How Artificial Intelligence is used in Websites/Web Applications

Last Updated on April 2, 2021 by Henry John

Ever wondered if artificial intelligence is used in websites/web applications? The obvious answer is yes.


And this article will show you how artificial intelligence is being deployed in websites. While we are at it, I could even go inch further to share my thoughts about the effectiveness of deploying/using artificial intelligence on websites.


There are a number of ways artificial intelligence issued in websites, they could be used on the websites (frontend and backend) and off the websites.


Without much ado, let’s get into the business of how artificial intelligence is used on websites.


And oh! I’m supposed to briefly explain what artificial intelligence (AI) is, in case you don’t know clearly what it is. But I have done that in-depth in this other article, do check it out.

AI Content/Product Recommendation System


Most (if not all) website owners, getting their web visitors deeply engaged with their site’s contents is of upmost priority. Really, every webmaster wants their users to stay longer on their site and to stay engaged.


And one of the most effective ways to get users engaged is to feed them with the kind of contents they want, desire or need.


To do this webmasters have to study their users’ behavior in order to understand their interest and then ensure that the users’ are served with contents based on their interest.


It’s a no brainer, serving users contents based on their interest will most likely get them engaged. But this whole ‘serving users contents based on their interest’ is easier said than done.


And this is where artificial intelligence steps in: AI systems are capable of studying users’ behavior, figuring out their interests and ensuring that contents are served/presented before each individual user based on his/her interests.


Examples of websites that deploys AI on their website to perform such task are YouTube, Netflix, Facebook, Pinterest and Twitter.


This explains why whenever you log on to your YouTube account, your YouTube Home is filled with video recommendations based on your interests (online behavior on and off the platform).


That was simple, wasn’t it?


On another hand, not all websites are content based, some are ecommerce sites and their utmost priority (objectively, in most cases) is to get users buying more products.


Flipping the coin, using AI product recommendation systems, ecommerce sites like Amazon are able to study users’ buying habit/behavior, figuring out the kind of products that they would be most likely to buy at a given time and recommend such products to the users as they browse the store.


Using AI in this manner, ecommerce sites have been able to get users/buyers to add more products to their cart (increasing their cart value) than they would have ordinarily.


I guess this explains why you go to Amazon to buy a toothpaste and you end up adding toothpaste to your cart, even though buying a toothpaste is not in your initial budget.

AI Chatbots


Deploying AI chatbots is one of the popular ways websites uses artificial intelligence. There are many purposes AI chatbots serves on website depending on why and where they are being deployed.


In a previous article I wrote about how artificial intelligence is used in marketing, I noted that deploying AI chatbots is one of the many ways artificial intelligence is used for online marketing.


Moreover, I have deployed an AI chatbot on this websites, and the results were quite impressive. The AI chatbot was named monics, and it enabled me convert a lot of visitors to join my mailing list at a conversion rate 1000% more than usual.


However, I had to stop running the chatbot for a number of reasons, one of which was that I wasn’t really selling any product at the time to get an ROI on the expenses incurred running it.


People loved it, evidenced by how often they interact with it and the way at which they do so.


Think of Alexa, Google Assistant or Siri and you will have a clue about what AI chatbots are.


Webmasters often deploy AI chatbots to proffer customer support, generate leads, increase ecommerce conversion or just keep users engaged on their websites.


Starbucks deployed an AI chatbot to enable customers make orders fasters, albeit on their Barrister app.


15 of the Best AI Chatbot Platforms to Increase Your Conversions in 2020


Just in case you are still wondering what AI chatbots are, they like the regular chatbots, albeit, powered by artificial intelligence. Through Natural Language Processing they are able to communicate with users more intelligently, instead of the binary (A or B) way regular chatbots are programmed to run.

Placing/Serving Advertisements


Many websites and blogs like mine make money running advertisements on their sites. To do this, ads have to be placed on the sites and served to users.


Using AI the process of placing ads and serving them to users can be automated. This means bloggers and webmasters alike don’t have to manually place and serve ads like being done years ago (actually some bloggers/webmasters still place ads manually).


Ad networks like Ezoic uses artificial intelligence to place and serve ads on their publishers’ websites. Fortunately for me, Ezoic’s AI manages (places and serve ads, and manage my ad inventory) the ads on my site.


I love automation, when it makes my life easy!


Who doesn’t?


Big websites like Facebook, YouTube, and Forbes also employ AI to place and/or serve ads on their websites.

Detect and Remove Objectional Contents


Websites like YouTube, Facebook, Qoura and StackExchange are filled with tons of user generated contents. And of course, not all contents generated by users are allowed on these websites. So, it’s the obligation of these sites to detect and remove contents that are not allowed on their websites (objectional contents).


Imagine screening contents on a site as big as Quora or Reddit manually and do so effectively. One thing is for sure, it will require a lot of manpower, and such manpower obviously cost tons of money to maintain.


This is a task AI systems have proven to be capable of carrying out effectively and as such, these huge sites that see tons of user generated contents daily deploy AI to detect and remove objectional contents.


Deploying AI systems as such saved Twitter specifically from becoming a “once-was”.

What Facebook and Twitter Are Doing to Remove Bad Content (entrepreneur.com)

Generate Contents


Many bloggers uses AI technologies like Word AI, to generate contents for their blogs. Albeit, technologies like this are far from perfect.


From my experience, I would simple describe them as ‘not good’ enough, but there’s no denying that such AI systems exist and are being used.

Some big websites (especially news sites) often use such AI technologies to generate news contents in real time.

Algorithmic Rankings


There are websites, especially search engines that are built or have portion of the site dedicated to ranking things algorithmically. Some of the sites like Google.com uses AI to make such rankings.


Google Search is really a great example of AI deployment on websites for algorithmic rankings.


The intelligence to match users’ queries to the right set of web pages before deciding which webpages best answers the queries in order based on perceived users’ intent.


If that’s not a demonstration of intelligence, then tell me what is.


Algorithmic rankings powered by artificial intelligence are used in different websites for different purposes, for instance, it is used on Amazon to search for products.

What Next


As you might already know, artificial intelligence is a ‘thing’. And deploying it on websites/web applications is feasible, albeit, in some cases complicated and expensive.


Day after day, new ways to leverage AI on websites are being created.


‘The more we advance, the more our problems become sophisticated’ somebody once said. I find this to be true in this instance, the more web technologies advances, the more sophisticated the accompanying problems becomes.


And the more web-related problems there is, the more AIs can be deployed to solving some of them.

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