The world’s most successful companies set their focus on customer satisfaction. The reason being that customers leave organizations where they are not satisfied with the service. New products with unique and improved features will continue to pop up in the market. Still, the customer would rather continue doing business with companies that serviced them well over time. This is why companies have to pay apt attention to customer loyalty and advocacy. Data Science in Improving Customer Satisfaction The advent of new technologies and the utilization of data science methods on huge amounts of data makes it easier for companies to place laser focus on the factors that cement customer loyalty for their products. Companies across the world now invest time and money in data science, analytics, and statistical testing. Data scientists help businesses navigate their way through the vast ocean of data available to them in a bid to make the right, timely business decisions. How B2C & B2B Companies Use Data Differently Data analytics is a source of valuable insights that can inform how both B2c and B2B companies make decisions about products, marketing, and sales. Though they each have a unique set of challenges, B2c and B2B businesses both collect, visualize, and analyze their most valuable asset – customer data. Both B2B and B2C companies use data analytics to unlock new pathways to increase customers, more profits, and better decision-making. But they access these pathways in totally different ways. So let’s go over the differences between how B2B and B2C companies use data. Sales Data B2C businesses often have shorter sales cycles, with a large part of their revenue coming from advertisements. This implies that the customers need to be engaged for longer and the sales cycle optimized. Leveraging data on the customer’s experience in making a purchase can help point decision-makers in the right direction. B2B companies, on the other hand, have much longer sales cycles. Here, the goal is to minimize the amount of time the customer spends making a purchase. Using data science, the company can improve efficiency and shorten the sales cycle. Data scientists can analyze sales data for insight into improvements in customer experience. Customer Data Since B2C companies typically have more customers than their B2B counterparts, there is usually no shortage of data to analyze. This allows data scientists to analyze several different customer data points related to their experience with the business. Data scientists can use customer data to segment customers accurately and outline better user personas to guide product and marketing initiatives.