Asking a voice assistant for help, whether in a smart speaker or mobile device, feels different from typing in a text box to search for information. After all, the term used for Google, Yahoo!, and similar services was “search engine,” not “question engine” or “answer engine.” Yet the growth of voice search has been rapid as people take advantage of the natural feel of voice search compared to text search. In fact, some experts estimate that voice search will make up about half of all searches by 2020. However, the differences between voice searching and text search are not necessarily intuitive and the differences between search engine optimization (or SEO) for voice searches and text searches are not necessarily obvious. Here are three differences between voice searching and text searching that may affect how web design companies approach search engine optimization when dealing with voice searching:
People Speak and Type Differently
Even though Ask Jeeves was founded in 1996, most users grew up typing keywords into search engines rather than using natural language. In fact, much of SEO web development focuses on keyword packing to raise search engine rankings. However, users of voice search products tend to ask questions using natural language rather than just spitting out keywords. For example, someone using a voice assistant could ask “how many grams of carbs are in a banana?” rather than saying “banana carb content,” although that might be exactly what he or she would type into a search engine. This could make a difference in search engine optimization because keywords like “carb content” did not appear in the natural language query. While most websites that do well in text search also do well in voice search, the ranking of those websites may differ due to the differences between keyword searching and natural language searching. How can this be addressed? Keywords will still be important, but keyword research will need to account for the differences between speaking and typing.
The answer, by the way, is that bananas have about 27 grams of carbohydrates.
People Expect Different Results When They Speak
Take any daily interaction, such as with a co-worker, or a spouse, or a child and ask yourself what would happen if they answered your questions with a list of places to find the answer. “Did anyone make coffee?” “Coffee can be found in the kitchen.” “Did anyone return the customer’s call?” “The call logs contain all the returned calls.” This would be frustrating, to say the least. However, this is the natural role of search engines – to tell the user where to find the answer.
Users tend to have different expectations from voice assistants. Users want to hear the answer, rather than hear a list of places to find the answer. In fact, users not only expect to hear an answer, voice assistants tend to select an answer at the ninth-grade reading level. This means that voice search tends to prioritize clear, short, and understandable phrases when ranking results. This can be addressed in search engine optimization by ensuring that websites include answers to common questions and that those answers are clear and understandable.
People Ask for Different Things When they Use Voice Assistants
Twenty two percent of voice searches are looking for local content. This is logical since most searches using a voice assistant occur on mobile devices. As may be appreciated, many of these voice searches occur when out and about looking for local services. But again, users of voice search interact with voice search differently and expect different results. So the query “where can I order a gluten-free pizza to go?” is different from “takeout pizza gluten-free” and the answer “Joe’s pizza has gluten-free pizza to go” is different from “here are three websites that mention takeout gluten-free pizza.”
In summary, voice search may not provide radically different outcomes from text search. However, the differences in outcomes that do arise may affect how search engine optimization is approached. In fact, voice search engine optimization may even provide an opportunity to leap ahead of competitors who are not prepared for the differences in voice searching and text searching.