“Machine Learning (ML) is no longer an exotic concept for businesses. No matter if you have a small business or a Fortune enterprise, the chances are that you can benefit from the nuances of Machine Learning.”


Machine learning is revolutionizing society around the globe. Naturally, the business sector was quick to adopt these new machine learning technologies for a variety of applications. But for many small business owners, machine learning technology just seems a bit too far out of reach. Thankfully, this is not true. Small business owners like yourself can also benefit from utilizing new machine learning applications at their companies.

ML is becoming more popular and easily accessible for everyone nowadays so the small business owners should not let themselves lack behind. They need to cope up with the changing technological environment and upgrade themselves accordingly. And machine learning can do almost anything today, from getting the feedback from the customer and analyzing it to making the most difficult documents.

Small business owners are always the last to get access to the newest business technologies. Machine learning is the one business application that has been made available to small business owners in its early stages. Once you know how machine learning is different from AI and what exactly it is, you can begin to experiment with machine learning business applications at your company. These machine learning technologies are sure to improve business operations in a number of different ways.


So In this Blog, we will Learn about How Your Small Business can Benefit from Machine Learning :


Before delving into how Small Business can build machine learning solutions, it’ll be helpful to understand what ML really is. If you are a small business owner, you probably can’t go a day without hearing or be reading the phrase “Machine learning”.

“Machine learning is a subset of the wider field of artificial intelligence. In the simplest sense, machine learning is the area of technology where computers are fed large amounts of data which the machine then applies algorithms to. This enables the computers to find patterns and make accurate predictions based on that data without any human intervention”.


For example, If you go to a supermarket and visit the billing counter they must be using some codes to manage the bill and their inventory at the same time. Just imagine if the person had to calculate it manually, it would take a lot of time and the chance of mistake still exists.

Similarly, machine learning can be used and some scanners can be used which pick up the item from your trolly and scan it and make the bill on its own and displays the amount at the last. And the person on the billing counter has to do nothing but stand and watch if everything is going perfect and collect the money at the end.

See, how Machine learning can make our lives so easy and convenient. like you just pick up the items and walk to the counter and pay the money and leave and the person on the billing counter has to do nothing but collect money.


How Can Machine Learning help my Small Business?

There are lots of ways to incorporate Machine Learning. Here are a few of the most prominent ways small business owners have found it useful.


Making Product Recommendations

A great way to use machine learning to grow your business is to utilize machine learning recommender systems. The perfect of example of a machine learning recommender system is on Amazon’s website. Based on the data of millions of customers’ buying and browsing habits, Amazon “knows” which specific products you are likely to purchase. Then it places those products right in front of you.

But recommender systems aren’t just for big companies like Amazon. Any business with an online or mobile presence can develop and deploy one of these systems. Netflix uses one to recommend movies you might like, LinkedIn uses one to predict people you may know, BestBuy grew its online sales using a recommender system, and the list goes on. If you sell products or services online, you too can improve your business sales with a recommender system. The caveat is that these are complicated systems that take lots of time and money to build.


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Fraud Protection and Data Filtering

Depending on your business and platform, you might find it very useful to use machine learning for fraud protection and data filtering purposes. These types of problems fall in the machine learning bucket known as “classification” problems. If you run an online business, these machine learning capabilities may be even more important to you.

Algorithms applied to fraud protection can help decide whether a financial transaction is real or fake. A classic example of machine learning applied to data filtering is spam filtering for email. Based on various pieces of data within the email (and some data not seen by the email reader), algorithms can decide whether the email is legitimate or fake. These types of algorithms can be applied to other problems such as whether a user’s posted comment or content is age-appropriate, against company rules, and so on.




Better Odds At Securing Loans

Machine learning processes have made it easier for new small business owners to secure startup funding. This is perhaps the biggest way that machine learning has improved small business ownership.

Prior to machine learning in finance, it was nearly impossible for new small businesses and their owners to secure traditional business loans.

Now, data science applications give businesses as young as six months old the ability to qualify for loans. This could prove to revolutionize small business. In the meantime, it is an excellent piece of information to keep in your back pocket should you need a business loan in the future.



Improved Decision-Making

Improved Decision-Making application allows small business owners to make more accurate predictions about future business operations. This enables them to make the absolute best business decisions possible for further growth and success. Thanks to new machine learning developments, big data decision making is no longer just for big business.





Easier Social Media Monitoring

Social media monitoring is simplified by machine learning technology. These applications make it easier for small business to track customer interactions across all social media platforms.

This is so crucial for developing an online presence that responds to customer needs and offers top of the line customer service.

It is also helpful for creating online marketing campaigns that customers want to engage with. This way, small business owners like you have more time to focus on the essential business functions that keep operations running.




Dynamic Pricing

Dynamic pricing, also known as demand pricing, is the practice of flexible pricing items based on factors like the level of interest of the target customer, demand at the time of purchase, or whether the customer has engaged with a marketing campaign.

This requires a lot of data about how different customers’ willingness to pay for a good or service changes across a variety of situations, but by Machine Learning Applications, companies like airlines and ride-share services have successfully implemented dynamic price optimization strategies to maximize revenue.




Automated Customer Service

Machine learning can also be used by small businesses to automate customer service online. This is one of the most common uses for AI in business. Chatbots have improved online customer support and the entire customer experience online.

They also cut customer service costs for business owners while providing better, more personalized customer assistance.

If you were considering how to use AI for small business to start bargaining for advantage, bringing chatbots to your online store experience could be a viable option.




Churn Modeling

Customer churn modeling can help you identify which of your customers are likely to stop engaging with your business and why.

The results of a churn model can range from churn risk scores for individual customers to drivers of churn ranked by importance.

These outputs are essential components of an algorithmic retention strategy because they help optimize discount offers, email campaigns, or other targeted marketing initiatives that keep your high-value customer’s buying.




Process automation

As a small business owner looking to reduce the manual workload of your employees and give more strategic positions, process automation is a big advantage.

It lets your employees move up from performing menial tasks to executing a strategy that will move the business forward a lot faster.

It is simply the use of technology-enabled solutions to improve business processes, service delivery or to drive down cost.




Understand and Predict Customer Behavior

the bulk of data on clients and customers include the number of times a customer has bought a particular product, how often they use their credit card at a store, how many times they have interacted with your business digitally – social media, Google Search, etc.

Having knowledge of specific customers, small businesses can then tailor their services to fit their customers’ habits using ML. They can know how best to reach and relate to customers or potential customers online, know when to offer them promos and discounts, and so on.




Finding Hidden Patterns Within Your Customer Base

finding hidden patterns within your current customers’ habits and then utilizing those patterns to sell more products or services is one type of machine learning algorithm called “Clustering”.


These mathematical models find a way to group data sets into meaningful buckets that perhaps a human couldn’t easily do or even consider. In this case, machine learning can help you perform customer segmentation in revolutionary ways. Once you are aware of these new groupings, you can easily tailor your business offerings to a bunch of warm leads and likely increase revenue in a short period of time.

You can contract an outside programmer who specializes in machine learning to create this analysis for you, but you can also utilize relatively inexpensive cloud-based solutions from companies such as IBM and Amazon.



AWS Integration

Small businesses often need to use predictive models to enhance their revenue and sales models. One of the ways to improve these models is through the use of machine learning. Entrepreneurs, who are running small businesses, often don’t have sufficient time or the resources to sift through massive data and derive intelligent decisions out of it; this is where machines learning techniques come to the rescue.

Such business owners can benefit immensely from the use of AWS Cloud-based services and AWS Machine Learning. The vast amount of data which is collected can be sorted, sifted, and analyzed to deliver helpful business-related insight efficiently.

Through the use of machine learning, small businesses can save on operating costs, while at the same time make sound decisions, and earn better profits than before. However, it is import to know that small businesses cater to customers at different stages. For this reason, it’s imperative to understand how customer behavior can change from time to time. Through predictive analytics and machine learning, such tactics can become a breeze.

No matter what the type of business you have, machine learning can come to your aid at any given point in time. From data collection to data storage and insights you can have it all; it not only helps enhance your business’s image through the use of chatbots but also helps you manage your inventory efficiently. Such is the power Machine Learning gives to its users.

For every small business owner out there, there is a unique benefit that you will get with the use of AWS Machine Learning techniques. It all depends on how you use the services to meet your company’s needs and wants at the end of the day.

Here are some of the main MLaaS providers:

AmazonML: Amazon Machine Learning: use cases and a real example

Google Prediction API: Google Prediction API: a Machine Learning black box for devs

AzureML: Azure Machine Learning: simplified predictive analytics

BigML: BigML: Machine Learning made easy

Datoin: Build Intelligent Apps.

ParallelDots: ParallelDots

DeepAI: Enterprise machine learning as a service

Deep Cognition: Deep Learning Studio simplifies AI development and deployment

Ersatz: Hosted deep learning with GPUs

ForecastThis: automated predictive modeling solutions

Google Prediction API: Google Prediction API: a Machine Learning black box for devs

MLJAR: Platform for building Machine Learning models

Natero: Customer Success platform that predicts churn and up-sell opportunities

DataRobot: Machine Learning Software – DataRobot

Vize AI: Custom image recognition API

Watson Analytics: Guided and automated analytics from the cloud.

Wise: Machine Learning for Customer Success

Today, one of the most exciting opportunities is the potential to leverage machine learning (ML) to give your business a competitive advantage. ML solutions automate workflows, enhance data-driven decisions and facilitate interactions with customers.

Big players like Google, Facebook, Deepmind, Apple, Microsoft, Baidu, Amazon are the leaders in AI research and winning the race for Artificial Intelligence. Except for those big players, there are few exciting start-ups that are using machine learning and AI techniques to transform various verticals like healthcare, education, auto and retail, Cyber-security, Internet of things, Vision, e-commerce etc.

I have listed few exciting Indian startups whose success might be far from assured but they are holding out the promise of a significantly improved product or service.


A list of Machine Learning (ML) and AI startups in India to watch for :

Active.ai (Active Intelligence PTE LTD)

Active.ai use AI to deliver Conversational banking services and help banks to redefine their digital strategy for the future, bringing in automation and insightful customer engagement. The company’s built for banking technology uses advanced NLP and machine intelligence to enable customers to have natural dialogues over messaging, voice or IOT devices.

AIndra Systems

AIndra Systems have a product called Drishti . which is having the ability to detect and identify people.Images that are captured using these device and sent to a cloud-based server are then processed by intelligent algorithms to detect and identify objects. Subsequently, useful data visualizations are generated for relevant stakeholders in an organization, all in a matter of seconds.


Modernizing Visual Commerce with AI. Their entire algorithms stack is built using Deep Learning which powers their product, and their research arm Artifacia Research remains very active in several deep learning projects across computer vision and natural langauge processing.


Arya.ai is providing the firm with the tools to simplify the process of building Intelligent Systems, creating the “neural network”—a vast computing system that mimics the human brain; which create a cloud system to allow the AI to evolve, learn from its earlier tasks and apply them to the next one.


Embibe, which runs a website and a mobile app, collects data from students, charging only for advanced analysis and personalized learning recommendations. Students can actually improve test scores by fixing basic mistakes using its AI platform.

Fluid AI

Fluid AI beleives that the power of AI can be used across industiries, sectors and use cases. Their team is working hard to bring about a future where our solutions redefine the landscape of what is possible using AI. They provide solutions for Finance, Web, Government and Marketing.


Flutura Decision Sciences and Analytics is an IOT intelligence company that is powering new monetizable business models using machine signals in the Engineering and Energy Industry. It is funded by The Hive a pure play big data fund based out of Palo Alto. Fluturas main offices are located in Houston, USA, Palo Alto, USA and Bengaluru, India.


Locus is a platform for enterprises to manage intra-city logistics for Scheduled and On-Demand deliveries with data analytics tools utilizing automation and geolocation to optimize logistics systems. It has now become essential for the Logistics Service Providers to ensure maximum utilization of their assets with tight control on wastage.

Mad Street Den

Mad Street Den is a Computer Vision & Artificial Intelligence Company building the AI architecture of the future. The company’s mission is to build models of generalizable intelligence on scale, that can be deployed through meaningful applications across industries to billions of people across the globe.


Morph.ai is the most complete Bot suit for enterprises to build chatbots. Chatbots are automated bots that runs over messaging platforms like Facebook messenger, web chat etc and help enterprises automate customer support, sell products, generate leads and many more over chat.


They have a product called Alex. Using Natural Language Processing and Machine Learning, Alex accurately and efficiently manages your calendaring needs seamlessly.


Netradyne is creating a groundbreaking AI platform to disrupt commercial vehicle and driver analytics. They first introduced the commercial vehicle technology provider to combine A.I. with video to detect, reason and determine causality of events. This allows the fleet to quickly apply resources; recognizing superior performance or addressing at-risk driving before it becomes a severe event.


Niki.ai aims to be the one-stop solution for a customer’s order. The startup leverages natural language processing and machine learning technologies to converse with customers over a simple chat interface, and places their orders with their partner businesses within seconds.


SigTuple builds intelligent screening solutions to aid diagnosis through AI-powered analysis of visual medical data. which helps to analyse visual medical data efficiently.


qure.ai started by folks from Fractal Analytics and IIT Bombay. They are using cutting-edge deep learning technology to help diagnose disease and recommend personalized treatment plans from healthcare imaging data.


Zenatix is the leading provider of IoT based energy monitoring and control products. It is a data-driven energy efficiency company using advanced machine learning based models to provide significant energy savings for large commercial consumers of electricity. The models are built by collecting and analyzing millions of previously unseen (“dark”) data points every day from electrical assets. They have office in Gurgaon.


Final Thought: It’s Time To Build

Machine Learning & AI is permeating our lives in larger ways than we can think. With most companies turning to data companies, the demand for tools and resources that can make sense of the piling data has increased many folds.

Machine learning is certainly here to stay, and as its adoption among businesses begins to grow, its capabilities will increase and the costs associated with using it will go down. It is very likely that your competitors will use the technology going forward, and for your business to stay competitive, you should continue to stay aware of the news and changes in the machine learning sphere so that you know what machine learning technology is available for your business.

Now is a great time for Small Businesses to use machine learning to give their businesses a leg up. The availability of quality algorithms and the wealth of data generated by SaaS products have made it possible for small business to effectively train their own ML models. In addition, cloud vendors have begun making several of their own proprietary ML models available as a service.

Machine Learning is fast becoming a crucial asset for small businesses. It can help boost growth and enables smaller players to compete with much larger organizations. “Your company may be small, but by making use of correct data analytics, it’s future can certainly be big”.

Thanks for reading, we hope you found it useful.

There are so many other useful applications of Machine Learning for Business.

If you want more information also read this blog : Machine Learning Applications for Businesses


Yatindra Sahu

Data Enthusiast


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