From memory to machines: how notifications actually work

Published: 11 hours ago (January 19, 2026 at 02:09 AM EST)

2 min read

Source: Dev.to

Source: Dev.to

How marketing thinks

We want to send messages.
We want people to remember us.
We want them to come back.

How engineering thinks

We need reliability.
We need scale.
We need control.

Both perspectives are right, but each is incomplete on its own. A notification system exists to bring them together.

The real flow, explained simply

Let’s use a food‑delivery example. You place an order. What happens next?

[ Order Placed ]
       |
       v
[ Notification Service ]

The order service does not send a push directly. It only notifies the Notification Service.

The Notification Service as a smart receptionist

Before sending anything, it asks a series of questions:

[ Notification Service ]
        |
        |-- Is the user logged in?
        |-- Do they allow notifications?
        |-- Have we sent too many today?
        |-- What device are they using?
        |-- Push? Email? SMS?

This is where marketing intent meets engineering rules.
Marketing says: “Send an update.”
Engineering asks: “To whom, how, and safely?”

Giving the message a human voice

Once the system decides to send, it prepares the message.

Template

[ Template ]
   |
   v
"Your order is on the way"

Personalization

[ Personalization ]
   |
   v
"Hi Ram, your order is on the way"

Without this step, notifications feel robotic; with it, they feel personal—like calling someone by name at the door.

Delivery workers (the invisible heroes)

Now the message needs to reach the user.

[ Workers ]
   |
   |-- Push (APNS / FCM)
   |-- Email (SMTP)
   |-- SMS

Workers are like delivery people. If one road is blocked, they retry. If a service is slow, they wait. If something fails, they queue again. This builds trust.

Closing the loop: learning from users

After delivery, the system watches how the user interacts.

[ User ]
   |
   |-- Opened?
   |-- Clicked?
   |-- Ignored?
   |-- Disabled notifications?

That data feeds back into the system:

Marketing learns what people care about.
Engineering learns what breaks.
Product learns what matters.

The next notification becomes smarter.

Real‑life version of this loop

A laptop shop gives you a branded bag.

[ Free Bag ]
     |
     v
[ Daily Use ]
     |
     v
[ Brand Recall ]
     |
     v
[ Return Customer ]

Same loop, different medium.

Why does this matter?

Most teams build notifications like plumbing—just pipes in.
The best teams treat notifications like memory design. They ask:

What should users remember?
When should they remember it?
How gently can we remind them?
When does it become noise?

It’s not just architecture; it’s psychology turned into systems. Notifications aren’t merely “Something happened.” They say, “Remember us when it matters.” When marketing and engineering agree on that, you stop sending messages and start building relationships.