Search? Still doesn’t work

It is 2023 and the topic of search is making the headlines again. After incremental improvements, even public beta of useless conversation with a machine is portrayed as a quantum leap forward.

Now the question for you: Is this the best search can offer? What else should we expect from a search?

Here is my take on the sad state of the search industry. After 30+ years of search development, this is what we got.

Let's pick a term: 'SEO expert' and enter it into Google. It returns 160,000,000 results. First two hits are paid links, then there is a top link for that topic, followed by similar questions asked by other people with more website links. Then there is a list of three businesses in my vicinity which fit the search criteria and the more links, more ads and then, a line with 6 pictures of SEO experts.

Doing the same thing on Bing brings 'only' 1,600,000 results with links to websites at the top, hard to notice ads at the bottom and links to videos (ironically from YouTube) on the right side combined with 'other people searched for'.

Where is the problem?

Let's start with - I had to describe what I am seeing, I can't share the search result with you.

Rather than posting here a link to my search where you would see identical content, I would have to copy link by link to an email and send it to you.

There is no group search function where a team can work on and refine a search criteria. Two companies with online collaboration tools can't even do that. If I perform the same search an hour, day or week later, how can I identify which content  is new or different? You can't even save the search query or its results.

Next, the results. The relevance of the result is indicated by the headline, a few keywords and 2 to 3 lines of text with highlighted keywords from the search query. It is up to you to start clicking on the links and identify relevant content.

First link? Not it. Second, an interesting paragraph. Third link, a few interesting bits. Fourth link, not even close. There is no feedback loop back to the search engine to share how relevant the link is to your query. You can't identify the relevant parts and as a result get better, to you more relevant links.

Going back to the search query: SEO expert. True, it was very short and with very little context. I would still think that the word 'expert' implied that I was looking for an expert in the art (or black magic) of SEO.

Google had 6 images of SEO experts at the bottom. Trying to identify the experts. The first one is Brian Dean from Backlinko and the text snippet informs me that '...Brian's SEO knowledge is insane. If you want higher rankings, you need to read his stuff – he's the Unicorn among a sea of donkey SEOs....' As you can see, researching the rest is a waste of time.  They are just the donkeys of SEO (Note: true experts talk about other experts with disdain).

The point here? Sometimes you want to just do a quick read of a subject area. But sometimes you want to talk directly to the subject matter expert. The inability of the search engines to identify a subject matter expert in the context of your query is surprising. It is especially shameful for Bing by Microsoft. This is the same company which bought LinkedIn, which describes itself as 'the world's largest professional network on the internet.' By now, you would expect LinkedIn/Microsoft to include the button 'talk to the expert' and become the middleman in the financial transaction between the question & answer.

So, here you go. Few examples of the sad state of the search industry.

We are led to believe that responding to our query with about 163,000,000 results in 0.46 seconds is better than the results itself. We get drawn into hysteria about conversing with the Language (not Knowledge) Model system as the ultimate in search technology. But we are nowhere near able to interact with a search engine to find our best result or to find the best expert for us.

Despite the billions of dollars available to both companies, their access to infrastructure and ability to collect zettabytes of data, employing thousands of data scientists and researchers, they are more interested in the ad revenue and marketing buzz than in the real innovation.

The recurrent pattern? Companies get so big that the people in them forget that innovation was the source of their success. Don’t believe me? Search for it.