When I graduated with a degree in Linguistics, I was not prepared for the idea of actual linguist positions being extremely rare. With such a small niche of companies needing linguists, it is reasonable to assume that will never be a career path for me, but lets say I had the choice. What type of company would I work for? Well, who employs the most or at least a good amount of linguists? The answer is Google.
Currently, there are 11 jobs open at Google using the search term, linguist (opening this search term up to include Natural Language Processing doubles the available jobs). This makes sense if you think of the core reason someone uses a search engine. Users utilize a search engine to speak to a machine with the expectation this communication will result in their questions answered.
The core of Google is language. Without communication, Google would not function, but there is a specific reason I believe Google will employ even more traditional and computational linguists in the future. Google will need more linguists because language will change the way people interact with Google, and it could change the traditional way marketers create their SEO campaigns. The move towards conversational search is in the future, which is seen in the recent extensive use of Voice Search and Conversation Search. If natural language search becomes the dominant model, will our traditional keyword strategy suffer? Currently, I think optimizing for voice search could help serve better content, regardless of Voice Search dominance.
Let’s find out why.
In October 2015, a survey was conducted with 1,800 adult participants about their smartphone use, including voice assistance and voice search. While the study revealed many facets of how users interact with their phones, the main finding that I thought was invaluable was the Rise of Voice Search. 60% of the participants stated they started using voice search within the past year and 50% were satisfied with their voice search functionality. The trend in voice search will only continue, as search engines utilize Natural Language Processing to continue bettering their voice search and speech recognition abilities.
The Rise of Voice Search could mean demise for the traditional keyword models, but phones are not the only ones to blame. Wearable technology and home voice assistants (think Google Home) could start to contribute to the emphasis on conversational search terms. As wearable items increase in popularity, more keywords will be conversational or even colloquial terms. But what will keywords look like when voice search is the main model of search engine and user interaction?
The main difference in keyword models will be based on the inherent informality and intention of spoken language. Using spoken search, keywords will be long tail with clear intention. This means users will ask Who, What, Where, & When with a voice search and expect a hyper relevant answer.
The best part about this model is voice search keywords will be actionable, therefore focused on conversions. This will especially affect local search for users that can find products or services near them. But sites where local search is not relevant can still benefit from voice search keywords. Users searching with voice will ask Who, What, When and Where, which means sites can rank for Quick Answers.
Now that we know what the structure of Voice Search will be, let’s optimize for the new version of SEO Keywords.
Tailoring content towards longer phrases and holistic ideas will be the future of content marketing with voice search. The focus will move less towards keywords and more towards user experience by answering users’ Who, What, When and Where questions. Content should be focused on predicting users’ questions and serving long tail keyword content around this idea. An easy way to start to incorporate long tail content is FAQ pages or step-by-step instructions with the intention to rank for Quick Answers. Another tactic is optimizing landing pages to include relevant copy surrounding natural language keywords. A user searches “What are the Caribbean vacation deals for July”. Reference this long tail query by adding “Summer Sale” or “Summer Deals” to the landing page copy, which is more likely to be clicked through since Summer is specific to July, the user’s vacation date.
Utilize schema markup- JSON or HTML- so crawlers can understand details about your content. Schema markup helps Google serve detailed information straight in the SERPs, which makes it appealing for mobile searchers looking for quick, accessible answers.
Using Natural Language to write content is the best way to make sure you are implementing keywords for voice search. Thinking of content as a conversation can help avoid the stagnation of traditional keyword models and that stressful balance between keyword stuffing and “natural” keyword integration. When writing content for voice search, emphasize conversational phrases. Instead of using the traditional one-word or two-word keyword research tactic, open your research to include Natural Language phrases and ideas- phrases or topics that would occur in spoken conversation.
Natural Language Processing will make Google a powerful tool for what it was designed to do: communicate with users. By thinking of keywords as part of a conversation, content can help continue a back-and-forth between the user and Google. This conversation can turn into conversions, especially for local search, as users look for immediate gratification in the form of products and businesses near them. Whether or not Voice Search completely changes the search landscape is too early to tell, but by assuming it could, we are producing content that focuses on user experience and inquiries. It also prompts us to pay close attention to Local Search best practices.