Analytics is Changing the Automotive Industry From Good to Great

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Written By EricAdamson

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Combining smart technology and the automotive industry has transformed the way that adventurers seek thrill and the way that even the most technically challenged drivers navigate. Big data analytics has allowed for rapid growth in the automobile industry over the past decade. The automotive industry is advancing in many ways thanks to big data analytics. This includes improving vehicle safety through cognitive IoT, decreasing repair cost and increasing uptime with predictive analytics. Carwatch Weekly compiles a summary of vehicle recalls that were published during the week prior. Although we get our data from various regional markets, we do not claim to have all the information.

Analytics is helping the automotive industry to develop
The Digital Economy is Challenge to Automotive Companies’ Retailing Norms. Automobile manufacturers now offer 24/7 connectivity, expanded access channels, and seamless digital experiences across all channels. Audi has partnered with Adobe to offer a consistent brand experience. The Audi website is no longer a place for corporate information. It is now a destination that Audi customers and long-time Audi enthusiasts can visit. Visitors will find current news, dealer links, vehicle guides, and an interactive Audi Configurator, which allows them to create their own cars.

Predictive analysis for customer satisfaction and building smart cities – Cars have 50 sensors that collect data about speed, emissions and fuel consumption. They also record data on usage for resources and security. These data can be used to identify patterns and prevent quality problems from occurring. Analytics can be used to improve customer satisfaction and quality control at a low cost. Automotive industry is plagued by product recalls. Predictive analysis and forecasting tools are being used to reduce the risk.

Telematics allows you to insure the best possible INsurance premiums. Telematics makes it easy for automotive sellers and manufacturers to collect information from various locations and use patterns. OEMs (Original Equipment Manufacturers), can track customers long after the sale has been completed. Data from sensor-driven cars is used to create driver profiles. It includes data about driving habits, speed, turning styles and acceleration.

Automobile Financing – Auto-finance companies collect massive amounts of customer information. Companies can now analyze customer financial histories and preferences using this data. Companies can now combine this analysis with geography and demographics to create personalized financial plans that meet customer needs. Auto-finance companies can offer differentiated services that generate more business leads and protect their customers from fraud and defaulters.

Prescriptive Analytics – IBM says that predictive analytics allows companies to understand customer buying patterns and predict which products they will want, when they will want them, and how many. Prescriptive analytics optimizes production planning, inventory, and supply chain logistics to meet business needs. Prescriptive analytics can be combined with mathematical algorithms, machine-learning and artificial intelligence to recommend the best action plan that will drive specific business outcomes. Marketing Mix Analytics is used in many sectors, including retail and banking, but is now being adopted by the automotive industry.