THE PREDICTIVE OEM Transforming the automotive ecosystem ... O… · 3 “Automotive...

T H E P R E D I C T I V E O E MTransforming the automotive ecosystem through data -driven innovation

2 | Rocket Fuel Institute | Predictive OEM

TABLE OF CONTENTS

INTRODUCTION ....................................................................................................................................................................... 3

THE PATH TOWARD AUTONOMY: Smarter vehicles, more data to drive business outcomes ...........................................7

THE RISE OF ARTIFICIAL INTELLIGENCE ............................................................................................................................. 8

DIGITAL TRANSFORMATION: The accelerating pace of connectivity, mobility, and technology utilization .....................10

URBANIZATION AND DIGITIZATION: Merging with the collaborative economy ..............................................................13

PREDICTIVE OEM: Real-time decision-making for operational agility and better customer experience ..........................15

SNAPSHOT OF A PREDICTIVE OEM ....................................................................................................................................18

FIVE STRATEGIC IMPERATIVES FOR THE PREDICTIVE OEM .........................................................................................20

ABOUT ROCKET FUEL ...........................................................................................................................................................21

ABOUT THE PREDICTIVE VERTICAL SERIES......................................................................................................................21


SHIFTING GEARS IN THE AUTOMOTIVE INDUSTRY

The automotive industry is facing rapid and exciting change. Innovations in technology, an increasingly consumer-centric world economy, and disruptive business models bring both challenges and opportunities to automotive brands.

The good news is, people are buying more cars. Since the economic recession in 2008, the automotive industry has made a comeback, particularly in the U.S. market, where automotive original equipment manufacturers (OEMs) and dealers have maintained performance and growth, fueled by technological and manufacturing innovation. Increasing consumer confidence, moderate fuel prices, and greater credit availability all contributed to the market’s rise in sales.1 People are justifying the purchase of larger, more expensive cars such as sport utility vehicles because gas prices are low. At the same time, new cars are also more efficient across the board, making them cheaper to own, which means that people will buy them even if gas prices are high.

In addition, the average age of the cars on the road has been at an all-time peak, with the average vehicle at more than 11 years old. Consumers finally are replacing their aging vehicles with new cars that are more affordable and easy to maintain.

1 “Driving Automotive Growth through Opportunities in the Digital World,” Accenture, 2015

However, people are buying cars differently than they were a decade ago. The explosive growth of digital technology in daily life and its increasing adoption by consumers around the world has had a profound impact on the automotive buying cycle for OEMs and dealers. In a global survey conducted with 10,000 consumers from eight countries, 93 percent of all surveyed drivers seeking to purchase a new vehicle said they used some form of digital process to research their buying preferences, while nearly two-thirds (62 percent) of them initiated the buying process online, including consulting social media, before entering a dealer showroom.2 This digital auto buying produces a lot of data. And rapid auto sales growth is an opportunity that will be won with data-informed execution.

More than half (54 percent) of the surveyed correspondents feel that personalized and tailored information from industry online channels makes researching a new vehicle easier. A personalized, customer-centric approach is being widely adopted across industries since customers are at the center of the value chain. In fact, customers expect it, and expect immediate response to their demands. As a result, as customers connect with one another and react instantly to social media and mobile channels, OEMs and dealers must react just as quickly to remain competitive and in good graces with customers. Between mobile devices, and social media, there are simply more ways for customers to communicate with one another—which means that brand

2 Accenture, 2015

INTRODUCTION


owners and retailers can create connections with them as well. But it needs to happen quickly and meaningfully. OEM brands understand the need to focus on customers. As a result, they are investing in centers of excellence, agile operational processes, and brand affinity strategies. These agile frameworks are critical for creating both business and customer value in an increasingly fragmented digital environment. Leveraging intelligence about customers will truly make companies more competitive.

Outside of their cars, customers have digital connectivity virtually all the time. More and more, they demand connectivity as drivers inside the car as well. It’s now common to have a monitoring and service channel such as OnStar,® Bluetooth®-enabled phone integration, a user-enabled mobile music platform, and even in-vehicle Internet access. Silicon Valley has arrived in the driveway.

And the digital revolution has only just begun. The way owners engage with their cars is being forever altered by technology. According to a 2016 report from McKinsey & Company, fully autonomous vehicles (AVs) are not likely to

be commercially available before 2020.3 But the technology is already having an impact. Even today, owners can “summon” their Tesla, let their Mercedes S-Class autopilot negotiate stop-and-go traffic, or have their Audi park itself. As digital transformation pushes cars toward complete autonomy, with it comes an explosion of data elements– logistical proxies, if you will–that can drive performance and provide a wealth of intelligence. Never before have automakers or their dealer partners had so much data and the chance to engage with customers in such a relevant, immediate, usage-based way.

This proliferation of data will only continue to increase exponentially. As humanity’s capacity to compute compounds, so will the rate of acquired consumer information and the need to decipher the signal from the noise (Moore’s Law in action). The human mind simply cannot process all the transactional moments generated in real time. Beyond processing, value comes from the ability to govern this data, analyze it, and optimize these moments between the brand and consumer. The fate of businesses,

3 “Automotive Revolution—Perspective Towards 2030: How the convergence of disruptive technology-driven trends could transform the auto industry,” McKinsey & Company, 2016

of all surveyed drivers seeking to purchase a new vehicle are researching via digital media.

are starting their shopping process online before even entering a dealer showroom.

93% 62%


industries, and brands will be intrinsically tied to the ability to leverage and willingness to embrace automated data platforms—particularly artificial intelligence (AI).

Even though fully autonomous vehicles may not claim a significant share of the market until after 2030, one underlying trend is perhaps providing the most significant disruption that will lay the foundation for the future not just in the automotive sector, but also in all of business and technology—the accelerating pace of technological change as embodied in compounding computational capacity and price performance efficiencies. According to Ray Kurzweil, in his book, The Singularity is Near (2001):

“An analysis of the history of technology shows that technological change is exponential, contrary to the common-sense “intuitive linear” view. So we won’t experience 100 years of progress in the 21st century—it will be more like 20,000 years of progress (at today’s rate). The ‘returns,’ such as chip speed and cost-effectiveness, also increase exponentially.”

As the rate of humanity’s capacity to compute compounds, so does the number of users coming online for the first time (3 billion new users by 2020), the number of devices per user (three to five), and the number of opportunities to reach them (more than 120 billion real-time impressions per day). Automotive companies, and especially OEMs, have a tremendous opportunity to leverage big data to better understand their customers, and more importantly, how to engage them across channels and touch points. This includes combining data from media and marketing observations to track demand, sentiment, and brand affinity, while combining this with product-specific data and logistical intelligence acquired from interconnected digital hubs in cars.

Emerging technologies, and the massive amount of data created through Internet protocol-based and mobile connectivity produces fruitful opportunities but also poses a key challenge. Making sense out of all this information requires significant time and effort if done manually and

is subject to theory bias. This is why machine learning, augmented by human interaction, is critical to building a competitive advantage for OEMs in the future.

These technological changes set the stage for a conversation around programmatic marketing—its ability to impact both business outcomes and customer experiences through leveraging signal-rich data. If OEM business leaders can build a cadence around converging customer data with business intelligence and marketing observations to make real-time decisions, they can bolster operational performance and exponentially increase customer value.

How do OEM brands stay competitive in this new reality? They can—and must—capture audience intelligence as a continuous series of integrated moments: a single interaction on a website, an instance in which someone builds a new car online, a connected device that monitors driving behavior, digital research on new wheels for the winter, a smart hub that detects a faulty transmission long before it breaks down, or a fulfilling experience through a call center that solves a pressing problem. These millions of moments in aggregate are data elements that can provide OEM brands with cumulative intelligence to inform how to automate customer service, segment audiences, learn from purchase cycles, and personalize experiences. Brands can evolve their businesses with agility and optimize at scale to provide both a seamless experience for customers and also acquire rich data sets to predict future outcomes for the automotive ecosystem.

Sophisticated business leaders, technologists, and marketers have already started to not only leverage new technologies to achieve insights on purchase behaviors and preferences, but also to use that intelligence to steer their companies toward dominance in wallet share and mindshare.

For the automotive sector, there are three distinct and vital macro themes that are disrupting the industry but can also be leveraged to bolster competitive advantage:

• The path toward autonomy: Smarter vehicles, more data to drive business outcomes

• Digital transformation: The accelerating pace of connectivity, mobility, and technology utilization

• Urbanization and digitization: Merging with the collaborative economy

Understanding these macro trends and building a customer-centric strategy around them is imperative to becoming a predictive OEM of the future. Going forward, successful, market-leading OEMs will be the ones that can quickly leverage large amounts of signal-rich data to impact customer experience and ultimately influence business outcomes and business models.

From this broader yet deeper perspective, we can redefine the way programmatic systems are leveraged to combine business intelligence with audience data. This approach provides a glimpse into a future state in which a holistic source of truth is the standard—dynamic in its ability to make automated decisions to bolster company value.

Predictive OEM is not just a trend or another buzzword that will soon be forgotten. It’s a visionary solution design that combines audience data with OEM business intelligence and logistical analytics to accelerate operational performance. OEMs need to start positioning themselves for a fully connected, mobile, and data-driven future.


10% Electronic Components

16% Electronic Components

44% Software90% Mechanical/

Structural Components

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INCREASING ELECTRONIC CONTENT IN AUTOMOBILES AS A PERCENTAGE OF VEHICLE VALUE

1975 2014

THE PATH TOWARD AUTONOMY: SMARTER VEHICLES, MORE DATA TO DRIVE BUSINESS OUTCOMES


The vision of self-driving cars is a staple in science fiction and popular culture, from Asimov’s I, Robot to South Park. But the time has come. According to McKinsey,4 up to 15 percent of new cars sold in 2030 could be fully autonomous. There are definitely technological, regulatory, and consumer acceptance issues that will need to be resolved before autonomous vehicles hit the road in earnest. However, once these challenges are addressed, autonomous vehicles will forever change the way consumers travel by car. For instance, consumers no longer need commute via bus or train to finish work, text and use social media, or rest while traveling. Self-driving cars can also solve a host of safety and efficiency issues—reducing traffic congestion, eliminating driver error, and drastically reducing accidents related to driver impairment or distractions, such as drinking or texting while driving.

As digital transformation pushes cars towards complete autonomy, manufacturers are already becoming less reliant on hardware and more inclined toward software platforms to power and operate vehicles. According to a report by Global Industry Analysts Inc., the increasing percentage of electronic and software content in automobiles is a growing measure of value—in 1975, electronics represented only 10 percent of an automobiles’s makeup. By 2014, software and electronics comprised 60 percent of a vehicle’s makeup.5

Software is increasingly becoming one of the most important differentiating factors for the automobile industry.6 The program code for the modern car has approximately as

4 McKinsey, 20165 “Automotive Software: A Global Strategic Business Report,” Global Industry

Analysts, Inc., November 20146 McKinsey, 2016

many object instructions as an aerospace flight control system. Prime Research points out that cars already have more lines of code than aircraft and operating systems such as Windows 8 or Apple Tiger.7 Software in cars, growing more complex and comprehensive by the year, will be used to deliver a wider range of features and services, including mobility services, advanced safety, location-based services, in-vehicle content, and remote analytics. Partnerships across technologies and services will grow the user base and reduce costs, leading to increased value for consumers.

More technology and software integrated into cars gives OEMs that many more opportunities to deliver features and functions to continually evolve the product for their current customers. For instance, for any Tesla vehicle, a new platform “pushes” exciting new features to a customer’s automobile even two years after purchase. Drivers get an “update available” notice, similar to what they would get on a smartphone or laptop. Tesla and Nissan, with the Nissan Leaf, can connect to home Wi-Fi. This is the evolution opportunity that technology offers OEMs, if they can decipher the signal from the noise to learn what customers are looking for, missing, or desiring as brand loyalists.

7 “World Car Trends 2015,” Prime Research, 2014

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Microsoft Office

Boeing 787

US Military Drone


Multiple information systems with bi-directional pipes—third-party auto health and intelligence systems, OEM product monitoring platforms, and dealership CRM systems—give rise to a connectivity ecosystem where the Internet of Things can help create business value by elevating customer experience. Automakers need to be strategic about which parts of the connectivity ecosystem they control in order to profit from connectivity and keep the vehicle itself from becoming a commoditized content platform. However, as cars become more connected, automakers will have no choice but to participate in the new mobility ecosystems that emerge as a result of technological and consumer trends.8 We will see significant disruption and an influx of new competition from telematics solutions, software companies, and digital communications systems that will strengthen growth. But we will also see an explosion of data elements. These new data elements are all the more reason to have data integration and activation architectures that enable OEMs to glean insight from information. Soon, advanced algorithms will be able to help determine what OEMs need to build next—one feature at a time–and improve the way they produce each feature at scale. With the advent of artificial intelligence, these algorithms can now extract information from these data sets at a velocity and scale that humans, with limited processing bandwidth, could never attain. With these advanced capabilities, companies can now build solutions to automate menial tasks and generate key insights that were once hidden, driving innovation at an exponentially accelerating pace.

8 McKinsey, 2016

THE RISE OF ARTIFICIAL INTELLIGENCEArtificial intelligence in the form of iterative algorithms—computers working on tasks and improving on their own with no human intervention—will be the foundation for building a predictive OEM enterprise and the key to driving unparalleled efficiencies in the future. AI and machine learning, in our opinion, are the most significant technology trends today. There are three ways in which artificial intelligence will manifest itself in automotive OEMs and transform everything from business decisions to product features.

DRIVING BUSINESS INTELLIGENCE

Automotive OEMs determined to succeed in the future, where digital information dominates, are already building data science and AI-driven competency internally. Data activation capabilities and machine learning are helping them to learn more about customers and make more informed business decisions.

There’s simply no other way to harness, govern, and interpret the enormous volume of data that will be coming from our cars, now and in the future. Our current and future data platforms need simulation capabilities, predictive solutions, and the ability to make sense of big data at scale. AI has the power to dynamically find pockets of data that are meaningful amidst the chaos of fragmentation—data that

THE DIGITAL CAR – REPRESENTED IN LINES OF CODE


would otherwise be left in the dark—giving technologists unprecedented insight and the ability to build products and solutions that leave us in awe.

With an AI data platform, companies already automate menial tasks, but increasingly, they can use the platform to amplify connectivity, achieve insights, and inform and augment product performance standards.

The trend of increased device adoption and connectivity is creating a new foundation for the entire automotive ecosystem. Programmatic advertising and marketing are central to this transformation, because of their capacity to inform real-time decisions with actionable signal-rich data captured from the surge in user interactions. Businesses need to invest in technology platforms that leverage business intelligence data combined with programmatic observations. Companies that use that data to become more agile and create meaningful experiences for customers will be competitive. Those who don’t will fall off the radar.

BECOMING CONNECTED AND CUSTOMER-CENTRIC

As carmakers recognize the transformative power of AI, they are not only investing in intelligent data platforms, they are also using that data to inform customer experience and product development. Artificial intelligence is helping automotive OEMs serve customers better with product and service innovations—and they are allocating their research and development budgets accordingly.

Car companies were once product- and sales-driven, with a focus on maximizing margins. In the future, auto brands will need to leverage this data to build a more customer-centric business, catering to demands and preferences in real time and offering products that reflect the way today’s connected customers live and work. Applying machine learning methods to big data can produce smarter products and dynamically inform characteristics about customers.

Carmakers recognize transformative power. Applying machine learning methods to big data can produce smarter products and dynamically inform characteristics about customers. For instance, Audi’s head of digital, Sven Schuwirth, has been vocal about helping to make

cars relevant again as behaviors change due to increased connectivity and technology adoption. Audi is researching how to use machine learning and robotics to give customers an extra 60 minutes of productivity during time spent traveling, via connected systems and, eventually, autonomous cars.9

Audi believes this extra hour translates to a significant revenue opportunity for both car owners and the wider economy. As car owners leverage a more connected or autonomous automobile, it is likely they will be using devices that will provide data-driven brand experiences, providing new streams of income for other industries.

THE ARRIVAL OF AUTONOMOUS CARS

The third incarnation of artificial intelligence for automotive OEMs is the emergence of autonomous cars that fully take advantage of insight from customer data and product and service delivery to deliver a connected, hands-free, exceptional customer experience.

Though autonomous technology is still emerging in the automobile industry, innovative automakers are beginning to incorporate autonomous features into the latest cars. Tesla already uses machine learning for autopilot and lane changing features in its automobiles and is rapidly patenting any breakthroughs to protect Tesla’s position in the marketplace. Tesla spent USD527.7 million between January and September on research and development for materials and testing of driverless features.

Built-in global positioning systems (GPS) already get you where you need to go. Blind-spot alerting features, automated braking based on proximity detection, and self-parking capabilities have begun to appear in today’s cars. And there’s more to come. Cars in the near future will be able to find parking spots on crowded streets and gain real-time information from “smart streets” and other intelligent locations. According to Techworld, Toyota will focus on combining AI and big data to create cars that can assist mobility both in and out of the car for aging and disabled drivers.

9 “Toyota, Tesla, or Google: who’s spending the most on artificial intelligence in the car industry?” Techworld, November 9, 2015

10| Rocket Fuel Institute | Predictive OEM

Every carmaker wants to be first in the race to create a safe, effective autonomous driving system, which could offset profit losses as younger generations gravitate toward Uber and the sharing economy over car ownership. Toyota has also put USD1 billion aside for a Silicon Valley artificial intelligence and robotics research unit—scheduled to open in January 2017—to further its driverless car technologies. The carmaker is enlisting some of the brightest computer scientists in the world—including Dr. Gill Pratt, formerly of the Defense Advanced Research Projects Agency (DARPA)—in the hopes of discovering new materials and methods for more efficient manufacturing, while creating safer, more accessible car technologies.

As other carmakers follow suit, data integration, combined with information transmitted through autonomous technology, will transform cars and automotive industry business models. Expanded connectivity will increasingly turn the car into a platform for drivers and passengers to use their transit time for work productivity and personal activities and for brands to know their customers better than ever before.

THE RISE OF CONNECTED VEHICLES

As customers demand connectivity in every part of their lives, conventional cars have become more intelligent. Gartner’s IoT forecast states that 4.9 billion connected devices were in use in 2015, up 30 percent from 2014. That number is expected to reach 25 billion by 2020.10 Technology advances and the fundamental infrastructure created by the web have made it possible for cars to have more advanced capabilities. Autonomous cars are on the way, but already web-connected vehicles are becoming commonplace. Connected vehicles will comprise a major portion of the IoT by 2020.11

The proliferation of connectivity will have profound implications across major investment areas, such as telematics, infotainment, and mobility services, in addition to autonomous driving technology. Other beneficial automobile features stemming from improved connectivity include enhanced engine controls, automatic crash notifications, and more timely and accurate safety alerts. Apps that communicate with cars may also allow owners to interact with their vehicle from any distance to further augment safety features and user experiences. In 2013, there were approximately 23 million connected vehicles scattered across the globe. Gartner forecasts that by 2020, one in five vehicles on the road worldwide will have some form of wireless network connection, totaling more than 250 million connected vehicles.12

10 “Predicts 2015: The Internet of Things,” Gartner, January 201511 Gartner, 201512 Gartner, 2015

DIGITAL TRANSFORMATION: THE ACCELERATING PACE OF CONNECTIVITY, MOBILITY, AND TECHNOLOGY UTILIZATION


“IoT is the infrastructure that allows the connected smart car to communicate with the ‘smart road’, creating a network of smart vehicles. Imagine, for instance a car that calls ahead to a connected parking lot to reserve space. This will influence OEM brands to think beyond just their vehicles and within the broader ecosystem that IoT supports, thus augmenting the car’s capabilities and offering new partnership opportunities, revenue streams, and new ways to differentiate their products.”

–James F. Hines, Research Director, Gartner

THE RISE OF MOBILITY

For companies, reaching people through devices makes sense. We are perpetually connected to our phones (in the bathroom, in bed, on a train, standing in line for coffee) and at some level, this replaces the need for owning an automobile. Teens text their friends, send them Snaps,

interact with them on Facebook and Instagram. “Meeting” friends relies less on having to physically drive a car. When we do have to drive, rideshare apps, like Uber and Lyft, bring cars and drivers to us with the touch of a button on your smartphone. These apps are supplanting the need to own a car.

But to OEMs and dealers, leveraging mobility is the key to staying competitive—keeping lines of communication open within the car to give people connectivity and personalized solutions even when they are on the road. Using connected GPS technology to get from point A to B in the most timely manner is the most obvious example. A connected car of the future should not only be able to help a driver avoid traffic, but also take into account construction sites, special events like parades or protests, and any useful information that would inform the driver’s decision on how to get there. Open communication also creates aftermarket opportunities, such as knowing when a specific part on a car will need replacement. The lifecycle of each part could set alerts within the system, providing timely notification to the owner for vehicle maintenance.

Mobility is disrupting buyer journeys and business models for all industries. According to McKinsey,13 consumer preferences, tightening regulation, and technological breakthroughs add up to a fundamental shift in individual mobility behavior. The automotive industry will feel this disruption as well. The traditional business model of car

13 McKinsey, 2016

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sales will be complemented by a range of diverse on-demand mobility solutions, especially in dense urban environments that proactively discourage private car use.

As cars get smarter through connected solutions, brands also need to be cognizant of reaching their customers on the go—as customers become more mobile, their engagement process also changes. As a result, brands need to know how to reach customers at the right moment based on relevance and personalized interaction. As we explored earlier, automotive brands need to consider the implications of not just mobility, but also the increase in mobile interaction when optimizing the customer journey. In 2014, mobile ad spending in the auto industry totaled USD2.15 billion, or 35 percent of the sector’s digital ad

spend.14 In 2016, mobile spending among U.S. auto brands is projected to total USD$5.25 billion, or more than 60 percent of total digital ad spend.15

Due to the increased utilization of ride sharing, mobility, and demand-based digital commerce during travel, and as programmatic technology continues to dominate digital marketing, there are more opportunities for those mobile ads to be seen, and to generate transactional data. More technology platforms will start to leverage this business intelligence data, combined with marketing observations to inform how to connect customers with brands to make their experiences more optimal. The very definition of mobility has changed, and in order to remain part of the digital ecosystem, OEM brands must participate in the conversation. This is accomplished by proactively and predictively engaging their customers and prospects when, where, and how they need to connect and meet specific needs.

14 “ The US Auto Industry 2016: Digital Ad Spending Forecast and Trends,” eMarketer, 2016

15 “ The US Auto Industry 2016: Digital Ad Spending Forecast and Trends,” eMarketer, 2016

DEEPENING CUSTOMER INTELLIGENCE VIA

PROGRAMMATIC MARKETING

Programmatic marketing presents an opportunity to align and coordinate crucial data across the OEM, dealer, and partners, without the massive disruption of an enterprise reorganization. Programmatic marketing continues to transform the digital landscape at an unprecedented pace. Advertising dollars are continuing to shift to programmatic media buying, and today over 50 percent of real-time buy (RTB) advertising opportunities are mobile.16

Programmatic marketing can be used as the equalizer to seamlessly distribute a coordinated message across tiers. It can enable agencies to collaborate and allow OEMs to look across brands and manage entry, midmarket, and

luxury targeted customers across life stages. For example, Volkswagen can start you off with a Beetle, move you up to an Audi Q5 as your income and need for capacity grow, and eventually deliver that beautiful new Bentley or Bugatti to your driveway to enjoy in retirement.

This type of cross-brand marketing is a big deal. Traditionally, customer records, behaviors, and profiles are rarely shared across brands. Programmatic technology enables OEMs to break down those organizational silos by centering on customer engagement and making informed decisions based on corporate results, which can determine the right brand, model, and even options to assign the task of winning or keeping that customer.

According to eMarketer, automakers tend to be optimistic about digital advertising and its return on investment. In 2015, Mazda USA reported that almost 60 percent of its efforts are in the digital world—whether it’s in-market, out-of-market, SEM, or social. Using this wealth of data and

16 Rocket Fuel internal research


sophisticated analytics, Mazda USA can determine which media channels should be used for targeted messages, and over 1,900 variables, such as inventory and incentives.17

As more auto companies leverage data beyond advertising and media data to more accurately segment audiences, they will be able to transition more easily into a different kind of automotive ecosystem, and to transition as the world and customer demands change around them: more platform-based solutions, ride-sharing applications, system integrations. These shifts will propel the industry toward holistic operational frameworks, and after-market business models that keep improving and changing the customer experience in a post-sales environment, with software upgrades, cross-sell opportunities, and more.

As part of a digital infrastructure that enables companies to utilize all transactional data, programmatic systems influence more than just real-time advertising and media buying. The pipes connecting all data across the company create the vessels through which knowledge can flow. This more holistic view of data can help companies see trends that would otherwise remain hidden—for example, how dense urban environments exponentially create change through augmented behaviors and evolving customer demands and increase the need for platforms that leverage algorithms to power the new age of supply and demand.

17 eMarketer, 2015

Programmatic capabilities can go beyond immediate customer service to helping companies track and gauge overall shifts in customer behavior and the automotive ecosystem. Behavioral intent data—whether customers are happy or sad, satisfied or dissatisfied, what issues they are worried about—can reveal how audiences feel about greater societal and environmental impact, which informs an expanded view of the customer. For example, the collaborative economy is at the center of consumption. Or, as Ernst & Young recently pointed out, “The rise of the collaborative economy is a result of growing urbanization and driven by digitization.”18 As we continue to concentrate into urban areas and digitization disrupts distribution channels, technology and peer-to-peer sharing will take center stage in designing a city’s intelligent transportation infrastructure.

Rapid urbanization, megacity population explosion, pollution, and congestion are exerting tremendous pressure on natural resources on a global scale. At the same time, digitization, mobile connectivity, and social media grant consumers unprecedented access to content.

Nontraditional players are not only disrupting most industries by enabling simplified access to resources but are also spurring entrepreneurship at a micro level. For instance, property owners are opting to lease homes and apartments as short-term vacation rentals, and even rent their garages short term via sharing apps, and vehicle owners are offering peer-to-peer mobility services. Companies that facilitate this new business model are more customer-centric and offer economical choices, greater flexibility and multiple payment options to consumers.

18 “Urban Mobility Redefined: Sharing is the New Buying,” Ernst & Young, 2015

URBANIZATION AND DIGITIZATION: MERGING WITH THE COLLABORATIVE ECONOMY


These changes are shaping our future transportation infrastructure and the global automotive economy, and automotive companies need to adapt. The roadmap to creating a robust automotive enterprise no longer hinges upon independent business units that aim to maximize margins. It is instead based on an interdependent ecosystem with a customer-centric focus and a creation of value across the entire brand family. That collaborative business models such as Uber or Airbnb are thriving in modern digital commerce underscores the importance of shared mobility business models today and going forward.

Upgradeable cars are an example of how these changes will impact both cars and consumers. According to McKinsey, the increasing speed of innovation, especially in software-based systems, will require cars to be upgradable. As shared mobility solutions (car sharing or e-hailing) with shorter automotive and technology lifecycles proliferate, consumers will be constantly aware of technological advances and will demand the same upgradability in privately used cars as well. Driven by shared mobility, connectivity services, and feature upgrades, new business models could expand automotive revenue pools by as much as 30 percent, or USD1.5 trillion. New mobility services may result in a decline of private vehicle sales, but this decline will likely be partially offset by increased sales in shared vehicles that need to be replaced more often due to higher utilization and related wear and tear. A real-time decision architecture and automated system present opportunities for OEMs to capture even more business intelligence data through these connected systems.

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The truly predictive OEM is one that can govern and use the enormous volume of first-party data to understand and respond to these macro trends and react to intelligence in real time. Every predictive OEM has two critical characteristics: operational agility and a customer-centric philosophy.

Predictive enterprises of the future will be able to make far more significant business decisions if they follow the five distinct strategic imperatives. This includes being able to successfully leverage the sheer volume of data produced today, captured through the connections being created as the ecosystem evolves. An open and connected philosophy around this data can give OEMs the insight and the operational agility to drive a successful, truly customer-centric business.

Operational agility requires flexibility across the organization. OEMs are faced with the challenge of transitioning from legacy systems to the digital platforms and advanced technologies of the future. This is not an overnight task. Patience is a virtue when it comes to operationalizing and aligning stakeholder groups, especially when building a data-driven architecture. But it must be done. Companies need the foundation for customer-centric operational agility: the ability to process millions of customer transactional

data moments, to derive real-time and predictive insight on customers with that intelligence, and to respond in real time with exceptional experiences and product guidance.

Companies can make operational and cultural changes that promote data sharing and agile decision-making, but ultimately the companies who thrive in the new automotive ecosystem will be the ones who can make this technological transition.

Operational efficiency creates value for the customer, who should be front and center within the organization, rather than the products that a company makes. This seems like an obvious statement, but many companies across industries look at business from a more product-centric perspective.

According to Accenture, establishing a compelling digital customer experience today is made more challenging by the fact that OEMs and dealers are not quite equipped to keep pace with the changing needs of the connected customer.19 Automotive brands will need to evolve to the place where they can constantly improve the digital customer experience, focusing on continuous enhancement in the distinct stages of the journey: presales, sales, ownership, and repurchase.20

19 Accenture, 201520 Accenture, 2015

PREDICTIVE OEMOPERATIONAL AGILITYDIGITAL TRANSFORMATION

PREDICTIVE OEM: REAL-TIME DECISION-MAKING FOR OPERATIONAL AGILITY AND BETTER CUSTOMER EXPERIENCE


Integrating customer and business intelligence data can help inform full-funnel marketing initiatives. eMarketer states that in years past, automotive digital strategy has been weighted toward investments in lower-funnel activities. There was an emphasis in steering consumers toward a purchase in the final weeks of the shopping process, using search and other tactics. But with display formats—especially video—becoming more measurable and targeted, there are more upper- and mid-funnel branding campaigns, designed to drive awareness and consideration, and cultivate brand loyalty.21 Because of its emotional appeal, digital video is quickly becoming the format of choice for automotive companies.22

Companies can also gain improvements in efficiency and return on investment by connecting digital audiences across tiers.23 Automakers have seen an 18 percent improvement in Tier 2 response when the audiences are informed by activities taken in Tier 1.24 25

21 eMarketer, 201622 eMarketer, 201623 eMarketer, 201624 Rocket Fuel Institute research25 eMarketer, 2016

MEETING BIG DATA CHALLENGES

Just as data can help industries solve problems and evolve business models, it presents challenges as well. In reality, data practitioners continue to struggle with a significant performance gap when it comes to applying audience data in support of broader business objectives. Though large numbers of marketers and publishers continue to see basic enterprise needs—such as “growing revenue” and “improving profitability”—as the broad, fundamental

“At the end of the day, while display advertising

is interesting, the story you can tell in a 15- or

30-second video spot is much greater.”

– George Kang, senior vice president of OEM business, Edmunds.com25

25

50

75

100

Enhancing customer

experience

Finding new ways to monetize

Servicing under-served

customers

New value o�erings

Lower cost models

GROWTH STRATEGIES–AUTOMOTIVE OEMS


(and expected) outcomes of their data-related investments, relatively few have succeeded in achieving expectations with respect to audience data and its contribution to baseline performance goals.

Proper visibility is another challenge. For companies who want to better engage with audiences and deepen their connection with the brand, data is the foundation for every significant interaction. However, if intelligence and insight lead to true competitive advantage in business, most companies often lack the visibility to see the breadth of the competitive landscape with the depth of technical acumen needed to make well-informed business decisions. For organizations that want to be more nimble, dynamic, and innovative in driving efficiencies, a core data asset is a step in the right direction. However, without very specialized skillsets and tools, the process often ends in frustration and confusion.

A programmatic infrastructure sets the stage for the future. It is closely aligned with the data-driven trends we’ve explored and is critical to meeting customer needs in a demand-based economy. The programmatic credo—getting the right message to the right customer within the right context at the right time—comes to fruition with an end-to-end business framework that supports:

• Ingesting, unifying, and transforming company and audience data to drive marketing and operational efficiencies

• Activating data across multiple channels to drive business outcomes

• Discovering a holistic view of customers and business operations through a centralized platform

As the rate of private vehicle purchases decreases, ridesharing and purpose-built

transportation utilities will dominate the market. Data activation will be absolutely

necessary to analyze the pertinent information collected from consumers and service providers alike across this transformed OEM ecosystem. New brand messaging strategies will need to be created, and OEMs

will need to be more nimble and predictive in creating operational

models with specific features that cater to the right cohorts. The days of simply

mapping brand messaging to basic lifestyle characteristics are over.

Data will need to be shared concurrently across fragmented platforms and channels and for different teams across the business. As data flows, for instance, from a data management platform as it records media observations, it should be seamlessly translated within the company’s CRM system. OEMs need a unified, always updated view of the customer available across the organization to inform the next best engagement action.

OEMs of the future will also have to be programmatic and predictive in their approach to the supply chain—with analytically quantified capabilities based on utility, driving preferences, geographic parameters, terrain calculations, and government regulations. This more calibrated approach will bolster the automotive ecosystem and leverage behavioral data on both the supply and demand side.

We’re already experiencing this shift all around us. The ridesharing economy is powered with programmatic technologies that determine optimal services based on customer preferences in real time. In the future, as adoption escalates, programmatic platforms will provide even more opportunities for marketers to change the way they reach customers through personalized experiences. The car will be a new intermediary for media consumption, interpersonal communication, and entertainment. Where there are means to engage with devices, there are channels in which brands can deepen connections with their customers.

RIGHT

C U S T O ME

R

R I G HT

CO N T

E

XT

R I G H T M E S S A G E

How might a programmatic platform turn your company into a more predictive organization? A data-driven solution that enables a customer-centric business model can rapidly bring about several new opportunities for OEMs.


SNAPSHOT OF A PREDICTIVE OEM

AUDIENCE HUB / DYNAMIC CUSTOMER

JOURNEY MODELING

OEMs with visibility across fragmented silos, systems, channels, products, and audiences can increase their flexibility in market, which creates more opportunities for innovation. Both Tier 1 manufacturers and Tier 2 dealers can align messaging through a data-driven approach, and brand families can not only differentiate messaging, but can also spot cross-brand opportunities and cross-marketing opportunities within brands. BMW enthusiasts are vastly different from Ford Motor audiences, but even within BMW, a 3-series driver, an X-series driver, and an M driver are vastly different animals. Dynamic customer journey modeling using huge volumes of first-party transactional data can help OEMs, dealers, service providers, and other tech vendors in the growing ecosystem to deliver unique, nuanced experiences at the touch point level and to spot previously hidden marketing opportunities and predict future ones.

FEATURE-SET OPTIMIZATION AND

DEMAND-BASED MARKETING

Automobile models and the countless products and services that support the industry can be difficult to bring to market and deliver to the right people. Data-driven feature-set optimization enables countless cross-sell and upsell opportunities to very specific audiences. It will be possible to create new segments of specialized vehicles designed for very specific needs. Because of this shift to diverse mobility solutions, 1 out of 10 new cars sold in 2030 may likely be a shared vehicle, which could reduce private-use vehicle sales, an effect partially offset by a faster replacement rate for shared vehicles.26 Based on this evolution, Tier 1 brands must reevaluate branding so drivers of the future are receptive to these new utility standards. Drivers that own vehicles primarily for services will have different preferences than, say, drivers who like to take long, cross-country road trips. Either way, feature-set optimization will allow OEMs to better understand how driving styles and preferences map to actual utilization. Since most cars will be digitally integrated, more data can be leveraged to not only improve maintenance workflows through improved notifications, but brands will also be able to create more robust profiles and messaging to appeal to certain drivers and anticipate their needs.

26 McKinsey, 2016

PARTS AND SERVICE AUTOMATION

As the transformation of consumer interaction continues to pivot toward digital, more data can then be aggregated to inform the supply chain, which can then be mapped more directly to customer preferences. Data can and should inform demand generation or alert service departments to fulfillment concerns by knowing life expectancy of parts (such as tires), available inventory, and up-to-the-moment supply levels. Examples range from dealer tire sale programs to recall or “service bulletin” notifications, to certified preowned inventory management. Data closely aligned with the supply chain presents a tremendous opportunity for aftermarket services. In addition, if OEMs gather predictive intelligence on which parts need to be replaced more frequently as a result of driving behavior, this can inform product requirements for next year’s model. Advanced tools such as machine learning and artificial intelligence are already being leveraged to simulate a wide variety of driving characteristics, helping the OEM to determine the optimal driving experience and design products and marketing around it to emotionally satisfy the needs of valuable lifetime customers.

F E A T U R E S ET OPTIMI Z

AT

ION

CONSUM

ER

RE

Q

U IREMENTS Scoring

& Validation

Safety

Luxury

Telematics & Driver Assistance

Price

Utility

In-Vehicle Content Access

PARTS & SERVICE AUTOMATION

CONSUMER MESSAGING

OEM

AUDIENCE HUB

SALES

T2

T3

T1

PRODUCT

T2

T3

T1


BUSINESS TRANSFORMATION VIA PROGRAMMATIC

TECHNOLOGY

Leveraging a holistic, programmatic system and platform is invaluable to helping OEMs make decisions about product development, supply chain distribution efficiencies, creative testing and research for audience understanding, and how to align fragmented stakeholder groups within holding companies. These are just a few examples of how a cohesive programmatic solution design can impact and accelerate business performance and transformation for OEMs and service providers at scale.

In today’s world of leaner budgets and shrinking resources, business leaders are under mounting pressure to improve the efficiency and effectiveness of their marketing and technology operations. More than ever, the office of the CMO has coalesced with that of the CIO. This has often led to new types of roles being formed such as the chief marketing technologist. This convergence is organic and remarkable, because technology and customer intelligence are now essential to business strategy. Technology that can govern and yield insight from large volumes of data, coupled with human decision-making power, is the intersection at which business transformation takes place—not merely through the framework of a well-architected technology stack that powers organizations, but also from the knowledge that emerges from the process. The catalyst

of this transformation is precisely what the predictive OEM of the future can embody through these business and technology principles.

Programmatic technology isn’t just auction-based media buying across display, mobile, and video. It isn’t just capturing viewable inventory for brand initiatives. And it isn’t just a means to frequency-bomb users through retargeting. Programmatic capabilities are a means to redefine the way brands leverage audience data to inform every aspect of their organization and ensure that they delight customers. For businesses, programmatic systems confer transformative power through data-driven innovation and reveal patterns where complexity and fragmentation overwhelm. The technology makes sense of millions of transactional moments that were previously ignored or overlooked but, in aggregate, unlock insight that informs a company’s vision, defines its direction, and helps predict outcomes and generate results that businesses are so relentless in pursuing.

HOW IT WORKS: PREDICTIVE OEM

FIVE STRATEGIC IMPERATIVES FOR THE PREDICTIVE OEM

20| Rocket Fuel Institute | Predictive OEM

MOMENTS NOT SEGMENTS Traditional marketing segments are rooted in historical data. Predictive businesses build models that include transactional moments for real-time accuracy and the power to anticipate and exceed customer expectations.

OWNED NOT RENTEDFirst-party data is a predictive organization’s biggest asset. The best decisions and innovations come when truly leveraging this proprietary data.

PEOPLE NOT DEVICESPredictive organizations are customer-centric, not product- or device-centric. All transactions and devices tie back to a universal ID of a single person or household.

JOURNEY NOT FUNNELPredictive businesses know that a sale or conversion isn’t the final transaction. The customer’s journey never ends, and the path to conversion is often nonlinear. Businesses that can anticipate future actions are the ones that will succeed.

DECISIONS NOT DATAFor the past decade, data management platforms have been hubs for data centralization, normalization, syndication, and analysis. Today, data management platforms must evolve into decision management platforms, exchanging models, with syndicated intelligence replacing syndicated data. In other words, one system’s AI talking to another system’s AI.


ABOUT ROCKET FUEL INSTITUTEThe Rocket Fuel Institute is a research initiative dedicated to the transformative

field of artificial intelligence in digital marketing. The RFI aims to transform

the digital industry, propelling it to the forefront of the global shift to artificial

intelligence (“AI”) by exploring innovation at the intersection of data, technology,

and customer experiences. We seek ways to enable and sustain AI-based growth

in marketing and across verticals by understanding how digital transformation and

adaptive automation combined with human intuition accelerates over time. Our

long term research goal is to converge academic research with applied sciences in

machine intelligence to understand the nature of brand experiences. For inquiries

into our existing or forthcoming work, or to discuss how you might partner with us,

please reach out to:

Nikos Acuña

Head of Rocket Fuel Institute

[email protected]

www.rocketfuel.com

ABOUT THE PREDICTIVE VERTICAL SERIESThe Predictive Vertical series explores the way marketers in respective industry

categories can gain a significant competitive advantage with best of breed

solutions. The series covers in-depth macro trends that are shaping the global

economy, defining the fate of companies and careers, while providing a sweeping

perspective on the most advanced tools that are changing the way brands interact

with audiences, and the way businesses achieve actionable insights to make more

informed decisions in finance, CPG, retail, healthcare, and travel.

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