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After recent years of diminished luster among some automotive marketers, sales and service customer prospecting appears to be striking gold once more.
Buoyed by a host of new statistical models and tools that facilitate the search for new car buyers and automotive service customers, prospecting appears to be recapturing the value that it held for many automotive marketing professionals before the economic downturn that began in 2007. The trend also suggests that direct marketers serving the auto industry are once again gaining a better and more focused understanding of contemporary automotive consumer behavior, after years of being buffeted about by dramatic and often incomprehensible shifts in car buying activities... or lack of.
Yes, there was the lure of digital initiatives, too, but for many marketers, the limited success of reaching new customers was frustrating. “During 2008 and the first half of 2009, companies really pulled back on prospecting, basically because consumers stopped responding,” says Brad Rukstales, president and founder of analytic consulting firm CAC Group.
Compounding this frustration, for some, has been the realization that automotive consumers are morphing in ways that made the traditional criteria used for pinpointing new car buyers and service customers increasingly less effective. “Many marketing operations haven’t been able to react very quickly to the changing consumer,” explains Aaron Davis, vice president, analytics team at DataLab, which produces large-scale direct mail campaigns for automotive enterprises.
But this is changing. Automotive Marketers are looking at customers in a new light, redefining them according to new criteria, new data. And they are fashioning new prospecting tools and revamping older ones to help them figure out what’s happening — and predict what will happen.
Chief among these tools: statistical prospect modeling.
Unlike previously sold customer marketing, where dealers and car companies often have several years’ worth of data about customer interactions with them, prospecting is limited by the type and amount of data accessible to dealers and car companies. Consequently, predictive model building is “all about narrowing down from a general market prospect pool of millions to the select few that are going to be good customers..." for a given new model launch, dealership or car company, says Davis.
Social media can enhance direct mail prospecting methods
In the past, prospecting was restricted by the limited amount of data available on automotive consumers. But now, armed with new, more robust automotive consumer information, dealers and car companies can fine-tune their prospecting efforts by building more targeted and more predictive models that also include relevant messaging. At the same time, many can lower the costs of their prospecting strategy because these more targeted mailings are smaller.
The two most popular models, the lookalike model and the response model, have both been boosted by the infusion of more precise auto industry data.
Social media is credited with improving the data needed to make both these models more effective for the auto industry. “Knowing that someone has so many friends on a certain social networking platform can be a very predictive variable in predictive modeling,” Rukstales says. He adds that an automotive brand’s newfound ability to pursue a customer active in social networking sites lets dealership marketers tailor the communications so that it makes sense for the recipient, such as with a pass-along offer.
Of course, even tailored communications are harder pressed to cut through the clutter these days, say experts. “With the occurrence of e-mail, smartphones and social media, you have this almost exponential growth in mechanisms by which consumers are bombarded by messaging and consume messaging,” says David Danziger, director of data and targeting products at data firm Acxiom Corp. As a result, automotive consumers are better at tuning out messages than in years past.
Consequently, continued media saturation means the most successful car companies and dealers will be those “that can clearly identify their target audience and have an idea of the offers and creative that will resonate with them,” Rukstales says. Having the right prospecting model “is critical” to this process, he continues.
The advantages of more targeted direct mail automotive sales and service business prospecting methods
Car Companies and their dealers are looking for prospecting models that will help them reach more well-defined groups of consumers, but also support their efforts in other ways, such as by assisting in tailoring the messaging to reach the right automotive consumers at the right time with the right message. Such strategies are becoming especially important as car companies and dealers have begun to step up their prospecting efforts, a trend that is expected to continue as the economy improves and the total annualized rate of new vehicle sales increase.
Gone are the days of untargeted, spray-and-pray mailings, when car companies and their dealers would send out millions of pieces of mail to general market mailing lists and hope for good results. “Marketers are trying to be more targeted in their prospecting and are looking for improved ways to drive successful campaigns and find profitable customers,” says Felicia Peng, director of prospecting and acquisitions at credit reporting agency Experian. “Our clients are hungry for alternative data sources and predictive analytics that can help them understand the consumer better,” she continues, adding that this is increasingly driving innovations in automotive sales and service prospecting.
Consider, for instance, how CAC Group and a retailer are currently testing to improve results by supplementing an existing prospecting strategy with information about consumers’ social media usage. Using a social influencers score, CAC Group is able to identify lookalike prospects most likely to be highly social online. The retailer sends these automotive purchase prospects a direct mailer encouraging them to visit a website where they can click to join the automotive retailer’s social networking group.
“Engaging prospects where they are socially active will far outstrip previous efforts, which were based on basic demographics and lifestyle scores,” says Ray Kingman, CEO of audience targeting firm Semcasting. “The expectation is that this type of targeting will increase over time, and response rates and customer acquisition programs will improve.”
A social influencers score is just one of several new prospecting strategies that are proving to be more flexible than older prospecting models, giving automotive marketers a way to better target their efforts and craft more relevant communications.
Franklin Mint Federal Credit Union (FMFCU), for instance, was able to target and align an offer to the right consumers using a “propensity to open” model from Experian. This model predicts the likelihood that someone will be in the market for a specific type of loan over the next 30 to 120 days. Meanwhile, Experian also offers “in-the-market” models in seven categories: auto loans and leases, bankcards, mortgages, home equity, personal finance, retail, and student lending. This model relies on a bevy of data to gauge the seriousness of a consumer’s intent to buy.
Initially, FMFCU sent a direct mail piece to 17,000 members with the goal of cross-selling them an auto loan. The company checked to see how the list of names of those who responded to the mailer ranked on Experian’s Auto In the Market Model. “The company saw that the highest Auto In the Market scorers were those who responded and opened a loan,” Peng reports. For its second mail drop, the credit union applied the Auto In the Market score against its mailing list, rank-sorted the results and mailed to the 15,600 names predicted most likely to open a loan by the model. This second mailing drove a 10-percent lift in the conversion rate as well as cost savings, with a mailing list that was smaller than the first drop.
Not only was FMFCU able to use the propensity to open model to improve the campaign results, but it also was able to save on postage and paper costs, Peng says.
Consumer transactional data is the key to direct mail prospecting in the auto industry
Further innovating prospecting is the growing availability of transactional data from dealership management systems (DMS), which can be followed over a period of time to determine trends in behavior, such as how much someone has spent money in the dealer's service drive, accessory or Finance and Insurance department, explains Davis.
Predicting When Owners Become Car Buyers
From a modeling perspective, vehicle purchasing cycles using a combination of dealer DMS and RL Polk data “is extremely predictive — far more predictive than knowing someone’s age and income,” Rukstales says. “When we have this information about how much households spend in a certain category, our ability to define the consumer improves.” This lets dealers and car companies better predict who will be a good vehicle purchase prospect and craft more meaningful messaging, and the result is often “a significant increase in response rates,” he adds.
An auto loan application, for example, could trigger direct mail from a car dealer trying to acquire specific used vehicles for the car company's Certified Used Vehicle Program that match the year, make and model of the current vehicle being driven by the loan applicant.
DataLab receives daily feeds from various sources for this type of data and creates prospecting files to go to a dealer or car company's mail shop the next day. While bigger companies have been engaged in this type of trigger marketing for a while, Davis says he expects it to become more prevalent in 2011 as dealership DMS based transactional data becomes more widely available. Some of this newer data “is not only more predictive of who will be a good prospect, but it lets companies deliver their message in a more timely fashion and in a way that correlates with a behavioral change or a trigger,” says Davis.
Semcasting is using an automated platform to generate targeting models for each individual car dealer in a franchise network that has multiple locations across a geographic region, OEM defined Marketing and Sales Zone, or for the entire country.
“One-size-fits-all regression models will tend to average the results between local markets and dilute the value of the targeting model,” says Kingman. “If you can generate a model for every location or situation on demand and have results in an hour rather than a month, the precision of local targeting improves overall, and campaign planning can be more effectively optimized.”
And, because software solutions can propagate models more efficiently than hand-built models, they make statistical prospect modeling practical to car dealers with smaller budgets. Semcasting’s clients, for example, are equally split between mid-size and large automotive marketing firms — many of which are new vehicle franchises, distributed sales organizations, political campaigns and nonprofit organizations.
While in the short term many automotive marketers remain focused on lower-cost digital activities, we could be headed toward a golden era for prospecting, as predictive modeling grows more sophisticated through new data and techniques. “Every company wants to be more effective in how they are reaching consumers and in the message they are delivering,” Danziger says. So, any information they can use to refine their efforts, they will use. “The implication is that customers and prospects over time will see more refined and targeted messaging.”