Text Analysis and Content Distribution
Social media and online publishing have opened up channels of mass communication to everyone. Now individuals, as well as organizations can use publishing techniques to persuade, build influence and spread ideas by sharing and distributing their content online. “Content is king” online today. However, “if you build it they will come” doesn’t always apply.
Content Discovery and Distribution
We recently spoke with Michael Schwartz, the founding partner of WebWire, who distribute business, organizational and personal news releases and press releases over the Internet. Michael told us about the four things he considers to be most important when distributing news releases.
Create well written informative content.
- Reach interested readers
- Reach appropriate influencers
- Reach appropriate members of the professional media
Michael also spoke about a common trend; “In the good old days (before the Internet), a media directory would generally guide the marketing professional to the appropriate target, and a room full of people with printed publications, scissors and tape would create effectiveness reports….those days are over.”
Traditionally the discovery, tagging and distribution of an article or piece of content would have often been carried out by a PR professional or marketer. In recent times as machines and software get smarter and the sheer volume of content out there continues to grow, parts of the process can be automated using technology. In order to match a humans work, however, machines need to be able to understand and categorize content effectively. That’s where Text Analytics and Natural Language Processing techniques come into play.
How Text Analysis enables “modern day” distribution
Creating good content that is well written, informative and engaging is central to attracting and retaining your audience’s attention. Just as “beauty is in the eye of the beholder” content needs to be well-written, informative, relevant and engaging from the viewpoint of the audience. While Text Analytics isn’t pivotal in the content creation process, elements of Text Analytics can be incorporated, into the process. For example, discovering trends, topics and identifying what is attracting engagement online can help you create relevant, informative pieces. Essentially writing good content comes down to knowledge and expertise in a certain field or area and this is particularly difficult to automate.
Once you have created an interesting, relevant and informative piece of content do you just sit back and hope it gets discovered organically?
To reach interested readers, you first need to identify who your audience is and meet them where they congregate. Today we don’t search for content we expected it to be pushed to us, through News Apps, Twitter, Facebook and so on. Analyzing content and being able to automatically extract concepts and topics from content and articles shared and distributed online allows us to identify where our target audience reside.
Text Analysis also allows us to prep our content for maximum discovery and exposure. One effective example of how this can be achieved is through the use of hashtags when sharing content on your social media sites. Being able to understand text and extract topics and concepts automatically means we can also ensure they are distributed appropriately for maximum exposure on social channels.
While you may distribute your content in the right place, to get it to stand out in an extremely crowded space online can be quite difficult. Traditionally relationships with the right journalists or individuals helped in this regard. Today, we have new targets to help with amplification in the form of influencers.
Influencers online have generally built up a reputation as trusted and knowledgeable sources of information in a particular subject area. People see them as thought leaders and rely on them as a source of content or informal advice in some ways. An influencer picking up on and sharing your content doesn’t always happen organically. Identifying appropriate influencers to target with you content was traditionally about relationships. Today technology has made the identification of and access to these influencers somewhat easier. By effectively analyzing content, we can match content to appropriate influencers, based on interests, keywords, entities, topics and concepts they write about.
That isn’t to say there isn’t a place for utilizing journalists to increase exposure.
Similarly, reaching appropriate members of the professional media can be achieved by matching articles to individual journalist’s areas of interest and writing style. It is vitally important that the matching process is accurate, as sending someone content they have no interest in is technically spam. Being able to analyze opinions can also help be a lot more targeted. Through Sentiment Analysis of content, we can understand a writer’s opinion and target them with appropriate releases. For example, a journalist who writes about technology but is of the opinion that Android trumps iOS isn’t going to want to publish a piece on how great the new iPhone 6 is.
The internet has fundamentally changed how we communicate with each other. Social Media sites, blogs, forums and mainstream media sites proliferate and rise and fall in popularity. Keeping track of the most appropriate outlets for any given piece of content is an increasingly important, difficult and time-consuming task. The ability to automate many parts of the process allows for large volumes of content to be matched accurately with the most appropriate audiences.Text Analysis can be used to reliably aid traditional distribution tactics and processes but while it may aid the process it is yet to be seen whether technology will trump human relationships with the right people built over time.