What is Interaction to Next Paint (INP)?

You know what? There’s a new sheriff in town when it comes to measuring how responsive your website feels to users – and it’s called Interaction to Next Paint, or INP for short. If you’ve been keeping tabs on web performance metrics, you’ve probably heard the buzz around this Core Web Vital that’s been making waves since Google officially adopted it in March 2024. But here’s the thing: understanding INP isn’t just about ticking another SEO box; it’s about mainly improving how your users experience your site when they click, tap, or type.

Let me explain what you’ll discover in this comprehensive guide. We’ll analyze deep into the mechanics of INP, explore how it differs from other web vitals you might already know, and most importantly, show you practical ways to measure and improve this important metric. Whether you’re a developer wrestling with sluggish interactions or a business owner trying to understand why visitors bounce from your site, this article will give you the tools and knowledge to tackle INP head-on.

Understanding INP Fundamentals

Right, let’s start with the basics. INP represents a paradigm shift in how we think about web performance measurement. Unlike traditional metrics that focus on loading speed, INP zeroes in on something far more key to user experience: how quickly your site responds when someone actually tries to interact with it.

Definition and Core Concepts

At its core, Interaction to Next Paint measures the time between when a user initiates an interaction (like clicking a button or typing in a form) and when the browser presents the next visual update on screen. Think of it as the digital equivalent of response time in a conversation – you ask a question, and INP measures how long it takes to get a visual acknowledgment that you’ve been heard.

The beauty of INP lies in its comprehensiveness. It doesn’t just look at one interaction; it evaluates every single interaction during a user’s session and reports the worst-case scenario (well, technically the 98th percentile, but we’ll get to that). This approach gives you a realistic picture of what your slowest users experience, not just the lucky ones who hit your site during off-peak hours.

Based on my experience working with various websites, I’ve seen how this metric can reveal hidden performance bottlenecks that other measurements miss entirely. A site might load quickly but feel sluggish when you actually try to use it – and that’s precisely what INP captures.

INP vs Other Web Vitals

Now, here’s where things get interesting. You’ve probably heard of First Input Delay (FID), which INP is replacing as a Core Web Vital. But the differences between these metrics are like comparing a snapshot to a full movie.

FID only measured the delay before the browser started processing the first interaction – essentially just the input delay portion. It was like timing how long it takes someone to pick up the phone when you call, but ignoring how long the actual conversation takes. INP, on the other hand, measures the entire interaction from start to finish, including processing time and rendering the visual response.

The threshold differences tell a story too. While FID aimed for under 100ms, INP allows up to 200ms for a “good” score. This isn’t because Google got more lenient – it’s because INP measures more of the interaction process, making it inherently more demanding to optimise.

Browser Event Processing Mechanics

Let me take you behind the scenes of what happens when someone clicks that “Add to Cart” button on your site. The browser’s event processing pipeline is like a well-orchestrated dance with several distinct phases, and understanding this helps explain why some interactions feel snappy while others make users want to throw their devices out the window.

When a user interaction occurs, the browser goes through three main phases: input delay, processing time, and presentation delay. The input delay is the time between the user’s action and when the browser can start processing it – this happens when the main thread is busy with other tasks. Processing time covers the actual execution of event handlers, including any JavaScript that needs to run. Finally, presentation delay is the time needed to render and paint the visual changes to the screen.

Here’s something that caught me off guard when I first started optimising for INP: sometimes the processing phase is lightning-fast, but the presentation delay kills your score. This happens when you trigger expensive DOM manipulations or force the browser to recalculate layouts and styles. It’s like having a sports car with flat tyres – all that processing power means nothing if you can’t get the results to the screen efficiently.

INP Measurement and Calculation

Alright, let’s roll up our sleeves and get into the nitty-gritty of how INP actually works under the hood. Understanding the measurement methodology isn’t just academic curiosity – it’s the key to knowing what you’re actually optimising for and why certain improvements work while others don’t.

Event Duration Components

Think of INP measurement like timing a relay race with three distinct legs. Each component contributes to the total duration, and weakness in any single area can torpedo your overall performance.

The first component, input delay, measures how long the browser waits before it can start processing your interaction. This delay typically occurs when the main thread is blocked by long-running JavaScript tasks. I’ve seen sites where this delay alone accounts for 80% of their INP score – usually because of poorly optimised third-party scripts or heavy analytics code running at the worst possible moment.

Processing duration covers the time spent actually executing event handlers and related JavaScript. This includes everything from simple click handlers to complex state updates in modern frameworks like React or Vue. The tricky bit here is that processing time can vary wildly depending on what else is happening in your application at that moment.

Presentation delay – the final piece of the puzzle – measures how long it takes to render the visual changes after processing completes. This phase often gets overlooked, but it’s where many performance optimisations fall flat. You might have lightning-fast JavaScript, but if you’re triggering expensive reflows or repaints, your users will still experience sluggish interactions.

Percentile-Based Scoring System

Here’s where INP gets really clever – and where it differs dramatically from other performance metrics you might be familiar with. Instead of reporting average response times or even the slowest interaction, INP uses the 98th percentile of all interactions during a user’s visit.

Why the 98th percentile? Google’s research shows this strikes the right balance between representing the typical user experience and accounting for genuinely problematic interactions. If they used the average, a few lightning-fast clicks could mask seriously sluggish interactions. If they used the worst case, a single anomalous interaction (maybe during a temporary network hiccup) could unfairly penalise an otherwise responsive site.

Let me paint you a picture with some real numbers. Imagine a user session with 50 interactions ranging from 50ms to 800ms. The 98th percentile would capture the second-worst interaction – giving you insight into the poor experience without being thrown off by a single outlier. It’s like judging a restaurant based on most of your visits, not just the one time they were slammed on Valentine’s Day.

Measurement Tools and APIs

Now, let’s talk brass tacks about actually measuring INP. You’ve got several tools at your disposal, each with its own strengths and blind spots.

The Web Vitals JavaScript library is your go-to for real user monitoring. It’s lightweight, reliable, and gives you the same measurements that Google uses for ranking. Here’s a basic implementation:

import {onINP} from 'web-vitals';
onINP(console.log);

For lab testing, Chrome DevTools and Lighthouse provide detailed breakdowns of interaction performance. The User Interactions timeline in DevTools is particularly useful – it shows you exactly which phase is causing problems for specific interactions. According to WP Rocket’s comprehensive guide, this visual approach often reveals issues that raw numbers miss.

PageSpeed Insights gives you field data from real users, which is key because lab conditions rarely match real-world usage patterns. I’ve seen sites that test beautifully in controlled environments but struggle with actual user interactions due to network conditions, device capabilities, or usage patterns that testing didn’t account for.

Data Collection Methods

There are two main approaches to collecting INP data: Real User Monitoring (RUM) and synthetic testing. Each has its place in your performance toolkit, and honestly, you need both to get the full picture.

RUM data comes from actual users visiting your site with all their real-world constraints – slow networks, older devices, background applications competing for resources. This data is gold because it reflects genuine user experiences, but it can be noisy and hard to interpret. Chrome User Experience Report (CrUX) provides this kind of data aggregated across millions of users.

Synthetic testing, on the other hand, gives you controlled, reproducible measurements. Tools like WebPageTest and Lighthouse let you test specific scenarios and device configurations. The downside? These controlled conditions might not represent your actual user base. I’ve learned to use synthetic testing for debugging and optimisation, then validate improvements with RUM data.

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The key to effective data collection is setting up proper attribution. You need to know not just that an interaction was slow, but which specific element, event type, and user context contributed to the problem. Modern RUM solutions can provide this fine data, helping you prioritise fixes based on actual user impact rather than guesswork.

That said, don’t get lost in the data. I’ve seen teams spend months perfecting their measurement setup while their users continue suffering from poor responsiveness. Start measuring quickly with basic tools, then refine your approach as you learn more about your specific performance challenges.

Conclusion: Future Directions

As we look ahead, INP represents more than just another metric to optimise – it’s a fundamental shift towards measuring what actually matters to users. The web is becoming increasingly interactive, and traditional loading metrics simply don’t capture the full user experience anymore.

The future of web performance measurement will likely bring even more sophisticated ways to understand user experience. We’re already seeing experiments with metrics that consider user intent, device capabilities, and contextual factors. But for now, mastering INP gives you a important advantage in creating websites that not only load quickly but feel genuinely responsive and engaging.

Remember, optimising for INP isn’t just about hitting Google’s thresholds – it’s about creating digital experiences that respect your users‘ time and attention. In our increasingly impatient world, the difference between a 150ms and 300ms interaction response can be the difference between a satisfied customer and a lost opportunity.

The tools and techniques for measuring and improving INP will continue evolving, but the fundamental principle remains constant: responsive interactions create better user experiences, which drive better business outcomes. Whether you’re running a small business website or managing a complex web application, understanding and optimising INP should be a core part of your performance strategy.