Episode 85  |  11:52 min  |  07.27.2021

“Data Does Not Make Decisions”: Leveraging Data for Consumer Brands (Multi Guest Review)

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This is a podcast episode titled, “Data Does Not Make Decisions”: Leveraging Data for Consumer Brands (Multi Guest Review). The summary for this episode is: <p>Marketing experts at Pearle Vision, Advance Auto Parts, Regal Cinemas and Nissan all explain how they use data to put their brand in front of the right people.</p>
Takeaway 1 | 01:07 MIN
Hiring For Passion, Not Just Expertise
Takeaway 2 | 00:47 MIN
Data Doesn't Make Decisions, Experts Make Decisions Using Data
Takeaway 3 | 00:35 MIN
Importance of the Small Things
Takeaway 4 | 03:13 MIN
The Critical Role of Data
Takeaway 5 | 00:59 MIN
Best Practices for Using Data Effectively

Marketing experts at Pearle Vision, Advance Auto Parts, Regal Cinemas and Nissan all explain how they use data to put their brand in front of the right people.

Jared Walls: Welcome to The Marketing Stir podcast by Stirista probably the most entertaining marketing podcasts you're going to put in your ears. I'm Jared walls, associate producer, and Stirista's creative copy manager. The goal of this podcast is to chat with industry leaders, to get their take on the current challenges in the market, but also have a little fun along the way. We're taking a break this month. We thought we'd reshare some takeaways from season one. In this episode we hear from Doug Zarkin, vice president and CMO of Pearle Vision. Yogesh Deep senior vice president growth and strategic pricing at Advance Auto Parts. Ken Thewes CMO at Regal Cinemas and Allyson Witherspoon CMO at Nissan. They all offer insight on how they leverage data in the marketing efforts of their respective consumer brands. Give it a listen.

Doug Zarkin: Let me kind of break it down a little bit. I think at the core, a core philosophy that I have really centers around people, and it's what I look for in building a team. I have found, throughout my career, to really focus on hiring passion, not necessarily just expertise. I've told this story before in a few settings, but I remember interviewing somebody and I had two candidates. One candidate ideally educated, another candidate, city, college educated, and on paper, the Ivy League educated had an incredible resume. But when I asked that person, that candidate, why should I hire you? They immediately went to, well, I was educated at X, Y, and Z. The city college educated basically said, listen, I want to make a difference. You know, I want to learn, I want to grow. I'm committed to this business. And that was very early on in my career. And I went with the city college educated candidate and it really reinforced the importance of hiring for passion. You can teach somebody a job. You can't teach somebody to be passionate. So for me, the first philosophy for marketing is to hire passionate people. The second philosophy really has to do with the world of data. And obviously you're an organization that has a wealth of data, but I am a firm believer that data does not make decisions. We make decisions, experts make decisions using data. And the reason is, is that data is only as good as the questions that you ask, making a decision based on what shows up on an Excel chart is a recipe for disaster because you lose the ability to understand the thinking behind what the numbers mean. I think one of the biggest challenges we all face as marketers is we have too much data now. 10 years ago, you didn't have enough. Now you got too much. And it's about trying to figure out what data is most meaningful. So I'm a firm believer that it's not the data that makes the decisions, the data that helps you make the decision, but it's people make decisions using data. Third philosophy is the importance of small things. I am a firm believer in life outside of work, as well as inside of work. That small things matter. The importance of saying thank you, for example. The importance of recognizing when somebody does something well in the moment. Those are things that really build trust. Not only when you're trying to put a brand on the brain of a consumer, but also amongst a cross- functional team. Those small little things of how people conduct themselves and how people run their specific function within a business, I think is incredibly important. I think the last philosophy I'll share is what I would call the 80 20 rule. 80% of the time, if you can get something to the 80% level of perfection, you're good to go. It's identifying the 20% of the time that you must be 100% perfect that is really the challenge, and it really speaks to the law of diminishing returns. Is making the logo 5% bigger, going to be a meaningful change? And if the answer is no, and your creative team is telling you to leave it, then you leave it. If the data that you have is at the 80% confidence level, does it give you enough to make the decision? If the answer is a decision that has hundreds of millions of dollars ramifications, you may want to spend a little bit more time pressing to get more data, but in reality, the majority of the decisions that we make, if you can get things to the 80% confidence level, you're pretty good to make a decision, positive or negatively. But really identifying and prioritizing what your team, what those 20% of the items are, I think is invaluable.

Yogesh Deep: This is what I would say. Data is a great hope. People call it as the next oil for the world as well. But when it really comes down to application of data, the number of use cases start to blend well, pretty fast. That's what my experience has been. In the advertising world, obviously, there are a lot of companies that I don't have to really name them, but, they may be flashing in your mind as we speak about it. They obviously have changed the word for good forever, by using data. But in the business world, if there is one function, which really tries to the power of data that I would say is pricing. And I'm not trying to be exaggerating here, or I'm not biased here. I truly mean it. Right from how we start to go and make our models, which tell us what pricing it should be. So they incorporate the feedback from customers. So that's data because they are shedding their inputs. And we convert that into data. What is our category's role in the eyes of the customer, how we really want to drive that rule as an organization? What is our intent? What is it that we want to go and do with it? You know, that's another data set which we need incorporated to into our decision making process. Obviously there's this thing called elasticity, as pricing changes, so does the demand and what are those impacts? So from a transaction level standpoint, that's data, we do keep a sense of the marketplace. What's going on, what our competition is doing, how inflation is shaking out, what else is going on in general from a macro economic perspective. So these are all waiting data streams and weaving that into our models. It starts itself. The whole journey itself starts with data for us. And then all along the way at the end of the day, it is about arriving to that specific price point, which really reflects the value of our offer to our customers. Data plays a very, very critical role, but what is very unique about pricing is the action itself is data. We have to transmit data, think about it for millions of our skews, across thousands of our stores, and even tens of thousands of our B2B customers. That data gets transmitted through a pretty intensive, I would say technology infrastructure, and we have to really go and stay on top of that. All those pipes are the conduits from a CSC customer service center, about a headquarters going into our stores. Where the moment of truth with our customers happen. The data flow itself also has to be really robust and well talked through flawless execution has to happen. So I think pricing is one of those unique use cases where everything starts with data and it ends with the data. So I think that is truly an oil for us. I would say. I'm a chemical engineer, right. So I have to use the oil.

Jared Walls: Use the oil, I like that.

Ken Thewes: With all of the emails that we do when we're open, we're sending at least one a week and there'll be times where we go two maybe three, depending on if there's news to share and we'll segment those, we'll do up to a hundred versions a week. We could go even more granular if we wanted to. But I think if you're a horror fan, we really want to focus on the horror movie that's opening up, that you see that front and center. We tend to include other movies that are open just in case, because the average consumer doesn't just watch one genre. By doing that we're just getting smarter and smarter when we see which customers and how they're segmented, what are they clicking on throughout the email? And that's just helping us get better down the road in getting again, more granular with how we segment our emails.

Vincent Pietrafesa: Yeah, that is interesting because my initial thought was, okay, well, there's, 500 plus theaters. It must be geo- targeted to try to drive people in, but that's really not the case. It's more of the event that's kind of going on. Is that a safer assessment, Ken? It's around the movies that you-

Ken Thewes: Yeah, it's both. You know, an example is if, when we refurbish a theater in Manhattan, we just spent about close to$ 15 million refurbishing our Union Square theater. Is, have to make the trek up there, Vincent, because, state- of- the- art, it's an incredible experience. So when we're open, consumers will get to see it. So we'll definitely craft some geo- targeted messages, letting consumers in Manhattan, know inaudible a theater. And again, there we do that across the country. There may be a movie or content event playing limited geographically and we'll do that. But then when a movie opens up wide, that's where we get into more genre charts.

Vincent Pietrafesa: I want to talk about data because you and your career and your role now you use data, but what advice do you have for marketers out there on the best, best practices, best way to use data effectively?

Allyson Witherspoon: That's a great question. Where I feel like I really got a lot of experience was, one, especially if you're starting out, learn, CRM learn the basic fundamentals of CRM because that you add in technology platforms you lack, you add in, things like DSPs, you add in things like that. And that those are enablers of the fundamental strategy of how do you reach the right consumer with the right message at the right time. And so I think for me, it's learn the fundamentals of CRN, stay on top of what the trends are when it comes to the Adtech and MarTech. That's going to enable that. And to me, I would just keep constantly learned. This is an evolving space, understand you're never going to be an expert in it because that's how quickly that it's evolving and just stay on top, leverage the people around you, leverage, the partners that you have, understand who the new players are as well. And just stay on top of your skills.

Jared Walls: Thanks for listening to The Marketing Stir podcast by Stirista. We'll be back with full episodes in September, but until then, please tune in for a month of special topic focused free caps from our season one guests. As always please like, rate, and subscribe. If you're interested in being a guest on the podcast, email us at Info @ themarketingstir. com. See you next week.

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