Marketing Analytics, Big Data, and Product Brand Management TXT

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Thank you for tuning into our first podcast series Supporting Lifelong Learning and Business Career Development Needs. This podcast showcases the expertise of our Smeal College of Business professors as thought leaders in business and industry. My name is Jennifer Nicholas and I'm happy to be here representing Smeal Alumni Career Services. Today, Dr. Andrew Petersen, Associate Professor of Marketing, will be interviewed on the practical implications of his research in the marketing industry and his latest projects. To start out, could you please give us a brief overview of your research and the programs you teach? 

Sure, so as you said, I'm an Associate Professor of Marketing here at Smeal and I've been here for the last four years. I generally teach mostly in the graduate programs. So I teach in the full-time MBA program, as well as our one year masters of management program. As well as I also teach in the online graduate programs. I teach in our graduate certificate program on marketing analytics and I'll start teaching an online master's in marketing analytics program this fall. 

In your vast experience of both work and teaching, what do you feel like right now is most relevant to what's happening in businesses today? 

Well, in the area of marketing at least, there are two let's say sub areas that are getting the most traction. On one side, there is a large interest in-- what we would say-- product and brand management. And in that space, a lot of the understanding is in terms of introducing and managing brands in a very new and different marketplace. And the other side of it, more of my area of interest and expertise at least from a research side, is in the area of marketing analytics. And in the marketing analytics area, the reason that's coming about is that there's so much data out in the marketplace that businesses and specifically marketers are collecting, and what we've struggled with to this point is understanding how to utilize that data in an effective way. 

So at least from the perspective of what can be done, the role in that space would be what we would call a translator function. So how can I take data and how can I turn it into some sort of marketing problem and come up with some insight that I can implement in my business. 

What can we get excited about with marketing analytics from both the customer perspective, but also from a larger perspective in business and industry? 

So, the nice thing about marketing analytics is that it gives you some way to make decisions that reduce uncertainty. So generally speaking, historically, if I was using my intuition to make my decisions, my intuitions are based on my past beliefs about what might happen. But with data, we can make decisions where we can have some degree of certainty about the outcome. And certainty not only helps us with actually better predicting what's going to happen in the future, 

But in the world of analytics, there's also what we would call prescriptive analytics, which is better explaining why things happen, so that we can better manage what our-- in the case of customers, let's say understand why customers purchase and maybe make changes to our marketing strategy. But it also, reduction of uncertainty can also help things like a sales force because a sales force will feel more confident going up to sell when they understand what customers are looking for. 

Could you give us an example of this working very well in practice? 

Sure, so a number of years ago we worked with IBM, who sells hardware, software, and services to B2B customers. And what we helped IBM sales force understand were what were the drivers of people adopting things like cloud computing. And when we understood those drivers, what it allowed the sales force to do is not only select which prospects to go out and talk to who were most likely to adopt the cloud computing solution, but also understand what were the things that the customers, or in this case the prospects, the messages that were most likely to resonate with those customers, so that it would be more effective when you had that conversation. So you can think about it as a customer selection, you're solving that problem as well as you're solving a problem of, let's say, positioning of your product to that customer to make it most effective. 

So in that case, what we found, we actually ran an experiment where half of the sales force were randomly assigned to a group where they were given the same tools they always had, and the other half were given the analytical tools that we had developed, which helps understand which customers to talk to as well as how to position. And we noticed remarkable increase in ROI from the marketing spend by just being able to better understand which customers were likely to purchase and how to have the conversation with those customers. 

As we've entered this era of big data, what do you feel like the future looks like for the field of marketing? 

So that's a very interesting question. So I don't know if there's ever going to be a slowdown in the amount of data that's flowing into companies, especially in the world of marketing the data is growing exponentially it seems by the day. So not only do you have your traditional data, like your customer relationship management kind of data, but you also have data flowing in such as social data, and market data, and all of this data is large and it's sparse and it's very difficult to manage. And most of the data is, unfortunately, not very informative. 

And so part of what we learn in teach in the area of marketing analytics has to do with understanding how to determine what data is useful or not. Understanding then based on the data I have, what kinds of questions I can ask and answer with that data. And then how I take that solution, that insight, to market and implement it in an effective way. 

So you can think about it as in marketing analytics we focuse a little bit on tools but we focus a lot on process. What's the question? What's the data that I need to answer that question? How do I get a result, so what tool do I use to get a result? How do I draw an insight and then how do I implement it and take it to market? 

And what data does end up being most useful from your experience? 

So certainly outcome data, right. So if whatever thing I want to drive, whether it be sales, profit, market share, whatever outcome that's of interest to me to drive, certainly I want to gather that data. Then on the other side, I want to think about what helps explain that data? Now this type of stuff varies from industry to industry, so that it's very context dependent. But categorically speaking, the types of data that tend to be useful are things that we call exchange characteristics or trying to look at how people buy stuff, right. So what channel do they buy and what product categories do they buy and how recently or frequently they buy. 

Those types of things tend to be pretty informative about predicting future purchase behavior. Sometimes some demographic information, although more often you're looking at things like lifestyle and psychographic information that can help explain why people buy stuff. And then like I said, some things are very context specific. So sometimes it's product category information that's very relevant. Sometimes it's more relevant to let's say look at channels of purchase, right, platforms, other things. It just depends on your industry. 

I've noticed that you've done a lot of research on product returns. What would you consider a best practice for managing returns? 

So one interesting thing about product returns is before I started working in this space, which was I guess now about 15 years ago, in the 90s and early 2000s a lot of firms were thinking about ways to disincentives people to make returns because returns were seen as a cost that had to be managed. And we sort of took the view that perhaps there is a benefit that can exist in returns. Perhaps the ability to return an item and to do it in a way that makes you feel good about your relationship with the company, would have positive spillover effect. 

So we had a company that came to us and said, they were a catalog retailer, and they said about 5% of our customers return over 80% of what they purchase. Is this something we need to deal with? And so we said, well, let's take a closer look at the data. And what we found was that the customers who returned about 10% to 15% of what they purchased, tended to be the most profitable customers in their data. And so we said maybe returns aren't a necessary evil, a cost that has to be managed, but maybe there's some upside to returns. Maybe if done well, if managed properly, you can actually create more profit as a result of the return interactions. 

And so we went on to run several experiments and we worked with several different companies. And what we found in general was that product returns should be managed and not necessarily maximized or reduced. And part of managing them would include if people are in the optimal range, then you would manage them normally as you would your regular customers. But if you have customers that haven't ever had return experiences, that you might induce them to engage in behaviors and interactions with you that might end up in a return but might not. 

And if it does, it gives you an opportunity to have another touchpoint with that person to lead to a stronger relationship. If you have customers that are returning too much, maybe in some cases, those customers who are the 5% who return over 80% of what they purchased. In that case, you might look for ways not to necessarily to disincentivize the return, but encourage behaviors from those customers that are more likely to not lead to a return rather than the behaviors that lead to returns. 

What would those positive behaviors look like? 

So, for instance, some of the things we found in this work with this catalog retailer is purchases that were bought on promotion were less likely to be returned, because people tended to think that when you bought it on sale, even if it isn't what exactly what you wanted, you had less motivation to take it back. When people buy gifts, they tend to be not returned as often. So even if the gift choices poor, people are less likely to return. 

Things like repeat purchases. So with this catalog retailer, if you had bought a pair of shoes that encouraging you when you're ready to buy another pair of shoes to buy the same pair of shoes was usually an effective strategy to get a purchase without a return. Whereas on the other side of things, if I was dealing with customers who were less likely to return, then I might encourage them to buy a new product category, or in a new channel, or something that would get them to engage with the company in a way that they weren't used to before. And those are riskier purchases, because they're more likely to lead to a return, but they expand the relationship between the customer and the firm in a positive way. 

I will tell you several clients in our Smeal alumni coaching program, who start out with a career in direct sales, sometimes grow disenchanted with that. If they continue with a career in marketing, what do they have to look forward to? 

So, it's not uncommon. In fact, I think the majority of our undergraduates who graduate with marketing degrees get opportunities to go into direct sales. That tends to be the most common path into a marketing type career. Now sales is a very rewarding thing, and I think there's a lot of people who enjoy doing it their full career. But there are a lot of opportunities to come back and refine your skill set and new opportunities to go into. 

As I was mentioning before, the two main areas that attract the most interest right now among more mid to senior level marketers, are the product and brand management space as well as the marketing analytics space. Now my expertise and my interest lies closer to marketing analytics, so I can speak more to that space. But there are a lot of graduate certificates, as well as graduate programs that we offer at Smeal, that will give you the ability to go from a sales role, direct sales kind of role, into a position of more of a marketing analyst or a marketing manager who is taking a more strategic view of the organization rather than necessarily being on the road and doing direct sales. 

Can you tell us more about those online programs or graduate certificates? 

Sure. So right now we have a four course graduate certificate program in marketing analytics, which includes one refresher course that gets you back into some of the statistical tools that might be necessary to learn some basic analytics. And then the three other courses, one is in brand and customer experience analytics, one is in digital analytics, and one is in customer analytics. 

Then we in addition to that, if you want even more, we have a new graduate program that's a master's in marketing analytics and insights, which includes those four courses that I just discussed in the certificate as well as six other courses which expand even further on the skills you'll learn in not only the analytics but also the application of the analytics and implementation of the analytics in an organization. That will give you a master's in marketing rather than just a graduate certificate. 

What do you see as the top competencies that employers are really looking for in our marketing graduates? 

Well certainly in the product and brand management space, the competency is let's say organizational strategy. So how do I take something at a very high level and sell it in the organization and get everybody on board with the implementation? In the analytic space, it's not necessarily becoming good at the collection and management of the data. That's more of an IT or a technology role in an organization. What it is as the word I mentioned before is a translator function, being able to connect with the data science side of the organization and to be able to say to them, here is the key business question that we need to answer. What data do we have? And then here is the analysis, we should be doing and when you give me the result, I can take it back to the marketing role in the organization and talk about implementation. 

And so that is a key role. And in fact, most firms I talked to say that in marketing that translator function of analytics between data science and marketing implementation, is one of the biggest gaps in careers in terms of being able to find people to fill those positions at organizations. 

Interesting. So I'm hearing a lot about strategy and analytics. If you were to choose two or three words to characterize the future of marketing as an industry, what would those words be? 

So dynamics is a big word that's used in marketing. In that when I teach in the core marketing program here and I'm teaching our incoming MBA students and our masters in organizational leadership students, and even our executive MBA students about what is marketing and what's going on, that we stick to four key principles. And the first principle is all customers change. The second principle is all customers are different. The third principle is all competitors react. And the fourth is all resources are limited. 

So if we think about those first two principles about customer change and about customer differences, that's where we're seeing on the customer differences side such micro level segmentations going on that that data is needed to be able to group customers in smaller and smaller groups. As well as in the all customers change is when we have these dynamics. Things in the marketplace are changing so fast and being able to identify and jump on an early trend requires the use of data analytics. 

Fascinating. If I were to be pegged as a customer, would I be then placed in multiple demographic categories? 

Well you could be, but generally speaking, I wouldn't necessarily segment customers ever based on demographics. Segmentation should be done on one of three dimensions or multiple of the three dimensions. It should be done based on what you've bought in the past, what your preferences are, and how you respond to marketing. And so if you segment that way, what you're going to capture is the ability to actually take action on those segments in a meaningful way. 

Now do demographics play a role? Yes, they do. They play a role in terms of profiling people. So what I want to do is once I do that segmentation based on people's behaviors or their intentions to do things, that then I can figure out the demographics part of it which is who you are, where you live, and how I can talk to you. 

Predictive analytics. 

To some degree, yes. 

Yes. Interesting. Well, thank you so much for sharing all this with us. Is there anything else you'd like to add about recent projects that you've undertaken, something that you're excited about? 

So there are many things that I'm continuing to work on in the space of analytics. As we said, the area of customer analytics in particular, which is my interest is growing rapidly and constantly. And so I'm working on a number of projects with some PhD students here and we're looking at things like understanding how people interact with each other in networks, whether it's social networks, where we're looking at how people's social networks impact their giving behavior, so donations specifically to say University foundations. We're also looking at how people in networks, such as salespeople in networks, impact their ability to do things like cross-selling and up selling organizations. 

So network analysis is something that's really interesting right now in the area of analytics. Also digital analytics. I'm doing a lot of work in the area of measuring things like measuring text and understanding search engine optimization and search engine marketing in a different way by understanding the semantics of how people search for things. Right, those are some new and interesting areas that I think a lot of pretty good insights can come out of that can help people better manage their networks, better manage their digital portfolios, and so on. 

Thank you so much for sharing your insights with us today. Smeal Alumni Career Services produces these online resources in collaboration with our Office of Professional Graduate Programs and the Penn State online MBA program. Please reference our Lifelong Learning Webinar with Dr. Brian Cameron, Associate Dean for a Professional Graduate Programs in the Smeal College of Business. And Stacy Dorang Peeler, Managing Director of the Penn State online MBA program, titled Online Graduate Business Programs Advancing Your Career Through Lifelong Learning. 

All webinar recordings, along with more information about Smeal Alumni Career Services programs, can be found on our website at