WHY MACHINE LEARNING?

 

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Churn prediction

Churn prediction enables businesses to predict enough time in advance which clients are at risk to churn and stop using their product/service. Several studies have shown that attracting new customers is much more expensive than retaining existing ones. According to the Harvard Business Review, increasing customer retention rates by 5% increases profits by 25% to 95%.

 

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Dynamic pricing

Dynamic pricing is an e-commerce and retail strategy that applies variable pricing instead of the more typical fixed pricing. As more data is analyzed, optimal prices for items are calculated. Some of the common dynamic pricing strategies include competitor pricing, customer behavior, peak pricing, and customer segment pricing. According to a survey by Ask Your Target Market, 78% of customers said that they compare prices from multiple sources before making their purchase. Today, some of the largest companies in the world including Amazon, Walmart, and Best Buy all employ dynamic pricing in their e-commerce online stores.

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Product recommendation

Similarly to an in-store sales advisor asking you about your preferences and then showing you items accordingly, in e-commerce a software that does this automatically is called the product recommendation engine. Recommendation engine helps to increase the number of items per order, meanwhile increasing customer satisfaction. According to Mckinsey blog, 35% of what consumers purchase on Amazon and 75% of what they watch on Netflix, come from product recommendations.

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Fraud detection

Fraud attempts have drastically increased in recent years, making fraud detection more important than ever. In insurance, 25% of claims contain some form of fraud, resulting in approximately 10% of the insurance payout. In banking, fraud can involve the use of stolen credit cards, forging of checks, misleading accounting practices, etc.

According to Experian 2018 Global Fraud Report, 67% of businesses reported that fraudulent transaction, that is not detected, costs more than a legitimate transaction that is falsely declined, while 69% of businesses reported the legitimate number of transactions, that are incorrectly declined, is a concern for their business.