It’s common knowledge that a business must acclimate in order to stay afloat—to ever-changing market conditions, customer trends and perceptions, technology platforms, entrenched and emerging competitors, supply chain variables and a glut of other micro and macro-economic concerns. But, at the end of the day, revenue generation is the metric that truly matters. “Unfortunately, the automotive industry in particular is suffering egregious opportunity loss, and is the proverbial ‘poster child’ for other sectors who are similarly leaving behind untold millions in lost revenue,” says predictive analytics expert Lang Smith, CEO of Cloud Signalytics. “Like so many others, the auto industry on the whole just doesn’t conceptually understand, or aptly appreciate, the value of repeat business and methods to proactively facilitate future earnings.”
“The auto industry’s ‘single transaction’ model just does not effectively cultivate long-term customers,” says Lang. “Today’s cost-conscious consumer will move from one automaker to another for even the slightest of reasons, like a favorable customer service interaction. The auto industry’s overarching mandate of selling as many vehicles as possible at any cost has indeed been costly—usually at the expense of a dealership’s reputation, damaging the image of the auto industry at large. Because the industry has realized billions of dollars in the process, far too many are apt to ‘leave well enough alone,’ turning a blind eye to untold levels of revenue that are going by the wayside. While that way of thinking may have been sufficient in the past, today’s leading-edge tech-driven sales operations can no longer forsake the fiduciary responsibility to promote maximum profitability right now and into the future.”
Lang goes on to explain that, because the auto industry largely utilizes the flawed marketing logic, “the more people we can reach; the more money we will eventually make,” they simply cannot maintain momentum—particularly amid persistently diminishing margins. However, add a predictive analytics engine into the mix—defined as the ability to more precisely predict a customer’s future spending based on their past behaviors—and the ability to make triple or even quadruple their sales revenue becomes a reality.
“Predictive analytics platforms are the Holy Grail for the auto industry—the make or break marketing methodology—the bleeding-edge, next-gen, game-changing technology—that will literally mean the difference of life or death for today’s breed of vehicle dealerships for whom status quo will no longer suffice. And for those who do survive, those using predictive analysis will be the ones who unequivocally thrive,” Lang urges.
Why? With the right analytics platform at a dealership’s fingertips, they can literally send offers to only those customers who actually want what they are selling at the time. For example, a dealerships executes a direct mail campaign to 5,000 people. They are trying to sell the last 5 minivans on their lot and, according to their limited customer database or CRM system, they have identified 5,000 people interested in minivans and haven’t purchased a vehicle in over 2 years. However, with a predictive analytics platform in play, rather than merely identifying 5,000 people in this circumstance, imagine sending a highly tailored marketing offer to only those folks in the 5,000 segment who desire a silver minivan with beige leather interior, navigation system, a sunroof, and a price point under $40,000.
In the first scenario, the dealership likely does not know that 50% of the 5,000 in their initial target group can’t even afford to spend $25,000 for a vehicle, and 1,000 of those people may not even like the color silver. So, if the campaign execution costs roughly $1.00 per person, that’s $5,000 wasted marketing dollars even before a single vehicle has been sold. Even if a dealership did such a campaign once a month, that’s $48,000 in entirely wasted funds for not having the proper systems in place.
“With profit margins at an all-time low and getting even tighter, dealerships must spend their marketing dollars very prudently and precisely to make any money at all on sales efforts,” notes Lang. “Then there are the financing concerns, which can be an extraordinary, and avoidable, drain as well relative to time, money and resources. Good predictive analytics software will allow dealers to only spend their valuable time working with customers who have already be financially pre-qualified even before even walking in the door. In this way, there will be fewer if any sales that ‘fall through’ after so much time, effort and expense has been put forth to get to that point in the transaction.”
With all of this in mind, Lang is pioneering a proprietary software platform that singularly addresses the auto industry’s glaring need to more precisely target their future customer and propel that prospect to take action. He envisions a customer walking through a dealership’s door and being presented with the exact type of vehicle they want, with all of the desired options and in a viable price range based on past purchases. The staffer could readily discern if that person is qualified for financing at the early stage of discussions, even being able to analyze that customer’s past interest rates. This predictive analytics can do and more—for the auto industry and throngs of other sales-driven businesses.
Lang is quick to conclude that, “Gone are the days of spending hours on deals that may not manifest, replaced by the opportunity to sell more in less time, also enhancing the customer experience in kind—all boosting a dealership’s current bottom line while cultivating repeat business up ahead.”
Of course, the above scenarios are just a few of the many ways predictive analytics should become top priority for those in the auto industry who intend to stay in business for the long haul and generate maximum returns throughout—the kind that’ll make the endeavor worthwhile for all involved.
Written by Merilee Kern, is an influential media voice who serves as Chief PR & Communications Strategist for multiple agencies.