SFMA is the San Francisco / Bay Area marketing agency for Mountain View companies that need website, SEO, AI visibility, paid ads, positioning, messaging, and conversion paths to produce qualified local demand.
Friday morning, 10:08 AM. The competitive map just updated. Three competitors raised in the last 30 days. Your category narrative is two months old. Your AI visibility audit shows zero citations.
The product is good. The team is technical. The narrative the company tells about itself was written before two of the three competitors existed.
By 10:24 the founder sends the message every AI-native team eventually sends. Are we losing the category.
Probably not yet. Definitely soon if nothing changes.
The market is being shaped right now. The companies that hold the buyer-question coverage hold the category.
AI visibility is not ranking work with new vocabulary. It is buyer recognition inside machines that summarize.
Mountain View AI-native teams hit this wall faster than other cities. The category is moving every week. The competitive set rewrites itself per quarter. The narrative window is short and the cost of being late is the category itself.
An AI Visibility Audit answers the question your team is too close to ask. Are we in the answer. If not, why. What does the 30-day fix look like.
$2,500 flat. 5 business days. Query-level audit. Citation gap. Schema readiness. 30-day priority list.
of the B2B buying journey is complete before the buyer ever contacts a vendor. The answer engine does most of the convincing.
Gartner · Future of B2B Sales · 2024
people on the average B2B buying committee, across 10-plus interactions. AI-native categories sell to all of them at once.
McKinsey · B2B Pulse · 2024
match rate between vendor self-description and buyer experience of the product. LLMs widen the gap when copy is generic.
TrustRadius · B2B Buying Disconnect · 2023
No invented benchmarks. Every number above traces to a publisher, a year, and a public URL in the citations section at the bottom of this page.
Because answer engines, not search engines, are the new buyer surface. The audit covers ChatGPT, Claude, Perplexity, Google AI Overviews, and Bing Copilot at query level, not at keyword level. That distinction matters at category-shaping speed.
Agencies execute. A marketing agency partner produces the document the agencies execute against. For a category-shaping window the document is the advantage point. Execution is downstream.
Yes. Mountain View signals AI-native operating altitude when the company actually sells into technical Bay Area and Silicon Valley buying groups.
A document the team executes against without the partner present. 14 business days. Category narrative, product narrative, ICP architecture, sales motion, 90-day plan. $7,500 flat. The sprint is structured to ship, not to recur.
Post-FAANG founders usually default to product-led growth and assume distribution will follow. ICONIQ Growth's 2024 cloud report shows the Series B teams that compound are the ones with disciplined sales efficiency, not the ones with the loudest product launches. ICONIQ Growth's 2023 SaaS benchmarks put median CAC payback at about 15 months, with elite teams under 12. The Positioning Sprint produces the document that aligns product-led distribution with a sales motion that actually closes.
Mountain View AI startups compete for the same buying committees Gartner described in 2024: about 70 percent of the journey done pre-vendor, plus the 10-person committee per McKinsey 2024. TrustRadius 2023 found only a 38 percent match between vendor self-description and buyer experience, and AI tools widen the gap when the website reads like every other AI company. The playbook is to write positioning specific enough that an LLM summarizing the company gets the category right, the wedge right, and the buyer right.
The strategic spine document. What every channel is supposed to prove.
Open the service →Go-to-market architecture for AI-native and applied-AI companies.
Open the service →Category narrative, product narrative, and ICP architecture.
Open the service →The page should explain who the offer is for, which buyer problem it addresses, and why a local operator should trust the strategy before adding spend.
Client-specific numbers stay private unless approved. Public proof is shown through method, source trail, offer fit, and the marketing review questions a serious buyer can inspect.
The page points the buyer to a fixed-scope marketing review, not an open-ended sales call. The document is the first deliverable.
No invented Bay Area benchmark. Every row below has a publisher, a year, and a public URL in the citations section below.
| Source | Year | Finding relevant to Mountain View AI-native teams |
|---|---|---|
| Gartner · Future of B2B Sales | 2024 | About 70 percent of the buying journey is complete before vendor contact. The answer engine carries the load. |
| ICONIQ · State of the Cloud | 2024 | Series B SaaS sales efficiency separates AI-native compounders from one-launch product spikes. |
| ICONIQ Growth · SaaS Benchmarks | 2023 | Median B2B SaaS CAC payback runs about 15 months. Elite under 12. Top performers 5 to 7. |
Mountain View buyers are used to technical depth and platform narratives. Marketing has to translate the product into a decision path the economic buyer can repeat.
The useful work is not more content by default. It is ICP selection, proof hierarchy, AI-search visibility, and conversion architecture around the strongest buying use case.
Use this page for AI-native, technical, and product-led companies that need the message to survive enterprise review.
Hold the answer before the category closes.
Start with the Marketing Strategy Review · $5,000 → Open the marketing review page firstUse this page when you are comparing San Francisco Bay Area marketing help for a Mountain View company with real pipeline pressure.
Decide whether the problem is local positioning, buyer proof, channel economics, website conversion, or the lack of a written 90-day plan.
Use the audit when answer engines miss, misdescribe, or fail to cite the company.
AI Visibility Audit →