Machine Learning Techniques to Optimize Enterprises

Every business (be it a small Chaiwala or a large MNC) looks forward to increase their turnaround as they grow. On the way towards their growth, they need to compete with their peers and be at par with them to remain in the market. The growth of any business is dependent on their business model, hence it needs to be continuously reviewed and optimized as per the market demands. Machine Learning can help a business in doing so with much ease. There are a few machine learning techniques that can help optimize a business.

1) Regression Algorithms:
Businesses are interested in knowing what a specific customer might want to do when he/she access their website. They try to predict that with the help of customer’s previous recorded activities, hence Regression Algorithms come into the picture. It helps to make a prediction based on given recorded data sets. It learns trends in the data sets and predicts based on linear variables. It is better to have large datasets for such algorithms as they learn utilizing them to provide better result. This gets better over time as more data pours in to the website and results in better predictions on the customer’s behavior. Many of the big enterprises like Amazon, Facebook, Google etc. utilizes this to provide us with the suggestions. This increases their overall sales to a great extent.

2) Clustering Algorithms:
It’s very common among different businesses and companies to look for the customer existing for their business. So, is it like one single group that buys from a company? or are there customers from different niches having a unique problem that company’s product is fixing. Clustering algorithms answers these questions. As the name suggests, it can ‘cluster’ the available data together into groups. For e.g., an e-commerce website that sells clothing and makeup wants to determine different types of customers who buy on their website. This information is further utilized to create custom content marketing for each group so that it can drive more sales and customer traffic.

3) Classification Algorithms:
Once the enterprise figures out the groups of customers who exist for their business, they want to know how to classify new visitors on their website so that they can adapt the website content to best suit their needs. In such scenarios, classification algorithm plays its role to ‘classify’ a new data point into a specific category or group. This helps pull the customer once they visit the website.

Big Enterprises utilizing Machine Learning

a) Google:  Google is considered as the frontrunner on the track of AI, Machine Learning and Deep Learning. It is evident from the continuous upgrade that they have been bringing up to their customers. One reason behind this may be the amount of money that Google has spent acquiring start-ups working on AI. The strongest point of Google in this area is probably the wide range of cloud-based services that it offers to developers, including various Google Cloud AI machine learning tools.
b) IBM: IBM has been working in this arena for long. Be it Deep Blue Computer of 1990s that challenged Garry Kasparov or Watson AI Computer that best the best of the contestants on a US television quiz. Watson Machine Learning is as good as Google Cloud AI machine learning tools, but high pricing prevents users from utilizing it at its best.
c) Microsoft: We all know that Microsoft has its visible presence in the technology market. The credit for this partly goes to different acquisitions that Microsoft has been doing for the last couple of years. If we look at the statistics as per CB Insights, It has been at the third spot when it comes to spending on different acquisitions over the last five years. One of its major acquisitions  was when it acquired LinkedIn for US dollars 26 billion$, a few years ago. It helped the company  to be competitive in the internet market. LinkedIn may provide one of the best platforms for Microsoft to demonstrate the enterprise applications that it develops using machine learning.
d) Baidu: Baidu is one of the Chinese search engines which has been very active in utilization of Machine learning and Natural Language Processing. It has also been very much in to the mergers and acquisitions so that it can make the best out of all. Baidu has been working towards the development of a workable voice-activated search function using NLP (Natural Language Processing).
e) Apple: We all know that Apple as one among the most valued companies in the world. Although Siri has been assisting all its iPhone users, still many feel that Apple is a latecomer into the machine learning arena. That’s probably not true. Apple was the first to launch any kind of voice assistant on a smartphone which is popularly known as Siri. Apple is looking forward and working towards extending the talking assistant application through HomePod- its new Smart home service.
f) Intel: Intel has been known for its processors and it’s been ruling  its kingdom for a long period. We should be aware that processing a set of data for AI or machine learning apps is different from usual software applications. Machine learning applications need less processing speed and response time. Hence, Intel is working towards building a new generation of chips which will be much more capable of running applications utilizing AI and machine learning concepts.

Interesting Statistics:
As per a recent study by Apptus,

  1. At least 40% of the companies surveyed have been already using machine learning to improve marketing and sales performance. 
  • 38% of the companies think machine learning helps them improve in their sales and performance. 
  • 76% of the companies say they are targeting higher growth in sales with machine learning. 
  • Many of the European banks have realized that their new product sales increased by 10% and churns reduced by 20%, credits to machine learning intelligence.