Why doesn’t Google care about speed spam?

What’s the economic rationale behind this statement?

Gary Illyes reveals here the analysis framework that Google applies before deploying anti-spam protections. The equation is straightforward: the effort required to spam a signal must be weighed against the potential gain for the spammer.

For speed, the calculation doesn't hold up. Artificially optimizing Core Web Vitals or other performance metrics requires infrastructure — powerful servers, global CDNs, code optimization. It’s costly and time-consuming. In contrast, generating spam content requires only a script and a few euros’ worth of API.

Does this analysis apply to all speed signals?

The statement refers to "speed signals" in broad terms, but the reality is more nuanced. Google likely references the technical metrics measurable through official tools: LCP, FID, CLS, TTFB.

Manipulating these indicators at scale indeed requires real investments. You cannot cheat on a Largest Contentful Paint without genuinely speeding up server-side and client-side rendering. The data comes from the Chrome User Experience Report, collected from real Chrome users.

Why does spam content remain the top priority?

The contrast is stark. Generating 10,000 pages of synthetic content takes a few hours and costs next to nothing with current LLMs. The potential return on investment — capturing traffic on long-tail queries — is immediate.

Therefore, Google focuses its resources on this front. Algorithmic updates like Helpful Content or anti-spam adjustments massively target this type of manipulation. It’s a never-ending race: as soon as a pattern is detected, spammers adapt their techniques.

• Infrastructure as a natural barrier: The investments required to manipulate speed discourage opportunistic players
• The CrUX as a source of truth: Data comes from real browsers, hard to manipulate at scale
• ROI-oriented anti-spam priorities: Google allocates its resources to the most profitable threats for spammers
• Content remains the number one vector: Free production, infinite scalability, complex detection
• No worries about legitimate optimizations: You can push performance without fearing penalties

Does this analysis really hold up in practice?

The economic logic of Google is consistent — up to a point. Yes, setting up performant infrastructure is expensive. However, this statement overlooks one element: low-cost workarounds do exist.

Let’s take a concrete example. A site can serve an ultra-optimized version to Googlebot and the CrUX crawl while delivering a degraded experience to real users. This requires smart cloaking, certainly, but not massive infrastructure. Does Google consistently detect these practices? [To be verified].

What are the grey areas not addressed?

The statement remains vague on several practical aspects. Aggressive lazy-loading, conditional pre-rendering, or optimizations that sacrifice functionality for metrics — where does spam begin?

Some sites manipulate user interactions to artificially improve FID. Others delay loading elements beyond the LCP measurement window. These techniques don’t require heavy infrastructure, just front-end ingenuity.

Should you keep investing in technical performance?

Absolutely. This statement does not diminish the importance of speed as a ranking factor and user experience. It simply tells you that you can optimize aggressively without fearing penalties for "over-optimization".

The Core Web Vitals remain a documented ranking signal. Beyond SEO, a fast site converts better, reduces bounce rates, and improves user satisfaction. The equation remains winning on all sides.

What optimizations should you prioritize without risk of drift?

Focus on legitimate technical gains that improve real experience, not just metrics. A 1.2s LCP achieved through misleading lazy-loading benefits no one — neither Google nor your users.

Priority areas: modern image compression (WebP, AVIF), smart caching, reduction of blocking JavaScript, optimizing TTFB through good hosting. These investments are sustainable and measurable.

• Audit your Core Web Vitals using PageSpeed Insights AND CrUX field data
• Prioritize optimizations that enhance real experience, not just scores
• Avoid cloaking or content masking techniques, even to improve metrics
• Invest in solid infrastructure: high-performance hosting, global CDN if relevant
• Test consistency between bot experience and real user experience
• Document your optimizations to justify your technical choices if necessary

How can you integrate this information into your overall strategy?

This statement should reassure technical teams who were hesitant to push certain optimizations. You shouldn’t fear crossing an invisible line when improving performance.

However, the arbitration remains the same: where to invest your limited resources? If your site has content issues — thin pages, duplication, questionable quality — that’s where Google focuses its monitoring. Speed comes afterward.

Performance remains a critical SEO pillar, but this statement confirms you can optimize it without hesitation as long as the improvements are legitimate. Prioritize technical projects that genuinely benefit users, invest in solid infrastructure rather than gimmicks, and keep in mind that content remains the primary battleground against anti-spam algorithms. These technical optimizations can quickly become complex to orchestrate — working with a specialized SEO agency often helps identify the most profitable levers and avoid costly missteps.