Digital marketers know how crucial it is to predict user intent whenever possible. Then, those professionals can adjust their online content so that it aligns with the intentions and is thereby maximally relevant to a site's visitors.
That's where content intelligence comes into the picture.
It involves using high-tech methods like big data analysis and artificial intelligence (AI) to see the full context of an individual piece of content.
What Could Content Intelligence Show?
When used effectively, content intelligence can reveal numerous useful things to marketers. For example, the insights gained could reveal which content a company should promote and the best ways to do it.
It could also shed light on which content they should update or share. Then, companies can rely on the learned information to shape their content strategies.
Here are some ways companies could begin depending on content intelligence or expand their current content intelligence practices.
Use AI Platforms to Determine Keyword Sentiment
Keyword sentiment is the ability to understand whether a word or phrase has negative or positive associations.
In February 2018, Bing showcased its use of intelligent keyword sentiment tools by giving people contrasting information about some topics. The company uses AI and deep learning networks to give people relevant information based on sentiment analysis and several other factors.
Some companies also use sentiment analysis and AI to find similar keywords to the ones dominated by competitors. Then, it's possible for less prominent companies to get their messages across without so much noise.
In one case study for the Food Water Wellness Foundation, an analysis was performed to see how audiences felt about the phrase "regenerative agriculture" versus "sustainable farming."
A marketing company working on behalf of that organization used AI and natural language processing analysis to achieve the same keyword sentiment for "regenerative agriculture" as for "sustainable farming." The latter phrase is more widely used, but content intelligence technologies allowed the organization to ensure that its online content achieved the desired results concerning sentiment.
Taking a similar approach could pay off if companies are struggling to determine which keywords will achieve the best results.
Deploy AI to Make Product Recommendations
When people shop in stores, they can directly communicate with salespeople and explain what they need, how much they're willing to spend and other factors, such as their favorite colors.
Then, those in-store employees tend to offer suggestions that match the parameters, thereby driving sales. Online shopping doesn't allow people to give their preferences to retailers so directly unless the shop has a live chat feature where people can get help. With that in mind, many companies rely on content intelligence to point online shoppers in the direction of products they might like.
IBM has an algorithm that delivers superior purchase recommendations compared to six other recommendation engines on the market. Although it factors in a customer's past purchase data, the technology knows that failing to buy a product does not necessarily mean a shopper dislikes it.
Purchase information could also be used to populate a website with supplementary content.
For example, if a person buys a tent online, they might next see prompts to visit a blog post written by the company that describes how to prepare a tent for potential wet weather. Such an approach encourages people to linger on the site and could inspire more purchases.
Ensure That Any Content Intelligence Takes Emerging Technologies Into Account
Making the most of content intelligence means coming up with a plan that's flexible enough to accommodate new technologies that are already gaining momentum or will in the future. As a start, more than 50 percent of internet traffic comes from mobile devices, and many of those gadgets have voice assistant capabilities courtesy of Siri or the Google Assistant.
For companies to have plans that cater to the evolving needs of today's society, they must seriously consider the user intent of voice searches in 2019 and beyond.
Surprisingly, a 2017 study found that most marketers had no plans to incorporate voice search into their strategies, despite the fact that such queries already constituted more than 20 percent of searches at that time.
When they're using voice search, many people may be out and about while on their phones. That means they likely want short, to-the-point answers and don't intend to do in-depth research.
Consider Enhancing Sales Tools Usage With Data Analysis
When content marketing teams work for companies that sell things, they may create and distribute material internally as well as to the public.
ut those internal materials aren't useful if they don't relate to the topics that salespeople bring up when they speak with their clients. A company called Elekta realized it was struggling with that common issue.
Elekta depended on a company called Seismic, which used a Microsoft tool to find out which sales documents representatives used most often and which were most effective with clients. The system analyzed which sales documents got used most often, and which got the preferred results.
In the end, Elekta saw a 350-percent rise in the adoption of sales content. And even before those findings, the company knew that sales content helped drive leads to take desirable actions if sales professionals had the necessary tools available to them.
Marketers could take inspiration and do something similar by using a big data analysis tool to see which customer-facing sales documents are most relevant to them at certain parts of the sales funnel.
They could remove the sales content that's shown as less effective and replace it with material that's most likely to achieve the best outcomes based on customer intent.
Since big data platforms can analyze tremendous amounts of content in a short time, they're ideal for uncovering insights about any content that could otherwise remain hidden. That's why marketers should think about investing in a big data solution for at least part of their content intelligence strategy.
Understand How Google RankBrain Works and Optimize Content for It
Today's forward-thinking marketers can also make progress with predicting user intent via content intelligence by getting a grip on how Google's RankBrain machine algorithm works. A few years ago, the company confirmed that it used RankBrain to process search results and ensure that users saw the ones that were most appropriate for their searches.
Although marketers cannot directly access RankBrain, enough information is available about it that people can optimize their content and give it a better chance of being seen as worthy of being near the top of search engine results pages (SERPs).
Getting started is as simple as creating genuinely helpful content. When people recognize that the material they've found online answers the questions they posed in their queries, they'll view the information as valuable. Google's RankBrain engine notices that and makes the content rank highly. The days of generic SEO practices are over, and Google knows that users experience changes based on query or niche.
It's also smart to scroll down to the bottom of a SERP and see the short list of related search terms. Those are the other things people search for when they look for content about the current keyword. It'll be obvious, then, that one of the ways to optimize for RankBrain is to focus on medium-length keywords instead of long-tail ones.
Analysts also believe it's crucial to improve metrics like click-through rate, dwell time and bounce rate, asserting that RankBrain likely sees those factors as having weight when deciding whether a site is worthwhile. Understanding these concepts is an example of how it's possible to predict user intent with machine learning before investing in a tool for company use.
Capitalizing on Content Intelligence Pays Off
It wasn't long ago that figuring out user intent seemed like an impossible task because marketers couldn't get inside people's heads to view their thoughts.
But thanks to the many tools covered here and others, it's possible for marketing professionals to turn their attention toward content intelligence and get insights about user intent that helps them understand how and why they should use specific content to entice people.