Episode 241 / Nendra van Wielink-Mohamed / The Kraft Heinz Company / Associate Director, GCOE Global Media
Leveraging Connected Data to Tell Compelling Marketing Stories
Nendra van Wielink-Mohamed, Associate Director at the Kraft Heinz Company’s Global Media Centre of Excellence, shares lessons learnt and strategies to utilise data to optimise business performance.
Data can drive results, but not all data is useful and sometimes, not all useful data can be available or collected. Being able to delve into the world of data, finding the right connections, and steering away from too many shiny new objects, are Nendra’s key recommendations for making data driven marketing a success.
Avoiding bad recommendations
Nendra’s career has taken her around the world, while also throwing a range of “bad advice” her way. She shared with us why automating everything is a bad idea - just because it’s easy, doesn’t mean it’s the right or optimal thing to do.
Connecting the dots
The key to successful data driven marketing is being able to find connections between data points and make them relevant to your organisation. “Data is just information… in itself, it doesn’t mean anything” - advises Nendra. Once you understand the business value and the way to tell a relevant story with your connected data, you can drive changes and bring about valuable results. Nendra suggests finding the least amount of complexity or effort for the highest business value.
Don’t chase the shiny new objects
Having access to huge amounts of data can be a problem for marketers, because ultimately, not all of it is useful and trying to crunch it via new and shiny tech doesn’t necessarily lead to actionable insights. For Nendra, brands need to start by having a rigorous process for data collection, governance, and selection. “If [your] house isn’t in order, no matter how many shiny new objects you have, it’s not going to help.”
Find out how Nendra uses data to create a story that everyone can buy into and what are her models for getting connected data by asking the right questions, in the full episode.
Transcript
The following gives you a good idea of what was said, but it’s not 100% accurate.
Nendra van Wielink-Mohamed 0:00
The true driver should always be business value. This is just information. In itself it doesn't mean anything.
Tom Ollerton 0:12
Hello, and welcome to the shiny new object podcast. My name is Tom Ollerton. I'm the founder of automated creative creative, the effectiveness ad tech platform. And I am sat in a weird corridor in Soho House in Amsterdam, but I'm not here on my own. Thankfully, I'm here with Nendra van Wielink-Mohamed who is Associate Director, Global Media Global Center of Excellence at Kraft Heinz. So Nendra, thanks for meeting me here today in this freezing cold corridor. For anyone who's listening to this, can you give the audience a bit of a background on how you got to be in this position? And what's gonna happen next?
Nendra van Wielink-Mohamed 0:50
Okay, Tom, thank you, first and foremost, again, thank you so much for having me here on your podcast. It's an absolute pleasure to be here. And actually, you almost made me go to Belgium. Hello, hello, everyone, I'm Nendra van Wielink-Mohamed. My most recent role is with Kraft Heinz exactly five years next month, I'm one of the first team members hired into the Global Media Center of Excellence team or GCOE, as we call it. Since its inception in 2018. I have to tell you, though, it's been one of my most exciting mind blowing journey. In my 25 year career span, to be able to drive capabilities and sophistication in media marketing from the center. That means I get to stand on the shoulders of the giants, and building alliances with industry bodies like WFA, and getting to the forefront of the industry bringing outside in perspective, I also get to get my hands dirty from leading agency management or transforming media operating model to leading data and tech discussions. And the next thing I know I would be driving global partnerships, budget setting approaches standardizing measurement developing mmm solution, as well as collaborating with our stakeholders internal or external, never a dull moment in Kraft Heinz.
Tom Ollerton 2:06
So, Nendra in this extensive experience you have what are the bad recommendations that you've heard over the years that you've tried and hasn't worked? How could you help the listeners on the show avoid some of those things that have been recommended to you?
Nendra van Wielink-Mohamed 2:20
That's a great question. You see, I've always been passionate about media marketing, tech and advertising in general. So after spending more than 20 years from the agency side, and I get to see things differently from an agency perspective, and then coming on to the client side, bringing and bridging agency knowledge into the brands I have heard and also being recommended bad recommendations in the profession that I've been in, right. And I mean, 20 plus years, it's a long time. But one of the few things that it's that got to the top of my head is automate everything, then set and forget because it's easy. Now, I think we know first off automation isn't an easy task, lots of work and time that goes behind it. And secondly, because that's you need human oversight. So what happens if you automate and you forget, and I think you can expect some disaster. The other bad recommendation I could think of is actually be honest, no filter. And let's just keep it at that maybe. The third one and, and this is more on a personal level. When I had an offer to actually transfer from our Singapore office on the agency site to Bangkok, during my early career, I actually received a very, very few strong recommendations. And to be fair by well meaning leaders and friends to actually stay in Singapore, and not be a quitter. And in Singapore, we have at that time, we'd be here if you leave, you're a quitter. And I was also reminded that it was it will not be wise to leave and work elsewhere, especially with transfers from Singapore to Thailand, because it will mean Korea suicide. I guess it's because there's a strong belief that Singapore has everything I'd ever need. Plus, you know, with a pay cut, think about it's really not worth the risk. And what's more, it was crazy to think that why would anyone want to leave Singapore, right? Everybody wants to get in, not out? I mean, are you crazy? Being a bit of a rebel, the rebel with really itchy feet, I figured I have got nothing to lose. In fact, if I don't like it, I can always go back home. It was never about money for me to be able to move or get transferred out. It was more for the experience and 20 plus years later, it was still still a decision. I have not regretted.
Tom Ollerton 4:46
Thanks for sharing three. That's brilliant. So let's just kind of dwell on those a little bit. So don't automate everything set and forget and I loved the way that you said that. There's a lot of work that goes behind automation, right, if you don't set it up the right way, it's just that's gonna follow the command and deliver the wrong thing. Right. So what is ideal like, because I always argue with our with people that I speak to is that people confuse automation with the optimal thing. Automation is just it happens. So the optimal thing is humans plus machines. So I'm curious to know, was there a lesson? Or was there a campaign? What happened to make you realize that you shouldn't automate everything? Can you talk to a specific experience?
Nendra van Wielink-Mohamed 5:28
Yeah, I think there was a story, if I remember from a previous life ago, we had a platform where we had to run to clients campaign. And because of automation, because of how easy it was to set things up on a platform, and fortunately, we had the campaigns running continuously. And over time, the campaign was not turned off even after the campaign was done. And when that happened, and we finally realized it, it was way over budget. And that was a case of when automation wasn't done right, when there wasn't any oversight. And when you think that it's easy, set it up and forget it, but it shouldn't be that way. And that was a huge lesson. For anyone involved.
Tom Ollerton 6:18
I always find it's the expensive mistakes are the ones that you learned from best. And when you said bad recommendations, but be honest and no filter, like what did you mean by that?
Nendra van Wielink-Mohamed 6:27
To be honest, and have no filter? I think over the years, it has given me some lessons in life. I generally like to speak up my mind say what I think over time, I realized that what you say or what you tend to think and then say it out might not serve you as well, that not everyone would appreciate honesty. So in that sense, exercise some discretion, because it might just impact other people. And language is also a barrier when it comes to honesty, what is being said, in a somebody's native language may not translate well to another person's native language, as well. And in the Dutch culture, interestingly, everyone, it's very direct. So you can expect that to happen. And in no way I appreciate that, because sometimes it's easier to just speak your mind, however, do exercise discretion.
Tom Ollerton 7:32
So those are some of the bad recommendations that you've heard in your career, but I'm looking for a bit of positive advice, what's a top tip that you would want to share when it comes to data driven marketing?
Nendra van Wielink-Mohamed 7:45
Top tip for data driven marketing. I think broadly, my perspective will be to constantly refine skills, not just what data has to be collected, rather, understanding what data means, what is being measured. And I think most importantly, why it's being measured. The other thing, it's really try to immerse yourself into data analysis. And for me, that's what I do to get better with understanding data. I love looking at raw data only when it's clean, and putting the numbers together. And I, I like data, and I love data I love. I toggle between zooming in and then zooming out to get a good perspective. And being able to connect the data together. Because that's quite a feat to get to if your data, it's just not connected if you have dirty data, for instance. And really having playing around with it understand what it means. And once the data are organized, that's when it gets easier to translate into insights or stories and get actionable strategies that can help optimize business and marketing efforts. And to me, and one of the things that I've learned over the years, it's the true driver should always be business value. That means the data is not... data is just information, in itself it doesn't mean anything right. It gets to get organized, it gets to get cleaned up, it gets to get connected. And once you know what the true value is in terms of business value, by that I mean it's either cost savings, revenue, productivity, or however you defined it, that ideally should get to the least amount of complexity or effort with the highest business value. And that also gets me to the tools that you use. Sometimes the more tools that you use, the more complexities introduced and the more complicated your data and your tech stack would become. So the last step would be always connect the dots between data and insights, actually get a lot of joy diving into nicely formatted, clean raw data to do analysis and create a story. And yeah, that's pretty much my few top tips.
Tom Ollerton 10:06
This episode of the shiny new object podcast is brought to you in partnership with Madfest. Whether it's live in London or streamed online to the global marketing community, you can always expect the distinctive and daring blend of fast paced content startup innovation pitches and unconventional entertainment from Madfest events, you'll find me causing trouble on stage recording live versions of this podcast and sharing a beer with the nicest and most influential people in marketing, check it out at www.madfestlondon.com.
So we're now going to come on to your shiny new object, which is a weird one, right, which is, don't chase the shiny new object. So your shiny new object isn't a shiny new object. It's the avoidance of shiny new objects, which is a bit complicated. But tell me what you mean by that?
Nendra van Wielink-Mohamed 10:56
Well, I wouldn't say avoidance avoidance per se, I love shiny new objects. And again, this is a contrarian thinking, right? It's more about doing more with less. I'm essentially a big advocate for pushing towards connected data. And that means business marketing, media, retail, ecom, creative audiences, whatever it is, and even better, coming from a media background, if we could put what is planned, what is what what is measured together. And I can if, if I could ever have all those things in one place? That's fantastic. It's a big ask, right? So here's the just a thought where I think it gets a little bit controversial. And I've said like, a little bit contrary to me actually liking or even, you know, diving into new, shiny object. So it's, when it comes to this, I think, how about let's start with what tools and data we already have first, especially when we talk about connected data and tech, right? So it helps us to just let's pass with the chasing, because there are two things here. One is, value comes from taking the data generated by the tools, and then putting them together in a way that makes sense and complement each other. So that's the first thing. And then the second thing is rather than choosing a new shiny thing, how about let's make what we have the better, not necessarily new, shiny thing, right? Because we live in a world filled with loads of data. And in the rave of fancy state of art, automated dashboards, and everything. It's about what dashboard spits out, right? But no matter how great it looks, or how intuitive that dashboard or certain technology is, it will not be reliable if the data behind it is just rubbish or not cleaned or not connected or just doesn't make sense, right? I cannot imagine a state of art tech sack that will help if the data itself isn't in order. So this is where I'd like to take a step back. I mean, I love data and all but from a broader perspective, a few things need to happen. First of all, we get into data, we need to be able to get an alignment of definitions and measurements in an organization. What actually is important, I mean to a media person, it could just be it could be reach and CPMs to a procurement it may be savings or to a marketeer, it could be brand awareness, brand health. And it's different when you looked at it from a pilot finance perspective. So without understanding the hierarchy or the altitudes of measurement, I think it will be a challenge to present it in a meaningful way and also act on the data in a meaningful way. Because how it is measured is essentially not the same. And knowing that the platforms measure things differently, and people will have a different understanding of what it means it does get challenging, and thereby going back to where we were, do we need a lot of new shiny things? Probably not. Because if the house isn't in order, no matter no matter how many new shiny things you have, it's not going to help. How do you use
Tom Ollerton 14:06
data to tell a story that everyone can buy into?
Nendra van Wielink-Mohamed 14:10
So I think first of all, this goes back to connected data, right? How, how are you able to just connect the datasets together, having a lot of data, it's great. There's this mantra where you can collect everything, and you need to collect everything. But I think before we even get to getting a story, just remember that the data is being meaningless if you can't make sense of it, because not all data collected can be useful. And not all useful data is collected or can be collected. So to be able to tell the story you need to be able to zoom in and zoom out and understand what those data is in the first place. Right. So there it's a example that I used to work with, with a brand I shall not name. That's a brand that seems to be from the onset just seems to be injecting a lot a lot of investment, but it wasn't showing any impact. And media unfortunately has been called out as being inefficient, or just spending way too much money, right. The reality was the spend was very much inferior to other competitors, the brand has not been spending a lot. But from a financial point of view, there was a lot of investment with it. So what happened was media inefficient, right. And year on year, this request for incremental funding, and media was seen as a cost and needs justification for that. Because then you need to have a proof that media increasing media dollars will improve sales is that the truth, and if the data is not connected, it would just be easy to just say, hey, media doesn't work, we're not going to give you any money, right? However, once we are able to stitch the data together and have it model together with distribution together with promotion, together with three together with revenue, all of that macro data that we have, we will actually able to see, based on all the data sources we have that the real problem was actually from distribution. And the fact that overall, because the brand has not been spending, there was a weak brand health to it, that we're offsetting the impact of media. Now, without all those macro data, we would not have been able to get a true picture what that story is, and we will not be able to make an action plan out of it.
Tom Ollerton 16:45
So what I'd like to understand better is how you get to connected data by asking the right questions. So the example you gave there was that media was perceived to be ineffective if you purely look at the media data, right, but what you're saying, if you look at it from a distribution perspective, and brand health measurements, there's like the... between the three of them, there's a problem that needs to be solved. So do a brand health job and a distribution job, then the media starts becoming more effective. So I get that, but what I want to do is understand how you knew where to look. So you've got one data point in the middle, which in this case was media, but there's all of these other data points around it, right? There's whether there's what the competition they're doing, there's a time of year, like what's going on in culture, but you looked at distribution and brand health. So if someone's listening to this podcast thinking, How do I connect my data? Do you have a process? Or is it was it quite freeform? Do you just think, Oh, I'm gonna go out and find lots of data sources and go through them all and see if there's correlation and causation? Or is there a fixed set of data that you should be looking at in order to connect your data?
Nendra van Wielink-Mohamed 17:52
There would always be fundamentally a fixed set of of data that you would be looking at. But this is where we get all the smart people to help us and I'm a big fan of MMM, so market mix modeling, and that it's where being able to get the right model, and the right approach to it to model the data, knowing the business and having the right business stakeholders to, to implement. And MMM, it's critical, because once you stitch the data together at the back end, and using regression model to to be able to surface those, that would be that would be helpful to help you pinpoint what exactly, it's causing your business impact.
Tom Ollerton 18:41
So get the model right at the back end as soon as possible so that every time you look at the data, you've got all of the different data's pulling from all the different places with the right regression modeling to help you point out what the issue is. Don't look at data in isolation, it needs to be compared to other data's that matter in the business. Brilliant.
Nendra van Wielink-Mohamed 18:59
You just triggered something right in what you said and exactly that. And the fact that I think, and this is where having a rigorous data collection and governance, it's key, it needs to be tracked, it needs to be monitored, and you need to be able to collect those data. And like I said, right, having lots of data, it's great, not all data collected can be useful, and not all useful data is collected or can be collected. So there is a case to be made. For all the data that cannot be collected, what is the best way to collect it and how can you collect it consistently. Because only when you have consistent data, you would be able to model something that's accurate.
Tom Ollerton 19:43
So really believing in your point of don't start going with a shiny new object, get your data connected, get your house in order, get your regression models in place, be in a position where you can analyze everything that you're doing in a way that the rest of the business understand. So when does The shiny new object come in, when do you open the door to the possibility of new tools and technologies and processes?
Nendra van Wielink-Mohamed 20:06
That's a very good question. By that, I think we should always keep abreast of what's happening in the technology space, right? Because there will always be new technology that helps us. But you start looking at that, when you believe that it would complement your current process to be able to help you build whatever you need to do. See, having data is a strategic strategic asset, right? More so if they're connected, or put together in such a way that they are connected. Now, in terms of the backend technical stuff, it's not something we'd be able to provide.
Tom Ollerton 20:46
Well, Nendra, unfortunately, we are coming to the end of the podcast now. Final question. If someone wants to get in touch with you about any of the things that we've talked about today, where's the best place to get in touch with you, and what makes a message that you will actually respond to?
Nendra van Wielink-Mohamed 21:01
The best way to get me is just through LinkedIn, and just send me a message. And I'll do that.
Tom Ollerton 21:05
Thank you so much for your time.
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