Loyalty defines the strength of your customer relationships. High-loyalty customers can have a higher average spend and can have more repeat purchases than low-loyalty customers. For example, research has shown loyalty program customers spend 6% more than non-loyalty customers. Not only that, but loyal customers are often your biggest fans; these are the customers that tag your brand on social media, use your hashtags, and tell their friends about your products. In some cases, a loyal customer can be more valuable than a new customer who makes a single purchase, which means the more loyal customers you have--and the more loyal they are--the better.

As an Applied Data Scientist at Civis, I implemented the latest data science research to solve real-world problems. We recently worked with a global tool manufacturing company to reduce churn among their most loyal customers. A newly proposed tool, called SHAP (SHapley Additive exPlanation) values, allowed us to build a complex time-series XGBoost model capable of making highly accurate predictions for which customers were at risk, while still allowing for an individual-level interpretation of the factors that made each of these customers more or less likely to churn. To understand why this is important, we need to take a closer look at the concepts of model accuracy and interpretability. Until recently, we always had to choose between an accurate model that was hard to interpret, or a simple model that was easy to explain but sacrificed some accuracy.

Putting the client at the focal point of the business today is in excess of an expression; It is an extensive methodology that any organization that needs to turn into a forerunner in its industry should execute. Notwithstanding, realizing the client isn't in every case simple: it requires steady and perpetual exertion, just as apparatuses fueled by Artificial Intelligence (AI, for example, chatbots. "An ever-increasing number of organizations are understanding that chatbots have different advantages. They are not simply virtual assistants, they are apparatuses that add to business development, since they permit us to know and comprehend the buy inspirations and the interests of clients dependent on the connections they have with them, including the after-deals needs of their buys " says Gustavo Parés, CEO of the Mexican organization worked in Artificial Intelligence, NDS Cognitive Labs. He also said that chatbots have the advantage of being able to get information'first-hand'.

I have a colleague who was refinancing his house a couple months ago. He was working with one of the top five U.S. banks that he's been banking with for his entire adult life. The mortgage branch of the bank required him to send documentation confirming that he was a customer of the bank. After decades of being a loyal customer, being asked to prove that you've been a loyal customer is frustrating enough to go bank elsewhere. If you define customer experience (CX) and employee experience (EX) as two distinct entities, you may think that the "mobile form downloads" that were available to my colleague was a great customer experience because he didn't have to go into the branch to submit the documents.

Personalization is something that has become critical to a brand's success, regardless of the industry. Customers expect a personalized experience across all touchpoints including web, mobile, in-store, email and many more. To succeed in your marketing efforts, you need to understand how customers interact with your brand, and then customise their experiences across the journey. To better understand the role of personalization in the ecommerce sector, we had a discussion with Mr. Shashank Misra – Senior Product Manager at Ferns N Petals (FNP). Read on to know more about how companies like FNP have successfully grown over the years by leveraging the power of personalization and recommendation engines.

Artificial Intelligence (AI) and Machine Learning (ML) are some of the hottest topics right now. But most people don't understand it well. But in this article, I will describe the simplest description of deep learning. The basic idea is to make this article as simple as possible which will give the reader an overall idea about the working principle of deep learning. There are some basic terms which we need to understand first.

Fintech or Financial technology is the industry that delivers traditional financial services in a technical manner. The industry has been there for a long time but made significant growth in the previous few years. New cryptocurrencies and payment solutions are surfacing, and the industry is projected to make significant growth of $309.98 billion at an annual growth rate of 24.8% through 2022. All this growth is due to huge customer value from consumers around the world. As the competition of FinTech is with a decades-old industry the need to retain loyal customers is important.

Artificial Intelligence offers a plethora of opportunities to bring a change in almost all spheres, be it health-care, education, e-commerce, research. Can marketing be left behind? With the abundant data and self-learning nature of AI-powered algorithms, retailers can leverage the power of AI to cater to customers and drive sales. AI is revolutionizing the shopping experiences by making them more personalized, fruitful, efficient, and relevant. AI not only helps shoppers find a perfect product but also recommends products, predicts the shopping list and speeds up the checkout process.