Content Marketing Technology Update: 9 Emerging Trends
Content marketing is proving to be the MVP in today’s inbound marketing world, with 87 percent of today’s marketers implementing a content strategy to drive sales, establish thought leadership or increase brand engagement.
Journalism techniques and automation platforms that are processing and mining content are now fused together in this type of digital marketing. Because of this, marketers are exposed to content technology and intensive tasks such as content curation.
Tying these all together can get confusing, especially with complex terms such as semantic search, machine learning and natural language processing. However, the importance of learning these terms is growing tremendously for content marketers. Here’s why.
People want fresh, purposeful content and they want it in one convenient place. Let’s say that place is your website. Now, if they aren’t getting the content they want every day on your site, they’re going to look elsewhere – potentially disregarding you as a dependable source and giving a leg up to your competition. So, how can you get them to stick around? Upload original and curated content, fast.
Content marketers don’t always have the time, or resources, to call in an IT team. If you haven’t mastered the technology behind today’s digital marketing world, and can’t get to that IT resource in time, it can be a recipe for disaster. It’s imperative to understand what’s going on in these behind the scenes technologies to be the go-to source in your field.
Here are nine introductions to these intelligent technologies and how they can be implemented to advance your content marketing strategy and make you a better digital marketer.
Let’s start with the basics. Artificial intelligence (AI) is a broad term that describes intelligent software and computing, allowing a machine to “think” through programming specifications. Although the term is popularly relatable to robots or video games, AI stands as the backbone to many fields, such as natural language processing and sentiment analysis. These technologies allow content marketers and their constituents to search for and discover relevant content, collect consumer data and explore predictive analytics, to name a few.
Machine learning is a branch of AI where machines can learn from data and predict potential outcomes. For example, machine learning utilizes predictive analytics to score leads, much like Infer or Lattice Engines, or to learn what content is the most relevant, like Curata. This leverages the potential of big data and allows marketers to focus on the information, or leads, that best match their service.
Natural Language Processing
The science of intelligently understanding or generating “natural language”, the language that humans write, is known as natural language processing (NLP). When a user searches “How much is a cup of joe?” their search results will include coffee prices. Even though “Joe” is also a common name, it doesn’t fit within the context of the sentence. NLP aims to understand the structure of human linguistics, not just the words themselves.
This is useful for content marketers looking to dive into the world of mobile marketing as part of their online marketing plan. NLP can be used to help generate content through automatic summarization, like Summly, on mobile so that the information presented is intelligently discovered, purposeful and presented on one page. Users seeking content on mobile devices don’t have the leisure, or space, to click from tab to tab.
NLP can also be used to help marketers understand customer inquiries and better educate their users, leading to improved buyer satisfaction and content congruence. The NLP experts at Q-go have engineered a new FAQ practice, by matching all of the same versions of a searched question with the same answer, i.e. “I need to change the address on my account,” yields the same result as “How do I update my address?” Information can be more easily found and buyer frustrations, and company costs, are kept to a minimum.
Curata’s ability to surface and analyze content within specific user guidelines, as well as our software’s ability to “learn” to improve search performance can be attributed to NLP.
This is automated content translation. You’ve most likely used the free translation resources offered by Google Translate or Systran. These machine translation tools can cost-effectively transfer content into new markets, international and domestic, reaching a larger audience and increasing potential for improved brand awareness.
Just as the name implies, sentiment analysis is an automated NLP task used to determine the feeling or “sentiment” of a piece of content. By understanding the sentiment of content posted by potential consumers on social media, marketers have the opportunity to adjust and present targeted information to those users. Crimson Hexagon has the ball rolling on this application by offering social data analytics to discover how people think by analyzing what they’re saying on the Internet.
In order to avoid an information overload, search results must be tapered and precise. Information retrieval is the field of retrieving the correct information given a query. This is the science that Google and other search engines use to return the right content to the inquirer.
Without understanding how Google works, marketers can have a more difficult time optimizing content. A solid understanding of Google’s PageRank algorithm and search algorithm, most recent being Hummingbird, gives content marketers an exponentially better shot at reaching a wider audience. Content curation technologies, like Curata, use information retrieval to identify relevant content for consumers.
The task behind document clustering includes the automatic grouping together of related content.
Document clustering proves itself useful for marketers because it often powers content recommendation engines to suggest other similar content for the searcher to read, improving the reach of content and usefulness for the user. This automation can also be used to suggest call to actions. BrightInfo modifies original content recommendations for individual site visitors, grouping your related information together to keep them around longer.
In short, collaborative filtering is a technique used to recommend content based on the content consumption habits of similar users. It filters through large amounts of data to obtain the most useful information available to the user. This technique is used by Netflix and Amazon – consumers who watched X also watched Y. Sound familiar?
This is helpful for marketers to understand how to optimize their content for sites that use collaborative filtering. It also proves as a great example of how content marketing and technology can be used to increase product awareness and drive sales.
Semantic Web/Semantic Search
Semantic web is a common data format for adding metadata to concepts and interpreting their relationship. This automation takes the intent of a query and polishes it to provide more customized search results. When a user searches “Veteran’s Day” on Google, not only does the date pop up at the top of the page in bold letters, but it is followed with a stream of history and news stories on the topic.
Semantic search is a beneficial tool for marketers because it can be used to find extended content related to the initial search, giving that associated content an expanded reach. However, the amount of human annotation required for semantic search is causing user interest to decline, as it cannot comprehensively “learn” from existing preferences to make the search process more efficient. Note the graph below via Google Trends, displaying the declining interest in semantic web since 2004.
Content Marketing Technology Update: 9 Emerging Trends
Now more than ever, it’s important to leverage the potential content marketing has for your business. Including content in your marketing strategy is essential to establishing thought leadership and staying ahead of the competition. In order to do this effectively, marketers must understand the technology behind the digital content they’re producing. This knowledge will make your content, and content curation, strategy more effective.
Ready to take the step towards content creation and technology integration? Download Curata’s 2013 Content Curation Look Book and see how these companies are using curation technology to enhance their content and take on the digital marketing world.
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