How Can Small Businesses Leverage Machine Learning?

Businesses are increasingly more interested in AI solutions that can automate business activities, increase savings, and help companies generate more profit. Artificial intelligence and machine learning have already penetrated many business areas and have changed the lives of millions of people – just read about the ways AI can transform your freelance career. 

While it may seem that only big players can afford AI and machine learning, it doesn’t mean that small businesses and freelancers are out of play. The cost of deploying machine learning should not necessarily be that high, especially if you know what tools to use. In this article, we want to show how you can benefit from machine learning, no matter the size of your company.

Pro-tip: Before you dive into this article, get to know the most popular AI terms, so you can get an idea about the difference between AI, machine learning, and deep learning.

Improve ad copy

As marketing knowledge has become more accessible, everyone can now master various marketing channels – send a cold email campaign, use PPC ads, or write a newsletter to email subscribers. As clients get used to the way companies advertise their products, they have become considerably less receptive to their messages.

The Internet is flooded with ad content. That is why standing out as a brand has never been that difficult. While your competitors are using the same strategy to attract the attention of your customers, you can use machine learning to produce content of the future that your audience is more likely to react to. Let’s see an example of machine learning fo creating an ad copy.

Chase, a major US bank, has used the algorithms trained by Persado, an AI development company, to test out the two headlines:

1. Access cash from the equity in your home
2. It’s true—You can unlock cash from the equity in your home.

The test has resulted in the second headline winning the experiment and bringing a 450% increase in conversion. That’s a big difference knowing that the headlines are somewhat similar. So how can machine learning achieve such results? 

The algorithms assess the previous history of user interactions with ads and predict what headlines or ad text can bring more conversions. Small businesses don’t need to hire senior Python developers to achieve the same result Chase did – they can already use off-the-shelf tools such as Persado.

Boost sales

Even a small business can process a huge number of leads – with cold email tools it hasn’t been easier to send bulk campaigns to thousands of recipients. Unfortunately, it can turn out that only a small number of them would turn into paying customers. 

Some people can claim cold calling and mailing is a numbers game – even if 0,05% of leads convert and you send 10,000 emails, you can get five new clients. That’s true – you would end up getting a few clients, but, at the same time, you would infuriate 9,995 other people who don’t find your offer relevant. 

Sending the wrong message to a lead that is a bad fit for your company can only harm your business. Your email deliverability will most likely go down; your employees’ emails will be blacklisted; and your conversion rate will stay low. 

AI for sales is a powerful tool you can use to increase a number of sales prospects. By analyzing the history of the leads that have converted, machine learning algorithms can predict what leads will convert in the future and, hence, should be outreached by your sales rep. 

By prioritizing the leads that have a higher chance for conversion, you can focus your sales effort on the high value tasks instead of sending bulk email campaigns and annoying the majority of contacts on your lead list.

Optimize pricing

There are a lot of factors that impact the price for products such as market demand, product availability, and an overall situation on the market. It is usually the responsibility of a price analyst to analyze these and many more factors on a continual basis and come up with price recommendations. However, the factors determining product price change in real time and the prognosis an analyst prepares can quickly get outdated.

By implementing a machine learning algorithm analysts can perform a much better analysis and update their pricing strategies much faster. While offering the right price that is most suited for a given market, the company introducing machine learning can better protect its bottom line and offer products at the right price that customers are willing to pay.

Provide better product recommendations

When it comes to online shopping, a whopping 80% of customers expect more personalization from brands. It can seem that they expect brands to read their minds and serve the right offer at the right time. As customers’ preferences differ and change, it is not easy to offer them what they want.

Thanks to machine learning, both established and small eCommerce companies can predict what every customer wants at a given time and show the product a customer will most likely choose and want to interact with. 

Machine learning can determine the relevancy of a product to a customer entering an online store based on their previous interaction with the business. For example, eCommerce companies can increase customers’ cart value by showing products similar to those that a customer has bought before.

Automate customer service

Machine learning is not here to substitute your customer support agents, but rather support them in achieving the goal of providing the best experience for customers looking for help. For example, with chatbots using machine learning, the interaction with human beings can be easily simulated. 

Also, chatbots can learn what responses are the best depending on a customer query. Over time, while “learning” new situations, chatbots can become more effective at providing answers to customers. They also can be trained to hand over communication to a customer support agent when help of a human being is needed.

Apart from chatbots, virtual assistants can also become a tool that assists customers at making the right buying decision. For example, with virtual assistants powered by machine learning, your customers can receive product recommendations that suit their needs better after going through a round of questions a virtual assistant would ask through a chat window. 

Sephora Virtual Artist can even recognize colors on images customers send and offer products in the color of a user’s choice.

Pro-tip. Consider bookmarking blogs with tech tips to follow how other brands are harnessing AI and get inspired to test it out in the field for yourself.

Make social media more effective

Better user targeting is one of the social media marketing trends that you can’t ignore when trying to stand out from competitors. This trend applies to social media too. How many times have you heard that your business needs to have a Facebook business page and post on a regular basis? 

However, registering an account on all possible social media channels and posting according to a social media calendar every day doesn’t guarantee success. Just think about how many other companies are doing the same!

Thanks to the social media planning tools powered by machine learning, social posts can be published when your audience is the most receptive to your business content. It means your Tuesday post can be published at a totally different time than your Thursday post and it wouldn’t appear on your profile at 9:00, but at 9:56 to bring you the most engagement. You can’t be that precise!

Predict customer churn

Companies tend to focus on growth by pulling all their effort towards acquiring new customers. No matter how great they are at client acquisition, their effort will go to waste as churn rate increases. 

However, churn is not always easy to eliminate as often customers leave before you even realise they are about to suspend a contract. Machine learning algorithms help you deal with churn more effectively and identify customers that are “at risk” and will most likely churn in the nearest future. 

This process is possible as algorithms learn from the historical events – when customers churn – and are able to find similarities in their behaviour to predict the next churning user.

While machine learning helps you understand what customers are at risk, you still have to prepare a strategy to regain their loyalty before they make a final decision. For example, you could offer some special discounts or suggest more favourable conditions of cooperation. 

Also, machine learning can empower you with insights on the reasons behind leaving. For example, a telecom company can find out that a user decided to stop using a phone service and wants to suspend the contract. Knowing this, they can offer a customer a few months of subscription for some VOD (video on demand) service as this might bring more value to the customer who is no longer interested in using a landline.

Final words

There are many areas where small business owners can benefit from using machine learning. You can work on personalising your ad content or your website. No matter what you choose first to explore, machine learning has got a lot to offer – give it a try!