Should you really invest in speed optimization to combat spam?

Why is Google talking about "speed spam"?

The very idea that one can spam performance signals may seem counterintuitive. However, with the increasing integration of Core Web Vitals as a ranking factor, some parties might theoretically seek to manipulate these metrics to gain a competitive edge. Unlike content or link spam, which can be easily automated at almost no cost, speed spam would require expensive technical infrastructure.

Google distinguishes between two realities here. On one side, there is classic web spam — content farms, link networks, cloaking — which deploy with minimal resources. On the other side, optimizing metrics such as LCP, FID, or CLS requires high-performance servers, CDNs, and advanced front-end optimization. This economic asymmetry changes the game for anti-spam teams.

What does "low priority for an initial release" mean?

This wording reveals that Google deploys its anti-spam systems in a iterative and prioritized manner. When a new ranking signal is introduced, the spam team assesses the cost-benefit ratio for potential manipulators. If the entry barrier is high — as is the case for speed — the risk of massive abuse decreases.

In practical terms, this means that the early deployments of Core Web Vitals as a ranking factor probably did not include sophisticated anti-manipulation countermeasures specifically targeting speed. Google reserved the right to add them "later if necessary," meaning if abuse patterns emerged. This is a pragmatic approach: investing engineering resources where the risk is evident.

Does this economic logic really hold up?

Google's analysis is based on a simple calculation. For a site to display excellent Core Web Vitals, it generally requires: fast server infrastructure (premium or dedicated VPS), a global CDN, image optimization (WebP, compression, lazy loading), optimized front-end code (minification, critical CSS, JS deferring), and sometimes server-side rendering or static generation.

All this represents a significant recurring monthly investment — easily several hundred euros for an average site, several thousand for a large portal. In contrast, creating 100 satellite sites with automatically generated content and reciprocal links costs... almost nothing. The investment/potential spam ratio is therefore unfavorable for speed, making it less attractive for large-scale manipulators.

• Classic web spam remains free or nearly free to deploy massively
• Optimizing speed at scale requires costly infrastructure and ongoing maintenance
• Google can therefore treat the risk of speed spam as secondary in its anti-manipulation priorities
• This approach reflects a pragmatic allocation of anti-spam engineering resources
• Anti-manipulation systems on speed can be added retroactively if abuses emerge

Is this statement consistent with what we see on the ground?

Since the integration of Core Web Vitals, we have indeed not seen the emergence of ultra-fast site farms trying to manipulate rankings through purely technical performance. The entities that invest in speed generally do so for good reasons — user experience, conversion rates — and not from a purely manipulative standpoint. This validates Google's intuition about the deterrent cost.

However, one point deserves nuance. We do see cases where sites use performance cloaking: serving an ultra-optimized version to Googlebot and a less performant version to real users. Technically, this is feasible at a low cost via user-agent detection. Google doesn't explicitly mention this vector in its statement, which raises questions. [To be verified]: do existing anti-cloaking systems already cover this case, or is this a blind spot?

What risks does this "wait and see" approach carry?

Treating speed spam as a deferred priority can create a temporary window of opportunity. If tomorrow an actor finds a way to optimize speed at low cost — for instance, through aggressive lazy loading techniques that deceive metrics without improving actual UX — and this works on a large scale, Google will have to react retroactively.

This has indeed happened historically with other factors. PageRank seemed difficult to spam at first — buying thousands of quality links is expensive — until link farms and PBNs industrialized the process. The economic barrier is never definitive; it can collapse with technical innovation or economies of scale. Google knows this, which is why it mentions "addressing it later if necessary."

In what contexts does this rule not apply?

For very large players — comparators, aggregators, high-margin e-commerce — massively investing in speed infrastructure is already an economic reality. These sites can afford to deploy ultra-high-performance architectures not to spam, but because every millisecond gained translates into revenue. In their case, speed is not a manipulation vector but a legitimate competitive advantage.

The real risk of manipulation concerns more niche players with high margins — finance, gambling, pharmaceuticals — where a few positions gained can justify a significant infrastructure investment. If these sectors begin to systematically optimize extreme speed as a ranking lever, Google might reconsider its position. For now, nothing indicates that this is happening on a significant scale.

Should you still optimize speed if Google doesn't prioritize it in anti-spam?

Absolutely, and for good reasons. The fact that Google does not consider speed spam a priority does not mean that speed is not a ranking factor. On the contrary, it confirms that Google values fast sites precisely because few actors can easily manipulate this signal. It is a "cleaner" factor than others.

The goal here is not to seek to manipulate Core Web Vitals but to optimize them for real business reasons: reducing bounce rates, improving conversion, and enhancing mobile experience. Speed benefits both SEO and business metrics, making it a doubly profitable investment — unlike classic spam, which only provides artificial ranking without real value.

What mistakes should you avoid in speed optimization?

The temptation of performance cloaking exists. Serving an ultra-light version to Googlebot while loading ads, tracking, and widgets on the user version is technically feasible. But this is exactly the type of manipulation that Google detects through its existing anti-cloaking systems. Core Web Vitals are measured via CrUX (Chrome User Experience Report) data, so they are based on real users, not Googlebot.

Another pitfall: optimizing only the metrics displayed in PageSpeed Insights without considering the real experience. You can manipulate a Lighthouse score by artificially delaying the loading of important content, which improves the technical LCP but degrades the perceived UX. Google cross-references its data; a site with excellent Lighthouse but high bounce rates and low session time will send contradictory signals.

How can you ensure that your speed efforts are properly valued by Google?

First step: check that your Core Web Vitals metrics reflect the real user experience, not just lab tests. Use CrUX data in Search Console to see what Google is actually measuring. If your Lighthouse is at 95 but CrUX shows an LCP of 3.5s, it's CrUX that matters for ranking.

Second point: speed must be part of a broader SEO strategy. An ultra-fast site with poor content or a disastrous link architecture isn't going anywhere. Conversely, a site with excellent content but red zone Core Web Vitals loses a competitive advantage. Balance is key, and this is often where the support of a specialized SEO agency becomes valuable to prioritize projects and avoid false good ideas.

• Audit Core Web Vitals via CrUX (Search Console) and not just Lighthouse in the lab
• Prioritize optimizations that benefit both SEO and the actual UX (images, critical CSS, intelligent lazy loading)
• Avoid any form of cloaking or significant differences between Googlebot and real users
• Monitor correlations between speed and engagement metrics (bounce rate, session time, conversion)
• Document infrastructure investments to justify budgets to management (speed ROI = SEO + conversion)
• Test changes gradually to isolate the real impact on ranking and business metrics