How can Machine learning help small businesses to prosper?

The word called “Machine learning” is not new to the marketing world. For digital marketers, machine learning is a channel to make quick data-driven decisions effective for business. If you see carefully most of the tools in digital marketing are because of Artificial Intelligence. If you see in machine learning- polynomial regression, logistic regression, clustering, etc- all actually help in the marketing of businesses. But if you are still incurring losses in your business, don’t ignore, hire the best outsourcing companies in Florida.

What is machine learning?

Machine learning learns itself and improves functioning from historical data without being explicitly programmed. It focuses on computer programs to learn by themselves with the help of past experiences. The primary focus of machine learning is to make machines independent and smart.


Types of Machine learning

  1. Supervised learning-Historical data are needed here.
  2. Unsupervised learning-Historical data are not needed.
  3. Reinforcement learning– Based on the trial and error concept.

Why machine learning is effective in Marketing?

This world is based on probability. Every business decision is probable. Nothing is certain. All the decisions (data-driven) are probabilistic in nature. The role of machine learning in marketing are-:

  1. Clustering– There is a concept of Segmentation in marketing that says to divide the whole population into different homogenous groups. This is basically needed for an e-commerce store or a retail store or any shopping mall. Common algorithms-k-means clustering
  2. Market Basket AnalysisDo you know what items to put besides butter so that maximum people buy butter. Well, association rule mining does exactly the same. This algorithm is very famous among marketers. Common algorithms-association rule mining.
  3. Predicts Sales price-If you are a broker, builder, or common flat owner then sales price can be determined. Also, the net revenue of a company in any year can be determined. Common algorithms-regression
  4. Churn Rate forecasting--Suppose some of your customers want to switch. This is called the Churn rate. We can predict churning customers. Then we can take strategies to retain those customers. Common algorithms- logistic regression, support vector machines, random forest, etc.
  5. LTV forecasting- -It is actually the total profit that is expected from a customer. This is a very good metric to take decisions. -If the LTV is very high, then we can do a big investment. But if the LTV is low, we can go with some less investment. The common algorithms are logistic regression, xgboost, random forest, etc.
  6. Recommendation systemBy this, we can recommend what customers want. This theory is based on Euclidean distance. A common algorithm is k-means clustering.
  7. Google ad words -Most of the algorithms in Google ads (expect manual bidding) are based on machine learning. These bidding strategies provide the best result when used with historical data.
  8. Chatbots -These things are very popular today. Most of the websites today implement chatbots.
  9. Time-series Prediction- -This is useful for seasonal businesses. We can predict the sales of something related to time.
  10. Search Engine- -Digital marketing is dependent on Search engine and search engine learns by the principle of machine learning. Therefore it is dependent on machine learning.

In the coming few years’ machine learning is going to completely change the concept of marketing. One thing is for sure that it is a boon for small businesses. Till then let’s keep our fingers crossed.