Solve the Mystery of Big Data by Asking the Right Questions

For a large number of business owners, including many in new car sales, the concept of big data remains mysterious and intimidating, even more so than personal computers were back in, say, 1989. But as was the case with a technological advance like the PC, the productivity, efficiency, and financial benefits that big data not only promises, but already offers, are immense. Early adopters have figured this out already, but it’s not too late to get in on this growing technological wave. In fact, now is a great time to harness the power of big data.

The key to unlocking the mystery of big data in the world of new car selling is to realize that you don’t have to understand why it works to be able to take advantage of its potential for analytics, market and lead analysis, inventory management, and much more. There are plenty of vendors who can help you figure out what you need from big data and help you get it, without you or your employees having to enroll in night school for programming and IT courses. You just have to know what questions to ask.

To help us unravel the mysteries of this technologically intimidating topic and identify the questions of big data dealers should be asking, we asked four industry experts to share their experiences with and knowledge of the subject: Jason Ezell, vice president of sales operations at DealerOn; Erin Ramsay, senior manager of product analytics for Technologies; Steve Cottrell, founder and CEO of DealerVault; and Brian Skutta, CEO of AutoAlert. Thanks to all for lending their expertise and wisdom.

Dealer Marketing Magazine: How would you define and describe big data in a nontechnical way that best explains what new car dealers need to know about the subject, and how it can help them?

Jason Ezell: Big data is the massive volume of structured (trackable clicks) and unstructured (derived behavior) data that is aggregated from multiple sources to give new vision or insights into a particular industry, product, or shopping segment. It is the science of tracking, capturing, aggregating, and analyzing huge amounts of data around a certain industry or product for the purpose of generating usable reports with new, deeper insights and accuracy.

Big data can only help when it is turned into consumable reports that address a specific question. For example, you would ask big data to tell you what vehicles are trending up in popularity in a specific market, and which cars are being cross-shopped the most to that particular vehicle.

The big data results would be massive amounts of data to analyze, but the quick answer could be derived to give a specific answer like “white Honda Accords have trended up in shopping activity in the last 30 days, and the three top competitors are the Camry, four-door Wrangler, and Hyundai Sonata.” This one report gives dealers a wealth of information for inventory stocking, marketing, conquesting, pricing, and trade valuations. Big data is used to answer specific questions to a very high degree of accuracy and detail.

Erin Ramsay: The digital medium has become an integral part of every purchase decision. According to industry sources, more than 90% of all media interactions are now screen-based, and as a result, data will quickly amass across devices and become a part of everyone’s digital footprint.

Big data identifies global trends happening in the automotive space—both online and even offline. Awareness around these trends can help dealers better understand their performance as it relates to the greater industry, and improve the management of their businesses.

Steve Cottrell: Big data is a broad term for information storage that is so large or complex that traditional computers and programs are incapable of dealing with the size and/or complexity of the information. Big data is alive in everyday life and impacts dealers in more ways than realized, as the automotive world is moving closer to this reality every day.

Brian Skutta: Big data is simply pulling together various pieces of disparate data to provide actionable, high-value intelligence. The primary benefits are efficiency, personalization, and the creation of new revenue opportunities not possible without big data.

DMM: What is your response to dealers who say that big data isn’t for them because it’s too complicated, or that their dealership and/or location is too small to take advantage of it?

JE: I would agree that big data is too complicated for most dealers to analyze themselves. But the use of big data to get specific answers can benefit all dealers, regardless of size. If a dealer could know specifically what cars will be selling more in the next 45 days, they can adjust inventory in time to acquire those vehicles, acquire competitive vehicles as bait cars, advertise the right vehicles at the right time, and get better indexing on searches knowing what the most popular searches for vehicles are.

This would actually benefit smaller dealers more to give them a competitive advantage against the larger dealers, and increase efficiencies. Dealers can minimize days in stock, wholesale losses, floor plan, and increase overall sales by just having the right cars at the right time in their market.

So dealers don’t need to understand, acquire, or use big data . . . they simply need to know what to ask of it and consume the actual results. Big data is simply the tool that would be used by a vendor or company to get a dealer the answers they seek. Much like a crystal ball, we don’t need to know how it works, we don’t even need to own one—we just need access to someone who has one and ask the right questions.

ER: A dealer has to manage a lot of moving parts to run a successful dealership, both online and offline, and continuously monitoring and taking the pulse of their business through the use of big data can help position their dealership for long-term growth. For example, there are certain times of the year when traffic, both to a dealer’s website or to the store, can lull or peak, which may be due to the cyclical nature of the industry. Knowing these patterns can help identify time periods of true over- or under-performance at the dealership level, helping a dealer to better plan overall operations, from vehicle inventory, advertising investments, [and] employee staffing perspectives.

SC: There is an old saying that ignoring something isn’t the first step to understanding or even mastering it. Think back to a time when there was no F&I department, no Internet process, and nobody had ever heard of a BDC [business development center]. Embracing these processes has proven to be very valuable. Big data is not only the next frontier, but the opportunities it provides could potentially eclipse the aforementioned multifold.

BS: I would advise them that big data actually makes things simpler, not more complicated. Simply put, it is a way of delivering “low-hanging fruit” to create new sales and service opportunities. As for dealership size and location, I would focus on the fact that utilizing big data focuses on each individual consumer so it can drive profit for all dealerships.

DMM: What types of information or reports coming out of big data do you consider most valuable—and manageable—for dealers to use for marketing, analysis, lead gathering, and more?

JE: The best use I have seen in action is inventory analysis because it affects so many aspects of the dealer’s business. Dealers would kill to know what cars will sell in the next month or two and adjust their inventory, marketing, sales spiffs, competitive strategy, etc., to meet consumer demand at exactly the right time. This has proven to be very effective for any size dealer, and has provided the most accurate sales predictions the industry has ever seen. And it’s not based on what sold last month.

Another great use is lead analysis, [which tells] what sources have the best quality leads, are these leads active in the market, how active, how close to purchase, what competitive vehicles are being considered, and how intensely a particular lead is shopping a certain vehicle.

This has taken lead scoring to a whole new level of accuracy, and allows dealers to revive old leads when their shopping intensity is at the highest point prior to purchase. This can only be achieved by aggregating and analyzing massive amounts of click data from anonymous shoppers from multiple sources to get a 360-degree view of their shopping behavior. This is what big data does, only dealers don’t need to master or even use the big data source, they just want the end results and the answers to their most important, actionable questions.

Also, website traffic analysis is extremely valuable to evaluate traffic when it is only from one source: your own website. You need to know what is happening outside your [own] four walls to know the whole story, otherwise the data is skewed only to your site, and will not give you the universal answer you want: What is the best source, best keyword, best campaign, best banner, etc., to spend my ad dollars on?

If we look at just one dealer’s site, these answers will be self-fulfilling, meaning we will only have answers from our own experience and our own activity. We as dealers want to know what else is working that we are not doing, and you can’t measure what you don’t do.

So big data can tell us, by market, that a certain type of traffic is much higher quality and converts at a much high level. But there could be sources here that a particular dealer is not even aware of or not using, so it wouldn’t even show up in their own data. But by aggregating and analyzing data from hundreds of websites, data companies can tell a dealer what is working for them, and what could work for them that they are not using.

For example, a consumer search with the word “dealer” seems like an obvious source to utilize, but these searches are actually very few and have a very low conversion. Whereas a shopper’s search using the word “price” has a low volume as well, but an extremely high conversion rate. Also, in certain markets, more shoppers visit than they visit, and vice versa. So which one should a dealer use?

Big data would tell a dealer the percentage of shoppers in their market going to each of these sites. Often the numbers are very different than we would imagine, and often there is very little overlap, meaning shoppers are visiting both of those sites. In some markets the overlap is less than 20%, so it dispels the opinion that dealers have to maximize exposure on both sites. Perhaps one is going to be the overwhelming favorite among shoppers in their market. This same strategy can be used for many traffic sources, and helps cut overall Internet marketing spend by a huge amount, but increases results—the ultimate dream for any dealer.

ER: Dealers need direct access to their own data, whether it is a part of their digital solution or through a partner vendor. It is important for dealers to assess their current state and come up with specific near- and long-term goals/questions that pertain to their business.

Once these questions and goals are articulated, the appropriate KPIs [key performance indicators] can be identified. A KPI does not mean much on its own, but when a KPI is assigned to a question and/or goal and is consistently tracked over time, a dealer is able to derive valuable information that will enable better decision-making.

SC: Perhaps the most valuable information currently being utilized in the big data realm for auto dealers is in two areas.

[First], movement of inventory and pricing information. [Second], automotive marketing like equity mining and service retention. We know that consumers in any given marketing area or county may find that dealership location has more to do with ease of service rather than proximity to home. Understanding where customers live and work is a great way for an auto dealer to understand and realize their marketing expenses. Big data makes this information easily and readily available.

BS: The power of proactive engagement enabled by big data is one of the most valuable insights I’ve seen. For example, we recently found that gross profit per vehicle is 17% higher for deals initiated proactively via big data versus initiated reactively via non-big data sources like website and third-party leads. That level of insight is a powerful tool that enables dealers to tangibly determine where to spend their marketing dollars to drive profit in a competitive market that is driving down gross profit per vehicle.

DMM: In the past 12 months, what have been some breakthroughs in automotive big data technology, or key new products for dealerships that have emerged from the technology?

JE: Very accurate lead scoring and tracking: Polk is now owned by IHS, which also owns Dataium. So these huge data sets are now being combined and utilized to provide very accurate lead scoring. Inventory analysis through companies like vAuto, which has access to huge amounts of data from,, VinSolutions, etc., can now give excellent reports on inventory analysis that is market-level and extremely viable for many uses.

Website best practices: We can now see, by using data outside our own company’s world, what website widgets, structures, buttons, etc., work the best for certain brands, markets, and shoppers. Before, we could only see what worked for us, not what was working in general. But now we can get data from Amazon, eBay, Google, and other sources outside automotive, and apply and test that data on our own dealer websites to see what changes have the highest impact on shopper behavior.

This allows us to build sites that convert at four to five times the national average, whereas in years past, most websites performed at about the same level. Today, using data from outside our industry, we can use techniques and ideas that work in other industries and push our dealer website conversion up drastically.

SC: The aforementioned inventory management pricing, equity mining tools, and lead generation are all key new products that have emerged from the technology of big data.

Our product DealerVault is a perfect example of big data in a real world application, [which works] by “freeing the dealer” from restrictions OEMs and DMS providers have been placing on dealers for many years. The breakthrough of DealerVault is that it is an industry-disrupting tool that allows dealers to take the small amount of information they have in their DMS and make it available to every other external application of their choice.

By adopting DealerVault, dealers on any DMS system are enabled to get in the big data game for free. Any browser, any machine, and any person with an Internet connection can securely manage the flow of their auto dealer data to and from the DealerVault big data farm.

BS: Soft credit pulls and selling in the service drive have been a pair of parallel breakthroughs in the last 12 months. Specifically, the use of mobile devices and dealers embracing the service drive as an extended showroom are changing the dynamic of customer retention and vehicle acquisition. Soft credit pull technology is becoming a turbocharger to those efforts, as dealers now have access to previously unknown financial and credit information for service-not-sold customers.

DMM: What disclosure information is a dealership using big data for marketing obligated to give customers, and is noncompliance in this regard a significant problem in the industry?

JE: If a dealer is using his own website data only to analyze and not aggregate—or using any other sources—the standard website privacy language is fine. However, if dealers want to join a big data network to share certain data in an exchange that would give them access to a big data warehouse, they have to have the proper verbiage in their privacy policy. They will need to define what types of data are being collected and what it’s being used for, and there has to be an opt-out link or path a shopper can use to excuse themselves from having any data collected.

It’s important to mention that “shopper data” doesn’t have to mean any personal information on [an individual]. Most big data benefits comes from data that is purely anonymous, which has no identifying information to any individual. It is merely looking at click data, trending, comparisons, etc. It has no impact on the data if we know who the person is, so big data is very usable in its most raw format with no personal information at all, not even name or email.

So dealers don’t need to worry about giving away or divulging any leads or personal data on any traffic; it is simply the click behavior that is of most use. Because of this, data can be shared very safely and with no negative impact to the dealer or shopper, but the dealers’ websites do need to inform the consumer [with a phrase to the effect of]: “Shopping behavior will be monitored and data collected for analysis, but no public or non-public personal information will ever be shared to a third party.”

SC: Dealers must understand what disclosure information dealerships are using for big data marketing. With current regulations such as PCI [Payment Card Industry], GLB [Gramm-Leach-Bliley Act], and FISMA [Federal Information Security Management Act], there is a general understanding that the customer has a choice.

It’s important to understand where and when that choice is appropriate, and how to best present it to the customer. Generally it’s considered to be good etiquette to choose a provider with a proven track record with the proper experience, certification, and information security programs, [and which] also allow the customer to opt out.

BS: Disclosure requirements vary significantly by state, interaction medium, previous business relationship, etc., so it is hard to label exact requirements specifically. Overall, I do not believe compliance specifically related to big data is a problem, but it will naturally be influenced by existing advertising, finance, and credit reporting requirements. So as big data enablement evolves, it will need to be done with those guidelines in mind.

DMM: What new or different uses of big data in automotive sales do you expect to see in the next few years?

ER: Measuring the ability to connect offline and showroom activity with online activity is going to be an insight for dealers. Right now the industry is starting to find ways that enable trend comparison between offline and online activities, but there is still no clear way to actually observe the purchase path from online research to offline purchase. The ability to do this in an aggregate manner across different segments is going to be quite powerful.

SC: The largest focus in big data for the coming years is certainly the smartphone-connected car. The amount of data that can be [gained about] a vehicle user through the smartphone is exactly what the definition of big data is, as I mentioned previously. [Let’s look at the hypothetical] example of a day in the life of Ed, a smartphone-connected car user:

Ed uses the alarm on his smartphone to wake him up, check his mail, send texts, and review his social media accounts. Ed’s phone is connected to his vehicle’s Bluetooth radio. We recognize that he’s going in the direction that he typically goes to work, and he’s skipped through three songs he disliked. All of these activities are recorded in the big data logs and are available for reporting or review.

The following morning, Ed’s phone says, “Good morning Ed, would you like to review your day?” His answer is recorded and [the device] opens his email and social media, and asks if he wants to shoot a text to any of the top five people he talks to most. Ed’s phone warns him that he might want to get on the road soon since there is heavy traffic on the route, and even recommends other routes.

As Ed gets in the smartphone-connected car, it filters the music that Ed suppressed the previous day and notices that the fuel is low. It alerts him through the sound system that there is a gas station along the route and even checks prices in the surrounding area, and asks if Ed wants directions. This is just a simple example of how [big data via smartphone-connected cars] can power everyday activities.

BS: I believe the next few years will see rapid advancement in the areas of fixed operations and customer engagement intelligence. Fixed operations will be greatly enhanced by in-vehicle data, predictive analytics, and the ability to use those inputs as a customer engagement and sales tool.

Regarding customer engagement overall, I believe we will see the emergence of Web analytics to include social media as a primary driver of personalized engagement that will provide efficiency and new sales engagement triggers. Simply put, we are just scratching the surface.

Is your dealership taking advantage of the analytical power, consumer insight, and other information than can be obtained with big data? If you want to share your experiences with big data, or if you have questions about the topic, please let Dealer Marketing Magazine know. Tweet your thoughts or questions to us @DealerMarketing, or email them to

Kurt Stephan


  1. Avatar
    TapCars November 16, 2015

    The complexity of data is one reason why most dealers are having doubts in using technological solutions to boost their business. The truth is, if they find the right martech tool,like TapCars (, data can be simplified.


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