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Customer-centric automotive data analytics proves maturity

The automotive industry and analytics have always worked in tandem, and now with a shift in focus from product to consumer prompted by market changes and economic downturn.

Automotive organizations have always been reliant on analytics to drive their products, but with the proliferation of data and the changing customer landscape, this dependence has only grown.

While the healthcare and banking industries are the drivers for analytics, the automotive industry is a close follower and maturing its adoption. Rather than building from the ground up, however, automakers have had to invest in their analytical maturity.

The shift in perspective

Automotive organizations are pushing their analytical capacity and working on their maturity. The market conditions have changed, and competition has only gotten fiercer while data availability has dramatically increased. As automotive organizations have shifted their perspective on analytics, data has simultaneously become more available.

"Broadly over the last 20 years or so, there has been a shift from being product-centric to being very consumer-centric in most of my automotive clients," said Ashwin Patil, managing director at Deloitte Analytics.

This shift in perspective has come from economic downturn and technological advancement. Customer-first is the name of the analytical game for the automotive industry -- mining customer data to discover habits and trends.

"What has changed -- and then how I see the pervasiveness grow -- is the ability to have that data broadly available for everybody so analytics is pervasive today, in the automotive space -- the maturity level for that is what is being challenged every day," Patil said.

Great Recession reset

The Great Recession between 2007 and 2009 and the resulting effect on the industry forced large automakers to restructure and look inward. The changes implemented during the following years have shaped the way these enterprises approach analytics.

"All of a sudden, companies were focused on 'what do my consumers need and how do I best serve those needs,'" Patil said.

As the economy declined and consumers became more conservative, sales on high-profit vehicles such as trucks and SUVs declined, and automakers found themselves facing disaster. Inability to predict this habit change helped alter their approach. Automotive data analytics shifted to follow relevant consumer trends based on any and all data available.

Modernization of technology

With semiautonomous vehicles on the road and more connected devices within vehicles, as well as external data sources and web scraping, the automotive industry is rife with available data. This has only increased in time with the greater complexity of vehicles.

"The ability that technology gave them to be able to mine large amounts of data and drive intelligence out of it has just steadily increased," Patil said. "And it's still increasing in that space."

More data has given automakers more information to base their decisions on and permitted their changes post-Great Recession. The automotive industry is now able to track consumer behavior better and better analyze the changes in the market.

Change in consumer behavior

Data proliferation has led to a better understanding of consumer behavior and made purchasing more predictable. The automotive industry adjusted their analytical focus on consumers around the same time because more data became available and consumer behavior altered.

"The amount of knowledge available, the amount of reach available, the amount of competitive intelligence that's available to consumers today has shifted very drastically," Patil said.

This has made for better-informed consumers who can understand the shortfalls across the automotive industry. There has never been more information available to consumers about the products available.

Changing focus effects

Increased consumer and vehicle data led to a new level of analytical analysis in the automotive industry. It isn't just the marketing and post-sale area that leads automotive data analytics but rather each step of the product lifecycle. Information gained from consumer purchases allows for product changes to match the market's needs and wants. This gives automakers the ability to shape their entire process to keep up with a fluid market.

Analytics at the end of the cycle affects the decisions that automakers make within their design department and how they shape their product line. Whether a driver relies on an infotainment system or never uses it, that is factored in for the next model and changes can be made immediately.

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