Most "AI platforms to optimise for" articles are listicles that treat all eight as equally worth your time. They aren't. The honest answer is that Google's AI surfaces and ChatGPT matter most by volume for nearly everyone, Copilot offers the best free data, Claude and Perplexity have specific exploitable characteristics, and Meta AI and DeepSeek belong on a watch-list rather than a work-list.
Key Takeaways
- Score each platform on four axes: realistic effort required, quality of first-party data, audience fit, and whether a documented lever exists at all.
- Google AI surfaces and ChatGPT carry the volume. If those aren't sorted, nothing else matters.
- Bing Webmaster Tools' AI Performance report is the best free first-party data in the category, and Copilot is the cheapest way to earn it.
- Claude is a possible arbitrage: its grounding reportedly routes through Brave, an index far less contested than Google's.
- Perplexity rewards exact phrasing and index inclusion more visibly than most platforms.
- Grok makes sense only if you're already active on X. Meta AI and DeepSeek have no documented levers: watch, don't work.
- Three worked allocation scenarios below: B2B SaaS, local service business, and edtech/course brand.
The Four Axes
Before the table, here's what each column means and why it's there.
Realistic Effort Required
Not "could you do something": everything can absorb effort. This is: how much genuinely platform-specific work does meaningful improvement require, beyond the general content and technical work you're already doing?
Quality of Available First-Party Data
Can you observe your own performance from the platform itself? First-party data is the difference between managing a channel and performing rituals at it. This axis is heavily weighted in my thinking, because unmeasurable work is unaccountable work.
Audience Fit by Business Type
Reach is worthless if it's the wrong reach. A platform with a hundred million users, none of whom buy what you sell, ranks below one with a million who do.
Is There a Documented Lever at All?
The gate question. If there's no documented crawler, no submission path, no observable citation behaviour, then any "optimisation" is guesswork with a budget attached.
The Platform Scorecard
| Platform | Realistic effort required | First-party data quality | Audience fit | Documented lever? |
|---|---|---|---|---|
| Google AI Mode / Overviews | Moderate, largely your existing SEO, plus structure and coverage work | Good, Search Console, though AI data is merged into overall metrics | Broadest of any platform; fits nearly every business type | Yes. Search Central documents crawling, indexing, and AI features |
| ChatGPT | Moderate, content quality, structure, plus presence in mainstream search | Poor, no first-party site-owner tool; server logs and third-party trackers only | Very broad; strongest for research-led and considered purchases | Partial. Crawler user-agents are documented; ranking and selection are not |
| Microsoft Copilot | Low, Bing indexing hygiene plus the same content work | Best available, Bing Webmaster Tools AI Performance report shows real grounding queries | Skews enterprise, Windows, and Microsoft 365 users; strong for B2B | Yes. Documented crawler, submission tools, and an AI performance report |
| Perplexity | Low-to-moderate, index inclusion plus precise, quotable phrasing | Poor, no site-owner console; citations are at least visible in-product | Research-heavy, technical, professional audiences; smaller but high-intent | Partial. Crawler documented; selection behaviour inferred |
| Claude | Low, largely piggybacks on general quality; check Brave visibility | Poor, no site-owner tooling at all | Professional, technical, developer-heavy; growing enterprise footprint | Partial / arbitrage. Grounding reportedly via Brave, a far less contested index |
| Grok | Low if already on X; high if not, you'd be building a social channel first | Poor, none. Manual prompt testing only | Narrow: tech, finance, crypto, AI, political commentary | Partial. X firehose is a first-class source; ranking undocumented |
| Meta AI | N/A, no platform-specific work exists to do | None, no webmaster tools, no citation UI | Enormous reach, especially in India and WhatsApp-first markets | No. No crawler docs, no tools, grounding leans on third-party search |
| DeepSeek | N/A, no verified mechanics to act on | None, no documentation, no tooling | Meaningful in non-US and price-sensitive markets, notably Asia | No. No primary sourcing on retrieval or citation behaviour exists publicly |
Reading the Scorecard
Google and ChatGPT: Non-Negotiable
Between them these cover the overwhelming majority of AI-mediated queries for most businesses. Neither requires exotic tactics: both reward comprehensive, well-structured, genuinely useful content and clean technical foundations. If your work here isn't solid, optimising for Perplexity is rearranging deck chairs.
The frustration is data asymmetry: Google gives you Search Console but folds AI data into overall metrics, while ChatGPT gives you essentially nothing first-party. You're managing your two biggest channels with partial instrumentation.
Copilot: The Data Play
Copilot probably won't be your largest traffic source. Pursue it anyway, because Bing Webmaster Tools' AI Performance report shows actual grounding queries, the real sub-questions that pulled your content into an AI answer.
That diagnostic transfers. The sub-questions Bing reveals are broadly the sub-questions every system generates, because they're driven by what the user's question logically requires. You're getting free reconnaissance on retrieval behaviour generally, funded by a channel that also happens to convert well for B2B.
Skipping Bing indexing hygiene is the most common unforced error I see.
Claude: The Arbitrage Case
Claude's web grounding reportedly routes through Brave's index rather than Google's. Brave's index is dramatically less contested, most SEO programmes have never given it a thought.
That's a textbook arbitrage setup: a retrieval path with real professional audience attached, and almost no competitive optimisation pressure. The work is small: confirm you're in Brave's index, check nothing blocks its crawler, sanity-check how you appear there.
I'd flag the mechanism as inferred from reporting rather than fully documented, so calibrate. But the cost of acting on it is an afternoon, and the downside is nil.
Perplexity: Phrasing and Inclusion
Perplexity visibly rewards two things: being in the index it retrieves from, and having content phrased in ways that are cleanly quotable. It cites in-product, so you can observe outcomes without special tooling.
Practically: direct answers under explicit question headings, specific numbers rather than vague claims, and self-contained passages that survive being lifted out of context.
Grok: Only If You're Already There
Grok's genuine distinction is that the X firehose is a first-class retrieval source, so social distribution is retrieval distribution. Marginal cost is near zero if you already publish on X.
If you don't, the honest accounting is that you'd be building an entire social channel to reach a small assistant audience. That's rarely the best use of the same hours.
Meta AI and DeepSeek: Watch-List
Both fail the gate question. Meta AI has no crawler documentation, no webmaster tools, and no citation UI worth targeting; its grounding leans on third-party search partners while Meta reportedly builds its own engine (per Marketing Dive). DeepSeek has real citation volume, it's one of only four engines tracked by Peec AI, but no primary source anywhere explains how it selects content.
Neither absence is a reason to panic. Both are reasons to set a quarterly review and spend the hours elsewhere.
Three Allocation Scenarios
Scenario 1: B2B SaaS, Mid-Market, Long Sales Cycle
Rough split: Google 40%, ChatGPT 25%, Copilot 20%, Claude 10%, Perplexity 5%.
Your buyers research extensively before ever contacting you, often across several assistants during evaluation. Google carries volume; ChatGPT is where comparison questions get asked.
The unusual weighting is Copilot at 20%. Your buyers are overwhelmingly Microsoft 365 users with Copilot embedded in tools they already have open, and you get the AI Performance report that tells you which sub-questions are actually pulling you in. Highest information-per-hour on the list.
Claude and Perplexity get small allocations because your audience is technical and professional, and both are cheap to serve, the Brave index check especially.
Grok, Meta AI, DeepSeek: nothing. Quarterly review.
Scenario 2: Local Service Business
Rough split: Google 70%, ChatGPT 20%, Copilot 10%, everything else 0%.
Local intent still resolves overwhelmingly through Google. Business Profile accuracy, review volume and recency, consistent NAP data, and location-specific pages do more for you than any AI-specific tactic.
ChatGPT gets a fifth because "best [service] near me" style questions increasingly start there, and answers lean on the same underlying local data, which means your Google Business Profile hygiene is doing double duty.
Copilot gets the remainder for Bing Places consistency and the free diagnostic.
Everything else is zero. Not "low", zero. A local plumber optimising for DeepSeek is a story I'd tell as a cautionary example.
Scenario 3: Edtech or Course Brand
Rough split: Google 35%, ChatGPT 30%, Perplexity 10%, Copilot 10%, Claude 10%, Grok 5%.
Prospective learners ask assistants exactly the questions a good content programme should already answer: is this worth it, what are the outcomes, how does it compare, what's the alternative, who is it wrong for.
ChatGPT is weighted unusually high here because course evaluation is a long, conversational, multi-turn research process: precisely the shape of interaction ChatGPT handles, and where a brand that answers the uncomfortable questions honestly gets cited over one that only markets.
The organic growth work I did with Masai School, taking Instagram from 26K to 117K and LinkedIn from 50K to 160K, was built on that principle long before AEO had a name: answer the questions people are actually asking, including the ones that don't flatter you. That content is now precisely what retrieval systems want to cite, which was a fortunate accident rather than a plan.
Perplexity and Claude earn small slices because course comparison is research-shaped. Grok gets 5% only if the brand already has an active X presence.
How to Actually Apply This
Score Your Own Audience Fit First
The effort and data columns are broadly stable across businesses. Audience fit is not, and it's the column that should reorder your priorities. Ask where your customers actually research, surveys, sales call notes, onboarding questions, and weight accordingly.
Do the Shared Work Once
Most of what helps across platforms is the same: comprehensive topical coverage, explicit question-shaped headings, direct answers up front, clean technical foundations, accurate entity information, genuine expertise. Do that once and it serves every platform on the list. Platform-specific work is the thin layer on top, and it's much thinner than most content on this subject implies.
Instrument What You Can
Set up Bing Webmaster Tools even if Bing traffic is small. Watch AI crawler hits in your server logs. Run a fixed monthly prompt set across your top two or three platforms. Imperfect measurement beats none, and it's what separates a programme from a hope.
Review Quarterly, Not Weekly
Retrieval behaviour changes fast: ChatGPT's site:-scoped query share jumped roughly 45x in a single day in August 2026, as Search Engine Journal reported. But your allocation shouldn't chase daily noise. Quarterly is the right cadence for reweighting, with a watch-list check for the platforms currently scoring zero.
Frequently Asked Questions
Which AI platform should I optimise for first?
Google's AI surfaces, then ChatGPT, they carry the volume for nearly every business type. Only move on once both are genuinely solid.
Is Bing worth the effort given its market share?
Yes, disproportionately. Bing Webmaster Tools' AI Performance report showing real grounding queries is the best free first-party data in AEO, and the underlying work is minimal.
Why is Claude described as an arbitrage opportunity?
Its web grounding reportedly routes through Brave's index, which almost no SEO programme optimises for. Low competition plus a professional audience makes it cheap upside. The mechanism is inferred from reporting, not fully documented.
Should I optimise for Meta AI?
No platform-specific work exists to do. No crawler documentation, no webmaster tools, no reliable citation UI. Keep it on a quarterly watch-list.
Is DeepSeek worth targeting?
Only if you sell into markets where it has real usage, mainly non-US and price-sensitive segments. Even then, there's no verified mechanic to act on, test rather than optimise.
How much of AEO work is platform-specific?
Less than most articles suggest. The large majority is shared: coverage, structure, direct answers, technical health, entity accuracy. Platform-specific work is a thin top layer.
Does Grok deserve effort for a B2B company?
Only if your buyers are on X: common in developer tools, fintech, crypto and AI, rare elsewhere. If you're not already active there, the cost of building the channel outweighs the assistant reach.
How do I measure AI visibility without first-party tools?
Fixed prompt sets run monthly with multiple runs per prompt, server log analysis of AI crawler activity, and Bing's AI Performance report as your one real window.
Should I use a paid AI visibility tool?
Useful once you have enough volume to justify it and a clear decision it will inform. Before that, a spreadsheet and a disciplined prompt set gets you most of the value.
How often should I revisit this allocation?
Quarterly. Retrieval mechanics shift weekly, but reweighting your effort that often produces thrash rather than progress.
If you're staring at eight platforms and trying to work out where the next quarter's hours should go, that's exactly the kind of problem I like. Four-plus years of marketing experience, mostly helping edtech and startup brands grow organically, has taught me that the hardest part is deciding what to skip. You can see the work at younusfardeen.com: and if you'd like to talk it through, the contact form there comes straight to me.