The shift from “text” to “voice” has already been started.Voice Search is not a thing of the future anymore, but has become a reality now. Many people across the world are using it either through their Personal assistants such as Siri, alexa,Google voice search or Cortana.
According to a report, “50% of all searches online will be via voice search by 2020, Therefore, for every 10 searches that are relevant to your business, 5 out of them will be directed via the likes of Cortana or Siri and voice-based shopping is expected to jump to $40billion in 2022.”
Internet Marketers need to find different ways to optimize websites for voice search along with traditional text based search.To get consistent user experience google is combining the power of data, intent and machine learning.
According to a report, “50% of all searches online will be via voice search by 2020, Therefore, for every 10 searches that are relevant to your business, 5 out of them will be directed via the likes of Cortana or Siri and voice-based shopping is expected to jump to $40billion in 2022.”
Internet Marketers need to find different ways to optimize websites for voice search along with traditional text based search.To get consistent user experience google is combining the power of data, intent and machine learning.
What Is Artificial Intelligence (AI), Machine Learning and Deep Learning?
Artificial Intelligence is a branch of computer science that deals with building intelligent machines that can think and respond like humans. The Turing Test, proposed by English Mathematician Alan M. Turing in 1950, was a test that determined the intelligence of computers and was taken in order to identify whether the computer could achieve human-level performance in all cognitive tasks sufficient enough to fool an interrogator.
Machine learning is a subset of AI that enables machines to automatically learn and improve from experience. Specialized systems are created for this purpose and no explicit programming is needed to add new definitions to the database. The machines can learn on their own.
Deep learning is a subset of machine learning comprised of extremely large neural networks and a massive collection of algorithms that can mimic human intelligence.
You get the idea now? The return of the direct answer by Google is powered by machine learning and the return of the “people also ask” section is powered by deep learning. Google is constantly learning and mimicking human intelligence without the need for humans to feed all the answers into its massive database.
Best example:What happens when you enter the following search query on Google:
What is age of Badshah? Google returns a direct answer:
What is age of Badshah? Google returns a direct answer:
Which AI is used by Google ?
RankBrain is a machine learning (AI) algorithm that Google uses to sort the search results. In 2015, Google rolled out RankBrain, which is a machine learning system capable of returning answers to users.It also helps Google process and understand search queries.
Reference: Wiki https://en.wikipedia.org/wiki/RankBrain
What makes RankBrain different?
Before RankBrain, 100% of Google’s algorithm was hand-coded. So the process went something like this:Based on past search entry Google engineers use trial and error , mix different code and based on testers report implement the algorithm.Human engineers still work on the algorithm, of course. But today, RankBrain also does its thing in the background.In short, RankBrain changes the algorithm on its own.Depending on the keyword, RankBrain will increase or decrease the importance of backlinks, content freshness, content length, domain authority etc.Then, it looks at how Google searchers interact with the new search results. If users like the new algorithm better, it stays. If not, RankBrain rolls back the old algorithm.
Here’s the craziest part:
Google asked a group of Google Engineers to identify the best page for a given search. They also asked RankBrain. And RankBrain outperformed brainy Google engineers by 10%!Accuracy.
In short, RankBrain works.Its becoming trend now
How RankBrain Understands Any Keyword That You Search For:
Best example: A while back Google published a blog post about how they’re using machine learning to better understand searcher intent:Google Open Source Blog project
In that post they describe a technology called “Word2vec” that turns keywords into concepts.
In short: Google RankBrain goes beyond simple keyword-matching. It turns your search term into concepts… and tries to find pages that cover that concept.
RankBrain Measures User Satisfaction by observing Organic Click-Through-Rate,Time on Site,Bounce Rate etc.These are known as user signals conveyed to search engine(UX signals).
How to boost your digital marketing efforts by using AI:
- Predict the Behavior of Your Customer with Propensity Modeling and Predictive Analytics
Propensity Modeling are statistical scorecards that are built to identify prospects who are more likely to respond to an offer.
The Adobe predictive analytics tool analyzes large volumes of data and helps to uncover the most impactful insights.It predicts purchase trend and user behavior pattern.
- Use AMP and Reduce Load Time
In October 2015, Google announced AMP webpages, which are a lighter version of the traditional webpages and aim to drastically improve the performance of the mobile web, such as reducing page load time to improve the user experience.
- Use AI-Powered Chatbots to Improve User Experience
Chatbots will make the job of sales agents easier than before and marketers can expect to have immediate insights on the best-performing ads or content.Ex. Banks to help customers find answers to common banking queries. Reference:.https://en.wikipedia.org/wiki/Chatbot
- Scale Up Your Content Marketing with AI-Generated Content
Wordsmith is a natural language generation platform that lets you produce human-sounding narratives from data. Reference wiki:https://en.wikipedia.org/wiki/Automated_Insights
It turns structured data into written prose that sounds like a person wrote it.
You can speak in a personalized way to your customers and employees, and scale your content production.
AI isn't able to write natural-sounding content for every topic, but it is useful for some types of data-focused content such as “quarterly earnings reports, sports matches, and market data.
NLG will become a standard feature of 90% of modern BI and analytics platforms.
NLG is being used commercially by companies Indeed, Gartner to summarize financial and business data.
It is also used in automated journalism, chatbots, generating product descriptions for e-commerce sites, summarizing medical records and enhancing accessibility (for example by describing graphs and data sets to blind people). Voice to Text and Text to Vice software is another example of NLP.
Another AI-powered tool called Acrolinx , which “helps you produce great content with the only AI platform for enterprise content creation,” regularly creates content for major brands like Facebook, IBM, Microsoft, Nestle and Caterpillar.
AI cannot replace niche content experts, but they can certainly boost the production of content based on sports matches, financial reports and market data.
- Deliver a Highly Personalized Website Experience to Every User
The relevant content and offers to be displayed to each and every web searchers by analyzing their prospect with their location, device, past interaction, demographics, etc, .
Also automate e-mail marketing and nurture prospective clients by sending regular push notifications based on the micro moments or their current interaction with your business.
Rare Carat uses IBM Watson technology that allows prospects compare diamond prices across various online retailers so that the buyers are able to find the right diamond at the right price.
The New York-based startup and e-commerce platform for buying diamonds does this with the help of an AI-powered robot called “Rocky.” The robot is able to answer all the queries associated with diamonds and also assists buyers with purchasing a ring at the best price.
- Optimize web pages for Voice Search Queries
With the rise in voice search queries, it is becoming more than necessary for marketers to optimize for natural language long-tailed voice queries.
Find out the web search users conversations objective that are having with your brand.
Create pages that provide a direct answer to the questions asked by them.
Questions normally start with “who,” “what,” “where,” “when,” “why” and “how,” so try optimizing your web pages accordingly.
Create local landing pages for every location that you are targeting.
Develop local website content that would engage the interest of the people in your area and make it easier for the search engines to understand the context of the page.
Find out the web search users conversations objective that are having with your brand.
Create pages that provide a direct answer to the questions asked by them.
Questions normally start with “who,” “what,” “where,” “when,” “why” and “how,” so try optimizing your web pages accordingly.
Create local landing pages for every location that you are targeting.
Develop local website content that would engage the interest of the people in your area and make it easier for the search engines to understand the context of the page.
- Customized news feed algorithm
AI would customize the news feed of your clients for their social media networks including Facebook,Twitter,Instagram,etc and with this posts will be shown only to the people who wants to see it.Target your ads by audience interests, Leverage the Power of Audience Insights to Boost Search Ads.
Summary: Google has disclosed in its blog that around 70% of queries that the Google Assistant receives consists of natural, conversational language and not the typical keywords that are used in a typed Google search.
Artificial intelligence and machine learning will not pose any threat to existing jobs; it will only make our tasks easier than ever. Recurring tasks can easily be shifted over to bots and tasks that need human intervention will still rest on the shoulders of people. AI-powered analytics platforms like Albert and PaveAI will provide more accurate and relevant data that will help marketers take robust and immediate decisions.
As a business owner or marketer, it is time to identify the problems that your business or marketing campaign is facing and how accurate insights can solve these issues. Gathering all the data spread across numerous applications into one place will help you to get accurate insights. Whether it's dynamic price optimization or automatic selection of ad copy based on the user demographics, AI has the power to do it all.
All you need to do is ask yourself what your most pressing needs are and AI can do the rest.
