How is NLP impacting content marketing?

Business leaders are starting to research more about technical topics like natural language processing and machine learning. In this post, we summarized the top 10 results on Google (as of May, 14th, 2018)  for the query “how is NLP impacting content marketing?”.  As a quick spoiler, these were the topics that got mentioned in at least 50% of the articles: unstructured data, business intelligence, search engine optimization, sentiment analysis, neural networks, chatbots, customer experience, automated content creation, digital transformation.

How can NLP technology be used for marketing (econsultancy.com)

Topics: business intelligence, unstructured data, structured data, search engine optimization, sentiment analysis, mobile apps, machine learning, scalability

  • The holy grail of NLP has been to convert ‘unstructured data‘ (text and multimedia) into structured data and we are inching closer towards that goal with advances in NLP and multimedia indexing technology.
  • Social prospecting solutions require NLP capabilities that can sift out passing mentions of a brand, and focus on those where this is an intent to purchase.
  • State of the art NLP systems can mine social media for such expressions of interest and return social handles of people matching the customer’s criteria.
  • The interaction of these two leads to compelling solutions, for example in leveraging socially trending topics (or brands) to promote customer content matching those topics or brands.

What Does Natural Language Processing Mean for Writers (portent.com)

Topics: natural language, machine learning, Natural Language Processing, neural networks, Artificial Intelligence, word processor, chatbot, language model

  • It’s not news that there are things computers are really good at that humans are bad at, and some things humans are really good at that computers can’t seem to manage.
  • Google made a splash in 2015 when the neural networks they’d trained on millions of images were able to generate pictures from images of random noise, something they called neural net “dreams.” And in 2016, they announced Project Magenta, which uses Google Brain to “create compelling art and music.”
  • “[Google’s algorithm] Hummingbird can find some patterns that can give it important clues as to what a text is about,” says Matthew, “but it can’t understand it the way a human can understand it.
  • Language takes root best in our “procedural memory,” which is the unconscious memory bank of culturally learned behaviors, rather than in our “declarative memory,” which is where you keep the things you’ve deliberately worked to “memorize.” Children can pick up other languages more easily than adults because they’re tapping into their procedural memory.
  • We can go into the idea that robots are going to take over the world and they just need to learn to speak first, and that’s kind of cool for a movie.

What do linguists make of AI and natural language processing? (econsultancy.com)

Topics: target language, natural language, machine translation, natural language processing, statistical machine translation, translation process, language professionals, foreign languages

  • One might assume that professional linguists would feel a constant need to stay updated on any impact such technology may have on their future careers.
  • — there is an apparent lack of understanding of the connection between AI, NLP, and advanced machine translation such as statistical machine translation (SMT) or neural machine translation (NMT).
  • Once the usage and purpose of statistical and neural machine translation are understood, most linguists start to think about how it could support them in their work instead of ignoring it as a threat to their livelihood.
  • It’s difficult to say how many linguists would admit to using SMTs for their translation projects, as despite improvements in the technology, its acceptance amongst clients is still low.

Can Artificial Intelligence Replace The Content Writer? (digitalagencynetwork.com)

Topics: content marketing, customer experience, structured data, augmented reality, natural language processing, Gartner, data processing, artificial intelligence

  • While less likely to be automated, these areas are not exempt—roles such as data collection and data processing, once revered for their level of required expertise, are now 64% and 67% likely to be automated, respectively.
  • This can be seen in the above example: the second extract, written by Wordsmith, is more matter-of-fact and event-driven than its human counterpart (and the overuse of ‘season’ at the end particularly gets to me).
  • With the information already at hand, writers will have more time to focus on how articles are structured, how argument or opinion is built to leave the best impact on the reader.

Artificial Intelligence for Content Marketing and Content Creation (techemergence.com)

Topics: content marketing, best practices, healthcare industry, content creation, search engines, Google, customer service, deep learning

  • With improvements in AI technology, newer NLP platforms can augment human researchers by creating multi-page summarized articles for even open-domain questions like ‘what is the future of AI technology going to look like?’ or ‘How is AI affecting the healthcare industry?’
  • Summarizing content through the use of NLP can be either “extractive” (where the system distills text into just the most relevant parts, cutting out the rest) or “abstractive” (which is machine learning based, and involves AI coming up with it’s own “wording” for summarizing a given text).
  • As opposed to what Google does in summarizing fact based questions, more advanced contextual summarizing would involve condensing information from the top 50 search results, finding meaningful relationships between these results and then extracting the most appropriate sentences from within those relationships.
  • Essentially, the platform offers a word processor that can learn from things that you write and can research contextual topics in the background and give you links for the topic etc.

Can Neuro-Linguistic Programming really Influence Sales? (maximizer.com)

Topics: emotional responses, skill sets, empirical support, Virginia Satir, human psychology, desired outcomes, specific goals, basic concepts

  • Stephen Covey’s habit of “begin(ing) with the end in mind” applies, a clear vision of a path to a successful sale, looking for visual clues that monitor how successful your sales pitch is, or whether your attempts at conversation are working well or failing miserably.
  • While wholesale subscription to NLP principles like anchoring and reframing may be less than ideal, managers should be aware of some general concepts that could impact an individual’s performance and potential as a team member.
  • This works on both sides of marketing equations, where sales prospects are less wary of the dogma of high-pressure salespeople that immediately put them on edge, and sales pros are less likely to be intimidated by negative feedback and clients that are unimpressed by their products or services.

How NLP Systems Help Marketers | Centric Digital (centricdigital.com)

Topics: natural language processing, natural language, target audiences, actionable insights, digital communication, digital transformation, social media, computational linguistics

  • The ability to keep a finger on the pulse of consumers’ reactions to a product on social media is immensely valuable, since, in the words of Apiumhub, “It has the potential to turn all of Twitter or Facebook into one giant focus group.” Countless SaaS offerings accomplish this by scraping the text away from social or publishing platforms and providing actionable insights based on interpreting those statements.
  • In fact, countless components of a potential consumer journey can be mined with the same datafied approach, creating a thoroughly personalized marketing touch point and driving sales on the basis of an overall sense of each consumer’s style and preferences.
  • As previously stated, the simple Amazon tracking that occurs when someone views a product page is a one-size-fits-all operation: The ad engine isn’t quite sure whether the consumer bought the item or not, and so it surfaces an ad for that item repeatedly in the middle of almost every subsequent site they visit.
  • If marketing content could make meaningful use of expressed language from the user’s entire web journey, including search terms, social media posts and reviews written customers would receive information in their preferred medium.
  • For example, when the user searches for a “baggy sweater” with the intention of finding a sweater that fits loosely, and instead the search returns sweaters made of a bag-like material, or sweaters with tote bags depicted on them — this is not product marketing on par with a premium ecommerce shopping experience.

 

Artificial Intelligence–the Next Frontier In Content Marketing  (blog.marketo.com)

Topics: unstructured data, machine learning, natural language processing, neural networks, deep learning, marketing automation, natural language generation, seamless integration

  • With the ability to process an enormous amount of unstructured data and decipher natural language, AI is used to extract insights and make recommendations based on previously established criteria.
  • This capability allows marketers to fully leverage the power of personalization and marketing automation technologies to deliver targeted content to each prospect or customer and increase the ROI of their content marketing efforts.
  • You can use AI to identify trending topics by using algorithms to track conversations on the Internet, such as those occurring on social media and within published content, to help you stay ahead of the trends and create content that will lead the conversations.
  • Leveraging the AI features in your current tools will not only give you a great starting point to familiarize yourself with the technology, but you’ll also be able to take advantage of the seamless integration that’ll allow you to get up and running faster and more cost-efficiently.

Artificial Intelligence in digital marketing (besttechie.com)

Topics: big data, search engine optimization, social media marketing, content marketing, digital marketing, search queries, search engines, Whatsapp

  • One of the most popular and common words that are consistently used in the world of marketing is “segmentation.” There are plenty of people with a variety of needs and interests, and the companies need to categorize them as segments to increase their sales and retain their customers successfully.
  • There are plenty of benefits that are brought by AI in the world of digital marketing, but there are many challenges that are faced by the digital marketers due to the entrance of AI.
  • AI based marketing tools can assist the digital marketers in developing an effective marketing strategy, but the thing is that these tools can be easily available to all digital marketers, which forces the digital marketers to increase their skills and constantly be aware of new tools and services in an effort to stay on top of their game.
  • For now, the digital marketers should keep on learning the new digital marketing skills, and they should keep themselves updated with the recent updates on artificial intelligence to be competitive in the world of digital marketing.

Content Intelligence: Will AI-powered Content Marketing be a game changer? (martechadvisor.com)

Topics: email marketing, content management, user experience, marketing automation, Content Marketing, customer engagement, data management, individual users

  • -A better breakdown of audience data by using data management platforms like Lotame can tell a content marketer what type of reader is consuming their content, what the reader’s other category interests are, location, etc.
  • Like several other companies, Wayblazer leverages the Ibm Watson technology for the travel industry by focusing on the language recognition API to analyze triggers from a traveler’s search so that they are further be able to share personalized hotel recommendations.
  • Also gone are the days of waiting for the RJ to play your favorite track what with platforms like Spotify, (a world digital music service) using AI and deep learning to provide music recommendations to users based on their past listening preferences.
  • To answer the glaring question as to why content marketers are increasingly looking at AI to supplement their content marketing efforts, Mark Schmukler, CEO and Co-founder, Sagefrog says, “Personalization has a big effect on the success of content marketing and can be well-executed through artificial intelligence and marketing automation tools.
  • A marketing agency with expertise in content marketing and marketing automation can help marketers find the tools and tactics that together create the best possible user experience throughout a content marketing campaign.”