Episode 2: Marketing in the Post-Pandemic World
As the world is slowly learning to live with the pandemic, it is imperative to consider what the post-pandemic world means for marketers. Successful marketing in the post-pandemic world will require marketers to make tougher and more informed decisions using the right marketing technology. This encompasses dealing with ever-changing customer behaviors, learning how to streamline marketing processes, utilizing the right data, creating transparency with customers, and leveraging data insights to create personalized offers for customers.
But how will that happen? Well, that brings us to an uber-interesting second episode of our marketing analytics podcast series – Marketing in the Post-Pandemic World.
What you’ll learn:
- Embracing Data-Driven Agile Marketing
- How to Keep Up with Customer Expectations Using Data
- Using First-Party Data for Personalization
- How to Curb Marketing Budget and Ad Waste
Executive Advisor, Digital and Marketing Transformation
David is a global executive advisor for digital and marketing transformation, a member of Grazitti’s advisory board, and has formerly served as CMO at Aetna. With over 30 years of experience as a Chief Marketing Officer, David has helped several consultancy businesses with product and digital marketing transformation. He works as an advisor to top executives at start-up, mid-sized, and enterprise-level organizations, driving large-scale change from both client and client-services sides. He holds immense expertise in Digital Marketing and Technology, Marketing Strategy, Organization & Capabilities, Branding, Customer Experience, and Technology Investment.
Marketing Automation and Demand Generation Manager, Grazitti Interactive
With decades of experience in the industrial automation space, Shayla is a skilled Marketing Communications Manager with a demonstrated history of translating complex business challenges and strategies into innovative solutions. Adept in the development and execution of international and multi-segment communications plans and programs for both the short and long term, she ensures that the company’s products and services stand out amongst the rest. Her impeccable skills in Sales, Analytics, Marketing Automation, Salesforce.com, and Business-to-Business (B2B) make her a seasoned marketing professional.
Can’t listen to the podcast? Read the transcript below
David: It’s great to be here Shayla.
Shayla: So we’ve talked a lot about how digital technology enables marketers to engage in innovative ways to meet the needs of their customers a lot more effectively than traditional methods. But for organizations to take advantage of these new possibilities, they need to move quickly and have a bias for action, which means they need to become agile. Many marketing organizations think that they’re working in an agile manner because they’ve adopted some agility principles like test and learn or reliance on cross-functional teams. But when you dig deeper, you discover that most are only partially agile for organizations competing in this era of disruption. This is a problem. David, how do you think there’s a way for marketing teams to become more agile by utilizing the right kind of data in the right way?
David: So, in many cases, most marketing organizations who’ve moved to agile have done it from the perspective of outbound, we have to go influence and do something from a campaign perspective, create, test, and learn the best way to do something that they want to do. And that’s extremely valuable. And we’ll get into it in a moment, some of the best ways to align the organization to do that. But there’s also our job in terms of reacting, understanding the pulse of what’s going on every single day. And the notion I like to think about is our war rooms. So war rooms, where you’ve got a cluster of folks who are looking at data from the marketplace. So to give you an example where you’re actually seeing things in customer journeys, like why are the calls into the customer service center spiking, uh, that could mean that something upstream is happening, that’s wrong. And there are tools, for example, there’s one tool on customer journey analytics that I’ve seen a lot of companies use. It’s called pointillist, where you can actually track customer journeys and start to see things like people having trouble on your app before.
And then, because they’re having trouble on the app, they’re calling into the call center. And so having teams that are clustered, for example, on customer experience data, and looking at where there are disruptions in that, and then swarming to figure out, okay, how do we fix? Maybe there’s something wrong with the app that we’ve got to fix. Maybe we’ve got to educate customers because something is happening that they’re not understanding. Maybe there’s new incentives we’ve got to provide. So reacting to the data, coming up with innovative and structured ways of going after the problem testing and seeing what works, that’s agile. And I think the most important thing to think about as you’re setting up agile is still coming back to the point you made earlier, Shayla, having cross-functional teams. And we set up quite a lot of agile war rooms. We had it for sales in our medicare business. We had small business sales. We had a behavior change going. All of that was a customer experience reaction. All of that was looking at what was going on in the market and constantly adjusting our leads coming in. For example, in small business marketing, where are our leads coming in from? So it’s not just the outbound programs that we’re doing, what’s happening in the nature of the market. Are there changes that are happening in terms of the cost of certain media?
So is it for some reason, getting more expensive to buy social media placements against the target, or certain keywords in Google are spiking in terms of costs and you have to react. So all of that is around moving quickly. You don’t necessarily know the answer. That’s why you’ve got to experiment and test and learn, but you’ve got to be lined up to see that data and be able to get in action out of the door.
Shayla: Oh, yeah, definitely. I love that idea of a war room. Um, the first CML I ever served under had this big idea as well. And so we would have a lot of meetings in this war room, you know, looking holistically at the customer journey and the marketplace. So, um, you know, that really resonates with me personally. I know. Um, so thinking you know holistically and some of these drivers, customer expectations, right? That’s, that’s always, you know, was one of the biggest drivers of customer expectations that were already on the rise before the pandemic. And considering the customers know that brands have their personal data, hyper-personalization has been the norm for a while now. How do you think companies can and should use the right data to deliver superior experiences and meet ever-rising customer expectations?
David: Yeah, personalization is becoming the expectation. Actually, I’m going to push back a little on whether hyper-personalization has been the norm. I think we still have a ways to go. I think it’s been given a lot of lip service. But I think there’s much more opportunity to think about it. So when you think about personalization, it’s not just about who you are from a demographic perspective or even who you are from how you have behaved relative to a brand. It’s also the context. Where are you in your customer journey? Are you just coming in based on a click from social media, are you calling into the call center? As I mentioned in an earlier comment, based on a problem, you may have had upstream with an app or with a bill that you got. So understanding the context of somebody and pulling that into the experience and using that is as important as understanding certain basics about who the customer is. And making that data accessible in some cases to a customer service rep so that they understand all the things that have happened to get you to a certain place where you are so they can see your past journey.
If you’re sending out marketing and reacting to people on your website, setting up different kinds of criteria based on where somebody came from, and thinking about what is the right next best action. So it’s all-around understanding the journeys and the context that people are in. I think that’s been an underutilized part of what’s going on in terms of personalization. There are definitely new tools out there. Both Salesforce and Adobe now have experienced manager products that allow you to set up all kinds of ways of understanding and tracking, and then triggering certain kinds of responses. Understanding the journey more broadly with tools like I mentioned, pointillist in an earlier discussion, you know, that’s out there now and there’s new customer journey analytics tools that are doing it. So we’re seeing a lot of tools that can do it. It’s a question though, of aligning and thinking about managing against context, that’s going to be absolutely critical going forward.
Cause where, where am I? So just because I’m a high-value customer. Okay. You can treat me well and try to cross-sell me, but I’m calling in actually, because I had a problem. I had a problem with my bill, so I want that to be the thing. Make me happy on that. Don’t just bridge to a sale for me. So it’s a question of what are the right dimensions to use. And most often from a consumer’s perspective, it’s more about context than necessarily who they are.
Shayla: Yeah. I would agree there, you know, um, personalization is maybe more of a focus to date on, you know, who the person is. You know, and less about the context and that’s, you know, excellent insights. So in most marketing teams, marketing mix models have worked well and we’ve gotten used to them as an industry, but in this time of extreme disruption, marketing mix models have been of limited use. Is there an alternative strategy that you can suggest?
David: Yeah. So the challenge with marketing mix models is they are a projection based on what has been happening. Uh, and there’s definitely a lag because these are regression-oriented models that need lots of data. And that looks at the extrapolation of trends. At a time of extreme disruption, you can’t necessarily just go to a trend line. So you do need to look at things like attribution models, um, and understand where is the traffic coming from now? Um, one of the problems is in many cases, Yours, you may still be marketing the way you were before and not necessarily testing new ways of where customers are. So on one hand, you’ve got to look at multi-touch attribution models and understand, are there shifts in where the traffic is coming from? Are there new Google keywords? Is there different content that’s leading people to come? Are people seeing you through, um, over the top media, but you also have to experiment to get that data.
So you have to be very deliberate in trying new things to know whether or not those are working because you can’t get the data unless you do something that allows you to capture it. Uh, and one of the things that I have not seen enough of with a lot of marketers are holding back some money for very deliberate experimentation. Uh, I generally ascribe to the 70, 20 10 rule where 70% of your budget is for safe things that you’re pretty solid, probably short going to drive to your answer, 20% where you push on those and test some new things within that. But then 10% try new things where you think the market is going. And you’ve got to get that data on the new stuff in order to really understand where the market is going. So some of it is tools, but some of them is also strategy and how you spend your money.
Shayla: Excellent! Thank you. Um, shifting gears a little bit back here to the customer experience, where new organizations are bringing their customer relationship management teams closer to their marketing and media teams to deliver transparent, personalized experiences to their customers. How do you think marketing analytics teams can contribute here?
David: I think one of the most important trends in marketing over the last few years has actually been the blurring of the meaning of what marketing actually is. Uh, in most traditional senses marketing was about the support for making a sale. And of course, that’s absolutely still true, but marketing is also around changing behavior to shape the customer’s relationship with a brand. And that continues after the sale, that is an ongoing part, especially for a service brand of how you interact, whether you’re in financial services, telecom, healthcare, and frankly, a lot of B2B also where you have all kinds of ongoing interactions with the customer that you want to influence. So all of that is around marketing, it’s around creating content that informs, that inspires action, that educates and guiding customers to some kind of, and I know this is an overused term, but it’s true a next best action. And so what marketing analytics teams need to do is understand all those other kinds of conversions beyond just simply sales conversions that happen on an ongoing basis and are around actions that deepen a customer’s engagement with a brand or help the company serve a customer in a lower-cost way. So looking at things, for example, of what drives digital containment. So keeping people in digital channels so they don’t call in. So they don’t have other high-cost interactions. What are the things that are causing leakage from digital channels that you want to educate people or shore up digital channels in order to make that low cost.
Looking at it from the other side, what’s driving calls into the call center? Um, usually those are problems, whether or not they’re digital, or they’re dissatisfiers. So can you bring data to bear that upstream, figure out what those challenges are, and as marketing brings the discussion to the table about the upstream customer experiences that are causing problems? So it is this blurring of marketing between supporting sales and driving the customer experience. It’s both. And you’re now starting to see the role of a chief customer officer where both of those roles, even more explicitly together or having them both under a CMO, which is what I did when I started at Aetna. I started right away. One of the things we had to build was a customer experience practice because there wasn’t a central place to manage it. And marketing analytics teams play an absolutely crucial role in bringing the data to the table on how to influence that.
Shayla: Definitely, it’s an exciting time to be in marketing for sure. Um, well thank you so much, David, for joining us today. That’s all the time we have for this episode. Please join us next time for Adding AI and Machine Learning to the Marketing Analytics Mix for achieving peak performance. Thank you!
David: Thank you!