What happens when you enter a query such as “where does Kim Kardashian live?” 

query such as “where does Kim Kardashian live?”

Not only does your search query shows you the states where Kim lives, but it also shows all the possible questions people ask Google regarding Kim Kardashian’s location. 

The results are not only relevant but are quite accurate, all thanks to Artificial Intelligence. 

Clearing the concept of AI, Machine Learning and Deep Learning? 

The process of creating intelligent machines which are capable to think and respond like humans is termed as Artificial Intelligence (AI). The term initially coined by the English mathematician Alan M. Turing back in the 50s. The Turing Test was a test performed by the genius mathematician to identify whether computing machines are capable to achieve human-level performance. 

To best understand the Turing philosophy, don’t forget to watch the movie The Imitation Game.  

Machine Learning, on the other hand, is a subset of AI which enables machines to learn and improve from experiences. The more a user interacts with an artificially intelligent system, the more it specializes in creating an interactive experience for the user. The ability of a machine to learn new things by adding new definitions to its database on its own is termed as machine learning. 

Like Machine Learning is a subset of AI, Deep Learning is a subset of Machine Learning which comprises of extremely large neural networks. It creates a strong web of algorithms which work together to give the machine a mind that mimics human intelligence.  

How Such Concepts Apply to Google? 

I am sure you do understand how these concepts apply to Google. If not, let me assist you with that. The direct answer that Google shows is commonly powered by machine learning. The section that shows “people also ask” is the by-product of deep learning where Google suggests more options mimicking human intelligence. It helps the user to search the massive database of Google to understand his/her query better. The whole process sums up into an AI-powered search engine.

Introducing Propensity Modeling & Predictive Analytics

Statistical scorecards which are designed to identify which of the customers are more likely to respond to an offer are termed as propensity models. Customer information is precious but you can only gauge its true value once you have put this information to test. Understanding your customer behavior is important and the propensity model is a predictive analytics tool which allows marketers to predict precise customer behavior. It helps businesses accurately reach out to the target audience. Optimove is one such platform, and it’s a fantastic choice for companies who need to follow and analyze customer behavior across many networks. Take a look at the Optimove price plans for your business.

Destination CRM covers an informative piece explaining what propensity model is and how it works

Marketing managers who use AdWords to run their ad campaigns have to define their target audience. They update such information using tools like Google’s DoubleClick Bid Manager. When you are accurately aware of which audience you should be targeting, it becomes easier for you to design campaigns. The tool is incredible as it recommends better strategies to help you achieve your goals.  

There are predictive analytics tools such as the Adobe predictive analytics tool which help organizations to analyze large volumes of data and extract potential information. Accurate data helps you create the right propensity models to run dot point accurate campaigns for best lead generation. 

AI-Powered Chatbots to Improve Customer Experience

Chatbots isn’t a new concept as it has been around for a while. But, progress in this field was rather limited; now, with the new entrants holding expertise in the field of AI and Machine Learning, a new breed of AI-Powered Chatbots have infiltrated the web design and development market. 

The agenda is to create a remarkable customer experience; to enable websites so they understand the user’s query much better. Businesses are already shifting their live chatbots to AI-powered chatbots. 

And here’s how Google describes it: 

“Think about what makes your website unique, valuable, or engaging. Make your website stand out from others in your field.”

For instance, Bold360 is an intuitive AI-powered chatbot which has its own natural language processing technology. It helps brand build chatbots which can understand customer requests. It doesn’t require a keyword matching algorithm to work and it delivers the most accurate answers. 

Use Audience Insight to Boost Search Ads

Do you know that you can now send targeted ads based on your audience interest? 

It is now possible with the help of in-market audiences.

The in-market audience is a way to connect with consumers. It comprises of customers who are searching and comparing products/services in real-time all across the Google Display Network. 

Google explains this with a good example: 

“For example, if you’re a car dealership, you can increase your reach among users who have already searched for ‘SUVs with best gas mileage’ and ‘spacious SUVs.’ In-market audiences use the power of machine learning to better understand purchase intent. It analyzes trillions of search queries and activity across millions of websites to help figure out when people are close to buying and surface ads that will be more relevant and interesting to them.”

Market audience utilizes the immense power of machine learning and unlocks new opportunities for marketers. It enables modern-day marketers to design robust digital campaigns and reach out.

Excel Your Content Marketing with AI Supervised Content

Back in 2016, we all came across this amazing tool called the Wordsmith. It was quite an awesome software as it was the first natural language generation (NLG) engine which turned data into the text at any scale, in any format, and in any language. Approximately, almost 1.5 billion articles were generated on the Wordsmith which sounding quite like an article written by a real-life person. 

Even though AI isn’t up to the mark when it comes to natural-language for every topic, it still pretty much got the tasks done especially for content pieces that greatly relied on data and statistics. 

Today, machine learning algorithms have accentuated marketers ability to create a sense of overwhelming information. It has allowed marketers to assemble large scale of information and optimize it effectively to deliver better customer experience. In fact, it has enabled businesses to generate content using tools like Acrolinx and Wordsmith. The power of artificial intelligence has remarkably changed the content marketing landscape and with deep learning things are getting better.

Some of the major brands such as Facebook, IBM, Microsoft, and Nestle are using Acrolinx. 

According to an article published by Marketing Artificial Intelligence Institute:

“Acrolinx uses a variety of techniques in its multilingual natural language processing (NLP) engine, including machine learning and knowledge-based approaches to ensure the best combination of scalability and precision.”

Delivering a Highly Personalized Website Experience to the Audience

People want to feel special, they want websites to make them feel special. According to a research report submitted by Ever Suggest, in 2016 more than 33% of the marketers used AI to deliver personalized experience. You can display personalized content by offering individual customers web experiences based on their past interactions, devices, location, and other such demographics. 

You can even custom-tailor your emails and automate the entire email marketing process to send regular personalized emails to your customers. There are several moments which you can cash out.

For example, a New-York based startup and e-commerce platform sells diamond with the help of an AI-powered robot called “Rocky” which is able to answer to all the queries associated with diamonds.

In fact, you can purchase a ring that fits perfectly at the best price, all thanks to “Rocky”.

Optimize for Voice Search Queries

Artificial Intelligence has founds its way to voice search queries and natural language long-tail optimization for voice search queries is becoming more common with the passage of time. 

Google disclosed in one of its blog that more than 70% of queries which the Google Assistant receives consist of natural, conversational language and not just the typical searches based on keywords.

It is important that you create website pages which provide you a direct answer to the question normally asked by searchers. These questions normally start with words like “who”, “what”, “where” “when”, “why” and “how.” Hence, it is best advised that you optimize your web pages accordingly. 

Create local landing pages for different locations. You can also opt-in to design separate local website content to target people in that specific area and can even use structured markups to make it all easy. 

In Conclusion

AI is designed to save marketers and businesses investing their time and money in making digital marketing more effective. For example, implementing chatbot in a website will eventually make the lives of sales agents much easier than before. Moreover, AI can deliver marketers immediate insights on which of their ads are performing best or which of their content is becoming quite a thrill in market. 

Artificial Intelligence is not going to put anyone out of jobs; it will just improvise the job for others.

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