited. Watched. Then found another way to reach the user at a better time.
No change in message. No change in audience.
Just a system that automatically takes over when a message fails, without needing manual input.
The result?
Their Delivery jumped from 52.73% to 92.6%.
And engagement came roaring back.
Too often, brands obsess over the what — the message, the audience, the offer.
But ignore the what if — What if the message doesn’t go through?
That’s where scale quietly breaks.
If your current setup doesn’t know how to handle failure…
…it’s not marketing.
It’s a coin toss.
This post was originally shared by on Linkedin.