Pick any segment of the business. You will not find the sole player! What does it mean? It simply means that almost all markets are intensified and to survive in such a market, you should not give a single chance to users to alter their choice. For that, you have to list out the preference of each user and show them only those products/services which they are interested in. You can do many more thing. But ‘Personalization’ is in the centre – “Personalization is a means of meeting the customer’s needs more effectively and efficiently, making interactions faster and easier and, consequently, increasing customer satisfaction and the likelihood of repeat visits.”
So, how do you offer a personalized experience to users? There is only one way you can actualize it – by using machine learning and AI technology.
In this blog, I will list out 5 real-life examples of providing a personalized experience to users by employing different machine learning and AI algorithms. But before discussing that, let me tell you the difference between Artificial Intelligence, Machine learning, and Deep Learning.
Difference Between AI, Machine Learning And Deep Learning
Generally, business owners can’t draw a line between AI, Machine Learning and Deep Learning easily, and thus they can’t put it in practice effectively. So, let me keep this really easy for you.
AI is technology (as well as technique) which makes the machine act and think like a human. In other words, If a machine solves a problem using some rules like a human, that machine is called AI-enabled machine.
Machine learning is nothing but the subset of the AI and it is very serviceable to find relations and meaning between different attributes of the big data. Using this meaning and relations, a machine learning algorithm can do prediction.
And deep learning is the sophisticated version of machine learning. To understand the difference between machine learning and deep learning. Suppose, you upload an image of a dog on a machine and the machine is supposed to identify whether it is a dog or cat. So, if you want to achieve the task with machine learning algorithms, you have to give attributes such as skin colour, tail length, eye shape, nose shape etc. Based on these attributes, the machine learning algorithm identifies whether it is a cat or dog. Whereas, in deep learning, you don’t have to give attributes. Algorithms automatically define the attributes and come to the conclusion.
Deep learning is useful to solve complex tasks. Meaning, you really do not need it in your online business. Machine learning is capable of solving some of the very common online business problems. So, now let’s discuss 5 different ways to apply machine learning on online business. (Since we are talking about the online business, we assume that you own a mobile app or website of your service/product.)
5 Easiest And Most Affordable Way To Apply Machine Learning On Online Businesses
Following are the 5 best ways to apply machine learning to online businesses. But to make learning more rational, I will link one usable machine learning algorithm with each way. After all, ‘machine learning’ is all about ‘machine learning algorithms’.
1. Knowing User Behaviour – Using Genetic Algorithm
Suppose, you are running a brick-mortar store. In that store, you display or place black trousers and white t-shirts far from each other, even if you know that people who buy black trousers prefer to buy a white t-shirt. What will happen? You will lose the sale. Right? Same happens in online business. Every user has a different buying pattern. But by studying the buying pattern of users of the same user group can help you (business owner) to come to an optimal buying pattern which is known as the rule in machine learning technique. These rules are generally in the form of IF and THEN. For instance, IF people aged between 18 to 30 who buy black trousers cost around $25 THEN they also buy the white T-shirt cost not more than $18. So, now when you have such data, you can show a white T-shirt which costs less than $18 to a buyer who has just bought black trousers. By doing so, you can double the sale. But the question is how can you define such precise rules?
Well, there is a machine learning algorithm called Genetic Algorithm which can be useful to define the rules. So basically, the genetic algorithm takes big data as the input and processes that data to come up with the optimal solutions. Using the values these optimal solutions have, the genetic algorithm makes the rule. These defined rules are later compared with details of the users to identify the preference of the users.
2. Classification – using Naive Bayes Classifier Algorithm
A mobile app or website of the business contains lots of data in terms of images and texts. If you want to apply machine learning on your business, you should classify the screen content of your mobile app and website. But classifying website or mobile app content manually takes a lot of time. Instead, you can deploy a classification machine learning algorithm known as the Naive Bayes Classifier Algorithm. All news app and apps like Pinterest app are working on Naive Bayes Classifier Algorithm and whenever new news or image is added, the algorithm places that content in the relevant category.
3. Showing Exact Search Result In E-Commerce App – Using K Means Clustering Algorithm
Showing precise results is the most fundamental requirement of the e-commerce app. But when there are many products in the inventory with the same name or similar name, conventional search modules of the e-commerce app gets confused and show irrelevant results. For instance, if a user searches for Apple smartphone and app module shows him apple fruit, that user will straightway use another site to make a purchase. So, to avoid such a situation, K Means Clustering algorithm is very purposeful.
K Means Clustering Algorithm makes different clusters and puts relevant items in those clusters. For instance, it places an apple in Fruit cluster and Apple in smartphone cluster. So, next time when a user searches for Apple smartphone, an e-commerce app shows data from the smartphone cluster.
4. Forecasting – Using A Linear Regression Algorithm
Businesses have to make many changes in their business model. But while revamping the business model, the major concern of them is the negative effect of demand. (They always have fear of losing customers if they increase the price. )
But, what if you can know how price change will affect the demand? Well, it is possible using Linear Regression Algorithm. It studies the historical data of your business and calculates the dependency of more than one attribute on each other. It then shows what will happen to other attributes if you change the value of one attribute.
This is a very popular algorithm in all big companies like Walmart and Target.
5. Matching – Using A Matching Algorithm
Almost all service providing companies offer apps from which users can book the service. As soon as the user books the service, the app selects the most suitable service provider and sends him the request for the job. For better user experience and quick service, the app considers many factors to select the most suitable service provider. But still, it fails to offer the ultimate result, unlike machine learning-based matching algorithms which learns from the past data and give a precise result. Almost all service providing companies like Uber, Grab, Go-Jek, Lyft, DoorDash, Deliveroo are finding the most suitable driver/service provider using a machine-learning-based matching algorithm. However, this is the custom algorithm which means your technical team has to create it specifically for your app or website. So, if you are planning to develop a taxi app or food delivery app, make sure you check the capabilities of your hired taxi app development company to integrate machine learning-based matching module in the app.
Amid rising competition in the market, a business owner should deploy the latest technology to survive. Machine learning is the best technology which can do justice with the businesses in all possible ways, regardless of the segment of the business. However, business owners seem confused when it comes to applying machine learning to their online businesses. So, in this blog, I have listed out 5 simple ways to apply machine learning in online business. These 5 steps are simple and affordable. But to actualize them, you have to ask your hired app development company as machine learning is not as easy as pie!