Social media ad platforms are optimized to measure what happens on-platform: impressions, engagement, and click through rate. Marketing teams, in turn, optimize toward the clearest and fastest feedback signals available to them.
None of these metrics confirm, however, whether the down funnel experience, often a landing page or landing flow, was successful.
- Did the page load successfully?
- Did messaging carry through?
- Did the experience match the promise of the ad?
- Did the user stay down-funnel long enough to form intent?
The illusion of performance at the top of the funnel
An ad can “perform well” even if the experience that follows is slow, interrupted, or fundamentally misaligned. When that happens, the platform continues to reward the ad for generating attention, even if that attention never had a chance to become real intent.
In other words, Meta or Tik Tok, or whatever other platform hosts your ad, is ambivalent about post-click performance and its narrow focus could be costing you.
The black box after the click
Too often users effectively disappear after they click an ad.
They move from a highly observable environment into a post-click (or post-scan if coming from CTV) experience that sits outside of where most optimization decisions are made. Ad teams operate in environments optimized for speed. Decisions about creative, budget, and delivery are made quickly, based on signals that appear immediately. The first post-click experience, by contrast, is often owned by product or growth teams, measured in different tools, and reviewed later, if at all.
As a result, what remains actionable to the ad team is a thin layer of signal. They can see clicks, sometimes landing page views, though measurement is not always optimized, and eventually aggregate outcomes. What requires more comprehensive measurements and deeper understanding is whether users actually experienced the journey as intended in the moments that mattered most.
A lack of comprehensive insight creates a structural blind spot. When performance drops downstream, teams are forced to infer the cause from incomplete information. Messaging gets blamed. Creative is refreshed. Budgets get shifted. Meanwhile, the real issue may live entirely in the experience after the click.
Even sophisticated organizations fall into this pattern, not because of poor execution, but because ownership, measurement, and decision-making are fragmented at the exact point where intent is formed.
Until that gap is addressed, teams will continue optimizing around the black box rather than expanding their visibility.
The most ignored ad performance measurement is landing page performance
Landing page performance is often reduced to a single question: Did it convert?... and conversion here, confusingly, does not necessarily mean conversion into a paying customer or subscriber.
Measuring ad performance requires an understanding of the full scope of landing page metrics and how they fit into the bigger picture.
How to Measure Landing Page Performance
To understand whether the post-click experience is actually doing its job and be able to repair any breaks in real-time, landing page performance needs to answer three questions: Was the experience delivered, did the user engage, and did the user move forward?
1. Was the experience delivered?
Measurement: Page views
Landing page views, as mentioned above, exist to answer this question. A meaningful gap between clicks and page views is not a messaging problem. It is a delivery problem. If you experience a noticeable difference between clicks and landing page views, it’s worth investigating possible slow load times, failed redirects, or in-app browser behavior that is preventing users from ever seeing the experience you designed.
It is also important that page views only include successful page views, so the measurement should occur once the user has the experience in view.
2. Did the user engage?
Measurement: Time on page, scroll depth, interaction
Once the experience successfully loads, the next question is whether users engage with it at all.
Engagement signals include time on page, scroll depth, or interaction with important content elements. These signals help distinguish between low intent and high friction. If users leave immediately without interacting, the experience may be confusing, interrupted, or misaligned with expectations set by the ad.
3. Did the user move forward?
Measurement: conversion to next step
Only after delivery and engagement are confirmed does it make sense to look at progression. These signals indicate that the experience was not only seen and interacted with, but trusted enough to support a decision.
Directional outcomes are not final conversions. They are moments where a user actively chooses to move forward, such as viewing a paywall, starting a sign-up, or initiating a trial.
It’s important not to conflate landing page conversion with purchase or subscription conversion. They serve different purposes and answer different questions.
Without the full picture of a landing page’s performance, it is impossible to tell whether an ad is underperforming or whether the post-click experience is breaking the journey.
When teams lack this visibility, creative is often blamed prematurely, and ad teams are sent back to do unnecessary work while the real issue persists. These signals are most valuable when monitored as close to real time as possible so both ad and growth or product teams have actionable insights about what is and isn’t working with an ad funnel.
A Fully Connected Journey
As ad platforms become more opaque and creative scales faster, the post-click experience carries more weight than ever.
If you can’t see what happens after the click, you’re not optimizing top-of-funnel, you’re guessing.
The future of top-of-funnel performance is not just better ads. It is better visibility into, and control over, what happens immediately after them.
This is the first step in a broader effort to rethink top-of-funnel performance through the lens of the post-click experience. Nami’s complete guide to social media ads for subscription funnels will go deeper into how these principles play out across major social platforms and how to optimize performance at the enterprise level.
