Do AJAX calls really consume your crawl budget?

Why is crawl budget a concern with AJAX architectures?

Modern JavaScript sites multiply asynchronous requests to load dynamic content. Each AJAX call triggered after the initial render represents an additional HTTP request that Googlebot must process. The question weighing on SEOs for years: do these additional requests nibble away at the site's crawl quota?

The crawl budget refers to the number of pages a search engine is willing to crawl within a given period, determined by the technical health of the site and its perceived “value.” On large sites with thousands of URLs, every request counts — and the idea that a resource-hungry JavaScript framework could saturate this quota with unnecessary API calls is chilling.

How does caching play into the equation?

Google specifies that the caching mechanism plays a crucial role. When Googlebot crawls a page, it caches already retrieved resources — CSS, JS, images, but also responses to AJAX calls. During subsequent crawls, if the resource hasn’t changed, the bot uses the cached version without consuming additional quota.

Specifically, a JSON API called on 500 different pages but always returning the same response only counts once, provided the HTTP cache headers are correctly configured (ETag, Last-Modified, Cache-Control). This is what neutralizes the dreaded “request multiplication” effect.

What does it mean to “version AJAX calls”?

Versioning an AJAX call involves adding a version parameter to the request URL — typically a hash of the content or an incremental number. For example: /api/products.json?v=2.4.1 instead of /api/products.json. When the content changes, the version changes, forcing a new fetch and invalidating the old cache.

This practice improves the cache hit rate on the Googlebot side: URLs remain stable between actual content changes, allowing the engine to efficiently reuse its cached resources. Conversely, URLs without versioning featuring random timestamps (?t=1678901234) undermine the cache and multiply the counted requests.

• AJAX calls generate additional HTTP requests during crawling
• Googlebot's cache neutralizes requests with responses that haven't changed
• Only new requests or those with invalidated cache consume crawl budget
• Versioning URLs improves cache stability and reduces unnecessary hits
• HTTP headers (ETag, Cache-Control) dictate the mechanism's efficiency

Is this statement consistent with what we observe in the field?

Yes, but with a significant nuance. On well-configured sites with clean cache headers and controlled versioning, it's observed that AJAX calls do not lead to a collapse of crawl budget. Server logs show that Googlebot reuses cached responses for stable resources — it's measurable.

The problem is that the majority of SPA sites are not “well configured.” Poorly set Cache-Control, lack of ETag, dynamic timestamps added by poorly configured frameworks — all of this disrupts the mechanism. In these cases, each AJAX call does indeed count, and we see sites with 10,000 crawlable URLs but only 3,000 indexed pages because the budget is consumed by redundant API requests. [To be verified]: Google does not publish any figures on the percentage of affected sites or a precise threshold where the impact becomes critical.

What common mistakes sabotage the benefits of caching?

The first classic error: adding a timestamp or a random ID in each AJAX call to “force the refresh.” Well-intentioned developers trying to avoid stale content on the user side end up undermining Googlebot's cache in the process. The result: each crawl triggers thousands of unique API requests, even if the underlying content hasn’t changed.

The second trap: having too restrictive or missing cache headers. A Cache-Control: no-cache or max-age=0 forces Googlebot to re-fetch systematically, nullifying all the interest of the mechanism. Some CDNs also apply aggressively default rules on JSON endpoints, which need to be manually overridden.

The third often overlooked point: URL variations related to authentication or personalization. If each user session generates unique tokens in API URLs (/api/data?session=xyz), Googlebot sees millions of different endpoints for the same content — and this is a disaster for crawl budget.

In what situations does this rule not fully apply?

When the site relies on an infinite scroll architecture with paginated AJAX calls on the fly, even with good caching, the sheer volume of requests may exceed what Googlebot is willing to crawl. On an e-commerce site with 500,000 products loaded in blocks of 20 via AJAX, the number of potential endpoints explodes — and Google will never crawl everything, cache or not.

Another edge case: sites with real-time content (news, stock market, weather) where data changes every minute. The cache becomes useless since each crawl encounters a different version, and in that case, yes, each AJAX call counts against the budget. Martin Splitt’s statement mainly applies to relatively stable content, not to live feeds.

How can you verify that your AJAX calls are not impacting crawl budget?

First step: analyze server logs to identify patterns of Googlebot requests on your AJAX endpoints. Look for repeated calls with 200 codes (server hit) vs 304 (cache hit). If you see thousands of 200s on the same URLs, your cache is not working — or Googlebot isn’t respecting it.

Second verification: test the HTTP headers returned by your APIs with a tool like curl or Chrome DevTools. Check Cache-Control, ETag, Last-Modified, Expires. Compare with what Googlebot receives via Search Console (URL Inspection Tool, More Info tab). Sometimes, the CDN returns different headers based on User-Agent — this is a classic issue.

What concrete actions can be taken to optimize?

Implement a versioning system for your critical AJAX calls. The simplest method: integrate the hash of the build or a version number in the URL (/api/products.json?v=abc123). Each deployment with content change alters the hash, properly invalidating the cache. Between deployments, the URL remains stable and the cache works.

Set aggressive cache directives for stable content: Cache-Control: public, max-age=31536000, immutable for versioned resources. For semi-dynamic content, a max-age=3600 with stale-while-revalidate=86400 offers a good compromise. Test the impact on cache hit rates in your server analytics.

On the architecture side, prioritize server-side rendering (SSR) or static site generation (SSG) for critical SEO content and reserve AJAX for secondary parts (filters, sorting, infinite scroll). This mechanically reduces the number of calls on the crawl side. If you’re stuck in a full SPA, at minimum, serve an HTML shell pre-filled with essential inline data (JSON-LD, main content) to limit AJAX dependencies.

Is it necessary to rethink the entire front-end architecture if it is already in place?

Not necessarily. If your pages index correctly and the logs do not show crawl budget saturation, the urgency is low. Focus first on quick wins: cache headers, versioning the most called endpoints, cleaning up unnecessary parameters in URLs.

However, if you notice an abnormally low indexing rate (Search Console, Coverage report) with thousands of discovered but not crawled pages, and the logs show massive waste on redundant AJAX calls, then yes, a partial redesign is necessary. Migrating to SSR or pre-rendering for key sections can unlock indexing in a matter of weeks.

These optimizations touch on both front-end development, CDN configuration, and server architecture — rarely mastered by a single person internally. If your team lacks expertise in these areas or development resources are overwhelmed, hiring a specialized technical SEO agency can drastically accelerate compliance and avoid costly missteps.

• Audit server logs to measure the 200/304 ratio on AJAX endpoints crawled by Googlebot
• Check and correct Cache-Control, ETag, Last-Modified headers on all public APIs
• Implement content hash-based versioning for critical AJAX calls
• Remove random timestamps and session tokens from API URLs exposed to crawl
• Test the impact on indexing rates through Search Console after 4-6 weeks of deployment
• Consider SSR/SSG for critical SEO content if full SPA poses persistent issues