Google is great at answering questions that have objective answers, like “how many billionaires are there in the world” or “what is the population of Iceland”? It’s pretty bad at answering questions that require contextual judgment, like “What do NFT collectors think about NFTs?”
Now there are tools like Notion, Airtable, and Readwise where people bring together content and resources to revive well-curated networks. But most of these sites currently operate alone — hidden in private or semi-private corners of the internet, fragmented, poorly indexed, and unavailable to the public. We haven’t figured out how to make them “multiplayer”. Where we make them public and collaborative – here’s a great example – these projects tend to be short lived and poorly maintained.
The stated mission of a company worth nearly $2 trillion is to “organize the world’s information,” but the Internet remains poorly organized. Or, to put it another way, in a world of infinite information, it is no longer enough to simply organize the information in the world. It becomes important to organize trusted information in the world.
How did we get to this point?
It’s hard to believe, but once Google got up and running, one of its main problems was that there wasn’t much to see online. It’s no use having a great search engine if someone types in “how to grow herbs in the garden?” and the answer doesn’t exist online. With the advent of Google AdWords, it became profitable to put out low-quality content to act as informative and populate Google’s search engine results. The end result is that the sites that rank high in Google are not necessarily the highest quality ones, but those that put the most effort into SEO. What started as a well-intentioned way of organizing the world’s information has become a business that focuses most of its resources on monetizing clicks to support advertisers, rather than focusing on providing people with trustworthy search results.
The question is very different now than it was ten years ago, not what to read/buy/eat/see, but to find the best thing to read/buy/eat/see/etc with my limited time and attention.
Bold teams, like DuckDuckGo and Neeva, are trying to compete head-to-head with Google by building massive horizontal search engines. Instead of crawling and indexing things their own way, they sit on top of existing data sources, positioning themselves as a privacy-focused alternative to Google. But protecting privacy isn’t a compelling reason to leave Google. For the vast majority of people, allowing them to “control their own data” is not a selling point, especially if that entails paying for something they’re used to getting for free.
I believe the opportunity in search is not to attack Google head-on with a massive, one-size-fits-all lateral aggregator, but to build boutique search engines that index, curate, and organize things in new ways.
Vertical Search Aggregator
Google is a great example of how the internet achieves scale and speed: every page on the web can be returned in an instant. Increasingly, however, we are seeing that scale at odds with a fundamental human need: relevance. Someone trying to find the best freelance designer, or the best sushi restaurant, or buy the best NFT, will not find the answer on Google.
No search architecture works universally across all categories. It’s hard to imagine wanting to search for recipes and search for freelancers with the same user experience. Google’s products start and end with a search bar, trading functionality for simplicity, and vertical search players like Yelp, Expedia, Zillow, and Behance have emerged to fill functionality and functionality with their industry-specific structured data. correlation gap. Users have strong opinions on how to organize information, so they favor filter functionality, and vertical search aggregators have distinct advantages that horizontal software cannot achieve.
But here, too, the relevance depends on the sociology of the moment. For example, in Behance, an online creative community, school and location are prominently featured as filters—meaning where you live and where you go to school is an important indicator of the quality of your design portfolio. In a world where talent is decoupled from credentialism and geography, these filters are losing relevance.
As this demand trend develops, new indexing methods and superficial innovations emerge. If Behance were designed today, I don’t think “location” nor “school” would be a filter.
On Yelp, a search for “electricians in Miami” starts with a page titled “10 Best Electricians in Miami, FL,” and the text below shows that most of these results are paid promotions.
When you monetize through advertising, curation gives way to advertisers, as there is less digital space available to curate your own recommendations. So these platforms end up making ethically dubious design choices that create a huge trust gap in user psychology.
Plus, in vertical search aggregators like Yelp, Zillow, LinkedIn, and Behance, anyone can have a profile. The combination of irrelevant filters, ad-based business models, and unfettered supply overwhelms consumers and makes it difficult for users to find what they’re looking for on these platforms.
Vertical search aggregators come into play when you know exactly what you want. But knowing what you want is often not the starting point, which creates an opportunity to help overwhelmed consumers better discover and curate down the funnel.
We live in the information age, and it’s become a popular saying that we need “curators” to help us sort through messy information. But so far, the conversation around curation has focused too much on content and not enough on structure. We seem to have embraced the curator’s job of providing product reviews, linked lists or song recommendations – all in a linear structure and chronological order, designed to surface ideas from the past 24 hours, rather than accumulate and Demonstrate knowledge as required.
As a side hustle, sending a daily email with Alibaba’s top five products feels fun and gimmicky, but it doesn’t help when you’re trying to find the best crib for your baby. Inevitably, you’ll want a way to search the mastermind’s archives.
When it comes to sharing bit-by-bit, isolated snippets in a feed-like architecture, curation is mostly about entertainment, not utility. It is not wrong to say that there is a market for this kind of planning. However, what people overlook is that this market has been taken over by Twitter, Facebook and TikTok.
The curation offered by these entertainment giants demands our attention, but they do not offer curation on demand. The opportunity lies in shifting the curated content feed from its never-ending present direction to a more purposeful interface. People should be able to find whatever content they want on their own terms, rather than being constrained by a curator to decide when to post.
Boutique search engines are high-level strategies
All curation grows until it needs to be searched, and all searches grow until it needs curation. —Ben Evans
Applying Ben Evans’ framework, it is clear that while vertical search players have grown too large to require curation, curated feeds have grown too long to browse, requiring search and structured data. The solution is better search and better curation, all wrapped up in a better business model — a combination of what I call a boutique search engine.
Searchable, curated interfaces will help us move from ephemeral, time-bound feeds into contextual, highly informative, trustworthy knowledge spaces. Because the searchable interface is densely linked, explorers can follow multiple leads through content rather than being dumped into a single “recent” feed.
With such a close relationship between curation and search, the real question is not if you need curation or search, but when, and how:
- Spotify doesn’t curate which songs make it to their platform. Instead, it finds endless ways to discover and search its music library from across the music world, including a mix of human curation (via playlists curated by its in-house curation team and users) and algorithms (like Discover Weekly).
- Wirecutter does not review every product. It manually curates top products, then uses search and other discovery tools to help you find what you need.
- Thingtesting doesn’t automatically scour the Internet for all consumer packaged goods brands. Someone on its team or community is desperate to add a brand to the database.
- If you’ve been searching On Deck’s membership database, you know that everyone has applied, been vetted, and paid a fee to participate in the program.
- If you’re reading the transcripts on Tegus, you know they come from experts handpicked by its team.
In all these examples, the value lies in what they exclude and what they include. Supply-side friction is what creates the value of information.
On top of the information value, these companies have built powerful search engines. For example, OnDeck has built an opinion map that lets you spot talent in a unique way. For example, you can filter by people with “software engineering” skills whose current status is “open to new ideas”. As a founder looking for engineering talent, I would always choose this curated dataset over LinkedIn’s dataset.
Unlike vertical search aggregators, boutique search engines feel less like the Yellow Pages and more like texting friends for recommendations. They limit supply, which is the basis of their greatest moat: trust. Importantly, boutique search engines have also introduced new business models that do not rely on advertising.
The problem remains because the search is difficult
Building a boutique search engine requires countless nuanced product choices. Getting the right mix of curation, search, algorithms and business models will likely prove to be very difficult and very rewarding. Below is a non-exhaustive list of questions we thought about as we built Startupy, our attempt to build a boutique search engine with qualitative insights.
If the value proposition is that the signal is greater than the noise, how do you scale the signal?
Time and time again, curation sites fall into an existential trap. They start with high-quality, curated recommendations. As they grow, they use crowdsourcing to scale, often scraping to fill in the gaps. Over time, the content went from good to good. At this point, vertical search integrators like Yelp offer more utility. For example, Yahoo became too big to browse, lost its signal strength, and reached the point where Google is better. The line between curators, compilers, and catalogers is thin, with a natural invisible asymptote—more data with diminishing returns over time.
What is the business model of this new wave of search engines?
On the surface, vertical search engines are simple — content is supply, and eyeballs are demand. But the last wave of vertical search engines was built on an ad-based business model, making things even trickier. In an advertising-driven marketplace, the eyeball is on the supply side. Their attention is what the demand side — the advertiser — wants. The downside of this ad-driven model is that advertisers and content producers are competing for the same attention, which is why these sites end up feeling like marketing blogs.
That’s why subscriptions present an opportunity. Subscriptions simplify network effects into two: content as supply and paying viewers as demand. But subscriptions by themselves aren’t a panacea, especially when usage isn’t frequent enough. How long do you need to find a freelancer? an investor? If usage isn’t frequent enough, the utility of a search engine won’t translate into a sustainable business model, and you’ll have to come up with your own “come for search, stay for something else” flavor.
Also, as my friend Joey pointed out in this post, any product you spend a lot of time using in incognito mode has a pretty big UX issue. How many New York Times accounts did you create before finally succumbing to the paywall? In today’s subscription model, customers have no real incentive to help the platform grow. Emerging token-based business models show early promise. Startups can overcome the cold start problem by handing ownership to stakeholders and allowing users to benefit from future growth.
While fascinating, the playbook for the tokenized business model has yet to emerge. I suspect this will change in the next few years, and I’m excited to improve my understanding of the issue.
Who will plan the planner?
Platforms like Twitter delegate this responsibility to their users, who must go through a long and arduous process of following large numbers of people, culminating in a self-curated timeline that mimics their interests. Some people centralize their planning — at OnDeck, you believe they’re doing the job of choosing who can join their network. Others, however, stay away from curation in favor of more traditional crowdsourcing. This range is wide.
First, how did you find the search engine?
At the beginning of this article, I argued that Google needed to be unchained. It’s a catchy title, but in fact, I believe that Google will be an important part of your engine being discovered first before you can build habitual recall into your product. Zillow and Airbnb are examples of search companies that enjoy a lot of direct traffic, but SEO was an important part of their early strategy. By being the first companies to create authority pages for houses, they benefited from the land grab of SEO, which has since been hard to replace.
We are far from realizing the grand vision of the Internet. The human knowledge item today is a vast ocean of fleeting and fragmented information and ideas, the best sources of which are nearly impossible to find. We need more interfaces, and the point of view of these interfaces is what information is missing, how it needs to be organized, and at what point in the value chain planning has to be done is also worth thinking about.
Posted by:CoinYuppie，Reprinted with attribution to:https://coinyuppie.com/a16z-the-next-generation-business-model-for-search-engines-is-boutique-search/
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