The Deliverability Tax: Why Your Content Is Being Silenced (and What to Do About It)

Most marketing leaders I speak with are focused on the right problems. Better creative. Cleaner copy. More testing. What they don't realize is that a significant portion of their messages are being filtered out before a human ever reads them. The issue isn’t the content. It’s the infrastructure around it.

We recently analyzed 40 billion marketing messages sent across push notifications, in-app messages, and email. The number that stopped me: generic push notifications are experiencing roughly a 35 percent drop in delivery. Not a 35 percent drop in engagement. A 35 percent drop in delivery. The messages never arrive. This is what I've started calling the deliverability tax.

The Hidden Filter

The crackdown started in earnest in early 2024, and has intensified since. Apple, Google, and Yahoo collectively shifted from treating sender best practices as suggestions to treating them as hard requirements. Operating systems began classifying poorly targeted messages as noise and actively suppressing them from users. Gmail tightened bulk sender requirements across the board.

The mechanics differ by channel. Apple’s mobile OS provides app developers with tools including interruption levels and relevance scores that let users control how notifications surface based on time sensitivity and message nature. Android requires notification channels and importance settings that govern how prominently notifications appear. The intent of these tools is user protection. The effect on marketers sending generic messages is significant.

This isn't entirely surprising. Consumers reached a breaking point with irrelevant digital communication, and the platforms responded. What's surprising is how many marketing teams still haven't adjusted.

The Metrics Are Lying to You

Here is the part that makes the deliverability tax hard to catch and easy to ignore: Your dashboard still shows the message as delivered.

Delivered is not the same as seen. Seen is not the same as considered. Most marketing teams are still measuring “delivered” as the primary baseline, which means they’re optimizing against a number that flatters them while the actual customer experience degrades.

When a generic push notification lands in a low-visibility notification bucket, or gets ignored often enough to hurt future sender reputation, the brand pays for that lost reach through compounding filters downstream. The cost is invisible in most dashboards. But it accumulates.

Where the Problem Is Worst

Our research found that push notifications carry the highest deliverability tax, at around 12 percent, when operating systems classify them as spam. But the problem extends beyond push.

What surprised me more was the in-app message data. Over half of marketers (46.3 percent) are not personalizing in-app messages at all. This is the channel where the user has already made the most deliberate choice to engage: They opened the app. Ignoring behavioral context at that moment is leaving the most available signal completely unused.

Email is not immune either. Among marketers still using batch-and-blast approaches, reputation damage builds slowly and is difficult to reverse once it starts affecting inbox placement.

The data also showed that 43.6 percent of marketers are not personalizing push notifications, and close to 40 percent of brand marketers overall are still relying on basic personalization tactics designed for how the industry worked three or four years ago. The operating systems have changed. The tactics haven't.

Personalization as Infrastructure

There is a tendency to treat personalization as a creative problem or a resource problem. Teams say they know they should do more of it, but the data isn't clean enough, or the workflow is too complicated. I understand those constraints. They are real.

But personalization in 2026 is not primarily a creative advantage. It is infrastructure for access.

Without behavior-driven relevance signals, messages are more likely to be classified as noise by the systems that carry them. That means a brand investing in thoughtful copy, strong creative, and careful targeting can still be losing reach to a competitor whose messages are simply better matched to individual customer behavior. The content and deliverability problems are now the same.

Behavior- and journey-based messages have a fundamentally different signal profile than broadcast messages. They are more likely to be opened, which builds sender reputation, which improves future deliverability. The system rewards relevance because relevance correlates with what users actually want to see. That is the logic the platforms are enforcing.

Closing the Gap Between Sent and Seen

The first step is treating deliverability as a strategic KPI rather than a technical monitoring metric. Most teams have someone watching deliverability somewhere in the stack, but the insight rarely reaches the people making decisions about campaign structure, segmentation, and messaging cadence. It should.

Second, audit the gap between “sent” and “seen” in your current reporting. This requires pulling delivery data at the channel level and comparing it against open and engagement data in a way that surfaces suppression, not just response. Many teams will find that gap is larger than they expected.

Third, look specifically at in-app. Of all the channels in the data, it carries the least risk and the most untapped potential. The user is already in the product. Behavior context is available in real time. The infrastructure to act on that context exists in most modern customer engagement platforms. The reason teams aren’t using it is usually prioritization, not capability.

The brands doing this well are not necessarily the ones with the most sophisticated creative operations. They have built systems that read customer behavior and respond to it in real time. Their sender reputation with both customers and platforms is strong enough to earn visibility before the message is even written.

The benchmarks dataset has more on how these patterns vary by industry and channel, and the differences across verticals are significant. Some categories are further behind than others. A few are already adapting. The gap between them is widening.

Ravi Dodda is the CEO and founder of MoEngage, a customer engagement platform used by consumer brands globally. MoEngage's research is drawn from the analysis of more than 40 billion messages across engagement channels.