Technology is advancing day by day and is now changing the way we search, voice assistants play a very effective role in changing the way consumers search. This is now a harbinger that users will create queries as if they are talking to someone while using the internet.
However, users soon learned to remove all prepositions and conjunctions to group short words together to work as Google needed to get to the core of the keywords. We all know that Google puts user experience first, so it wants to make users feel more comfortable communicating naturally through conversation.
This guide will explain what voice search is, how it works, and how, as digital marketers, we can effectively optimize our site for voice search.
What is Voice Search?
Voice search is a specific voice/speech recognition technology that allows a user to query through a voice assistant or a device. The assistant then responds with a correct answer to fulfill the user's intent. These assistants are available in several versions, including Alexa, Google Home, Cortana, Siri and more.
How Does the Voice Search Engine Work?
Voice search works by connecting speech recognition to complex natural language processing (NLP) systems. These systems must accurately identify and understand what the individual is looking for and then interpret how to respond. NLP is a system driven by artificial intelligence to fully understand the text.
In 2012, voice search started using Deep Neural Networks (DNN) to improve the overall speech recognition process. The combination of Google's powerful search algorithms with advanced NLP technology has undoubtedly increased the accuracy of the results.
Over the past 5 years, there have been attempts to improve speech recognition accuracy. To increase its accuracy, a model is used that employs temporal classification and sequence discrimination training techniques.
Temporal classification is a specific type of training neural network output that handles sequence problems where timings are an important variable. Sequential discriminatory training aims to better match and improve speech recognition performance by analyzing sequential constraints in different language models. These models are extensions of recurrent neural networks that make searches faster and more accurate in noisy polluted environments.
What is Voice Search SEO?
The world of search marketing may be changing as users test voice search assistants to make lower-risk purchases. As it is known, voice calls were one of the most popular topics of 2019. To optimize for voice search, traditional SEO practices must be implemented, but they must also be changed or include layered content strategies to meet the demand for how many users are currently searching by voice.
Voice search SEO therefore replaces part of the way we optimize on-site content. The keywords that we need to force to rank for are inevitably long tail in the conversational aspect of the user's voice search. This feature will increase the chances of visibility in featured snippets such as featured snippets. This is where voice assistants will most likely pull search results, thus increasing the chances of ranking for the voice search query as well.
BERT Model
During October 2018, Google's AI language researchers introduced BERT, which helps any individual train the most advanced answering system. Google recently announced that its BERT neural network-based technique for NLP is now implemented as part of its search algorithm. This will help to better understand the context of words in organic search and match user queries with the most relevant results.
How Does the BERT Search Algorithm Update Work?
The BERT modeling system works by processing words in relation to all other words in a sentence, rather than evaluating each word individually. By analyzing the words in a sentence holistically, this is especially used to understand the purpose behind the query.
Prior to this update, Google provided featured snippet results that would not always respond to the user's specific query. By incorporating the Google BERT model into its algorithms, it allows users to make more detailed search queries and provide detailed answers that are most concise and valuable to the user. This is especially visible in audio and in visual assistants where the answered search result speaks more as if you were speaking to a real person.
The following explains how the BERT model will replace rich snippets opportunities within SERPs.
Brain and Artificial Intelligence
While BERT is the biggest update to search since the launch of RankBrain 5 years ago, these advances in AI and NLP will help our voice assistants understand the language more and more people. As we have naturally flowing conversations with our assistants, they will be able to learn from our experience to properly formulate a sentence, cross-reference with our planned diaries, and offer personalized choices.
How to Optimize Audio Results?
There are many different ways to test when optimizing for voice search. We want to share some tactics with you to ensure your SEO strategy is suitable for voice search, while planning long-term strategies and gaining a first mover advantage over your competitors.
Focus on Using Long Tail Keywords
Long tail keywords are queries that users focus more on because they are lower in the funnel. These queries generally have a lower search volume, are easier to rank for in search results, and as a result, higher conversions are achieved when users are closer to the point of purchase as opposed to their generic keywords. Therefore, take care to create content that clearly and comprehensively answers the user queries that are mandatory in voice search queries.
Generic Keywords and Long Tail Keywords
When it comes to on-page SEO, keyword research is arguably one of the biggest factors in understanding what users are searching for and presenting new opportunities. Generic keywords are considered phrases of about 3 words or less, which are the main product terms.
Examples include "house plant" or "shoe store". Long tail, on the other hand, is much more specific to users' intent. These are the words that users tend to buy the product/service.
Conversation Content Strategy
When creating content strategies for voice search optimization, it's crucial to map out longer-term queries at various stages of the customer journey. This creates natural and interactive content, helping users more efficiently assist when they search for queries via voice search.
Here are sample queries brought by different aspects of the funnel.
Various Content Strategies
To rank for different terms and rich snippet opportunities, it is recommended to create diverse and layered content strategies to further increase organic visibility in SERPs. This may include informational, navigational, commercial and transactional content. Examples of each content intent are summarized below:
- Informative (how-to guides, detailed guides providing an overview)
- Navigation (users searching for a specific landing page increased targeting to improve UI)
- Commercial (where a user looks for more information before purchasing, e.g. product descriptions, FAQ pages, distribution options, location-based, customer service information)
- Action (possibly purchasing a product or service, videos, comparisons or product stories).
Most importantly, by producing a variety of content types, the end goal is to add value to specific types of users at points in their customer journey.
EAT
The best way to optimize landing page content for a specific search intent is the EAT (expertise, authority and trustworthy) method. This helps you create reliable content that is valuable to the user, and they are unlikely to have any further questions after reading this knowledge guide.
Mobile Compatible Site
It's important to have a mobile-friendly version of your site, as the majority of voice searches are mobile-derived and mobile-first indexed first. Therefore, the mobile version of your site is called your primary version in the index Google provides to users. An unresponsive website can affect the overall user experience as well as organic ranking within the SERP.
Structured Data
Structured data, also known as Schema Markup, is a configuration of HTML data that you can embed in your website's code to help you become more discoverable by search engines. This can help you increase your visibility within relevant search results and increase the likelihood of earning rich snippets like the Ask People result.
Site Speed
Since voice search users are more likely to use their smartphones to perform these queries on the go, it's critical that the load time is sufficient to prevent users from creating another query and not interacting with your site. In fact, the loading speed of the voice search result should be much faster than your average website.
If you are not currently ranking in the organic SERP because your site is slow, increasing your site speed is considered the first step to increase your chances of ranking.
Focus on Local Business Strategies
As we mentioned earlier, voice calls are more likely to be used on the go. As an extension of this; in 201958% of usersThey reportedly used voice search primarily to find local business information. You can perform the following items to optimize your business for local organic search.
- Fully optimize local pages on your site with location-specific keywords.
- Set up and stay active on your Google My Business profiles (Location, opening hours, high resolution images and contact info)
- Review and respond to local reviews to ensure you're giving your users the best possible experience. In addition, send accurate credibility signals to Google.
- Include local business chart markup to help Google understand your location.
In summary;
The voice search app is happening right now and is affecting many websites with more accurate algorithm updates. With that in mind, voice search is certainly not expected to disappear anytime soon.
It's fascinating how users now feel more comfortable typing and speaking to our search engines in a more natural and interactive way and getting an accurate response in return. Language understanding still remains, but with the introduction of artificial intelligence algorithms (like BERT) it will be interesting to see how they continue to learn from their users to deliver the most useful content and ultimately help the user.
If there's a takeaway from this voice search optimization guide, it'll be the voice assistant and smart talk screens bringing together artificial intelligence in an accurate and informed way. Therefore, websites should create informative and concise answers to optimize this shift in organic search.
0 Comments