By Eric Brown, LotLinx President

In 2018, the U.S. Automotive industry is predicted to spend $11.3 billion on digital advertising, a 13.7% increase from last year. This rise in digital media spending has resulted in a flood of new martech buzzwords like “big data” and “attribution,” leaving dealership general managers, internet directors, and marketing managers scrambling to reassess their digital marketing strategy.

Artificial intelligence (AI) is another buzzword seeing increased use, but AI has the potential to be much more than marketing jargon. AI has the ability to analyze massive data sets to optimize processes that can be cumbersome, costly or inefficient. Dealers stand to benefit from utilizing AI to derive new insights, create greater efficiencies, and take advantage of new business opportunities. With higher efficiency comes higher profitability – the holy grail of many dealerships today.

My goal with this article is to share my perspective on AI and spark new ideas for discussion among the auto dealership and vendor community.

What Exactly is Artificial Intelligence?

Believe it or not, AI has been in the auto industry for decades. AI-powered robots were first utilized in American assembly lines as early as 1961. Today, the modern assembly line is one robot after another, all designed to mimic the actions of the assembly worker that came before.

That ability to “mimic” human behavior is the simplest form of artificial intelligence. Using machines to perform tasks that manual workers were once responsible for is now the standard for any profitable factory today, because these robots have mastered the process – and they don’t need to sleep, eat, or support families. Robots reduced costs and boosted productivity simply by learning to do things humans want them to. So, naturally, once these robots were in place, the question that followed was, “Is there a better way to do this?”

From there, machine learning was born, whereby a computer analyzes data from its own actions, and takes input from additional resources to find – through trial and error at lightspeed –  a new, better, more proficient way of doing things.

Once a machine can learn to find a better solution to a “problem”, the next logical question is, “What problems can it solve?”

AI Comes to Sales and Marketing

For hundreds of years, marketing and advertising has been defined as the art and science of identifying who will buy your product or services, and creating compelling content which motivates them to buy. This has been true from the town crier to newspapers, to radio, to television, to the internet. As time has gone by, the balance of “art and science” has shifted more and more toward science.

Purveyors of marketing research have developed demographics, psychographics, look-a-likes, and behavioral targeting to “move the needle” on audience targeting. For too long the conversation has remained about the “audience,’’ with the “science” of marketing merely used to better define said audience.  Because of this, marketers have largely remained in the business of “buying haystacks” in hopes that their art and science will shake out a few needles interested in buying their product or service.

AI sets the haystacks on fire

Today, massive amounts of data are collected from billions of connected devices which tells a story about consumer habits and intent.

Artificial intelligence allows us the ability to analyze this data in seconds and identify the very best sales prospects. In other words, AI shifts through the chafe and quickly identifies the needles in every haystack, greatly reducing cost and driving up sales margins.

In a recent Tier 1 new vehicle test, campaigns powered by the /AI/ developed at LotLinx reduced the dealers’ cost per new shopper by 60% ($5.04 vs $12.74)[1]. That’s because AI technology uses the results data collected from previous campaigns (with both positive and negative outcomes) to make better-informed decisions moving forward. For example, if it spent too much on a shopper that didn’t convert, the machine would remember that path as negative and use that information to avoid waste in the future. AI is constantly learning and evolving over time, until it determines the equation for the “optimal solution” to whatever problem we created that robot to address.

By starting with the “needles”, you start with the best possible shopper or likely buyer then move on to the next. That is, you start with one shopper, they don’t buy, you move to the next, then the next and so on.

After all, it only takes one buyer to drive a car off the lot. Therefore, every dollar spent to target a shopper after the first shopper is wasted spend.

This “one shopper at a time” approach that only AI can deliver dramatically reduces cost, as the cost of buying haystacks is eliminated. In fact, our research shows an 80 to 85% reduction[2] in cost to sell compared to the NADA-reported $627.00 cost per sale.

AI fueling the modern dealership’s future

Driving down shopper acquisition cost is one aspect of AI, but more importantly driving sales is the true goal. To that end, auto shoppers targeted by the LotLinx /AI/ were 19X more likely to purchase a car than shopper from other digital marketing solutions.

Given the current margin compression that dealers are experiencing and the always competitive sales environment, the automotive industry is welcoming AI with open arms. Over the next several years, AI will make its way into nearly every sales and marketing tool or solution that a dealership uses. From CRM systems, DMS, chat tools, and service reminders to every form of advertising, AI will be incorporated in one way or another.

Why? Because AI delivers a result that every sector of every industry has chased for a hundred years. Simply, doing more with less effort and cost. And AI accomplishes this with astounding proficiency.

Sources:

[1] Research from March 2018 Canvas OEM LotLinx VDP study conducted by Oracle Data Cloud

[2] 2018 LotLinx research found the marketing cost per sold VIN to be $78 on average for vehicles targeted by LotLinx campaigns, excluding OEM programs.

About the author:

Eric Brown is a graduate of MSSU with studies in Executive Leadership and E-Commerce Strategies from Harvard University and Columbia University. Mr. Brown is a highly sought after industry speaker with engagements at JD Power, DrivingSales Presidents Club, Automotive Intelligence Summit, and Autovate among others. He has been a guest expert on Fox News and quoted in the Wall Street Journal, Forbes, USA Today, Digital Dealer and CBT News.  Eric was named “Innovator of the Year”, 2012, Nashville, TN and was a finalist for the 2018 DrivingSales “Most Valuable Insight” award.