Each small business has a unique set of problems, but all of them revolve around affordability, and time.
With machine learning, small businesses can save on operations cost, make better business decisions, make more profits and save time through automation of workforces, better sales & marketing techniques, more engaged employees, more satisfied customers & demand forecasting through emotion gauging and predictive modeling.
To know more about how these ideas work, keep reading this post.
What is Machine Learning?
It’s a technique of developing self-learning machines. It consists of data and algorithms. The algorithms are setup to capture, store, sort and analyze data to solve business problems.
The kind of data machine learning algorithms handle is impossible to be processed by humans, due to its size and complex nature.
When we discuss machine learning solutions, we actually refer to technologies like deep learning, natural language processing, and machine intelligence (sentiment analysis, demand forecasting, chat bots, predictive modeling etc) altogether.
How Your Small Business Can Benefit From Machine Learning?
1.To Automate Your Workforces
Amidst the concerns about massive spurt in unemployment rate of humans, why your organization would want automation? It’s because it’s good for business.
Machine learning powdered computers and robots can perform many routine work activities much faster, better and at a cheaper cost. Even activities that involve cognitive skills can, now, be automated.
- Need to assess data to find what type of people would buy your product more? Predictive modeling techniques can be implied to come up with a solution.
- Need to understand if your employee is satisfied with his job? A chat bot can predict that by interacting with the employee.
- Need to understand the market trends and patterns? An ML-based research assistant can help you do that.
Many such possibilities where cognitive skills are of prime importance are now realizable through machine learning solutions.
According to a recent Mckinsey report, through automation, small businesses can reduce work errors, improve quality, speed, performance and business outcomes. Automation may stir about 0.8 to 1.4% productivity growth annually.
Currently, there are less than 5% occupations that can be fully automated but the percentage of occupations that can be partially automated is quite high. Businesses can opt for this partial automation, freeing their workforce for more productive tasks and improving productivity of their employees as well.
Do you know about the 80-20 rule (the Pareto Principle) of management? The well-known rule states that 80% of the results achieved by an employee come from 20% of the work she does. The remaining 80% of the tasks are repetitive and do not contribute to an employee’s productivity. These tasks are the prime candidates for automation.
The same Mckinsey study estimates that over $15trillion in wages can be saved and put to better use through automation. Here’s the automation potential of various sectors. Sectors like retail, food service, manufacturing and accommodation have the biggest potential for automation.
But here’s the problem - there’s no one cap fits all solution available, or even possible in the near future. Each machine learning solution has to be tailored to meet a business’ specific needs. Our data scientists can help you figure out what types of automation you can go for.
2. To Improve Your Sales & Marketing
There are endless possibilities to improve the efficiency of your sales and marketing team through machine learning technologies.
In our post on chatbots for marketing, we have listed five most used ways to integrate chatbots to drive conversations with customers, serve them better and build brand loyalty.
In our post on chatbots for social media marketing, we discuss how machine learning enabled chatbots can boost sales through product recommendations, handle your social media presence, help in social media research and improve your employees’ productivity through automation of several processes.
Facebook uses machine learning to deliver its ads and generates billions of dollars in revenue. Did you know Facebook generated over $12 billion in just the fourth quarter of 2017?
Even Google uses machine learning to deliver better search results to its users. In our post on machine learning and SEO, we discussed how strategies of SEOs and marketers changed drastically due to this technological development.
Retail brands like Sephora, Amazon, Tommy Hilfiger, and many more are coming up with innovative ways to use machine learning to make more money. Read more about it in our post on chatbots for retail.
It’s almost impossible to beat Amazon with its recommendations - upselling and cross-selling. They’re getting better every day. That’s how machine learning works. Once you set the algorithm in motion, the solution gets better at what it does, every day. The more data it collects, the more intelligent it gets.
Small businesses need to understand that while they’re still thinking, all the business giants and Fortune 500 companies are investing heavily in these technologies, making it look like they’ll always dominate. That doesn’t have to be true, as your data makes you unique and can give you an edge.
To prove that fact, you’ll just have to look at the startups that are getting funding these days. The AI-driven startups are being preferred by venture capitalists. Why? Because, it’s this technology that can level the play field.
3. To Get More Engaged Employees
According to a recent Gallop report, nearly 70% employees of a company aren’t actively engaged, causing loss of over $7 trillion due to lost productivity.
These ‘not actively engaged’ employees are the ones that are performing, but not giving you their best. They just don’t care enough about your business.
For a small business, this is a crisis situation. Either you lose money due to these indifferent employees or you invest heavily on HR solutions. Both cost you money.
You have a chatbot that talks to your employees. Depending on these casual conversations, the chatbot tells you which employees are dissatisfied and suggests you a possible solution. The chatbot is your spy but a much-needed friend of your employees. Employees can ask questions, get their concerns addressed immediately and even, share their feedback for you - all through this software.
Many employees actually would love to talk to a chatbot instead of a real human. Why? Maybe because they’re too shy or maybe because they don’t like your human HR professional and don’t feel comfortable with her.
Machine learning is solving many HR problems - recruitment, employee retention and employee satisfaction. So, wouldn’t it be better to have a machine learning powered HR solution?
4. To Deploy Emotion Gauging
I read a very interesting thread on Reddit a few days back. It was about funny incidents that happened due to people imagining that others don’t understand their native tongue.
So, there were these two people having a business meeting with Japanese delegates. The two, looking very much Americans, presented their idea. The Japanese discussed it in their native tongue assuming the others couldn’t understand what they were saying. But they could. So, after lunch break, the two go back and address every concern of the Japanese, as if they had some sixth sense.
What if you could do that? What if you could read the brains of your customers?
Your potential customer visits your site, leaves and searches for whether your products are fake or real. In two minutes, he sees a Facebook ad; the copy of which tells them how your products are authentic with proof. There’s no way that person isn’t going to buy from you right away.
It’s possible to do that with machine learning.
Sentiment Analysis is a machine learning technology that uses chat surveys, social media, image recognition and many other techniques and algorithms dedicated to gauge human emotions about a specific topic.
In 2012, President Obama’s election campaign used this emotion gauging to analyze the public opinion about various announcements and policies.
Similarly, small businesses can have bespoke machine learning solutions that can be used to gauge their customers’ reactions and preferences.
It could be especially helpful for food and retail sector, where product planning highly depends on audience demand and social trends.
5. To Save Time Through Predictive Models
Small business owners and entrepreneurs are busy people. They’re juggling too many things at any given time and they simply don’t have enough time to sift through pages of data, trying to make sense out of it or research for hours. Welcome to the club!
However, a smart small business owner also knows that there’s no way around hard work. It has to be done.
Through use of predictive models, it’s possible to gather all the data, sort and analyze it to make intelligent decisions. The only difference is there’s no human intervention. Everything happens automatically.
Using such predictive models, you can improve inventory stocking, be better at demand forecasting and at foreseeing the upcoming trends for better customer service & satisfaction.
Look at this:
- You save operation costs.
- You make better decisions.
- You earn more profits.
- You have more satisfied customers.
- You still have time to do a lot more, because all of the above is being done by machine learning, actually.
Summing up, we can never list down everything a machine learning solution can do for a small business. But one thing is for sure - it’s time to act. Even with limited funds, you can leverage the power of machine learning.
Whether you’re facing a big problem and unable to find the solution so far or you’re looking for business optimisation, chances are the ultimate solution is this new technology.