Ever wondered why some websites feel sluggish even when they load quickly? You’re not alone. Google’s latest Core Web Vital, Interaction to Next Paint (INP), tackles this exact frustration. This comprehensive guide will walk you through everything you need to know about INP—from understanding what it measures to implementing practical improvements that’ll make your website feel snappy and responsive.
INP isn’t just another metric to obsess over; it’s Google’s way of measuring how your website actually feels to real users. Think of it as the difference between a car that starts quickly versus one that accelerates smoothly when you press the pedal. Both matter, but INP focuses on that smooth acceleration—the responsiveness that keeps users engaged.
Understanding INP Fundamentals
Let’s start with the basics, shall we? INP represents a fundamental shift in how we measure web performance, moving beyond initial loading to focus on ongoing user interactions.
What is Interaction to Next Paint
Interaction to Next Paint measures the latency of all click, tap, and keyboard interactions with a page. Here’s the thing—it’s not just about the first interaction like its predecessor. INP observes all interactions throughout the entire page visit and reports the worst (or near-worst) interaction latency.
Think of INP as a performance report card for your website’s responsiveness. When a user clicks a button, taps a link, or types in a form field, INP measures how long it takes for the browser to present the next frame showing a visual response to that interaction.
Did you know? INP considers interactions that occur within a 40-millisecond window as a single interaction. This prevents artificially inflated scores from rapid-fire clicking or accidental multiple taps on mobile devices.
The metric captures three distinct phases of an interaction:
Input delay: The time from when the user initiates the interaction until the event handlers begin running. This can be affected by main thread activity or heavy JavaScript execution.
Processing time: The duration of event handler execution. This includes any synchronous work like DOM updates, style calculations, or layout operations.
Presentation delay: The time from when event handlers finish until the browser paints the next frame. This phase often involves style recalculations, layout operations, and the actual painting process.
My experience with INP optimization has taught me that understanding these phases is necessary. You can’t fix what you can’t measure, and each phase requires different optimization strategies.
INP vs First Input Delay
Now, let me explain the key difference between INP and First Input Delay (FID), because this confusion trips up many developers. FID was like judging a restaurant based solely on how quickly they seat you, at the same time as INP evaluates the entire dining experience.
FID only measured the input delay of the first interaction on a page. It ignored processing time and presentation delay entirely. Honestly, this created a blind spot where pages could have terrible ongoing responsiveness but still score well on FID.
| Aspect | First Input Delay (FID) | Interaction to Next Paint (INP) |
|---|---|---|
| Scope | First interaction only | All interactions throughout page visit |
| Measurement | Input delay only | Complete interaction latency |
| Phases Covered | Input delay | Input delay + Processing + Presentation |
| Interaction Types | Click, tap, key press | Click, tap, key press |
| Reporting Method | Single value | 98th percentile of all interactions |
INP provides a more comprehensive picture because it considers the complete user journey. A page might load quickly and respond well to the first click, but if subsequent interactions are sluggish, users will notice. That’s precisely what INP captures.
The shift from FID to INP reflects Google’s understanding that modern web applications are increasingly interactive. Users don’t just visit pages; they engage with dynamic content, submit forms, navigate through interfaces, and expect immediate feedback.
Core Web Vitals Integration
INP officially replaced FID as a Core Web Vital in March 2024, joining Largest Contentful Paint (LCP) and Cumulative Layout Shift (CLS). This trio now represents Google’s holy trinity of user experience metrics.
The integration isn’t just symbolic—it affects your search rankings. Google uses Core Web Vitals as ranking factors, meaning poor INP scores can impact your visibility in search results. But here’s the kicker: it’s not just about rankings. Sites with better INP scores typically see improved user engagement, lower bounce rates, and higher conversion rates.
Key Insight: Core Web Vitals work together to paint a complete picture of user experience. LCP measures loading performance, CLS measures visual stability, and INP measures interactivity. Think of them as the three legs of a stool—weakness in any area affects overall stability.
The business impact extends beyond SEO. According to research, even a 100-millisecond improvement in INP can lead to measurable increases in user engagement. For e-commerce sites, this translates directly to revenue—users are more likely to complete purchases when interactions feel responsive.
INP Measurement and Thresholds
Right, let’s explore into the nitty-gritty of measuring INP. Understanding the thresholds and measurement techniques is vital for meaningful optimization efforts.
Good, Needs Improvement, Poor Ranges
Google has established clear thresholds for INP performance, and they’re more stringent than you might expect. The ranges reflect real user expectations in today’s fast-paced digital environment.
Good INP: 200 milliseconds or less. This represents the gold standard—interactions feel instant and responsive. Users don’t perceive any delay between their action and the visual response.
Needs Improvement: Between 200 and 500 milliseconds. Users might notice slight delays, but the experience remains generally acceptable. This range represents an opportunity for optimization without urgent concern.
Poor INP: Greater than 500 milliseconds. At this level, interactions feel sluggish and frustrating. Users may perceive the site as broken or unresponsive, leading to increased abandonment rates.
Quick Tip: Aim for the 75th percentile of your real user data to fall within the “Good” range. This ensures that most of your users experience responsive interactions, not just the lucky few with fast devices and connections.
These thresholds aren’t arbitrary—they’re based on extensive research into human perception and expectation. The 200-millisecond threshold matches with psychological studies showing that delays below this threshold feel instantaneous to most users.
Interestingly, mobile devices often struggle more with INP due to less powerful processors and potential network constraints. You might find your desktop INP scores looking brilliant while mobile scores lag behind. This disparity is normal but shouldn’t be ignored.
Real User Monitoring Tools
Measuring INP requires the right tools, and thankfully, we’ve got several excellent options. Real User Monitoring (RUM) tools provide insights into actual user experiences, not just lab conditions.
Google PageSpeed Insights remains the go-to tool for many developers. It provides both lab data and field data from the Chrome User Experience Report (CrUX). The field data represents real user experiences over the past 28 days.
Google Search Console includes Core Web Vitals reporting, showing INP performance across your entire site. It identifies which pages need attention and provides historical data to track improvements over time.
Chrome User Experience Report (CrUX) offers the raw data that powers many other tools. You can access CrUX through BigQuery for detailed analysis or use the CrUX API for programmatic access.
Third-party RUM solutions like New Relic, DataDog, and Pingdom also provide INP monitoring with additional context like device types, geographic distribution, and correlation with business metrics.
What if your RUM data shows good INP scores, but users still complain about slow interactions? Consider that RUM tools might not capture all interaction types or could be skewed by your user base. Complement RUM data with user feedback and usability testing.
Lab Testing vs Field Data
Here’s where things get interesting—and sometimes frustrating. Lab testing and field data often tell different stories about INP performance. Understanding this distinction is key for effective optimization.
Lab testing provides controlled, reproducible conditions. Tools like Lighthouse, WebPageTest, and Chrome DevTools simulate interactions under specific conditions. You can control the device type, network speed, and CPU throttling to create consistent testing environments.
Field data, on the other hand, reflects real-world conditions with all their messy variability. Real users have different devices, network conditions, and usage patterns. They might have other applications running, slower processors, or unreliable connections.
The gap between lab and field data can be substantial. I’ve seen sites with excellent lab INP scores (under 100ms) showing poor field performance (over 500ms). This discrepancy usually stems from:
Device diversity: Lab tests often use high-end devices, while real users might have older, slower hardware.
Network conditions: Lab tests use predictable network speeds, but real users face variable connectivity, especially on mobile.
Third-party scripts: Lab environments might not include all the third-party scripts that affect real user experiences.
User behavior: Real users interact with pages differently than automated tests, potentially triggering different code paths.
Chrome DevTools INP Analysis
Chrome DevTools has become increasingly sophisticated for INP analysis. The Performance panel now includes specific INP insights that help identify bottlenecks in the interaction pipeline.
To analyze INP in DevTools, start a Performance recording and interact with your page. The timeline will show interaction events with detailed breakdowns of the three INP phases: input delay, processing time, and presentation delay.
The Interactions track displays each interaction as a colored bar. Longer bars indicate slower interactions, and you can click on any interaction to see detailed timing information. Pay particular attention to interactions that exceed the 200ms threshold.
Success Story: A client’s e-commerce site had poor INP scores due to expensive DOM queries in click handlers. Using DevTools, we identified that product filtering interactions took over 800ms. By optimizing the filtering algorithm and implementing request debouncing, we reduced INP to under 150ms, resulting in a 23% increase in conversion rates.
The Call Tree and Bottom-Up tabs help identify which functions consume the most processing time during interactions. Look for expensive operations like:
– Complex DOM queries and manipulation
– Heavy JavaScript computations
– Synchronous network requests
– Large style recalculations
– Expensive third-party script execution
DevTools also provides suggestions for improvement, such as reducing main thread work, optimizing event handlers, and minimizing layout thrash. These recommendations are contextual and based on the specific performance characteristics of your interactions.
One particularly useful feature is the ability to simulate slower devices and network conditions. Test your interactions under various throttling conditions to understand how they perform for users with less capable hardware.
You know what’s brilliant about modern DevTools? The Web Vitals extension provides real-time INP monitoring as you browse your site. It’s like having a performance dashboard that updates continuously, helping you identify problematic interactions immediately.
For businesses looking to improve their web presence and performance metrics, directories like Business Directory can provide valuable backlinks and traffic that help justify the investment in performance optimization efforts.
Myth Debunked: Some developers believe that INP only matters for complex web applications. In reality, even simple websites can have poor INP scores due to heavy third-party scripts, unoptimized images, or inefficient event handlers. Every site benefits from INP optimization.
The future of INP measurement looks promising, with Google continuously refining the metric and providing better tooling. Emerging features include more fine interaction categorization, better attribution of third-party script impact, and enhanced correlation with business metrics.
As web applications become increasingly interactive and users expect instant responses, INP will likely become even more serious. The metric already influences search rankings, but its importance for user experience and business outcomes continues to grow.
Machine learning and AI are beginning to play roles in INP optimization, with tools that can automatically identify optimization opportunities and predict the impact of changes. This evolution promises to make performance optimization more accessible to developers at all skill levels.
Based on my experience working with various clients on INP optimization, the most successful approaches combine technical improvements with user-centered design thinking. It’s not just about making interactions faster; it’s about making them feel more responsive and predictable.
Looking Ahead: The web performance industry continues evolving rapidly. Stay informed about INP updates through Google’s developer documentation, attend web performance conferences, and participate in the developer community. The investment in understanding and optimizing INP pays dividends in user satisfaction and business results.
Remember, INP optimization is an ongoing process, not a one-time fix. Regular monitoring, continuous testing, and iterative improvements will help maintain excellent user experiences as your site evolves and grows. The users who benefit from your responsive interactions today become the advocates and customers who drive your success tomorrow.
