03/01/2019 dehtrain

Rank SEO with AI Artificial Intelligence


Ranking Your Website SEO with AI Artificial Intelligence Tools

Do you know the use of AI in digital marketing? At present, digital marketing artificial intelligence is used to collect ad targeting data, determine content relevance, experience multi-segment customer segments, streamline ad campaigns, and evaluate the emotional values that disturb the target market. However, only some organizations use artificial intelligence to improve search engine rankings.

AI is not always static or it is a growing machine designed to classify, classify and present data that is most likely to meet customer needs. Artificial intelligence skills will improve the future of SEO, in addition to simple keyword keywords.

Marketing using AI - Artificial Intelligence Training Malaysia

Marketing using AI – Artificial Intelligence Training Malaysia

AI help It improves the data communication of the people

Natural language processing (NLP) and machine learning (ML) are features in a broader field of artificial intelligence that can be used to improve product findability, the overall customer experience, and improve dealer goals.

Speech recognition, NLP and natural language understanding (NLU), natural language generation and text-to-speech are all functions that allow people to interact with computer systems using spoken and written phrases. Well-known examples are Siri, Google Assistant and Alexa. Consumers can use it to communicate requests directly without having to communicate through a user interface on a device (eg mobile phone, tablet, laptop, etc.).



If you are looking for something in the AI / SEO technology, the results shown will retain many considerations such as your region, search history, favorite sites, and other customers who click on the same issue in memory. The improvement of AI means that you can ask from the question of changing the ranking factor, because the click type algorithm is the learning outcome on learning and determines which factors must be considered most relevant in each search.

This type of search algorithm has so far led SEO practitioners to be able to abuse the system – and always think in a more innovative way to bypass Google’s authority. As customer satisfaction is at the forefront of the online industry, it is important to make search engine results more versatile and effective for customers and search engines themselves. Here, KI successfully developed an important factor.


Basically, NLP translates spoken words to capture the user’s intent, and when intelligence is used in conjunction with the user’s context, intelligence can look more than just “artificial.” For example, if you ask Siri, “How cold is it outside?”, The technology uses your GPS location to determine and retrieve the outside temperature.

This feature can be further enhanced by syncing with your calendar, such as determining that you want to fly to another city and proactively providing weather information. If your thermal jacket can be picked up, please remember the dry cleaning. Your self-driving car can give instructions on the way to the airport. The AI can then provide the opportunity to make transactions for these experiences, such as coupons or events that can be used in a dry cleaner or airport lounge.

Other cognitive methods such as Deep Learning and Predictive Modeling can go one step further. With advanced monitoring and unattended ML techniques, advanced models and algorithms can be created to adaptively learn and get better predictions.


The AI customer service revolution is here

AI can help understand the contents of each customer

Marketers already use large data and predictive analytics to personalize – aggregated buying behavior to identify patterns and deviations. The logic is as follows: The larger the dataset, the stronger the algorithm is used and the higher the probability is. For example, if some people buy it, they will be promoted. But as machines and deep learning become personal, it becomes more personal in real time.

AI It allows you to learn dynamically

Daily dynamic volatility is one of the biggest challenges facing price managers. Uber is a common example of high demand time. For e-commerce companies, the platform can manage this offer and demand at the ML to segment the customer base. It gives the company the opportunity to better determine the price a customer is willing to pay at the individual level at any time. He will also review information about the client’s intent and determine the price he is willing to pay, which will exceed the purchase limit. However, multiple data needs to be collected, including customer interactions and purchases, global navigation behavior and business information such as product information, price options, inventory and delivery. .

Therefore, when customers interact with them, the company can “adjust” the price to help determine a more appropriate price. This dynamic real-time price optimization combined with extensive customization should be the goal of any brand to keep customers while balancing revenue.

The neglected advantage of artificial intelligence may be the way e-commerce and customer service change, away from clumsy chat bots, using a more intuitive and natural system. AI/ML technology provides a hidden pattern in user behavior to “learn” intent and the next step or identify proposals that provide the best chance of success. While using NLP, customers can also get a better experience, and the business unit can get valuable information. It is a successful solution for customers and brands.


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