Boutique Search Engines

What will it take to dethrone Google Search? Aside from privacy-focused alternatives like DuckDuckGo, we haven’t seen much outside innovation in the search field.

Google is great at answering questions with an objective answer, like “# of billionaires in the world” or “What is the population of Iceland?” It’s pretty bad at answering questions that require judgment and context like “What do NFT collectors think about NFTs?” – Sari Azout

When you search subjective information on Google, you’re not receiving the best content or the best ideas. You’re receiving the content that was best positioned from an SEO (Search Engine Optimization) perspective or the content that paid for placement.

The solution could be in niché search engines that are ultra-specific to a topic and curated by their users. Sari Azout calls them Boutique Search Engines.

The Tech

The purpose of a Boutique Search Engine is to curate the best information without the inherent flaws of an ad-based, SEO-dependent model. There’s so much great information that is hidden deep within hour-long podcasts, on personal blogs, in one-off Tweets, in chat-based communities, etc. But this information is rarely parsed by Google Search because it isn’t packaged into an article with great SEO.

Boutique Search Engines combat this through human-curation and a system for ranking/weighting this information whether through peer reviews, status markers, or even an algorithm. (Personally, I think this is a place where Token Curated Registries could thrive.)

Boutique Search Engines can’t just be curated feeds, though, because they quickly turn into never-ending listicles that are hard to navigate. Knowledge Graphs are still needed to parse this information and make it searchable. (What is a Knowledge Graph?)

The business model of Boutique Search Engine will either be a pay-per-search (likely through tokens) or subscription. But definitely not an ad model, as this is the problem we’re solving.

Further reading on Boutique Search Engines:

• Sari Azout’s vision for Boutique Search Engines
• Hacker News discussion on Boutique Search Engines
• How web3 models will help usher in this new era of information share/search

The Stats

SimilarWeb data shows that Google tops the global search engine market share at 90.63%, with Yahoo following at 3.25%, Bing at 2.88%, Yandex at 0.45%, Naver at 0.44%, and other search engines at 2.34%.

The Use Cases

Below are some of examples of Boutique Search Engines in operation today:

• Startupy – Startup insights created, curated, and indexed by founders, funders, thinkers, and operators.
• GummySearch – Customer research via Reddit. They organize and curate opinions on Reddit to help you discover problems to solve, sentiment on current solutions, and people who want to buy your product.
• True People Search – Find any person via a name, phone number, or address.
• Thingtesting – Brand search index to research and review internet-born brands.
• Tegus – Research engine for institutional investors which aggregates and indexes public financial data, qualitative customer insights, investors call transcripts, and other pertinent company data.

My Take

I like the idea of Boutique Search Engines because it separates information share into nichés and thus surfaces the people that are most thought-provoking and dedicated to that niché. It’s very much like subReddit communities but with a search functionality (Reddit search isn’t that great).

The question is how many Boutique Search Engines will be too much, though? At what point does search fragmentation lead to a worse user-experrience?

I don’t think that’s something we must worry about right this moment. We can always build a search engine for Boutique Search Engines.

Ultimately, when you create something that is one size fits all you actually end up with “one size fits no one.” And I think we’ve just accepted the one size that Google has offered us.