Big data is going to revolutionize the way that dealerships sell vehicles. Using the information a dealership has to connect with customers isn’t new, but new technologies have changed what is possible. Before big data, dealerships used what info they could find to try and draw in customers looking for new vehicles or service with direct marketing, email marketing, phone calls, etc. This method did bring in new customers, but for every interested customer that receives a mail piece or email, many others just throw it in the trash, because it’s not relevant to them, which is a waste of marketing dollars. If you could determine the customers most likely to be interested in your offer and only market to them, you could save money and bring in even more business.
The problem has been that dealerships didn’t have the necessary technology to mine the information in their CRM and DMS. Thanks to advances in technology and processing power, however, dealerships today are able to comb through the data they already have to find the right customer and send them the right message, at the right time, and get the sale. But in order to do that dealers need to understand the data they have and how advances in big data technology can help them do that.
In order to help our you better understand big data and how you can use it in your dealerships, we spoke with three experts in the field: Boyd Warner, CEO of AutoAlert, Jason Ezell, VP of Sales Operations for Dealeron Inc., and Curtis DeGroote, Director of R&D and Partner with DriverLoyalty. They helped us understand what big data is, how it works, and how dealers can use it in their own dealerships.
Dealer Marketing Magazine: Big data has become a catchphrase lately, but what exactly does it mean?
Broadly speaking I view “big data” as simply the promise of technology and how it can positively reshape the way we do business. It represents an opportunity to analyze individual data sets or to join more than one data set in to a value-creating event. The application of big data can vary significantly across industries, but perhaps the most meaningful application for individual dealerships is the ability to enhance the consumer experience with timely and relevant content. For example, we can now connect variable operations and prospect data with fixed ops ownership and financial data to create compelling consumer engagement content. The net result for dealers is the ability to create new sales and vehicle acquisition opportunities we would not have otherwise had in a world without “big data”.
“Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.”
- Big data uses inductive statistics and concepts from nonlinear system identification  to infer laws (regressions, nonlinear relationships, and causal effects) from large sets of data with low information density to reveal relationships, dependencies and perform predictions of outcomes and behaviors.
Basically, it is the aggregation, normalization and analysis if huge amounts of unstructured, unrelated data to find relationships and trends in the data that before were not possible based on standard data processing software or practices. Big data has to combine massive of amounts of data from different sources and translate and normalize that data to the same measuring stick, to be able to combine and compare this data. It’s like in math, not being able to add two fractions with different denominators, you have to normalize the fractions to the same “scale” or denominator before adding them properly.
According to 360i.com’s CMO Guide to Big Data: “In its simplest form, big data can be defined as large volumes of information, including both structured and unstructured data. Structured data is found in traditional enterprise databases or data warehouses. Unstructured data includes raw machine-generated data, data from personal productivity applications such as email, word processing, and presentation software, and rich mixed-media data from social networks.” In Layman’s terms its more data than we know what to do with using our past methods. To handle big data you need to have a big powerful provider to aggregate the structured and unstructured elements but even more importantly you should have a logical goal in mind. Sure you may have access to big data, but what do you want to accomplish with it. Remember Billy Beane and the movie Moneyball? It was the first use of big data in the baseball industry. In 2000, Billy Beane was the first general manager in major league baseball to use advanced analytics to fully exploit the data available to him. By 2003, a number of other teams had caught on. In 2004, the Boston Red Sox broke the curse of the Bambino and won the World Series for the first time in 86 years. They will publically acknowledge that they did so by hiring Billy Beane’s second in command (after offering Billy himself the largest general manager salary in baseball history) and implementing a rigorous advanced analytics program that capitalized on a richer set of data than anyone had used before. Billy had a goal in mind, then a plan and then the execution. And he stayed the course, he was consistent. It seems silly to ignore the existence of big data, but it’s equally foolish to engage in the practice of trying to use it without first having a need and then a goal to best leverage this rich data.
DMM: What kind of information can dealerships find in their data that they couldn’t find before?
Because there are so many sources of data outside the dealership, dealers can now leverage big data to analyze and compare what goes on inside their dealership, to the trends happening outside their four walls. For example, a dealer can now see shopper demand in their own market, not from their own websites stats, but from the aggregation of other data from their market. This would allow dealers to align their inventory in stock, to that of the vehicles being most shopped for in their market, thus increasing turn and reducing wholesale losses. Just as easily, dealers could see demand on certain vehicles falling, and get rid of those vehicles sooner to avoid losses.
Mainly, dealers can take their existing data from the CRM or DMS and cross reference that data with other sources of big data. For example, dealer might have limited info on a new prospect lead or current client/service client. Dealers can take these client lists, send them to Experian, Polk, Dataium, and others who can append large amounts of additional data on that person so dealers have a full profile of all consumers. Experian and others are specialist in big data, because they produce so much and gather even more. So now a name, address, and phone number, can allow you to know income level, currently owned cars, education level, even current internet shopping behavior to show if they are a likely candidate or not, and where they are in the buying funnel.
Most DMS’ information really hasn’t changed. However the focus on big data in combination with the DMS data has allowed dealers and vendors to focus on new trends, better interpretation and use of historical triggers, the ability to predict, communicate, and close deals more profitably by recognizing behaviors and varying the message and offer based upon the concept of a customer profile, rather than just a customer list.
Today we can find almost any data we want and most importantly we can deliver the data in a digestible and actionable format. We can index, rank and manipulate data via queries and algorithms to create insights that were previously unavailable at the dealership level. For example, we now have warranty information, rates, residuals, and manufacturer incentive data at our fingertips with the ability to cross-reference each data set. All of those data sets were previously isolated and managed by hand, via fax or via phone.
DMM: How can dealerships use that information to market to their customers?
Depends on what they want to accomplish. If your goal is to obtain new customers, than many dealers use the geographic information to determine where they do the most business, not just using the old “radius” as a rule. If their dealership is more progressive, they will look to establish a culture of transparency in message. Early adopting dealers that have embraced transparency have found that just like open-source in the programming world, transparency in the market place build trust and confidence which leads to a higher close rate. Transparent dealers recognize that with 25,000 customers in their database, they can’t sell all of them this month so there has been a significant shift from hunting to farming in process. It’s never been as important as it is today to plant the seed and take care of it so that you can reap the harvest. Big data makes it possible for the dealer’s customer to get the same information they have from the smartphone while in the showroom. As such, many dealers have committed to be the “trusted provider” to their customers instead of letting them get that information from their competitor. The presence of big data gives them the ability to narrow the old list down to reach those that are most likely to buy now and in the near future while delivering them a very personalized presentation to upgrade right on their smartphone, thus preventing them from seeking out the desired information. This gives them the first shot at closing a deal and at a great profit.
Dealerships can use this information to market to specific consumers with the highest probability of taking action and avoid the inefficiencies of marketing to a broad audience or demographic. By marketing to a specific consumer we now have the ability to create a compelling and personalized call to action. For example, knowing a consumer’s equity position, or lack thereof, in a vehicle can greatly impact your ability to convert a lead generation campaign. In addition, knowing that information up front will dictate my marketing message and whether or not I will market at all to a certain set of consumers for a given campaign.
Big data is what is being use to retarget shoppers across the web. So when you shop for shoes, then go to weather.com, you will see an ad for shoes. This is probably the best advantage big data can offer dealers, and they don’t even have to know or use big data. So after a shopper leaves a dealer’s website, and shows up on ESPN, weather.com, CNN etc., dealers can now put their message in front of that shopper whereas before the OEM was retargeting that person. But now dealers have that same advantage to sniper target their own website shoppers all across the web on non-automotive websites by using companies who have this ability through big data
DMM: How can dealerships use big data to segment their customers and send them the right offer at the right time?
Offering the right message at the right time requires aggregating your database in to meaningful and high propensity to act segments. Some of the most common and high value segments include lease versus buy, warranty versus no warranty, equity versus inequity and so on. Once you’ve defined your large segments you must then define specific execution strategies within each bucket. In the case of a lease segment you will want to further refine the data by lease term, monthly payment, equity position, mileage, etc. in order identify value creating opportunities. Then you can begin to execute. For example, consumers 6-12 months out from lease termination in a positive equity situation are some of the highest value opportunities in a dealer’s portfolio. This segment affords opportunities to pull forward a new retail sale with similar payments terms for the consumer while also acquiring a late model vehicle that is likely a CPO eligible unit that can lead to yet another higher gross sale. And the best part is that you have created a compelling and personalized consumer message that adds value for you and the consumer.
One of the big breakthroughs is to be able to use big data to gain insight into shopper behavior. One website will not give you enough information on a shopper to do much with. But aggregated data on that shopper certainly can.
For example, you want to be able to put the right incentive in front of the right shopper at the right time. With lead scoring and active shopping data from these shoppers, dealers can know if a shopper is a 1 or a 5 in the funnel and give them incentives to match. A “1” might get an offer for a $25 gift card with a test drive, whereas a “4” or “5” might get a “$1000 off on this car only this week”, knowing that shopper is hot and the vehicle he is hot on.
There are several ways to leverage the information. Today dealers use DMS data and combine it in an automated fashion to deliver Tier I offers available from captive finance providers directly to Tier 1 customers as well as Tier II, III offers to customers that fit those buckets. The other automated process that exists is vehicle finance escalation. This is where the logic, when calculating the matched model and trim for a customer, will automatically submit the structure of the deal via secure feed in real time, to check if that finance advance amount works for the captive finance at that Tier. If it doesn’t, then the logic will select another trim level and repeat until it finds either another trim level or a comparable model that it does work for, in order to deliver a personalized payment to the customer. The payment includes the amount to finance, the trade-in, tax, title, license and registration. The customer receives an out-the-door payment. If they want to choose something different, they have a private web portal that has the same logic engine for them to select from the dealer’s inventory and recalculate on demand to find the vehicle and payment they want and the total cost to upgrade. These process run based on triggers that are set ahead of time so the customers receive it when they actually qualify instead just receiving a blanket type advertisement.
DMM: Are there legal issues about using big data to market to customers that dealerships need to be aware of?
Privacy and disclosure have never been more important than they are today. The dealers customers are commonly receiving offers that do not have the proper disclosures. The staff are not attorneys and often send communications that would cost the dealership dearly if the FTC wanted to focus on these communications. The most obvious examples are having FTC Compliant payments in any calculated payment that goes out in a marketing message. There are few vendors that actually provide this, and it’s unlikely any of the payment messages coming out of the staff’s email tool are compliant. None that I know of.
Privacy is another component that is overlooked when marketing is done. When a dealer calculates a customer’s payment, or list’s their VIN# on the outside of a communication, they are putting their customer at risk. The best practice is always use an enveloped letter. Variable print technology leverages the power of big data in printed communications and studies show a 25% lift in engagement with personalized communications. Since the best dealer average of email collection results in having less than 50% of email addresses in their database, its stands to reason that every dealer is at risk, either to potentially violate the privacy statues or risk of losing a customer by not communicating at all. The simple fix is to either use a compliant vendor to execute the communications in enveloped letter, hire an attorney to inspect every outbound communication or establish a policy that any letter that contains variable information beyond the customer’s name should be inside an envelope.
Disclosure: The best practice for disclosure is to hire a legal firm that specializes in Automotive Advertising such as Hudson Cook, who wrote the book Carlaw. Even though you may find inexpensive legal advice, you are likely to spend more as you may have to teach them the car business and how you advertise and this extends the amount of hours and cash you will spend. Finally you can reduce your legal pain by simply disclosing how you are related to the customer. Such as a simple line that says “You are receiving this because you purchased or serviced your ‘variable vehicle’ at our store on ‘variable date’. ” Every email communication should have an opt-out link. There is no debate here, this is a required legal element of email.
Big data is an emerging topic that dealers need to learn about if they want to succeed in the twenty-first century. If you want to read more about big data or anything else about running a more profitable dealership, visit www.dealermarketing.com.