Sharing user intent data creates trillions in value.
Keyword data was already transforming the web—AdWords formalized the feedback loop and monetized it with auctions.
Keyword data came first. AdWords monetized it.
➜ Early search engines (AltaVista, Yahoo, Lycos, Excite) used keyword-based algorithms to index and organize the web
➜ 1998: Google Search launched with superior keyword relevance algorithms
➜ User search behavior was already revealing market intent and demand patterns
The insight was already there: Search queries = User intent = Market intelligence
✓ The Good Part: AdWords formalized sharing keyword performance data with businesses (impressions, clicks, conversions, search volume)
✗ The Bad Part: Wrapped it in an auction-based extraction system—pay-per-click, bidding wars, gatekeeping by wallet size
AdWords didn't invent the feedback loop—it monetized it and formalized it.
By giving businesses access to keyword data (what users were searching for, how often, what converted), Google created a feedback loop that helped businesses build better products and marketing.
But they charged a toll for every interaction. That was the extraction layer.
Why AdWords actually worked
Users searched with intent
Real people looking for real solutions
AdWords fed search behavior data to businesses
Market intelligence on what people actually wanted
Businesses built better products
Products that actually matched market demand
Better product-market fit
Users got what they actually wanted
Loop repeats infinitely
Continuous improvement for everyone
This feedback loop created trillions of dollars in economic value.
But the extraction system meant small businesses had to pay Google just to be found. The mechanism worked. The business model shifted all risk to the front of the transaction—you paid whether or not the customer converted. We accepted it because there was no alternative, but it was a high-friction, high-cost way to access market intelligence.
Closed LLM systems are breaking the loop
User prompt data is hidden from businesses. The most valuable signal about user intent is locked away inside closed LLM systems.
No feedback loop exists. Businesses can't see what users are asking for, so they can't build better products to meet that demand.
The open web is dying. Without access to user intent data, the virtuous cycle that made the internet thrive is being destroyed.
| Channel | Avg. Conversion Rate | Business Insight | Cost Model |
|---|---|---|---|
|
💰
PPC (AdWords Era)
|
2-5% | ✓ Full Data |
Pay per click (High friction) |
|
🔍
Organic SEO
|
0.5-2% | ~ Limited |
"Free" (SEO investment) |
|
🤖
AI/LLM Systems
|
~0%
(Unmeasurable)
|
✗ Zero |
??? (No pathway) |
The trend is clear: As the web fragments and AI intermediates, conversion rates plummet. Businesses lose visibility, users get generic answers, and the feedback loop breaks completely.
* Industry averages vary by sector. PPC and SEO rates based on standard ecommerce benchmarks (2020-2024). AI/LLM rates unmeasurable due to lack of direct transaction pathways.
AdWords was flawed—an extraction machine masquerading as infrastructure. But at least businesses got something (user intent data) for their money.
Now closed LLMs are destroying even the feedback loop. No user intent data. No intelligence. Just silence.
We're left with the worst possible outcome: dying visibility AND no market intelligence.
Why closed systems destroy American business
The AI shows three products on screen.
User sees a simple comparison table.
The AI rewords all the brand messaging.
Your carefully crafted voice disappears into generic AI prose.
There is NO opportunity to build brand.
No relationship. No trust. No differentiation.
RESULT: Price becomes the ONLY determining factor.
You might as well hang a placard on a factory in China.
There is no opportunity for American business to operate in a price-only environment. It will not work.
American business operates on BRAND. We manufacture nothing.
We compete on innovation, execution cycles, customer relationships, and brand trust. Take those away, and you've taken away the only competitive advantages American businesses have.
Restoring the feedback loop for the AI era
OWAQA creates a structured way for businesses to see what users are asking for—just like AdWords did 23 years ago. User intent becomes visible again.
Armed with intent data, businesses can create products that meet actual market demand at a higher level. Innovation accelerates because the signal is clear.
Businesses speak directly to users through structured APIs. Your brand messaging stays intact. Relationships can be built. Trust can be earned.
User intent → Business intelligence → Better products → Better product-market fit → Repeat forever. The virtuous cycle returns.
OWAQA takes the ONE good mechanism from AdWords (the feedback loop) and removes the extraction.
✓ Keep: User intent flows to businesses
✓ Keep: Businesses build better products
✓ Keep: Users get better product-market fit
✗ Remove: Pay-per-click extraction
✗ Remove: Bidding wars for visibility
✗ Remove: Gatekeeping by wallet size
What they must give up. What they get in return.
This is the painful part. This is what has to happen:
✗ Share User Prompt Data: LLMs must open the black box and share aggregated user intent insights with businesses. Not individual prompts—but the patterns, the questions, the market signals.
✗ Give Up Control: This means loosening the grip on the closed garden. It means transparency about what users are actually asking for.
✗ Enable Direct Business Voice: LLMs must allow businesses to speak directly through structured APIs, not reword everything through their own lens.
Yes, this is hard. Yes, it requires giving up some control. But here's what makes it worth it:
In exchange, LLMs get something they desperately need: high-quality training data at scale.
🎯 Thousands of Curated Content Variations Per Product
Businesses using OWAQA will generate 1,000+ human-edited, proofread, and approved content pieces for every product. Each variation is tailored to specific user contexts, personas, and use cases.
✅ Quality Over Quantity
This isn't scraped web junk. This is business-approved, professionally written, context-aware content that businesses have a direct incentive to keep current, accurate, and high-quality.
📈 Continuous Improvement
Because businesses see what users are asking for (via shared prompt insights), they'll continuously refine their content. This creates a virtuous cycle of improving training data that gets better over time.
🏆 Gold for Future Model Training
LLM providers can license this structured, high-quality, human-curated content for future model training. This is exponentially more valuable than scraping random websites and hoping for the best.
The trade: Give businesses user intent insights → Get oodles of training-quality data in return.
Right now, LLMs scrape the web for mediocre content, get sued, alienate businesses, and poison their own training data with AI-generated slop.
OWAQA offers a sustainable alternative: structured, curated, business-approved content at massive scale.
LLMs just have to open the door and share the prompts.
A sustainable ecosystem where everyone wins
With access to user intent data and the ability to maintain their brand voice, businesses can innovate, compete, and build lasting relationships with customers. American business survives and thrives.
LLMs get access to high-quality, human-edited training data. Businesses create thousands of product variations, all proofed and accurate. Everyone's AI gets better.
Better product-market fit. Authentic brand relationships. Transparent information. Products that actually match their specific needs. Higher satisfaction across the board.
Just like 23 years ago, we have a chance to build the right foundation for the next era of the internet.
We have a chance to build the right infrastructure for the AI era—one that creates value for businesses, AI systems, and users alike.
This isn't about fighting the old system. It's about establishing a fair, useful protocol that benefits everyone. Just like keyword data proved its value 25+ years ago, structured user intent data will prove its value again.