September 2025: Spam Update Ends, FastSearch Powers AI Citations & ChatGPT Ecommerce

August Spam Update & num=100

Google’s August 2025 Spam Update finished rolling out on 22 September after a 27-day run. This was the first, and possibly only, spam update of the year and it was global in scope. The impact was unusually big for a spam update.

At the same time, Google removed support for &num=100 query parameter, which most rank trackers have historically relied on to pull the top 100 results for a keyword in one request. This change has broken a lot of third-party tools, scrambling position tracking (including in Search Console, with knock-on effects on impressions and CTR). Tools are being forced to rethink their entire architectures, in some cass resulting in them having to make 10× more requests to reconstruct a top-100 list from Google, pushing up their costs significantly.

Google also posted (and quickly closed) a new "Engineering Analyst, Search, Anti-scraper" job role explicitly aimed at detecting and blocking SERP scraping. This poignantly underlines the retirement of the num= parameter, confirming that it was not a one-off tweak but part of a broader anti-scraping push.

My Take: Google didn’t just roll out a spam update... it rewired the data exhaust that our industry runs on at the same time. Expect to see quirks in rankings/volatility graphs, odd GSC deltas (impressions down, average position up), and some combination of higher prices, less data and slower refresh cycles from SEO tools that scrape Google results.

Operationally, a move to reporting only top 20 or top 30 rankings still gives you the core detail on what's working for you right now (steering short-term thinking) and what's in striking distance (guiding medium-term thinking). You just lose some of the data granularity that might otherwise have guided your longer-term strategy. Is it really a game-changer for contemporary SEO, though? I'm not so sure it is. It just means you need marketers, not data scientists, back at the helm of your long-term SEO plans. Good SEO in 2025 is just good brand building. It's persona-based, value-driven ,topically-optimised marketing.

With that said, you can still fold in first-party analytics to gather up some data, and where you can get your hands on it, you can still treat “daily top 100 by keyword” as a luxury, just not a baseline expectation. Our rank tracking tool, NeuralHQ, still tracks the top 100, so for those readers working with us already, there's that.

Of course it's super frustrating when period-in-time baselines get recalibrated and rearchitected, like what we've seen in Search Console, because it makes comparisons that much harder. It also forces us to rethink our "go-to" reporting stack. In the end, though, this reminds me of Google removing 98% of keyword data from Google Analytics back in 2011... after all the fuss and furore, the marketers, strategists and innovators kept doing what they were doing, the results kept coming, and new ways of reporting progress were developed. Get the right marketers in the driving seat now and these changes will only serve to thin out the herd for you.

FastSearch, RankEmbed & how Google grounds AI responses

Newly surfaced documents from the Google antitrust case Remedies Memorandum explains that AI Overviews grounds its answers (i.e. find citations) via FastSearch, a system based on RankEmbed signals. FastSearch pulls a much smaller set of documents much faster than the full Search algorithm used in the production of traditional SERPs, but with lower quality than the fully ranked results. The key ingredient of FastSearch, called RankEmbed, leans heavily on click-and-query data plus pattern-matching against human-rater scoring data.

My Take: The thing most people seem to be focusing on—“backlinks don’t matter for AIO citations”—misses the point. It misses the mechanics. If FastSearch starts from user-interaction-shaped subsets of the index, then the only way into that shortlist is to win real search demand in the first place, and links remain one of the most scalable ways to earn that demand. That's not a coincidence, nor is it intellectual acrobatics... it's the entire reason why FastSearch works as a fantastic proxy for the full ranking system which does include backlinks! It's why Google do it this way.

get links → get rankings → get clicks → get in FastSearch → get cited‍

Build your SEO, generate brand and content authority that attracts consistent user engagement, and you’ll bias citation selection, even if links aren’t directly used as a signal at the final grounding step.

AI Overviews, AI Mode, ChatGPT & Perplexity brand citations diverge

Fresh BrightEdge research shows increasing divergence between citations in Google AI Overviews/AI Mode and ChatGPT for the same queries. Different systems, different retrieval stacks, different brand exposure. Our own study found a ~52% overlap between AI Overview citations and the traditional organic top-20 results for the same keyword, and an uncorrelated c.46% overlap against AI Mode, due to the grounding processes being based on different query sets (the 'fanout queries' made behind-the-scenes during grounding and citation selection). It is becoming more and more apparent that there is no linear or single route to "AI visibility".

My Take: Treat “AI search” as multi-channel. One content object will not win everywhere. Create answer units mapped to distinct intents (e.g., explainer vs buyer’s guide vs troubleshooting), and target multiple retrieval modes: classic SEO for organic, citation-friendly passages for SERP Features and AI citations, entity markup for answer engines, and brand-forward, PR-style materials for LLM seeding where publisher authority is favoured.

Apple Intelligence: 2026 Gemini partnership?

Apple is reportedly in talks to license Google’s Gemini to power a revamped Apple Intelligence, with some upgrades publicly delayed to 2026. While nothing is signed, multiple mainstream reports (and earlier Reuters coverage) point the same way.

My Take: If Apple puts Google’s model in the loop, then it could be distribution, not model quality, that wins the game. In that scenario, you can expect Gemini-flavoured answers inside the iOS surface areas where a lot of commercial search begins. For marketers, this would mean even more weight on brand/entity optimisation and structured product data that travels well across assistants (i.e. Siri). Keep a close eye on how Siri selects products and cites sources. If it mirrors Google’s grounding biases, then AI Overview/AI Mode playbooks will port almost 1:1.

ChatGPT’s Instant Checkout ushers in agentic LLM-commerce

OpenAI has added Instant Checkout to ChatGPT – a native, in-chat purchase flow powered by its new Agentic Commerce Protocol (ACP). The first wave is US-only, starting with Etsy sellers and “over a million” Shopify merchants “coming soon”, with payments initially via Stripe. OpenAI’s docs confirm an open protocol and a lightweight merchant integration path, with access currently limited to approved partners.

OpenAI’s help materials also outline how merchant lists are ranked: by availability, price, quality, whether the seller is the maker/primary seller... and whether Instant Checkout is enabled. In short, enabling the ACP flow can itself improve your placement inside ChatGPT’s shopping UI because ChatGPT will favour it. That aside, it looks very similar to the approaches taken by Amazon, Ebay, Etsy, and perhaps unsurprisingly Shopify (Shop) when it comes to ranking products.

My Take: This is the first credible zero-click retail surface built on an LLM. The near-term playbook is commercial, not “SEO”:

- Be buyable inside ChatGPT: implement the ACP/Instant Checkout spec and ensure catalogue, price and stock data are clean and real-time. Early adopters gain distribution and a ranking nudge within ChatGPT’s merchant selector.

- Structure for retrieval: product pages need tight entities, rich product schema, and clean variants so ChatGPT can resolve items and map them to an Instant Checkout flow.

- Rethink attribution: expect leakage from traditional PPC/PLA funnels as discovery and purchase compress into ChatGPT. Start tagging ACP orders distinctly and model assist value from ChatGPT exposure.

This is assistant-led commerce becoming real. If you sell D2C, pilot the integration now; if you’re a marketplace seller, prepare for a world where the AI chat surface is the shop window!

In Other News:

1. In the US antitrust case against Google, Judge Amit Mehta imposed behavioural remedies: Google must end exclusivity deals and share certain data with rivals. But, crucially, no divestiture of Chrome/Android was forced. By contrast the EU Commission fined Google €2.95B ($3.45B) over ad-tech market abuses and signalled that divestiture remains on the table if Google can’t resolve its conflicts of interest. Political heat then rose when President Trump threatened tariff retaliation against the EU, prompting a late procedural pause and continued uncertainty.

2. Google has tested AI Overview layouts that blend with Knowledge Panels and sometimes drop the “AI Overview” label, shifting citations into columnar cards. Traditional SERPs, in certain areas, started to look indistinguishable from feature-rich AI Mode SERPs.

3. UX tests gave even more prime real estate to AI Mode. Certain keywords were spotted as showing AI Mode suggestions in the autocomplete dropdown. Clicking them took users directly to the AI Mode tab, completely bypassing traditional search. By nudging users into AI flows before the SERP even loads, Google's UX is further embracing front-of-funnel zero-click experiences.

‍