Pick an Engine by Where Your Buyers Ask — Then Keep a Baseline Everywhere

Optimize first for the engine your buyers already use — ChatGPT, Perplexity, or Google AI Overviews — then keep a thin, honest baseline on the other two. Vendor blogs will tell you their surface is the only one that matters. Your CRM and sales calls will tell you the truth.

This spoke is the priority decision tree under the Answer Engine Optimization playbook. It compares how each system selects sources as of August 2026, with hedges where vendors do not publish full internals. It is a surface map, not a trophy ceremony.

The short answer

• Priority follows buyer behavior, not the loudest LinkedIn thread.
• ChatGPT mixes training memory with selective web search via partnered providers. Bing is documented. Exclusivity is not.
• Perplexity is citation-dense and retrieval-first. Community sources, notably Reddit, show up often in third-party studies — and the percentages move.
• Google AI Overviews pull from Google’s index with query fan-out and passage-level synthesis. Classical rank helps eligibility. It does not guarantee a citation.
• Shared baseline work (entities, answer-first pages, crawl health) transfers. Engine-specific bets come after the panel.

How do the three engines choose sources differently?

Vendors publish product behavior, not full ranking formulas. Treat the table as an operator model, not a leaked spec.

Surface	Retrieval trigger	Candidate pool (what we can say)	Citation style	Hedge
ChatGPT	Selective — search when the product decides the prompt needs live info	Partnered search providers plus OpenAI’s own crawl and index layers. Bing is a named partner in OpenAI help and privacy docs	Inline chips plus a Sources panel when search ran	Do not treat “ChatGPT = Bing index only” as settled doctrine
Perplexity	Effectively every factual query hits live retrieval	Perplexity’s own search stack. Historically used Bing APIs; now runs proprietary indexing. Vendors and analyses disagree on the exact mix	Dense numbered inline citations	Focus Modes change the eligible domain set
Google AI Overviews	Query-dependent Overview trigger on Google Search	Google’s web index plus fan-out sub-queries. Gemini-class synthesis selects passages	Short Overview with a handful of linked sources	Organic top-10 helps. It is not a hard citation requirement

OpenAI’s ChatGPT Search help page says search “sometimes partners with other search providers,” rewrites the prompt into one or more targeted queries, and names Bing (and Shopify) in the privacy list. Google’s AI features page says Overviews and AI Mode may use query fan-out — multiple related searches across subtopics and data sources — and that Overviews often do not trigger at all.

Shared across all three: if your page is blocked, unreadable, or factually inconsistent, you lose before “optimization” starts.

Why is there no universal winner?

Because the three surfaces do not share a citation pool. Ahrefs’ June 2025 Brand Radar cut — 86% of top mentioned sources are not shared across ChatGPT, Perplexity, and Google AI Overviews — found only seven websites in the top 50 for all three. The sample was large: about 76.7 million Overviews, 957k ChatGPT prompts, and 953.5k Perplexity prompts for that month.

That is the whole argument against a winner-take-all roadmap.

What the study showed	Operator read
86% of top-50 mentioned sources appear on only one of the three surfaces	A page that “wins ChatGPT” can be invisible on Overviews
Only 7 domains sit in the top 50 for all three	Do not copy a competitor’s ChatGPT screenshot into a Google-only plan
Google Overviews lean toward familiar Search-authority and Google-owned properties	Classical SEO still feeds this surface
ChatGPT leans toward publishers and licensed / partnered media	Training memory plus selective search, not a Google clone
Perplexity pulls a broader international corpus in that snapshot	Different geography and domain mix than the other two

Tinuiti’s Q1 2026 citation work, written up on Search Engine Land, lands the same way: there is no universal top source. There are patterns shaped by intent, platform, and category. Reddit’s share grew across their panel and hit 24% of Perplexity citations in January 2026 — and 0.1% on Gemini in the same write-up. Same domain. Different surface. Different weight.

If a conference slide says “just do Reddit” or “just rank #1,” the slide is selling a religion. The data is selling a panel.

Decision tree: which engine first?

Answer these in order. Stop at the first yes that fits.

1. Do buyers discover you mainly via Google Search (local pack, how-tos, category SERPs)? Prioritize AI Overviews plus classical SEO hygiene. Keep ChatGPT and Perplexity on the monthly baseline.

2. Do sales calls start with “I asked ChatGPT…” or do buyers live in ChatGPT for vendor shortlists? Prioritize ChatGPT (search-enabled prompts in your panel). Verify Bing Webmaster and IndexNow hygiene as a cheap eligibility bet — not as a religion.

3. Do buyers research with Perplexity, or does your category show heavy Reddit and forum corroboration in answers? Prioritize Perplexity plus community presence that is real, not spam.

4. Unsure? Run a 30-prompt panel across all three for two weeks. Rank engines by citation rate × deal influence, not by vanity screenshots.

Signal you can collect this week	What it points at
Closed-won “how did you find us?” mentions ChatGPT	ChatGPT first
Google Search Console still drives demo traffic on money queries	AI Overviews first
Engineers paste Perplexity threads into Slack	Perplexity first
You sell locally (field service, clinics, trades)	AI Overviews plus local consistency
Nobody on the team can name a source	Run the panel. Do not guess

I have been SEO certified since 2021. The certification does not pick the engine. The buyer does.

Which engine should B2B prioritize?

Default B2B bias in 2026: ChatGPT first, AI Overviews second, Perplexity third — unless your panel says otherwise.

That default is only a prior. B2B shortlists often happen in chat products during research hours. Procurement still Googles vendor names and comparisons, so Overviews matter on those queries. Perplexity punch rises in technical and “show me sources” cultures.

B2B signal	Tip priority toward
“ChatGPT said try X / Y / Z” in discovery calls	ChatGPT
Category how-tos still drive demo traffic from Google	AI Overviews
Engineers paste Perplexity threads into Slack	Perplexity
You sell locally (field service, clinics)	AI Overviews plus local AEO
Healthcare or other restricted ChatGPT workspaces	Confirm whether web search is even on before you plan for it

OpenAI’s Enterprise and Edu search note is easy to miss: workspace admins can disable web search, and ChatGPT for Healthcare workspaces do not use Bing for web search. If your buyers live in a locked-down workspace, “optimize for ChatGPT Search” is a category error. You are fighting training memory and whatever the admin allowed.

Freeze the prior after your first panel, not after a conference talk.

Which should local and consumer prioritize?

Default consumer and local bias: Google AI Overviews plus local-pack hygiene first, ChatGPT second, Perplexity as the citation and community check.

Local / consumer signal	Tip priority toward
Maps / “near me” / service-area searches	AI Overviews plus GBP and LocalBusiness consistency
Viral “best X in city” TikTok, then a Google follow-up	AI Overviews
Younger buyers using ChatGPT for recommendations	ChatGPT
Category debates live on Reddit	Perplexity (and honest Reddit presence)
Bookers, patients, or homeowners still start on Google	Do not abandon Search Console for chat screenshots

Local operators: do not skip NAP and schema while chasing chat screenshots. Overview citation work for Google specifically lives in how to get cited in AI Overviews. This page decides whether Google is your first engine. That page decides how you become extractable once it is.

ChatGPT will still invent a phone number if your site, GBP, and directories disagree. Perplexity will still prefer a thread that already settled the “who is good in this city” argument. The local job is consistency first, then surface-specific bets.

What work transfers across all three?

Fund these once. They are the shared baseline.

• Entity and fact sheet consistency (site, schema, directories)
• Answer-first pages with tables, steps, and FAQ
• Crawlable HTML on money URLs
• Sane robots for the bots that actually feed search surfaces
• Corroboration plan (PR, partners, reviews)
• Prompt panel logged monthly on all three surfaces
• Hallucination watch on brand facts

Engine-specific bets after the baseline:

Bet	ChatGPT	Perplexity	AI Overviews
Index / discovery	Bing Webmaster plus IndexNow as an eligibility hedge. Allow OAI-SearchBot	Fresh publish plus PerplexityBot fetchability	Google Search Console plus classical rank
Content shape	Clear entities. Shortlistable criteria pages	Citeable stats. Community-aware angles	Passage blocks that survive fan-out sub-queries
Off-site	Roundups and directories models already trust	Reddit and forum corroboration (earned, not spam)	Topical authority across the cluster
Measurement	Same prompts, search-on, Sources panel logged	Same prompts, citation list logged	Same prompts, Overview present/absent plus cited URLs

The transfer list is why you do not run three content calendars. You run one baseline and one priority engine. The other two get instrumented neglect.

Does ChatGPT depend on Bing’s index?

Partially, and not as a slogan. OpenAI’s own ChatGPT Search documentation states that ChatGPT search partners with third-party search providers, rewrites the user prompt into one or more queries, and names Bing in that partnership and privacy context. Enterprise docs are more explicit: search “may share disassociated search queries with the Bing search engine.”

What we will not claim as fact: that ChatGPT “just uses Bing’s index” for every answer, or that Google rankings transfer automatically.

Claim	Status as of August 2026	What you do
ChatGPT sometimes sends rewritten queries to search partners	Documented by OpenAI	Treat search-on answers as retrieval, not memory
Bing is a named partner	Documented	Keep Bing Webmaster and IndexNow healthy
ChatGPT is Bing-only	Not documented. Do not put this in an exec deck	Hedge exclusivity in every slide
Training memory answers many prompts without live search	Observable product behavior	Brand-fact pages still matter when search does not run
Independent 2025 tests claimed Google-only bait terms appeared for paid users	Secondary reporting. OpenAI has not confirmed a Google partnership	Do not rebuild the stack on a bait-term blog post

Training memory still answers many prompts without live search. OpenAI also operates its own crawler split — indexing versus user-triggered fetch — which is a separate checklist from Bing Webmaster.

Operator move: verify important URLs in Bing and keep Google healthy. Hedge the exclusivity claim in every exec deck.

Search eligibility is a bot question, not a Bing slogan. Three different user agents. Mixing them up is how a legal review deletes you from ChatGPT Search while “blocking AI training.”

OpenAI’s crawler documentation is blunt: each robots.txt setting is independent. You can allow OAI-SearchBot so you can appear in ChatGPT search results while disallowing GPTBot so crawled content is not used to train foundation models. Search opt-out can take about 24 hours to adjust.

User agent	Job	Affects ChatGPT Search citations?
OAI-SearchBot	Surfaces sites in ChatGPT search features	Yes — this is the search opt-out
GPTBot	Training crawl for foundation models	No — training, not search
ChatGPT-User	User-triggered fetch. robots.txt may not apply	Not the Search opt-out. Use OAI-SearchBot for that
OAI-AdsBot	Landing-page checks for ads on ChatGPT	Only if you are running ads

• OAI-SearchBot allowed on public money URLs if you want ChatGPT Search citations
• GPTBot decided as a training-policy question, not a search-policy question
• WAF is not silently 403ing OpenAI IP ranges published at openai.com/searchbot.json
• You did not copy a “block all AI bots” snippet from a 2023 Twitter thread

Sites opted out of OAI-SearchBot will not be shown in ChatGPT search answers, though they can still appear as navigational links. That sentence is from OpenAI, not from an agency PDF.

Why does Perplexity cite Reddit so often?

Because Perplexity is retrieval-first and citation-dense, and community threads are cheap, opinion-rich passages for recommendation queries. Third-party studies in 2025–2026 repeatedly find Reddit among Perplexity’s most-cited domains. Exact percentages move by dataset. Do not tattoo a single number into your strategy doc.

Source / window	What it reported	How to use it
Semrush, 5,000 keywords / 150k+ citations (2025)	Reddit dominated across AI Mode, Overviews, ChatGPT, and Perplexity in that cut	Treat Reddit as a real corroboration surface
Tinuiti via Search Engine Land, Jan 2026	24% of Perplexity citations from Reddit in that commercial-intent panel	Category-specific. Not a law of nature
Semrush 13-week, 230k-prompt study (Jul–Oct 2025)	ChatGPT’s Reddit share collapsed mid-September, then restabilized; Perplexity was more stable	Percentages move. Re-check your category
Secondary write-ups quoting 46.7% of Perplexity citations	Recycled from 2025 Semrush-class cuts	Do not freeze 46.7% as “the” number

Perplexity also ships Focus Modes that constrain the eligible domain set. The company’s own getting started guide tells users to narrow results with Focus — Academic for journals, and similar source-type filters. If your buyers run Social or community-weighted Focus, a clean corporate blog is not the candidate pool they asked for.

Practical meaning: if every competitor has credible threads and you have zero presence, Perplexity has fewer corroborating passages that mention you. Spammy astroturf backfires. Earn mentions where the category already debates.

Fetchability is a bot question, not a Reddit strategy. Two user agents, two jobs. Perplexity’s crawler docs say PerplexityBot is designed to surface and link websites in search results and is not used to crawl content for foundation-model training. Perplexity-User is a user-triggered fetch and “generally ignores robots.txt rules” because a person asked for the page.

Changes can take up to 24 hours. If you run a WAF, Perplexity tells you to allow the published IP ranges, not just the user-agent string.

Agent	Respects robots.txt (vendor claim)	What blocking it does
PerplexityBot	Yes	Removes you from the indexed candidate pool for search results
Perplexity-User	Generally no — user-requested fetch	Live citation fetches can still happen when a user asks

• PerplexityBot allowed on public money URLs if you want Perplexity citations
• WAF allowlist uses current IPs from perplexity.com/perplexitybot.json
• You did not treat a 2023 “block all AI” snippet as a 2026 visibility policy
• You are not confusing “block training” with “block search”

This is eligibility, not ranking. Allowing the bot does not make Perplexity cite you. Blocking it makes the rest of the conversation theoretical.

Do AI Overviews require traditional Google rank?

No hard requirement for top-10 organic rank to earn a citation. Rank still helps you enter broader candidate pools and win the non-Overview SERP.

Ahrefs’ March 2026 update — 38% of AI Overview citations pull from the top 10 — looked at 863k keyword SERPs and about 4 million Overview URLs. About 37.9% of cited URLs also appeared in the first 10 blocks. The rest split between positions 11–100 (31.2%) and beyond the top 100 (31.0%). Their July 2025 cut had been about 76%. Ahrefs itself warns the two datasets are not fully comparable because citation detection improved. Search Engine Journal’s write-up of the same update notes BrightEdge’s February 2026 panel put top-10 overlap nearer 17%.

Study (do not flatten these into one %)	Top-10 overlap reported	Hedge
Ahrefs, Jul 2025	~76%	Earlier detection. Do not treat as current law
Ahrefs, Mar 2026	~38%	Larger sample. Methodology changed
BrightEdge, Feb 2026 (as reported)	~17%	Different panel, different method

What matters more for citation selection once you are eligible: passage extractability, topical authority across fan-out sub-queries, and the trust filters Google describes at a product level. Internals remain opaque.

Google’s own AI Overviews and AI Mode PDF describes AI Mode issuing multiple related searches concurrently across subtopics and data sources. Search Central says both Overviews and AI Mode may use that technique, and that the two surfaces may use different models — so their links will differ. Passage work for Overviews is the job of the citation spoke. This page’s job is to stop you from treating “we rank #3” as “we will be cited.”

Should you chase Copilot separately?

Usually not as a fourth religion. Microsoft Copilot sits in the same broader Microsoft and OpenAI retrieval neighborhood as Bing-linked experiences. Run a small Copilot spot-check if your buyers live in Microsoft 365. Do not invent a separate content calendar for Copilot until the ChatGPT plus Bing eligibility work is done and the panel shows a unique gap.

Situation	What to do
Buyers live in Microsoft 365 and mention Copilot in calls	Add 10 Copilot prompts to the monthly panel
Nobody mentions Copilot	Skip the fourth calendar
Copilot answers match ChatGPT on your money prompts	Fold it into the ChatGPT workstream
Copilot invents different facts than ChatGPT	Fix the entity sheet first. Then decide if Copilot is a real surface

Copilot is a spot-check, not a department.

How should you split a quarterly roadmap across engines?

Pick one priority from the buyer decision tree. Spend most of the quarter on shared baseline plus that engine. Keep a monthly panel on the others. Re-rank priority each quarter from CRM plus panel data.

Month	Shared	Priority engine	Secondary
1	Fact sheet, schema, five answer-first rewrites	Deep work on #1 engine from the tree	Baseline log on the other two
2	Cluster spokes plus corroboration outreach	Citation-gap fixes for #1	One Overview or chat experiment on #2
3	Measurement review. Prune losers	Double down or rotate priority	Keep the thin baseline

Cap engine-specific experiments at about 30% of the quarter so the baseline does not rot.

Budget leak	What it looks like	Cut it
Three full “AEO programs”	Three calendars, one exhausted writer	One baseline, one priority
Reddit sprint with no buyer signal	Founder saw a Perplexity screenshot	Put Reddit under corroboration, not under the homepage
Copilot workshop before Bing eligibility	Fourth religion	Spot-check after ChatGPT hygiene
Tooling before a panel	Buying a citation dashboard with no prompts	30 prompts first. Software second

If you cannot name the priority engine in one sentence, you do not have a roadmap. You have a mood.

What “good enough” looks like on engines you are not prioritizing:

• Monthly panel (same prompts) with pass/fail on accuracy
• No blocking of relevant crawlers without a written reason
• About, offer, and pricing pages remain extractable
• Critical hallucinations queued within one week

“Good enough” is not “ignore forever.” It is instrumented neglect.

Baseline item	Pass	Fail
Monthly panel	Same 30 prompts, dated log, three surfaces	Ad-hoc screenshots in Slack
Crawl sanity	Relevant search bots allowed on money URLs	A 2023 “block AI” robots.txt still shipping
Extractability	First 80 words state the offer or the answer	Hero slogan, then three screens of memoir
Hallucination SLA	Brand-fact errors queued inside seven days	“We’ll get to it next quarter”
CRM tag	“source: ChatGPT mention” (or Google / Perplexity) on new deals	Attribution is a vibes field

A baseline that is not logged is not a baseline. It is a story you tell yourself.

Failure mode: optimizing for the loudest demo

What breaks: a founder sees a viral Perplexity screenshot and redirects the entire content team for a quarter while every closed-won deal still starts on Google.

What it costs: missed Overview citations on money queries, plus a demoralized SEO lead, plus a Reddit campaign that reads like astroturf.

What you do instead: attach engine priority to CRM tags (“source: ChatGPT mention”) for 30 days, then re-rank the roadmap.

Loud demo	Quiet reality	Correction
“Perplexity cited a competitor’s Reddit thread”	Your last 20 deals came from Google how-tos	Keep Perplexity on the baseline. Finish Overview extractability
“ChatGPT named three vendors and we were missing”	Buyers still Google the shortlist before they book	Fix ChatGPT eligibility and keep Search Console
“We rank #2, so Overviews should cite us”	Ahrefs’ 2026 cut says most citations sit outside the top 10	Rewrite the passage. Do not buy more links for vanity rank
“Block all AI bots for safety”	You opted out of the surfaces you are paying to “optimize”	Split training opt-out from search opt-out

The demo is a screenshot. The business is a CRM.

How do you design a panel that forces an honest priority?

Do not run twenty vanity brand prompts and call it strategy. Build the panel like a sales-funnel mirror.

Prompt class	Example shape	Why it decides priority
Recommendation	“best [category] for [ICP]”	Shows who gets named
Comparison	“[you] vs [competitor]”	Shows claim accuracy
How-to / criteria	“how to choose a [vendor]”	Shows citeable method pages
Brand	“[your brand] pricing / founded”	Shows hallucination risk
Local (if relevant)	“[service] near [city]”	Forces Overview and local weight

Score each engine on citation rate, mention rate, and accuracy fails. Multiply by a rough deal-influence weight from sales interviews. The product of those numbers is your priority — not a conference keynote.

1. Freeze 30 prompts. Do not add “just one more” mid-test.
2. Run all three surfaces the same week. Search on in ChatGPT. Default Focus in Perplexity unless your buyers use another mode.
3. Log citation URLs, mention (yes/no), and factual errors against your fact sheet.
4. Weight by deal influence from ten sales calls, not from your own usage.
5. Re-run monthly. A one-week spike is weather. A quarter is climate.

If you want the measurement method written as an operating procedure, that is a different spoke. This page only needs the panel to be honest enough to pick an engine.

What can Semrush (and peers) tell you — and what can they not?

Semrush-class tools help you find the classical SERP and competitor URLs that feed Google surfaces. They do not replace sitting in ChatGPT and Perplexity with your panel.

Semrush’s own AI Mode comparison study (5,000 keywords, 150k+ citations) is useful as a category weather report: Reddit showed up as a leading citation source across the LLMs they studied, and overlap with Google’s top 10 was incomplete. Their later most-cited domains cut showed ChatGPT’s Reddit and Wikipedia share dropping hard in September 2025. That is the point. The weather moves. Your panel has to move with it.

Use SEO suites for:

• Query discovery around money intents
• Competitor content that already ranks
• Technical indexation clues

Do not use them as a fake AI Overview citation oracle. Log the Overview yourself on the queries that matter.

Question	Tooling can help	You still have to do this yourself
Who ranks on Google for the money query?	Yes	Confirm the live SERP, not a stale export
Did an Overview appear today?	Sometimes	Screenshot and note the cited URLs
Did ChatGPT search run?	Rarely	Look at the Sources panel
Did Perplexity cite you?	Sometimes	Open the numbered citations
Did this influence a deal?	No	CRM plus sales notes

A dashboard that cannot tell you whether a buyer used the engine is a reporting layer, not a priority engine.

Write for the surface’s quotation habit, not for a generic “AI-ready” voice.

Surface	How sources show up	Page shape that survives
ChatGPT	Chips and a Sources panel when search ran. Many answers still cite nothing	Shortlistable criteria. Named entities. Facts that stay true if search never fires
Perplexity	Numbered inline citations as the product	Stats with dates. Tables a reader can verify. Pages worth clicking from a footnote
AI Overviews	A handful of supporting links on a short synthesis	40–80 word answer blocks. Steps and tables. Fan-out sub-questions covered for real

• First 80 words can stand alone if a model lifts them
• Numbers have dates or sources
• Comparison pages name criteria, not slogans
• Local pages agree with GBP on name, address, phone, and hours
• You did not ship a different “AI version” of the page that humans never see

Google’s AI-features guidance is people-first content that is indexed and snippet-eligible. Perplexity’s product is a cited answer. ChatGPT’s product is a conversation that sometimes grows sources. One page can serve all three if it is extractable. Three “AI variants” of the same URL is how you get a mess.

What does a first-week operator pass look like?

Do this before you hire a “GEO agency” or buy another dashboard.

1. Pull ten closed-won notes. Tag the discovery engine. If the notes are empty, fix CRM this week and stop guessing.
2. Freeze 30 prompts that mirror those deals.
3. Run ChatGPT (search on), Perplexity (default Focus), and Google (Overview present or not) on the same day.
4. Check robots and WAF for OAI-SearchBot, PerplexityBot, and Googlebot on the five money URLs.
5. Rewrite the five money URLs so the first answer is a sentence a stranger can repeat.
6. Pick one priority engine from the decision tree. Write it at the top of the quarter doc.
7. Schedule the next panel in 30 days. Put the hallucination SLA on the same calendar.

Day	Output
1	CRM tags plus the 30-prompt list
2	Three-surface log (citation, mention, errors)
3	Bot and WAF pass on money URLs
4–5	Five answer-first rewrites
5	Priority sentence plus the 30% experiment cap

If day two shows Google carrying the deals and ChatGPT hallucinating your price, you do not have a Perplexity problem. You have an Overview-plus-fact-sheet problem. Ship that.

FAQ

Does ChatGPT depend on Bing’s index?

When ChatGPT search runs, OpenAI documents partnerships with search providers and names Bing in that context. That is not the same as “every answer is Bing-only,” and training memory still answers many prompts without live retrieval. Keep Bing eligibility healthy. Do not abandon Google.

Why does Perplexity cite Reddit so often?

Perplexity is retrieval-first and citation-dense. Third-party studies repeatedly find Reddit among its top cited domains, and Focus Modes can emphasize community sources. Percentages vary by study and by month. Treat Reddit as a real corroboration surface, not a spam target.

Do AI Overviews require traditional Google rank?

No. Rank helps eligibility and still wins clicks when Overviews do not appear, but citation selection can pull passages from outside the organic top 10. Optimize extractable passages and topical depth, not position vanity alone.

Should I chase Copilot separately?

Only after ChatGPT and Bing eligibility and a panel show a distinct Copilot gap for your buyers. Most teams can fold Copilot into a monthly spot-check instead of a fourth content program.

How do I split a quarterly roadmap across engines?

Pick one priority from the buyer decision tree, spend most of the quarter on shared baseline plus that engine, and keep a monthly panel on the others. Re-rank priority each quarter from CRM and panel data.

What is “good enough” baseline on engines I’m not prioritizing?

Monthly accuracy checks, crawl sanity, extractable money pages, and a one-week SLA on brand hallucinations. Instrumented neglect beats unmeasured panic.

CTA

Pick the engine your buyers already open — then instrument the rest.

Lane overview: /visibility. Need a prioritized panel and engine roadmap? Start a visibility audit.