If you type “what is machine learning?” into Google today, the results would be a mess of scholarly articles, forums, and jargon. This blog post simplifies the definition of machine learning and presents a few examples of how businesses are using machine learning.

What is Machine Learning?

 “Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.”

Below are three common machine algorithms that are common within the business world.

Customer Lifetime Value Modeling

Often, businesses consider Customer Lifetime Value (CLV) be one of the most important for them to employ. CLV is commonly used with a marketing concept because its purpose is to represent what each customer is worth in monetary value. This can help a marketing team identify how much they should be willing to spend to acquire each customer, especially in direct response marketing.

Customer Lifetime Value Modeling Examples:

  • Bonobos: Insights into which channels are attracting the highest-value shoppers has helped Bonobos increase the predicted lifetime value of its new customers by 20%.
  • Netflix: The average Netflix customer stays on board for roughly 25 months. According to Netflix, the lifetime value of one of its customers is $291.25. Netflix realized their customers were impatient waiting for movies and in response added a streaming service. By tracking these stats and behavior, Netflix has reduced its customer churn by 4%. That doesn’t seem like a lot but considering Netflix has 137 million subscribers, that adds up.

Churn Modeling

It is not a secret that customer retention is extremely important for many companies. Acquiring new customers can be several times more expensive than retaining existing ones. Churn modeling can help identify which customers are likely to stop engaging with a business and why. With this information, businesses can build retention strategies, discount offers, email campaigns, to keep high-value customers buying.

Churn Modeling Examples:

  • Subscription services. For example, cable or internet companies. Customers that are likely to churn at the end of their subscription are contacted and given special offers or discounts.
  • E-commerce. For example, Amazon.  If a customer isn’t buying anything for a long time, they are being sent a promotional offer to buy again.

Recommendation Engines

Another way that machine learning can help drive business value is through recommendation engines. Recommendation engines sift through large quantities of data to predict how likely any given customer is to purchase an item or enjoy a piece of content and suggests it to the user. These recommendations can be based on items such as past purchases, demographic info, or their search history.

Recommendation Engine Examples:

  • Best Buy: They began using a recommendation engine in 2015 at a time where brick and mortar stores were in a severe downturn. In 2016’s second quarter Best Buy reported a 23.7% increase, thanks in part to their recommendation engine.

Conclusion

In conclusion, to put a face on what machine learning is, we discussed three common machine algorithms within the business world.  These help put a face on what machine learning is and how it can be drive value within a business.


Free eBook Download

In the eBook “Having a Conversation with Data”, learn what the current BI infrastructure has been and associated challenges with the traditional approach. How important the user experience is in order to best maximize data’s value (think visualizations!!) to your organization and how to gain a competitive advantage with modern analytics platforms. Click here to download.

Kiel Briggs

Kiel has 10+ years of experience delivering reporting and analytics solutions across many industries. He is a member of the eCapital Analytics Team where he specializes in data visualization, machine learning and system architecture.

Leave a Reply

Your email address will not be published. Required fields are marked *