Tailoring content to match search intent
First steps in optimizing content for intent have been taken but are they in the right direction?
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Content and online search have enjoyed a symbiotic relationship since the latter’s birth. Both face a big challenge today, and that is to ensure that content matches an online searcher’s intent. Or, for starters, the intent of a category of searchers.
The task of matching content with intent is not new. It would not be wrong to say it’s been there since search went online. But the urgency is being felt more now because of content explosion.
When one looks at the website traffic channels’ pie chart, online organic search is still number one, accounting for as much as 60% of the traffic. Much of that is from Google Search Engine, followed by other assorted engines such as Bing and DuckDuckGo. It is quickly followed by inorganic search as a traffic source.
Intent - what exactly is an internet surfer looking for when searching for a particular topic - is a science that search engine algorithms have yet to master. Not surprising because the computer software-driven search engines simply work on a “match the search word with a keyword” formula. It’s been trial and error so far, so to speak, although there’s certainly a method to the madness, which is, mating the search word(s) with the keyword(s) in the content indexed by the web crawlers. Helping along are search engine “allies” like tags, backlinks, headers and all those offline and online SEO tactics and tools. But figuring out (or near about) what exactly a human searcher wants when he types in a set of search words is like getting your hands on the holy grail of online search.
That’s why even today, you have search engine results pages (SERPs) that display outcomes that have no direct bearing on a searcher’s wants. Here’s an example: when you type in the words, “fruits of labor” in the search bar, the SERPs display everything: from a performance that goes by that name, to fruits grown in sunny California. While the idiom does feature on Page 1 of the SERP, the rest of the “wrong” results are due to a lack of the understanding of the searcher’s intent. In this case, it near-failed to understand that the searcher wanted, i.e. to only know about the idiom, and perhaps its usage.
Search engine ‘algos’ are evolving, getting more and more sophisticated with the passage of time. But even with artificial intelligence (AI) and machine learning (ML) technologies added to the mix, SERPs are only about 40% accurate today. The hope of search engine developers is that when AI, too, makes progress, the gap will finally be bridged.
For starters, right now, they are figuring out group “intent” before moving on to each individual searcher. Example: A group of shoe buyers. How are they different in their online search from a group of data scientists? Or, how does one category of sneaker buyers differ in its search from another group of floaters buyers? Only when a search engine can make sense of all this, and become sophisticated enough to differentiate can they then move on to becoming more granular - understanding the intent of an individual searcher. Which could be a pipe dream for now for the reasons enumerated below.
Search algos have to reach such a high level of savviness that they must be able to grasp the fact that even though two different searchers have keyed in the same set of search words, what they are looking out for are two different things altogether.
Here’s why it is such an uphill task for now: on average, Google alone processes over 40,000 search queries globally every second. That’s about 3.5 billion searches daily, and 1.2 trillion searches annually. Google alone has indexed hundreds of billions of webpages, and is well over 100,000,000 gigabytes in size.
They are now creating content that’s driven by search intent (trying to)
On an average, a searcher keys in 3 words in the search box. The content writer’s job, and that of the search engine, is to ensure that as far as possible, those 3 words get matched with the exact content the searcher wants, and ensure the latter walks away fully satisfied.
Because content and keywords have a collaborative relationship, to fine-tune the search for intent by search engine algorithms, content providers and SEO experts are being advised to develop content based “around the intent of a searcher”. But that’s easier said than done. As the first steps in this process, efforts are on to compartmentalize content as well as searcher purpose (plus other things), to ensure that the SERP matches the intent behind the search words to the best degree.
Experts have started talking about how web searches come in 4 broad types like (a) Informational (b) Navigational and so on. This exercise is essentially straitjacketing content in the “Go”, “Do” or “Know” categories. (You may refer to this excellent blog post by Ahrefs.com for a bird’s eye view on search intent.)
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Content providers and content marketers are being directed to write/develop content that will “fit” into one of these 4 categories. Digital marketers have started talking of how much of a searcher’s intent also aligns with his buying journey.
It’s the start of an experiment; one does have to begin somewhere. But search engines and content clients who are asking providers to develop content with “intent” at the back of their minds, are merely replicating the past. By compartmentalizing content into neat categories, they are once again resorting to the old formula of trying to match search words with keywords. Where is the matching of intent?
The problem is simple - a machine (computer program) is trying to gauge intent, a human trait. Take this as an example of search gone horribly wrong….when you key in the words, “What is intent?” in Google search engine, the first results are around “Intent in an Android Operating System”. The first two SERPs are all about intent as a computer coordinating activity and not intent as a human action.
That’s the whole point, isn’t it? For a machine to understand human intent, of a group or at an individual level, is a very long shot. It calls for far elaborate computing powers and computing “sense” than one that simply matches 2 with 2, i.e. complements a search word with an indexed piece of content. For now, based on certain industry-accepted tools, copywriters or writers can choose from some keywords and then bung them in a piece of content to make it fit in one of the 4 categories. An SEO expert based on experience, knowledge and science then tries to use certain words and phrases in the piece of content that he the expert thinks, will match intent or the search words.
Search is moving to long-tailed keywords, very much driven by intent. Search algorithms, too, are changing to accommodate intent. All that’s fine but the result today is still not anymore sophisticated as compared to a few years ago.
Also, it’s looking like becoming a chicken and an egg situation, i.e. what comes first, search or content? With much of the world’s content mapped (pre-search era content, most of it), search engines today have to deal with post-search era content, i.e. content which is also “SEO-optimized”. It’s all very fine to tell content providers to keep human readers first while developing content, but the truth is, like it or not, content is also being developed with search engines in mind. Content has to be marketed in order to be “discovered”, and what better way for that then (free) organic search. That’s why search words exist, so do keywords, and so do SEO experts.
To put content providers in the driver’s seat where intent is concerned is perhaps not the right approach. Those chaps are filling the pipeline, but the team developing web crawlers are the people who need to figure out the allotment of the fuel (content) at specific stations.
The ‘intent’ search example above is a classic illustration of this. Human intent was born millions of years before programming intent. Ideally, when one keys in, “What is intent?”, the SERP should first throw up answers related to human intent, yet, it threw up Android OS intent, instead. In this particular instance at least, that search engine clearly forgot the so-called golden rule, “Search/content by/for humans first”.