Making a sale in the mobile moment can be pretty straightforward. But keeping your user interested and engaged long after the deal is done—especially if it’s a big-ticket item with an even longer lifespan-- is a much more significant challenge. TrueCar, a digital automotive marketplace that provides comprehensive pricing transparency about what other people paid for their cars and allows people to connect with TrueCar dealers to buy cars, is winning the battle with a smart approach to advertising and audience data. Our host Peggy Anne Salz catches up with Rachel Wang, TrueCar Manager of Data Science, to talk about the *real* value of TV advertising. Rachel also reveals how she connects the dots in data to turn browsers into buyers and shares her pick of engagement tactics to keep consumers interested and open to interacting with TrueCar again and again.

Peggy: Hey, welcome to Mobile Growth, the podcast series where frontline growth marketing experts share their insights, experiences, expertise, everything so you can become a better mobile marketer. And I'm your host, Peggy Anne Salz from MobileGroove where I help clients grow their revenues and audience reach through content marketing. And on my watch, this series will introduce you always to the people who know how to drive growth because that is what they do. And we have a great roster of incredible, accomplished UA ninjas, speakers, people in the industry that understand growth because that is their job. And my guest today is Rachel Wang, manager of Data Science at TrueCar. Rachel, first of all, thanks for taking the time and joining me.

Rachel: Thank you for having me.

Peggy: So Rachel, I'm excited, you know, manager of Data Science because we know now that everything we're doing in apps whether it's UA, whether it's engagement, it's all about the data.

Rachel: Exactly.

Peggy: I mean, it makes you almost wanna go back to school and say, "Hey, you know, I should have studied something else." I'm just curious what is your background?

Rachel: I had a bachelor's in mechanical engineering and I realized that digging oil or just kinda like exploiting the environment, it's really not really something I'm interested in. I want to do things that really can help people. So, I moved into Data Science and I've been working in TrueCar for almost three years. And it has been a great journey because I actually enjoy the feeling when somebody meet me and say, "I have used your service and it has been pretty good." I enjoyed that feeling. So, it's pretty awesome.

Peggy: And also lets you get beyond just the numbers because it's about human behavior, it's about audiences. And what you're doing at TrueCar which we'll get to, you know, is using the data to make a better experience. So, TrueCar for everyone out there who doesn't know it, I mean, it's obvious it's gonna have something to do with cars because of the name. But tell me about the app and the website because you have both.

Rachel: Yes. So, we were founded in somewhere around 2005 and we have been a public company for four years now. We are an online car buying service and we connect consumers and dealers, and by providing them the right information in the middle. So, a lot of TrueCar are really just like data products. We gather data from all around the market and study the consumer behaviors, and help dealers kinda like market their inventory in a sense. Yes.

Peggy: And the mobile app, what's the background on that? Because you have the site that's well established. The app, is it complementary? How does that work with the website together?

Rachel: They're essentially providing the same service. We started with the website because car information is sometimes just like so detailed and you see a lot of photos and like that. And we were doing well on desktop until we realized that how many people are actually expecting this kind of service on mobile. So, we started building the mobile app probably seven, eight years ago and it has been crazy like, to realize how much free traffic you can get by doing mobile and by doing a good app. Yeah.

Peggy: I mean, it's interesting because I'm a veteran in the industry. I've been around a while in mobile and I remember this big conversation in the early days with mobile payments like. But are people ever gonna use mobile to do anything serious like buy a car? It's like, "Oh, hell no." They're not gonna do that. Excuse me, but...

Rachel: It's always funny even in the hindsight. Yes.

Peggy: So what is the usage on your app? I mean, what are they doing? Are they anyone like, you know, getting a Porsche on these things or is it big ticket items or it's just like, "Oh, yeah," you know, some run down easily, you know, sort of used car, but nothing special? What are you seeing?

Rachel: So, being able to transact on the app is the ultimate dream that I think the whole car buying industry is chasing at, but nobody has really been able to do it. But we have finished most of the upward process which is helping to research the car, research the inventory, get the car pricing, then you kind of get the dealer's direct pricing for you. And when you're happy with that we give you our car buying certificate, and you can save it on your mobile. And when you go to the dealership, you can take this with you and dealers will honor that price for you for this specific car.

Peggy: That's really smart because then you escape that whole, you know, abandoned... Well, it wouldn't be a shopping cart. It's a car, right? But, and the abandoned cart thing about getting people almost to take that leap and make that purchase. So you have got that price, you've got, you know, a feeling that you got a social contract that you could actually really go and execute. So what is your like... I don't know. Is there like, a higher rate then because you've moved them all the way through the funnel or do you still have people who drop off and say, "Well, it's great to have that price, but I'm moving on"?

Rachel: Yes. It is a higher rate.

Peggy: Can you share or...

Rachel: Yes. I think this is basically public information. So we charge 299 for a new car transaction and 399 for a used card transaction. So compare it with other competitors, we really make sure that the dealer has sold that car before we charge them. So, it's pretty cool.

Peggy: Okay. And it helps... So, it's basically creating, you know, one of those marketplaces. It's like the on-demand world, you know, we saw it with ride sharing and driver services, with Uber, we see it with, you know, food delivery. And now, we're seeing with cars. So, you're making it possible for dealers. They have cars on their lot, we've got users, you're bringing them together. What's your business model in the middle?

Rachel: Our business model, I think it can go back to our value proposition which is ultimate transparency because buying a car sometime is feel so intransparent, it can feel so intransparent sometimes because you just feel like you never know if the price you are getting is a real price and things like that. So, we first create a market pricing model that gathers other people's transaction to show you that if you are buying this car, this is the fair price you've been paying and that model is actually very, very solid, accurate, and has been pretty successful. And with that model, we are able to gain a lot of visitors to the site. And then we have our own dealer network which by the way today has reached somewhere around 13,000 to 14,000 dealers. And we let the local dealers decide which price they will be willing to offer to these consumers. And we pick the dealers that are most likely to close to the consumers to help them smooth this process. Yeah.

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Peggy: And we are back. Welcome back. We have Rachel Wang, manager of Data Science at TrueCar. Rachel, great to have you here. And in the first part we were talking about your company, and then how you're growing, and what you're enabling. But of course, you're a big company, you're not a startup. But this is about growth. So, how are you at high level first harnessing data to drive that growth? Because it's a big topic, but you have to start somewhere and be very focused. What are you precisely focused on at this moment?

Peggy: Yeah. I think I can really divide that into two parts. One part obviously is how we are spending our marketing money. Like everybody else, we're spending with Google, with Facebook. But interestingly enough when you study your user to some level, you realize that for a lot of our users who are people with family, people who are middle-aged who can afford to buy a new car, they actually live in the TV world. And by spending and buying on TV ads, we have actually done pretty well if you look at the data, the conversion, the little spike of visitors who have seen the ad and come to our site is actually pretty impressive. So, I think that's something that's really interesting to find out. Yeah.

Peggy: It's interesting. So, I'm hearing that a lot from app developers also in games, you know, they're saying, you know, in some cases, TV time is also cheaper depending on that...

Rachel: Yeah. Exactly. Yeah.

Peggy: I mean, what have you seen? I mean, could you give some numbers in either, you know, what is meant for your budget. You're obviously getting them more mileage out of your budget or what it means in uplift because you're using a multichannel approach, right? There's more to life, I hate to say it, than Facebook and Google.

Rachel: Yeah, yeah. I think we started by spending somewhere around like 5% to 10% of our marketing budget to TV and it has performed so well that we are actually increasing it to a pretty good amount somewhere around 30% or even 40%. And it's really about which channels you are advertising on as well because people who make the car buying decisions, they probably like a certain kind of TV show or they watch TV, you know, in a certain time range. And by starting all of that it has really helped with our way on just like market spending. Yeah.

Peggy: Okay. So one message I'm hearing is, you know, think multichannel, don't just think about, you know, digital advertising, performance marketing. Think about, you know, beyond that. Another way you're probably using data is to, you know, segment, target, engage, re-engage, convert, move your users through the funnel by understanding, you know, who they are and what they're doing, and all that. Maybe you can lift the lid on that a little bit.

Rachel: Yeah. Of course. We have a great amount of traffic and one of the challenge there is how to convert them all the way to the end of the funnel. And the key thing to understand there is why do people browse. And I think this is probably a shared question of everybody in the industry, which part do they exactly not understand to make them leave the website? And we have been using some interesting service to help us understand that question. So for example, one thing we're using is to track the movement of the mouse of a consumer on the website to see where are they staying at, which part are they clicking that really shouldn't be clicked and stuff like that. We are also really experimenting a lot with messaging because car buying is complicated unless you are in the industry. So, by seeing something here under this number, what are you leading the consumers to believe in or to expect. And sometimes it really can backfire. So, we do a lot of messaging experiments around that. Yes. And see the data, and see which is a good way of messaging we should be going with.

Peggy: I mean, that's great because, you know, we do have to use messaging in apps because we have to create a conversation. It's great to be on the phone, but you're not gonna be the brand in the hand, you know. We hear so much about, you know, low usage, you want frequent usage, you want frequent engagement. And you can't just say, "Here, use my app." You haven't used it usually and not everyone's buying a new car every day, right?

Rachel: Yeah.

Peggy: So, what are your lessons about maybe some engagement, some literally, okay, pun intended rules of engagement for your app experience? What can you share?

Rachel: We have reached the stage where we are actually tracking our old customers because some of them have bought a car with us five or six years ago and it's probably time to buy a new car again. So, we do e-mail campaigns around that. We also have partnerships with insurance and banks so when people apply for car insurance or are rethinking about their insurance or are just like browsing car loans, it probably is a good indicator of them being ready in the market to buy a car. And we leverage that data as well. We have really found like very meaningful just insights by deeply combining the data of ours with the data of our partners.

Peggy: That's interesting. Of course, you know, UA is, you know, it's good to acquire users. It's also expensive. You wanna have valuable users, you just don't wanna just, you know, prey and spray, just put it all out there, all the ads everywhere. So, it's good that you're looking back in your data and saying, "Hey, you know, we can re-engage with users five, six years ago, whatever. It might be time again." What else are you seeing in the data? Because it's data science, a lot of this is about pricing. That's what your panel was about. But what else are you... What other clues are you getting in the data to how you can be getting your customers to use you?

Rachel: That's a very good question actually because there are so many indicators and user behaviors indicating how ready they are to buy. And some people are just browsing, and they probably are thinking about buying a new car in six months to a year. And some people are coming back every day browsing the same entry over and over again because they are so ready to buy the car. So, how do you message differently to these kinds of consumers is a very interesting question obviously. And how to not annoy those who are not ready to buy with excessive messaging and campaigns, things like that is also something we are learning from the data

Peggy: But it's fascinating that you can learn that from the data.

Rachel: We can, you can learn from that.

Peggy: I mean, there are probably indications, clear indications of behavior. I mean, you won't share it because it's gonna be your secret sauce, it's gonna be your IP. I'm not gonna say how do you do that. But maybe just at a high level because, you know, our listeners, we're practitioners, we do this stuff. They do it rather, I talk about it. But, you know, is there something you can tell me about the key indicators of intention in the data that you can lift the lid there?

Rachel: Yes. One thing is absolutely the time somebody is staying on the website, the time people are returning to the website. And if you're even able to do cross-platform tracking, you can see if somebody has moved from researching it on the desktop to do it on mobile maybe indicating that they are more ready to buy since they are already on the road visiting dealerships. I think these are definitely those three probably most like, a strong indicator and common use indicator for anybody in the industry

Peggy: So, last really quick question because I'm just curious myself. I can't let you go yet, Rachel. I have to ask. So, what was your biggest surprise in the data to date? You know, you dig down, you're in the weeds, you're like, "Wow, I didn't know I could know that."

Rachel: That's a very good question. I have to think on that. Can you give me a few seconds?

Peggy: Yeah. I give you 10 seconds to think.

Rachel: Biggest surprise. I think the biggest surprise has always been being able to pull yourself out from the industry and to really comparing yourself to just a normal consumer. Because the car industry is so complicated and when you have been in there for such a long time, you don't realize how complicated it is for normal people. But the data is constantly reminding you of that when you see a large amount of people browsing the website at the stuff they really shouldn't be browsing, it recalls to the question and ask yourself, which is the part that we are not explaining right? And are the numbers making them surprised? Are the numbers not within their expectation? Who are your competitors that might be providing better experience on that? Stuff like that. I think that has always been a constant surprise to my work life. Yeah.

Peggy: Yeah. And it's also not just always the price, it's the journey, it's the friction. And you see all of that in the data. And I personally have to see you again, Rachel. Great to have you on the show. In the meantime, our listeners, you know, they might wanna get in touch with you, they might wanna find out more or even connect with you, I mean as a data scientist.

Rachel: Sure.

Peggy: You know, you have learnings to offer.

Rachel: Absolutely.

Peggy: I don't know if you freely offer them, but, you know.

Rachel: I know.

Peggy: You might have a blog and you might answer some questions. That's what it's all about here at Mobile Growth. So, how could someone get in touch with you?

Rachel: You can just search Rachel Wang, TrueCar on LinkedIn and you'll be able to find me. I check LinkedIn every single day. So, I'll be happy to connect with everybody. Yeah.

Peggy: Perfect. I'll do that too after the show.

Rachel: Cool.

Peggy: And that’s a wrap of today’s show, thanks for listening to this episode of Mobile Growth and a quick reminder to visit for a complete listing of our upcoming events. And don't forget to use the very special promo code MGSPODCAST30 for 30% off of your next order.  And remember no matter what kind of app or business you have this is the destination for everything you need to move the needle on growth. So, until next time make it real, make it matter, and we'll talk to you again soon.