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Steve Schmith, Automotive News: Hi everyone, this is Steve Schmith with Automotive News, welcome to the All Ears Podcast, sponsored by Ally and produced by the Automotive News Content Studio. In each episode, we delve into topics important to executives working in automotive retailing and gain insight and perspective from some of the Ally’s best thought leaders who also share their recommendations on how dealers, and others, can navigate transformational change underway. Our objective is to provide actionable insights that you can use immediately in running your business and offer perspectives to help inform your business decisions. In this episode, we’re talking with David Hixon, executive director of marketing at Ally, about the types of data available to automotive marketers and how dealers can use that data to serve up targeted advertising to current and potential customers. David says there are many ways automotive marketers can use first, second and even zero party data, data that consumers themselves provide, to execute very customized and focused marketing. He says investment in technology plays a key role in that, including investments in customer data platforms to help better understand consumers and CRM systems to better execute marketing campaigns. He says Ally has learned a lot in how it uses its data to engage with existing and potential consumers and says there are best practices dealers and other marketers in automotive can also adopt. What are those lessons learned and best practices? Here’s my conversation with David Hickson, executive director of marketing at Ally. David, thanks so much for joining me today on the All Ears podcast. How are you, sir?
David Hixon, Ally: I’m doing well. How are you, Steve?
SS: I’m doing wonderful. Really excited about today’s conversation. Understanding customer data and figuring out how to use it is such a huge topic right now in the automotive industry. Can you talk about the differences between first, second and third party data and how each of those can be used in marketing and advertising?
DH: I think this is one of those questions that depending on who you ask, you probably will get subtle differences in the answers because there’s there’s a lot of nuances to this type thing. I think to start with is probably most important to understand how we use it and then we can get into the specifics. So in general, I think the data that we gather, whether it’s first party, second part or third party, is used primarily to drive relevance and personalization in the conversations that we have with consumers and customers. And the way I like to think of it is, you know, if I’m if I’m selling a widget and if I go grab a hundred people out on the street to try and sell that widget to them, likely many of them already have it, or many of them aren’t even interested in the widget that I’m trying to sell. So if we can gather data on those folks, it helps us isolate. You know who might be interested or who wouldn’t be interested and it drives all of the conversations that we have. So very, very important in what we do from a marketing perspective. As far as the different types of data, I’m actually going to throw in an extra one two. There’s a there’s a newer term out there now called zero party data, which kind of comes before the first party data. So the way we think of it is zero party data is data that a customer proactively gives to us. That can be something as far as them telling us what their marketing preferences are, i.e., “you can call me and email me, but you can’t direct mail me.” Or maybe something as useful as telling us when they may or may not be in the market for a particular product. We actually, on our side, spend a lot of time asking our customers, what is it that you’re interested in and when would you be interested in it? So the stuff that they give us proactively like that. We consider that zero party data. The first party data is a little different. It’s still owned by the company, you know, the company of the customer. And it’s things that we observe our customers doing. So think of Ally, obviously, we have lots and lots of customers. We pay attention to the products that they have, the transactions that they make with those products. We pay attention to their browsing behaviors on our site. So these are all things that our customers are doing when they interact with us and we track every bit of it and then use it to drive the conversations that we have with them. So that’s first party data. Second party is essentially another company’s first party data. So imagine in the case of Ally, imagine if we were to team up with somebody like an Amazon and say, Hey, tell us for our specific customer set, tell us what their shopping behaviors are within your four walls, Amazon. And that data coming back to us obviously helps us round out the view of what our customers may or may not be interested in, but because it’s not interactions that they’re having with us, that’s what’s considered that second party data. And then third party data is a lot looser. Third party data is usually purchased not from the original collectors, but companies that we think of as data aggregators. And there’s a ton of them out there, and this usually comes in the form of things like propensity scores or zip code based demographics and things like that. So we might acquire third party data to understand, you know, customers of ours that are in a particular zip code have a general net worth of x, things like that. It’s a lot less specific, but still very important and kind of rounding out the view of the customer. So you know, of those four different types of data, the level of importance or level of usefulness, I guess starts with that zero party data and then gets less useful as you go first, second and third. But the kind of the Holy Trinity is putting it all together, and that’s what we try to focus on here is get as much data as we can gather for our customers. And then that gives us that 360 view so that it can drive everything we talk to them about.
SS: So what has Ally learned about using a data-driven approach to marketing? And are there any lessons that can be applied to other marketers?
DH: We’ve learned a lot, and we continue to learn this isn’t a kind of a one and done thing. There’s there’s always new things to learn and new data sources that help us get better. But I will say there’s there’s two key things I think that have that we’ve learned and that are kind of our North Star on why we do it, the way we do it, and that’s that using the data to drive the conversations drives two very important things. One is marketing efficiencies. And by that, I mean higher conversion rates, higher ROI and frankly, just more effective outreach and then a better positive customer experience. Think of us as human beings, we’d all rather have conversations around things that we’re interested in or things that are relevant to us versus things that are not, and that creates a better customer experience and we reach out to Ally customers. I think a couple of good examples of that, or I guess one key example of that, is we spend a ton of time at Ally mining our customer and mining that first party data that we just talked about and looking for what we think of as behavioral triggers. So things that customers do that that lead us to believe that they might be in market for whatever that next best product might be. And that’s what we use to drive our communications. And as we do more and more and more of that, it really leads to, like I said, better ROI, which is the the key metric for us as marketers, and then that better customer experience for us is measured in things like unsubscribe rates to the emails that we send out when we’ve seen time and time again, when we when we aren’t using a whole lot of data to drive the conversations, people just opt out because they’re not interested. So the key thing is, I guess, to be blunt, data-driven marketing works, that’s what we’ve learned and that’s what we continue to focus on. I also think it’s not always about targeting with data, it’s also about versioning. Of course we’re going to use data to understand who to talk to, but we also use it to to drive how we talk to you. And a good example of that, I think, is we spend a lot of time in the cross-sell realm. Within Ally of there’s there’s lots of different lines of business and it’s very, very efficient for us from a marketing standpoint to try and drive volume by selling products across those lines of business. And then I think the last thing or I guess the last thing I’ll mention today that we’ve learned that’s very, very important is life stages matter. It’s kind of a no brainer to think about it, but when you market to folks based off of specific life events that they’re going through, you will always win. The efficiencies go through the roof when you’re talking to somebody who just got married, just bought a new home, just had a kid, things like that, and even certain age demographics. We’ve seen when people reach a certain age, it’s time to start talking about specific products, so focusing on where folks are in their life stages is also proven to be very important as well.
SS: We’ll be right back with more.
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SS: That’s a lot of complexity. Zero party data, first party data, second third party data. As I spoke with Ally’s Kevin Howard on the last episode of the All Ears podcast, regulations are changing and some of this third party cookie data is going away. If I’m a marketer in the automotive industry, can you suggest any best practices in terms of gathering and using data in marketing today?
DH: Yeah. And you bring up a good point. With all the regulation. And best practice number one is definitely develop a very tight partnership with legal and compliance partners within the four walls of your company. We’ve got a whole lot of data and you know, we as marketers can find lots and lots of creative ways to use it. But I think what’s most important is understanding from a legal perspective what we can and can’t use. And you know, we focus today on not only what are we legally allowed to use, but what do we as human beings feel comfortable using because there are instances where there’s things that we probably could use, but we just don’t feel comfortable doing. And there’s a lot of opportunity to do things like that because, like I said, we have our hands on so much data. So best practice number one is to understand those rules to make sure you don’t overstep any bounds and do things you shouldn’t be doing. And that’s something we focus on quite heavily. I also think, you know, you mentioned gathering that data. You know, gathering, it sounds again kind of like a no brainer, but gather as much as you possibly can. And I think that can come in the form of spending a lot of money and going out and buying some of that third party data that we talked about because it rounds out the view of your customers. Or it may come in terms in the in the way of investing in the right types of people that can have the skill sets to best organize all of that data so that it’s useful and meaningful in your marketing outreach. And like I mentioned before, I also wouldn’t be afraid to ask. We spend a lot of time asking our customers for data, and I think, again, it all kind of boils down to that human element of if you’re asking somebody for data and you’re in, you’re clear that I want to know this so that I can tailor my messages to something that’s meaningful to you, then I think it would be surprised how many people are willing to tell you, you know, the types of questions that you want to know. So once that data is gathered, the next best practice is really start mining that data. And the way I think of it is the data is gathered, the data is organized. Now it’s a shift to the strategy of thinking of things in terms of what I call an if-then logic. So go back, put yourself in the shoes of a consumer and think about all those breadcrumbs that you leave as a consumer every day that might tell companies whether it be a bank or an auto dealer or whatever else. What types of things you’re interested in a given time. So things like, you know, if it’s been six months since your customers last car service appointment, then it might be time to build a personalized comms journey around the benefits of routine maintenance. So, you know, you might think for every, as each one of my customers hits that six month milestone, it’s time to trigger a campaign to go out to to remind them of the benefits of the maintenance. Or if a customer has expressed interest in a product but didn’t convert. Maybe that’s through a page visit. Maybe that’s through a call center interaction. Then it’s time to build a personalized comms journey, reinforcing the value props of that product that they showed interested in. Or if a customer just turned 30, maybe it’s time to talk about life insurance. If a customer is six months from the lease end date of their vehicle, maybe it’s time to start reinforcing the lease end instructions and promoting that current model year of the lease vehicle. These are the things I could go on and on, and we could probably all go on and on again as consumers and think about those examples. But I’ll tell you, at Ally, we have literally a hundred plus campaigns like that that go out every single day based off of individual behavioral triggers that drive a lot of the behavioral change that we like to see within our customer base.
SS: So let’s close with some recommendations on tools to help marketers and automotive better use their data. Could you offer any recommendations, any advice?
DH: So there are some foundational things for sure. There’s lots of kind of sexy terms flying around in the industry right now. You’ll hear things like CDP, which is a customer data platform, which is basically just a very organized database of all of your customer information. Again, that 360 view that we talked about. So having that CDP or that customer database, in an organized fashion, is kind of foundationally important. I think you also are going to need to have some sort of a CRM platform, which is, in my mind, is essentially the execution engine on top of that database so that you can execute campaigns to them, whether it’s an email or an SMS campaign, or even some of the third party digital banners that we might see out another website. And then beyond that, it becomes a people thing, right, like you’re going to need to have data-minded analytical thinkers that can mine that data and find those opportunities that we’ve talked about throughout the course of this conversation. And that can be anything from what I’ll call a general analyst or depending on how sophisticated you want to get, it could be true statisticians that can go in and look at your data and build propensity models with regression analysis and things like that so that you can start to rank order your customers in terms of likelihood to do X, whatever X might be, come back and buy another car, come buy a checking account, do whatever it is that we’re trying to drive. So it’s getting those people, it’s getting the data ready, it’s getting the people that can access the data. And then there’s a utopia of tools and systems that you could use beyond that. And I think some of the most important stuff is the third party data that we talked about before. That’s where you start to get into some interesting overlays in terms of things like propensity scores and demographics. And what I think of as off us in the market triggers that we might not have from our first party data that might tell us things we didn’t already know. So in that data driven marketing world, there’s the technical tools, which is essentially just the data and the ability to execute it on it. But beyond that, the additional tools are the additional data points that we can append to make use of.
SS: David, such a fascinating conversation in a fascinating time when it comes to consumer data and digital marketing, thanks so much for spending a few minutes with us today on the All Ears podcast.
DH: Yeah, of course. Thanks for having me.
SS: That’s all for this episode of the All Ears podcast. Until next time, on behalf of Ally and the Automotive News Custom Content Studio, thanks for joining us.
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