Your brand can rank first for a query and still be missing from the answer sitting above it. That is the core finding behind netpulse’s AI search visibility data, and it should change how you manage Google Ads bidding. If your bids assume organic strength equals AI presence, you are probably misreading demand.
What netpulse actually measured
netpulse AG is a Winterthur-based agency that combines SEO and Google Ads management with generative engine optimization. According to a press release on its measurement work, the team tracks how companies appear in answers across ChatGPT, Perplexity and Google AI Mode, and watches how AI Overviews affect traditional results. It does this with tooling it built in-house, because third-party scores did not match what it saw in live AI results.
Two findings matter for paid media. First, brand presence in AI answers does not consistently match classic rankings. A company that sits well on conventional results may be absent from the summarized answer above them. Second, visibility can vary considerably between Switzerland’s German, French and Italian language regions for the same brand.
A caveat before you rebuild anything. The release is qualitative. It publishes no visibility percentages, no click-through deltas and no conversion lift. Treat it as a directional signal from an agency with a stake in selling GEO services, and verify the pattern against your own queries.
Why a visibility gap should touch your bids
Most paid search teams treat organic as a backstop. Strong rankings let you trim brand and generic bids, because the free listing catches some of the clicks. That logic gets shaky when an AI answer pushes the organic listing down the page or replaces it with a different set of sources.
Google is explicit that the systems are separate. Its Ads Help documentation says ads are eligible to show above, below or within AI Overviews, and that existing auction signals still decide ad ranking. So you cannot buy your way into the organic answer. You can only decide whether to be present in the paid slots around it.
Organic rank no longer tells you whether you are visible. Paid coverage decisions should start from where you appear in the AI answer, not where you rank beneath it.
That reframes the question. Not “do we need to bid on this term?” but “who owns the answer on this term, and what is left for us if it is not us?”
Four bidding adjustments worth testing
1. Segment queries by AI-answer presence
Build a query set from your top spend and top conversion terms. For each, record whether your brand is cited in the AI answer, whether a competitor is, and whether neither is. You can do this manually for a few hundred queries or with a tool. netpulse’s own point is that you need to observe live results rather than infer them from rank.
Then group them:
- Cited and ranking: hold or trim bids, and watch for cannibalization.
- Ranking but not cited: your organic listing is weaker than it looks. Protect paid coverage here.
- Competitor cited, you are not: the highest-risk group. Decide deliberately whether to defend.
- Nobody cited: classic auction logic still mostly applies.
2. Stop trimming brand bids on organic strength alone
The “we rank number one, so cut brand spend” argument was always an incrementality question. Now it is an incrementality question with a new variable. If the answer above your listing names three alternatives, your paid brand ad may be the only controlled message on the page. Run a geo or time-based holdout before cutting. Our piece on holdouts before scale covers the design.
3. Widen match types for complex, answer-seeking queries
Here the Google documentation is useful. It says AI Overviews tend to trigger on complex queries where there is no single right answer, and that advertisers are less likely to be targeting those keywords. Google’s guidance is to use broad match or keywordless targeting such as AI Max for Search, paired with Smart Bidding, so ads can match against both the query and the content of the Overview.
Be skeptical of the vendor’s own recommendation, which happens to expand spend. But the underlying mechanic is real. Exact-match lists built for 2022 query patterns will miss conversational, multi-clause searches. The answer is a controlled expansion with tight negatives and a capped test budget, not a blanket switch. We went deeper on that sequencing in test before you shift budget.
4. Set separate targets for discovery traffic
Google’s Google Marketing Live announcements describe Smart Bidding Exploration as an update that pursues less obvious, potentially high-performing searches, aimed at moments when people are researching. Research-stage traffic rarely converts at the same ROAS or CPA as branded demand. If you pour it into one campaign with one target, the algorithm either starves it or flatters your blended numbers.
Give exploratory campaigns their own target, their own budget and a longer evaluation window. Judge them on assisted conversions and new-customer rate, not last-click CPA.
Check eligibility before you plan around it
Do not assume every market gets the same treatment. According to Google Ads Help, ads above and below AI Overviews are eligible across 200+ markets where AI Overviews are available. Ads inside AI Overviews are narrower: English-language, on mobile and desktop, in a list of countries that includes the US, Canada, India and Singapore. Google also says it does not currently show ads in AI Overviews for sensitive verticals such as finance, healthcare, alcohol, gambling and politics.
That has practical consequences. A Swiss advertiser, which is netpulse’s market, should not model in-answer ad inventory from that documentation, because Switzerland is not on the list. A fintech or health brand elsewhere cannot lean on it either. Eligibility notes belong in your planning doc before anyone builds a forecast.
Multilingual markets make this harder
The netpulse observation about language regions deserves attention if you run campaigns across Belgium, Canada, Switzerland, India or the US Spanish-speaking market. The same brand can show up in one language’s AI answers and vanish in another. If your Google Ads structure mirrors a single-language organic strategy, you may be underbidding exactly where you are invisible.
Split your visibility audit by language and region, not just by country. Then check whether your search campaign structure lets you set different bids and budgets for each. Where AI presence is weak in one language, a higher paid share there can be rational. Where it is strong, test pulling back.
Organizational fallout: who owns this?
This work sits awkwardly between SEO, paid search and content. Visibility audits are an SEO or GEO task. Bid changes belong to paid media. Fixing why you are not cited belongs to content and PR. If those teams do not share a query list and a weekly review, the data goes stale and nothing changes. We looked at the staffing side in paid search and GEO merging.
Also keep humans in the loop on budget calls. Automated agents can reallocate spend faster than you can, but they do not know why a competitor suddenly started appearing in answers. See speed versus judgment for where that line sits.
What to measure, and what not to claim
- Share of AI answer presence by query group, tracked monthly.
- Incremental conversions from brand and generic campaigns via holdouts.
- New-customer rate on exploratory campaigns.
- Blended CAC across paid and organic, not channel-level ROAS alone.
And what not to do: do not report AI visibility scores to clients as a performance metric without explaining the methodology. Scores differ by tool, by prompt set and by language. That is exactly the gap netpulse says pushed it to build its own tooling.
FAQs
Does netpulse’s data prove AI Overviews reduce paid search performance?
No. The published findings are qualitative and describe a mismatch between organic rankings and AI answer presence. They do not report click or conversion changes. Use them as a hypothesis to test in your own account.
Can I pay to appear in an AI Overview’s organic answer?
No. Google Ads Help states that ads are served through the existing auction, and ads are labeled separately from organic content. Your paid spend does not change whether your site is cited organically.
Should I switch all campaigns to broad match because of AI Overviews?
No. Google recommends broad match or keywordless targeting with Smart Bidding for these placements, but run it as a capped test with strong negatives, a separate budget and a holdout. Expand only if incremental results justify it.
How do I measure my AI visibility without a paid tool?
Build a list of 100 to 300 priority queries, run them in Google (with AI Overviews and AI Mode) and in ChatGPT and Perplexity, and log whether your brand and competitors are cited. Repeat monthly with the same prompts, split by language where relevant.
Are ads in AI Overviews available in every market?
No. Ads above and below AI Overviews are broadly eligible, but ads within AI Overviews are limited to certain English-language markets and exclude sensitive verticals. Check Google’s current documentation before forecasting.
Next step: pull your top 100 spend queries this week, tag each by AI-answer presence, and launch one brand-bid holdout on the group where you rank but are not cited.
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