Intention is a state of mind. A driving force behind human behavior powered by belief, desire and goal. It has been studied much in such disciplines as philosophy and psychology. And now, intent computing is a growing area of research, particularly in the field of digital marketing. It is based on predicting the probability of a specific intention held by an end user by applying machine learning and data mining methods.
Search engines have the hugely difficult job of having to process end users’ information need in the form of queries entered into an oblong box on a web page, by the billion. And a major part of the problem they have is that end users have no real idea how to solidly communicate their information needs. This is not a skill, which is generally taught in school (limited subjects, such as library and information science, law, and chemistry, perhaps). So this is why information systems have to be designed to elicit information from users rather than expecting the end user to volunteer it. End users simply have neither the knowledge, nor the desire to devote much time or energy to this. And the success of trying to determine intent behind a query, is crucial to the success of search engines, such as Google and Bing.
Web queries, generally, are very short. Numbers differ from study to study, but consistently we discover that most queries are still around three terms long. And, of course, the topics of these queries cover the length and breadth of all human interests, such as health, entertainment, commerce, and the number one subject of them all… Take a guess anyone? Yep. Sex.
Given that I’ve already touched on the stumbling block of the search engine/end-user-as-a-dumbass situation, when it comes to actually entering a query, we should also take into consideration that search engines, even though complaining about the problem of short queries initially, discouraged longer queries. I’ll write another column on how search engines have transitioned from needing an exact match between terms in the query and also in the link anchor text, so as not to exclude equally relevant results that may not actually contain the terms. Many times I see a result that is totally relevant to the query, and yet the query terms don’t actually appear anywhere on the page.
I’m very proud to have been one of the first people in the online marketing world to have interviewed Andrei Broder, distinguished scientist at Google (although he was chief scientist at Alta Vista at the time of the interview) following the publication of his seminal paper “A Taxonomy of Web Search” based around the “informational need” of the end user at search engines. He broke it down to three types of search behavior: Informational; Navigational; Transactional.
Broder’s original work has been expanded upon significantly, including a hierarchy of user goals. The “transactional” category is also known as “resource” category. A local type query also adds to understanding intent, and the stronger the “commercial” element, the stronger the intent to purchase is indicated. This is a strong signal as to whether or not to show ads, of course.
The last study related to query volume I had sight of, suggested that as much as 80 percent of queries at search engines fall into the “informational” category, while the rest are split fairly equally between “navigational” and “transactional” queries.
Ultimately, click-through curves provide a huge signal to search engines, when determining the intent behind a query. We know already that the top 10 results get the most clicks. But this is much more complex than how many times a particular result gets clicked on. There are many more clues given about intent by studying the percentage of click-through for the top ten ranked results. Each click-through represents the first result clicked by a different user entering the query.
Like many others in the digital marketing world, I firmly believe that, gradually, we are moving away from our current “attention economy” into a newer “intention economy.” It is well documented that we have access to more information and more resources than ever before. At the same time, the capacity for producing information now vastly exceeds the human capacity for processing it. The need to examine large quantities of information in such short spaces of time affects our decision-making processes. We suffer from information overload, difficulty, or impossibility of processing much of it, the irrelevance or non-importance of most of it, and lack of time to understand it. Plus, there are multiple sources containing the same information. Yes, this is a gift of the world wide web that just keeps giving.
It’s said that nearly everyone in the modern world is influenced, to some degree, by advertising and other forms of promotion. However, dramatic transformations in the way that we are served marketing media, and the way we consume media generally, is fundamentally changing the art and science of advertising and marketing. A recent survey quoted by Inc. Magazine stated that 70 percent of consumers want to learn about products through content as opposed to traditional ad methods.
We are moving forward into a whole new world of marketing communications. A world where one way mass media advertising is being replaced by a multitude of two way media channels. The marketer and the audience are both senders and receivers in what is becoming more of a digital marketing dialogue.
Audience intelligence, the real “big data” in the marketing world, is the fuel that will power what I’ve already referred to as the “intention economy.” The more we understand the end user (and the more they understand us, the marketer), the more relevant (and therefore more useful) we become to each other.
As co-author of “The Cluetrain Manifesto” and, more recently, “The Intention Economy” Doc Searls states, this new economy will outperform the attention economy that has shaped marketing and sales since the dawn of advertising. Customer intentions, well expressed and understood, will improve marketing and sales, because both will work with better information, and both will be spared the cost and effort wasted on guesses about what customers might want.
Perhaps my favorite quote from his recent book is: “The Intention Economy grows around buyers, not sellers. It leverages the simple fact that buyers are the first source of money, and that they come ready-made. You don’t need advertising to make them… The Intention Economy is about buyers finding sellers, not sellers finding (or “capturing”) buyers.”
Imagine, once you understand end user intent, the likelihood is, you’ll develop the appropriate content to satisfy that informational need. Here’s something that kind of sums it up. During a chat with my friend Avinash Kaushik, digital marketing evangelist at Google (it’s recorded if you want to view it, here), he sort of dismissed advertisers’ use of conventional demographics to target audience segments.
The short story goes something like this: “Imagine you’re targeting a demographic group that includes 80-year old females, and you’re trying to sell them wheelchairs. How do you know they want one? Now imagine if you knew something about their intent, like for instance, if you knew they had been online looking at the Apple store, you’d be selling them an iPad, not a wheelchair. That’s the difference: understanding INTENT!”
* Sponsored content in collaboration with Acronym.
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