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Artificial Intelligence for Customer Behavior Analysis: A Practical Use Case

You can think what you want about Artificial Intelligence and Machine Learning, but one thing you can't deny that it's wider adoption is just around the corner. The prediction of customer behavior was always a tricky task for marketers all over the world. But now, with AI/ML innovations that get on the entirely new level, never before imagined!

Introduction

The more the businesses know their customers, the better. To provide the best customer experience, you need to know as much information on your customers as you can. Getting this information is pretty hard if you use traditional methods. However, with the power of Artificial Intelligence, it could be much more effective. Seventy-five percent of companies that have implemented AI and its subdivision, Machine Learning, are boosting customer satisfaction by more than 10%, according to Forbes.

 

Analyzing customer behavior with the capabilities of AI could save an enormous amount of time, compared to human employees. All the errors that people could make would be eliminated. But that doesn’t mean that data analysts are becoming useless. No, the experts in this scenario will be used for more sophisticated tasks, while machine intelligence will take on routine ones.

 

Gartner reported that AI-driven business value will expand to $3.9 trillion in 2022, while 40% of the work of data scientists will be automated by 2020. That means that 40% of the work of human experts will be automated, giving room for more nuanced activity. But that’s the future; let’s look at the current situation on the market.

Customer behavior analytics for retail

Nowadays we are witnessing a very exhausting battle. There are an enormous number of companies and brands competing to hear and understand their customers faster than their competitors. While businesses are used to reacting to customer interactions, events, and behavior in real-time or after the fact, it’s getting obvious that it is not enough. To keep user experience at the highest level possible, something else must be done.

 

That’s where Artificial Intelligence comes into play. This technology has all the potential to transform the way retailers interact with customers. In particular, AI can offer deep CRM analytics, more valuable insights on customer behavior, expectations, tastes, and wishes. If done right, AI can empower companies with the ability to offer the right products in front of the right clients when the time is right.

 

Unfortunately, companies invest in strategies and tools that are built to react to customer interactions. As a result of these methods, customers receive products and offerings that are already slightly or completely off track with their current preferences and wishes. No wonder it turns into lost opportunities, waste of resources, lack of Return On Investment, and less revenue.

 

Intelligent analysis of customer behavior is the only thing that can change this scenario in 2020. Relying on guesswork is next to impossible to make an accurate prediction on a potential purchase, the success of a certain marketing campaign, or the ability to create unique and personalized individual customer experiences.

What makes Artificial Intelligence for customer behavior analysis great

Artificial Intelligence and Machine Learning are specifically what retailers and marketers need. Advances in these technologies allow the segmenting of content and products for customers based on analyzing and understanding their purchasing habits. But personalization is not effective enough. Retailers need solutions and tools that will individualize interactions with customers and increase brand loyalty.

 

AI can provide individualized customer experiences by forecasting how customer behavior will influence current business models, and help change marketing campaigns.

 

This could be achieved by AI/ML data analytics tools that are able to offer projections of metrics like customer loyalty, affinity, estimated transaction value, and purchase probability. This information could be used by marketers to adjust their campaigns on the fly, allowing them to change tactics, individualize offers, and decide what to do next.

 

Artificial Intelligence and Machine Learning offer some obvious and clear benefits for retail businesses. With the power of these technologies, marketers would be able to correctly forecast the value of individual customers, as well as the potential revenue from certain segments of the client base. As a result, marketing budgets will be spent more effectively and generate more profit for retail businesses.

Originally posted here

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