Episode 5: Building a Highly Efficient Marketing Analytics Team for Organizational Success

Shayla: Welcome back to the fifth episode of our six-part marketing analytics podcast series – Marketing Analytics Central – Conversations on Blazing Ahead with Data. I’m your host, Shayla Wentz. In our last episode, Enhancing Data Visualization for Better Healthcare and Business Operations, we talked about understanding customer behavior with data visualization and why organizations should make it a priority as well as how data visualization can help improve healthcare, simplify business decisions, and maximize return on operational efforts. Today, we’re going to talk about the cornerstone of marketing analytics efforts, the analytics team. Well, assembling a team with people that look good on paper is relatively easy, it is challenging to build a truly efficient team that lives and breathes marketing analytics. And here to talk about this, I have with me marketing expert, David Edelman. David is the former CMO of Aetna, a global executive advisor for digital and marketing transformation, and a member of Grazitti’s advisory board. Thank you for joining us again today, David.

David: Pleasure to be here, Shayla!

Shayla: So we know that technology by itself isn’t going to set you up for success with marketing analytics. You need the right people in the right roles, supporting your coding and insights. So David, what are the key roles the organizations must look to fill in their core marketing analytics teams?

David: Generally, you got to start when you’re thinking about marketing analytics with the use cases of where analytics is going to provide more lift and for most organizations, it’s usually in marketing organizations now it tends to be in three areas. One is the most obvious that most people think of is customer analytics. So what’s going on in the market? How do we segment, who do we target, thinking about, um, getting the, the actions right for different segments and being able to set up what’s going to happen in a campaign. The second is media analysis. So, understanding the cost trends in media, how to optimize, spend across media. And then the third is actually in all of the tests and learning and the backend of understanding how to set something up so that you can get a lot of insight through the actual act of experimentation. And so those aren’t necessarily titles. They’re just areas where you need to get analytic talent. In each of those though, you need to have people who, and you may call this a data scrum strategist and it could be somebody who gets down into data engineering, but think about what is the data we need. So working through, based on the use case, what’s the map of the data we have, we don’t have, how does that need to come together? How do we normalize the schema? Can we do it ourselves? Do we need new tools to help us with things like a CDP or AI support to actually normalize that data? So there needs to be someone who’s actually focused on the data itself and the hygiene of that data and making sure it’s comprehensive and it’s usable.

Then there’s the actual analysts – people who are working with that data, who are looking for patterns, who are understanding anomalies in that data, who are using it to figure out things like whom we should target, who we should not, setting up, all of that. There’s a whole set of data analysts that need to happen. And then there’s something more deep, which is more of a data scientist and really thinking through the end-to-end protocols for how we’re going to do something like large-scale multi-variate testing. How are we going to set that up and work with all of the systems to have the processes there? How are we going to tag what we’re going out with, so we can capture data on the backend?

How do we then make sure it’s going into the right systems? So there’s some architecture and some data science in there. So there are common tables for a lot of these data strategists, engineers, analysts, and so on. But I think those are the main ways to think about it in terms of people who are making sure that data itself is usable, who own the content of the data, people who are analyzing it, and then people who are sending up and managing the processes by which that data is going to generate value.

Shayla: Excellent! Thank you. Now let’s shift gears for just a minute and talk about the power behind the people, the technology piece. So when we talk about building a marketing analytics team, it goes without saying that we need to provide the right tools to enable them to perform. Marketing analytics tools help marketers measure and manage marketing performance with the ultimate goal being to maximize the effectiveness of marketing activities and justify their investment. With that in mind, David, what kind of tools or high-level functionality should marketing leaders consider when evaluating analytics technology?

David: So coming back to the way I talked about the different roles, there’s tools that actually do that as well. So you need some kind of onboarding, data onboarding, and infrastructure in which to hold the data more and more companies are using CDPs customer data platforms, and, in order to do this. And the key here is making sure that data is normalized, usable, and accessible. Um, that’s really important so that you can access it and get to it ideally on as real-time of base real-time basis as possible. So that’s one core. Then there’s various types of modeling and insight tools. And this is where some of the AI stuff that I’ve talked about earlier comes into play. So you’re seeing technologies from one company I mentioned earlier, ELSY for analyzing that data and modeling different media scenarios, understanding anomalies in the data, setting up media. Companies like Offer Fit, who can actually use that data to create multi-variate testing routines that can help you understand how different populations are going to react and then work the optimization of that.

And then the third part is orchestration. Actually the execution of the marketing campaigns in a way that’s going to maximize your ability to execute on a segment of one basis and capture data on the backend. And that’s where the large platforms like Salesforce, Adobe are very strong. But you know, there’s others that are for smaller ones, Microsoft Dynamics for smaller ones, Pardot, HubSpot, you’re seeing, you know, for smaller companies that you can use. And then you’re also seeing things that actually can help you execute and get data in the call centers as well. So companies like Genesis, um, being able to have, um, data on the interactions and be able to help the reps, um, understand patterns and be able to give different prompts to different people. So you’re seeing lots of different areas in terms of the core data, the analysis, the insight, the ability to mobilize, and then the orchestration and the execution.

Shayla: Wonderful. Okay. Now digging a little deeper though. What are the features and capabilities you think are absolutely non-negotiable when it comes to building an app marketing analytics tech stack?

David: I think I’m a consultant. I tend to think in terms of 3s. Um, so I think there’s three things that are essentially non-negotiable. I think one of the first is an open platform that allows you to bring data together and be able to plug in and use other systems. As you grow, new channels are going to come up. New data sources are going to come up. You need to understand the flexibility and openness of that system.

Secondly, you’ve got to be able to have great data visualization, and you’ve gotta be able to work with that system, those systems to see what’s going on, um, that being able to spot trends, spot abnormalities, being able to bring information from those tools to the frontline people in order to enable them to use that. That’s absolutely critical.

And then the third is actually not as much about the technology, but about your relationship with the company providing you that technology. You need to think about these things as not just transactions, but as partnerships and is the company who you’re going to work with, providing you with reasonable support, because they’re probably going to have ongoing releases. You’re going to have new people who need to be trained. And you’ve got to think about your partner as somebody who’s going to be around to help you through that evolution. So you can keep getting value.

Shayla: Thank you for that insight, David. Shifting gears again, a little bit here, um, for our last topic, um, something that we haven’t really addressed this far, but is obviously, you know, um, on the minds of marketers globally is privacy, right? Um, a major privacy concern arises from the use of data and gathering data from different sources that have a partial picture of the environment and putting it together based on time and location. So how can marketing analytics teams maintain data security, ethics and privacy in a world of connected devices?

David: I believe there is a role which is essentially a chief privacy and security officer that needs to help organizations understand, first of all, the rules, the boundaries and best practices for staying on top of this, whether it’s GDPR, CCPA there’s so many both internationally and, you know, for example, the California rules that are happening and there’s going to be more. There’s also gotta be a way to understand if accidents do happen, how do you respond? But I think there’s several things. One is it’s an organizational responsibility. Not just an IT responsibility. Everybody has to understand the importance of keeping data secure, data anonymized. And if they see breakdowns in the process, they need to pull the cord and say, we’ve got to make a change. Um, this is also something that has to be seen in terms of the way data is used with customers so that it’s not creepy. Uh, and from a marketer’s perspective, they have to be on top of it to say, are we really putting our brand at risk through the way we’re using data um, and be a part of it too. So it takes a village. It’s not just about the analytics team. Everybody has to have responsibility. I do think there needs to be a galvanizing role though, that makes sure the orchestration is happening to keep everything above.

Shayla: Right. Yeah. You know, keeping ethics top of mind, but also don’t be creepy. I, you know, feel like that should almost be a slogan for many marketing communications teams out there.

David: Yup!

Shayla: Thank you again for joining us here today, David, uh, appreciate your time as always, and look forward to you joining me again for the last episode in our podcast series, where we discuss Building Future-ready Marketing with Data and Analytics.