Three auto industry data leaders, who are also siblings, share how relevant data can help dealers create outstanding marketing plans.
Imagine sitting at a large family gathering at Thanksgiving or Christmas and the hot topic of
debate is . . . wait for it . . . data! If you’re part of the Stapleton family, it’s only natural. Siblings Sean Stapleton, Meg Stapleton and Kate Donovan grew up surrounded by data, as their father, John Stapleton, launched a data mining company that was eventually sold to A.C. Nielsen in the 1970s.
Data is a passion for them, and when that data is combined with digital and social marketing for the auto industry, you get some fervid discussions at family reunion time in Minnesota. Sean is CEO of Dealer Teamwork, a digital marketing firm focused on merchandising, personalization, and optimization for the auto dealership industry. His sister Kate serves as Chief Client Officer for the company. Meg is Executive Vice President and General Manager of AutoAlert, the leading data mining and trade cycle management company for the auto industry.
With personalized marketing and search engine optimization taking such a leading role in the merchandising of cars, it is inevitable that a discussion on how to use data to design the best marketing plans turns to Google.
“It’s all about search engine optimization,” Sean said. “We don’t make advertising and marketing for people anymore. We make it for search engines, because if the search engine doesn’t like it, people will never see it.”
Kate agrees. “You don’t create the optimization, personalization opportunities, or the incentives for the customers, but you’ve got to create it for Google in order to get to the customer –
all while making sure you’re answering the customer’s question.”
But since Google is continually adapting its criteria for what it displays, doesn’t that make it difficult for those in the auto industry to implement proper SEO?
“Those changes make it better for us all,” Sean says without hesitation. “Google is changing based on what it is learning, so it is constantly evolving. Remember, Google is a data company. There are two types of searches – paid and organic – and both are predicated on one word – relevance. The more relevant and precise the original query is, the more relevant and precise the response.”
Relevance in data has never been more important. Everyone has experienced the frustration of getting a notice for a car they no longer own. Relevance and personalization go hand-and-hand, but the data has to be spot-on.
A sample of a personalized offer statement was sitting on Meg’s desk.
“Here’s what’s really effective,” Meg said. “From the data, we know this person is already pre- approved from the OEM, we know they can swap key for key for the same monthly price, they have shown intent via their shopping, their contract ends soon, they are coming in for service, they are over their mileage, and their warranty is almost up. We know all that information because of relevant data.”
Avoiding Fragmented Data
Data should never be viewed in isolation, nor in a fragmented or siloed manner. Good data science considers a wide variety of data to get the complete and accurate picture.
“The complicated part of data is taking all the disparate data points and understanding how they come together,” Sean said. “I think of data as a beautiful mosaic. If you zoom in, that mosaic is thousands of individual pictures. But when you stand back, it becomes a clear picture. If you do data right, it becomes very clear.”
All three agreed that data has the potential to be a double-edged sword, if viewed improperly or in isolation.
“It is very dangerous to look at just one piece of data. It will give you the wrong answer,” Sean said. “It is both a blessing and a curse. If you interpret it wrong, you’ll go in the wrong direction. You’ll spend the wrong money.”
“Data exposes everything,” Meg said. “Transparency is vital.”
But lack of transparency, plus a lack of non- standardization of data, can make data hard to grasp. The confusion surrounding data is what contributes to complications in marketing, Kate noted. The answer lies in education.
“We don’t just give our clients data – we show them the data with transparent tools such as Google Ad Words or Google Analytics – that’s not even our data, it’s a third-party,” Kate said. “That’s how we’re breaking through some of the confusion – with education.”
“True democratization of data – that’s what some people are really afraid of,” Meg said. “Because if it is democratized, then only your secret sauce is what keeps you separated.”
Lack of Data Standardization Creates Confusion
Sean provides an example of how the lack of standardization is causing confusion in the auto industry.
“We’ve all heard about bounce rates. In data language, a bounce is yucky,” Sean said. “If you go to a single web page, and spend 14 hours there, but don’t go to any other page, it is a bounce. If you go to a page for 13 seconds and leave, it is a bounce. But wait a minute – the first person got everything they needed, but it is still a bounce. Both look the same to a data scientist. See how that doesn’t make any sense?”
“Someone could go to a page, be there for 3 seconds, but get the phone number they need and make a call,” Meg said. “But that is now considered a bad experience. But no, it’s not. You need to connect those data points.” Those data points could include tracking website visits, locations, area codes and time stamps.
“If the bounce rate is 68%, but the conversation rate and calls are phenomenal, that tells you that you have to look at all the pieces of the data, and that’s what complicates it,” Kate said. “What do I need to look at to actually see the story?”
Sean said the way some dealers implement marketing plans tells him that there is much progress still to be made in using data as efficiently as possible.
“Data will show cause and effect, and how to become more efficient,” he said. “For example, television ads are a very difficult form of media to track. Did it work or not? Yet every dealer is scared to death to quit TV advertising. But statistically speaking, the return on investment can’t be demonstrated. So why does everyone keep doing it?”
That scenario exemplifies why it is important to have trained data specialists who can help decipher the critical information.
“I have data storytellers on my team, and I have data scientists,” Meg said. “I’d much rather have data storytellers because they can tell you the ‘so what’ about the data. Data alone isn’t important, it is the story it tells.”
How to Make Data Relevant
The issue of making data useful and beneficial all boils down to the R-word – relevance. Sean said for Google or Bing, relevance often focuses on transactional data, such as price, program exclusives or specifics to a deal.
“Good data management will display that information seamlessly for the consumer. This translates into better engagement, which lowers the cost of doing business.”
Relevance also means using the most up-to- date data possible, or even real-time data.
For instance, Meg noted when dealers use AutoAlert’s PandoAlert for their service drive, each customer VIN is scanned, which sends a real-time notification of the customer’s presence to sales, plus complete information of the types of offers the customer is best suited for.
“Data that is timely, personalized and very specific to the situation is what helps sell cars,” Meg said.
Kate said dealers must know their demographics intimately, and develop plans for data usage based on market segmentation.
“The days of one-size-fits-all offers are over,” she said. “Those just don’t resonate with today’s shoppers.”
To get the dealership team to follow data, be sure to track, measure and then share the results.
“Use data to win the argument,” Meg said. “And don’t be afraid to make changes based on what the data is telling you. Change is how you stay relevant, because markets, vehicles and shopper preferences constantly evolve.”
Sean said that data intensity has the potential to create an overwhelming situation. He said dealerships should use filters so they only see what is relevant. Often it is helpful to focus on just one area – for instance, service drive, used cars or leasing – and as a team gains expertise, then expand.
“Be sure to first create a baseline so you’ll remember where you started, then you can tweak one lever at a time.”
Sean noted that data and marketing are inextricably linked. Never make a marketing plan without considering the quality of the data that the plan is based upon.
“Good marketing costs less,” he said. “And what drives good marketing? Excellent data management.”
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