Episode 177 / Narsingh Dixit / Unilever / Digital Growth Marketing Manager

Podcast: How to Build Truly Personalised Marketing Strategies

Narsingh Dixit is the Digital Growth Marketing Manager at Unilever, while also teaching digital marketing at BrainStation. He has pursued a wide variety of roles in different industries, always with the same common focus on marketing, which has taken him through big tech, healthcare, real estate, and now at Unilever. In his view, although we have been talking about personalisation for a long time, we are still far away from unlocking its true 1-1 potential – this is why personalisation is Narsingh’s Shiny New Object.

 

Looking back at an extremely varied career where he’s routinely pushed himself out of his comfort zone in order to learn and grow, Narsingh Dixit believes that his experience has helped him understand what running a business entails. It has given him a holistic sense of understanding different consumer needs and problems and different business challenges.

As a proponent of the growth mindset, Narsingh believes in adaptability before anything else. We know that human beings don’t like change by default, and yet it’s change that helps us develop and thrive. For Narsingh, the challenge eventually begins to wear off once he’s changed industries, so this is what drives him to continue moving on to newer projects.

Regardless of the industry, however, Narsingh thinks that personalisation should be a key part of digital marketing strategies going forward. Although brands have developed more and more targeted communications, the tension between a want for privacy (as illustrated by GDPR type laws throughout the world) and an interest in a customised customer journey means that personalisation has a long way to go before reaching its full potential.

In Narsingh’s view, true personalisation begins with gathering first party data and continues with the dissipation of the linear customer journey we’re so used to. The latter means that marketers need to build the ability to understand and react to consumers’ needs, rather than providing them with a one-size-fits-all end-to-end journey. In this alternative, context is more important than the journey. Finally, the last building block is leveraging AI correctly and in a proprietary fashion, to truly unlock personalisation at scale.

Listen to Narsingh’s top marketing tips, his take on the growth mindset, and more on how he sees personalisation developing in the future of marketing, on the latest podcast episode here.

Transcript

The following gives you a good idea of what was said, but it’s not 100% accurate.

Tom Ollerton 0:07

Hello, and welcome to the Shiny New Object podcast. My name is Tom Ollerton. I'm the founder of Automated Creative. And this is a weekly podcast where I get to speak to cool smart marketing people from around the industry from around the world about their vision, what they think is going to happen next and where we think the industry is going. I'm on a call with Narsingh Dixit who is digital growth marketing manager at Unilever. So, Narsingh, for anyone who doesn't know who you are and what you do, can you give them a bit of a background?

Narsingh Dixit 0:38

Absolutely. First of all, thanks, again, for having me on this podcast. I'm a big fan of it myself. And I think you've done a wonderful job of curating a really cool selection of guests. So hopefully, I can leave something meaningful behind for your audience today. In terms of what I'm currently doing, so, you know, digital growth at Unilever. I've also recently started teaching at BrainStation where I teach digital marketing to, you know, young professionals that are also experienced professionals that are looking to learn a little bit more about the space. And I think I've been really lucky in my career, so far to kind of have the opportunity to work across multiple industries spanning big tech, healthcare, real estate, along with a stint in the agency world. And while my roles have primarily been within marketing, I've kind of gone out of my way to learn a bit more about sales, IT, product and operations as well. So a lot of different, you know, verticals, and a lot of different work sizes really allowed me to get a more holistic sense of, you know, running a business, understanding different needs, states and problems, and thriving, regardless of the situation.

Tom Ollerton 1:50

So, you mentioned some odd thing I think, real estate, you mentioned that?

Narsingh Dixit 1:54

Yes.

Tom Ollerton 1:54

Definitely our first guest who's mentioned real estate in 200 episodes, so it's kind of interesting to know a bit more about that, but that was sales, IT, products and ops and agency experience as well. I mean, that's pretty broad. So I'm kind of curious to know, what new belief or behavior have you taken on in the last five years that's really helped you with your work life?

Narsingh Dixit 2:15

Yeah, I think, yeah, that's a good question. You know, for me, what I realized through this process was this idea of, you know, forcing myself to be in an uncomfortable position. And the more I kind of learned about it, you know, having a little bit of a psychology background, through my, through my university time, I did a little bit of research and discovered the idea of growth mindset, which has become popularized over the last, you know, five to seven years now. And I guess, maybe I want to backtrack a little bit and talk about what, you know, a growth mindset isn't. And, you know, there's a misconception that, you know, people are born with it, and, you know, it's just something they've always had. And that's really not the case, you know, everyone has the capability to work with a growth or a fixed mindset. And the second thing is, you know, the growth mindset is usually thought about as rewarding and praising effort, I think there's also sort of a territory you can enter there, where it starts to become limiting in and of itself, where you start to believe, for example, you know, if you tend to reward people for being intelligent, they might seem to think that they're intelligent, and that by itself becomes a fixed mindset. So I think, you know, to me kind of experiencing different areas, different business types was all kind of related to my goal of seeing if I can put myself in positions and still be able to thrive and yield results. And so real estate, as you pointed out, was a little bit of left field industry to get into, but I think the beauty of it was because the real estate industry is relatively traditional. It allowed me to introduce, you know, digital marketing concepts, and really mature and at least the company that I was a part of really mature that digital function, you know, from something that was really paid media oriented, right, to becoming a full fledged overall holistic strategy.

Tom Ollerton 4:19

So, the growth mindset is popular, but what I found myself thinking when trying to understand is like, I would never say that to someone socially, like if I've met someone at a party, or in the pub, what kind of growth mindset kind of person suddenly said that to me, I'd be like, I've heard those words, and I kind of understand what it is. But what's the kind of plain English like no BS version of that mindset?

Narsingh Dixit 4:47

Yeah, you know, I would say it's maybe to kind of shape this another way, you know, there's a quote by Darwin, that goes something along the lines of, you know, it's not the most intelligent or strongest that survive, but it's those that are most adaptable to change. And, you know, it's kind of interesting because by default, human beings don't like change, you know, we kind of like to be in a virtual, you know, routine sort of an environment. But, you know, to me, I think I thrive off of learning, off of being in discomfort. And that's been part of the reason why I've kind of been in different industries is because you know, that challenge eventually starts to wane off, depending on the projects that we're working on. And, you know, in simple English, I think what I would say the growth mindset is all about is just embracing change.

Tom Ollerton 5:49

That's a really nice way of putting it. So my next sort of provocation on growth mindset is that, I love that idea of challenging, constantly being uncomfortable, not looking for the path of least resistance, moving into new roles, new verticals, whatever it was, and all these things you've done, which is really impressive. But at some point, the description of an expert, which I really love, which is something along the lines of an expert, is someone who's made all the possible mistakes there are to make in any given field. It's not really a growth mindset, it's just repetition. It's repetition, with slight, slight changes, it's repetition with like, an ever so slightly different angle on and you just do it so many times, and it by the end of it, you just you're really good at it. And so, but that's kind of the opposite of the growth mindset, the growth mindset is well change jobs move country, like, you know, get any partner, like learn anything. So, so do you start off with a growth mindset? And then when you find your love, do you go deeper into it?Help me understand the tension between having a growth mindset and being open to change? And actually the fact that if you want to be amazing at something, you've got to repeat it over and over again.

Narsingh Dixit 7:05

Yeah, that it's a really, really good question. Because it is about, you know, finding that balance between that frictional process and so to kind of kind of paint the picture a little bit, you know, although I've had experiences in a lot of different verticals, my foundation has primarily been within the marketing world. So what that's allowed me to do is, whether it's b2b, whether it's b2c, I've been improving the ability to be able to market and you know, just be be a good marketer, you know, fundamentally, and, you know, as you know, you know, b2b, b2c are different types of marketing, obviously, the fundamentals are the same, but the tactics that you use, the strategy that you use, the way you think, the questions you ask, are very different. So it kind of forces you to start to understand and ask better questions along along the way. And, you know, there's this interesting thought around specialization that I stumbled upon, I think it was earlier this year, that, you know, specialization is for insects, right, as a human being, you know, you have the gift of being able to really do whatever you want. And to live a rich, fulfilling life, you want to be able to expand your wings and really see what's out there and, you know, experience life for what it is. So, while specialization is great, I think it's about, you know, realizing that, you know, you don't have to specialize in one industry, you know, in one domain, you can start to build on top of that, right. So, being a generalist is actually very powerful. So if you look at, let's say, CEOs today, they usually tend to have, you know, background in multiple different domains before they kind of take that generalist role to be able to run an entire organization, right, you're not going to find, you know, just, uh, hyperfocused specialists to be able to, you know, run a company, you know, that has to solve a lot of different problems. So, so that's sort of how I find the balance between the two, where you kind of, you can still specialize within the broad sense of, you know, marketing, but you can still do it, you know, across multiple different areas.

Tom Ollerton 9:17

That is a very good answer to the question, so we're gonna move on now. I want to know what your top marketing tip is. So marketing being your core, and all of this experience around it being your growth mindset, but what was the tip that you share most often with the people you work with?

Narsingh Dixit 9:32

Yeah, I think my favorite tip, and this is something that I learned a long time ago, was people don't know what they want. And it's something that, you know, I obviously say, with caution, especially as a data marketer, because, you know, definitely please listen to your customers. But, you know, I think this is where the art and science of marketing really, really shines. And I want to paint this picture by talking about spaghetti sauce. And this is something that, you know, I had read or heard a long time ago, but it's stuck with me. And it was the reinvention of spaghetti sauce. There's a researcher, I think his official title is like a psycho physicist who goes by the name, his name was Howard Moskowitz. And he had done some research, I think it was for Pepsi, where, when they were releasing Diet Pepsi, they come to him with the problem that, you know, we've figured out that, you know, we have aspartame, the range is between 8 to 12%. But we don't really know what the sweet spot is. So can you go out there and figure out what is the sweet spot that's going to sell with consumers. And when he did the research, most researchers would expect some sort of a normal distribution curve, where most people kind of, you know, congregated towards one sort of a data point. But what bothered him and what was unusual was that the data was all over the place. And, you know, this kind of plagued him for a couple of years, and he was trying to figure out what went wrong. And what he realized was, you know, they were asking the wrong question, you know, it was not what is the perfect Diet Pepsi? It's, you know, what are the perfect Diet Pepsis. And, to kind of illustrate that picture, he finally got a breakthrough opportunity with Campbell, to really prove that hypothesis, and this was when Campbell was struggling with their Prego brand spaghetti sauce, which was, I think, objectively better, you know, even in those blind tests that they used to do back in the day, it was better than Ragu, but it was just not doing really well in the marketplace. And so, what Howard ended up doing was, I think he tested like 45 different versions of spaghetti sauce. So 1000s, and 1000s of customers came in and tasted. And when he looked at the data, he was able to find three large clusters. The first cluster was people who like plain spaghetti sauce, the second cluster was people that like spicy spaghetti sauce, but the third cluster, which was really the breakthrough was extra chunky, and this was unheard of, right? You know, all the research that had been done in spaghetti sauce, extra chunky was not really an option, though, that was even relevant. But, you know, lo and behold, you know, Prego went to market with extra chunky, they made, I think, $600 million in the next 10 years off of that product line.

And you know, the key takeaway from that was, it's not, you know, if you asked the consumer what they wanted, they wouldn't really tell you that they wanted extra chunky. So it's kind of you as a marketer need to do your due diligence to look at the data, understand the data, and also be able to derive the insights of relevance and then provide a solution that you believe is going to address that particular problem. And as a bonus takeaway for your listeners, this was also the introduction of the concept of horizontal segmentation, within product category. So this is why we today have you know, multiple different olive oils and multiple different vinegar options and multiple different, you know, ketchup variations, etc. This all kind of stemmed from this one little research project that changed the way researchers thought.

Tom Ollerton 13:18

You make it sound all so simple, but another time, we'll get into the weeds of why that doesn't happen. But we are going to talk about your shiny new object, which is personalization. So some might argue that that's very shiny and new for some brands, but an entirely old school for some others. So why is personalization, your shiny new object? Why do you think it represents the future of this industry?

Narsingh Dixit 13:48

Yeah, you know, I think what's really interesting about personalization, as I think a few years ago, I think McKenzie had come out with an article about why digital personalization at scale is the holy grail of marketing, which I still still do believe it is truly the Holy Grail. And it's interesting to see the evolution, right, because it's not that personalization is a new concept. But, you know, marketers got pretty sloppy over time. And, you know, a direct consequence of that was consumers started to feel uncomfortable. And, you know, it resulted and rightfully so, in the introduction of privacy laws, and you know, GDPR, and in Canada, we have Castle, which are two of the strictest laws that exist in terms of data acquisition, governance, etc. And I think, although we've done a good job to get to the point where we can personalize, you know, communications better advertising better, we're so far away from unlocking that true, you know, you know, one to one personalization, that would drive impact at scale. Right. I think the scale part is pretty important there and, you know, just a personal example, you know, the pair of headphones that I'm wearing right now I shopped for this two months ago, I'm still getting ads about, and it's like, I'm long gone, I'm not buying another pair of headphones, you know, anytime soon. So, you know, things are still not there in terms of being able to, you know, manage that experience better. And if you think about personalization, I mean, the benefits are massive, right, you can reduce your acquisition cost by 50%. You know, uplift your revenue, increase the efficiency of marketing spend, you know, by up to 30%. So, you know, I guess, for me, the way I think about it is that there are three building blocks to, you know, driving personalization better, and really get to that last frontier of personalization. And it all kind of starts with first party data. And I know this is not easily accessible, especially if you're a smaller business to be able to control the data to that extent. But, you know, it truly is something that unlocks the end to end personalization that you would need, you know, to give you a couple of examples, 35% of Amazon sales come from their recommended product section, right, like similar products, recommended products, etc. And let's think of Starbucks for a second, you know, their rewards and loyalty program drives 50% of their revenue. That's massive, right. But the key insight here is that they have access to the data, they own that data. And so therefore, they can enrich learn and be able to control the narrative very, very cleanly. And that kind of leads me to the second building block, which is also kind of interesting, is, I think, we're starting to see the dissipation of the linear consumer journey. You know, obviously, this has been brewing up for the last few years. But context is more relevant than a linear consumer journey. So it's almost as if, as a marketer, you need to start building and constructing a lot of roads, and all of these roads, lead to Rome. And having the ability to listen to customer signals and respond to them immediately. Right. So that agility is super important. But it all revolves around context. So it's not really having the perfect customer journey, but it's being ready to respond to what your customer needs, when they need it, which leads me to the last building block, which is top down segmentation. And going back to the spaghetti sauce story, it's kind of starting broad, building into clusters. And then finally, and you know, this is I guess what Automated Creative does does really well as well is, is leveraging AI and machine learning to try the personalization, right? Human beings are just not possible to be able to, you know, personalize content to a million different people. So it's really trying to understand how you can leverage the much better AI that we have today. And ideally, do it, you know, in a proprietary fashion that's strictly for your company. So whether that's Unilever, or any other company, for that matter, if you can leverage AI for your company, based on the data that you have, and you own, maybe you'll be able to truly unlock that, you know, epitome of personalization.

Tom Ollerton 18:12

So I'm going to say something you said earlier, and play it back to you. So, personalization works, when you show someone an ad, be that through Starbucks, like their loyalty program, or Amazon, people bought who, you should buy this because you someone else bought this or sorry, the other way around. But you also said earlier that people don't know what they want. So there's a bit of a, there is a tension in what you're saying here that then the brand should personalize and give people what they want. But you also said earlier, people don't know what they want. So how can a brand possibly guess, how can a brand make a decision tree? How can a brand create a structure, AI driven or other, that promotes certain things when people don't know what they want anyway?

Narsingh Dixit 19:08

Right. Yeah, that's a good question. I'll kind of answer this using the Amazon example. I'm trying to think of something that's probably relevant to Okay. So for example, let's say you're doing a home office setup. Right? And, you know, you've got everything kind of set up and, you know, someone comes to me and they're like, Yeah, you know, what else do you think would improve your home office experience? I don't know. People don't know what they want. I'm not sure Amazon has access to data that all the people that have been setting up their home offices, for some reason have recently been investing in a ring light, right to improve their, you know, Office experience. And that's, that's the data point that they have which they can start to test, you know, with multiple consumers based on the relationship that they have there, where okay, so let's, let's try and you know, promote the ring light. And if they do see that trend, that sort of that personalization, kind of marrying up to, you know, not knowing what you wanted, by uncovering something that might be of interest looking at the data, you know, at an individual and cluster level, right. So hopefully that kind of answers that, you know, that the tension between me not knowing what I wanted, but, you know, because Amazon had access to millions and millions of data points, they were able to recommend something of relevance.

Tom Ollerton 20:36

I find myself thinking about this a lot. It's kind of slightly embarrassing, but there's also a ton of data that Amazon doesn't have, like, you know, there's loads of things in life, there isn't any data for, right. But yeah, we, you know, we obsess about the things that there are like so. So say, for example, someone wants to improve their home office, the thing that might have the best impact on the home office might be half an hour's more sleep, for example, I've just been completely tangential, but Amazon has no idea. Maybe Alexa kind of pumps back snore sounds? I don't know. But they're certainly not, as far as I know, leveraging that data. So you don't always have this thing I talk about a lot is that, you know, Facebook has, sorry, brands have data on which ads work, but they don't have any data on what ads they were seen alongside. So people assume that the creative is the thing that drove the outcome that they were interested in. Whereas actually, it's the context within which that creative was seen. So an example would be if you've, if you just watch a Netflix documentary about veganism, you're going to feel differently about a McDonald's advert. So if you've been in a bar and had six beers, no lunch, do you know what I mean? Like, it's, there isn't any data for the thing that that you can't see. And so that's the thing with personalization for me that like, I almost don't think it's personalization, its recommendation, right? You know, based on that, based on a huge data set that is still limited, we can recommend that you should try these things, but I don't really feel that that's personalized. Personalized is someone you know, me walking into a shop, saying, Hey, Tom, how's it going? Would you like your usual? How, you know, how's your dog? How's your wife? You know, that kind of thing? So, yeah, I think that the advertising gives these technologies and these techniques, words, that like, oversell what they actually do.

Narsingh Dixit 22:30

Absolutely, absolutely. And you know, to that point, that's why I think it's the perfect definition. I think personalization is the holy grail, will we ever reach it? I'm not sure.

Tom Ollerton 22:42

So, so who do you think does personalization well, like, who do you experience personalization from? And you're like, ah, that yeah, that is amazing.

Narsingh Dixit 22:52

Yeah, you know, I do want to say, like, again, just going back to Amazon, I think they do a great job. And you, when you talked about sleep, it just started to make me think about, you know, when you start to expand, like a Google or an Amazon, right, obviously, this is something only bigger companies can achieve. But when you start to expand your portfolio to multiple verticals, it actually does give you access to some really interesting information, right? So let's say Amazon, from a shopping perspective, might not be able to derive a lot of insights. But they also have Amazon Prime video, or they have Prime music. And think about what you can do with that, right? Like imagine you're able to now see, oh, well, Tom actually is not asleep at midnight, because he's watching the new show that was released, right? So you can actually start to get into these deeper levels of analysis if you have access to verticals around a single person, but you know, through multiple different offerings that you have. So yeah, I don't know, I just kind of went off into a tangent there. But it was interesting just made me think about just the access that you have, you know, with different technologies these days.

Tom Ollerton 24:02

So, you've obviously put your hand up and said, you're talking about big businesses with a lot of data. So what do you do if you're a marketer, and you don't work for Amazon, you don't work for Google, you can't leverage this kind of huge amount of insight. And you're, you're a CPG brand who isn't a Unilever, like how would you approach personalization when you don't have a ton of first party data?

Narsingh Dixit 24:27

Yeah, I think in that case, it's kind of important to still focus on research and be able to still make use of the data that you have access to, right, something as simple and free as Google Analytics can tell you quite a lot about your consumers, what they're appreciating about your app or your website journey, and still be able to kind of personalize at that level where you can again, start to form data clusters, you can start to see your website path. How do customers convert, right, and at least optimize at that second block that I, that I touched upon. So, you know, block one is a lot of data and no organization, block two is clustered organization, which is achievable for anyone. And like I said, block three, which is the ultimate layer is AI driven anyway. So it's kind of irrelevant what size of business you are, because that's the area that everyone's trying to figure out. So I would say, at the very minimum, at least, you can get to the cluster level and optimize experiences for those clusters. And just to kind of paint the picture a little bit better here. You know, if you asked a group of people, let's say, an audience of three, or 400 people to come up with the coffee that they would like, you know, to drink, they would probably arrive at something like they themselves would score it at, like 60-62 out of 100. Right. But if you were able to create clusters out of that same group, that satisfaction level actually jumps to like a 70-75 out of 100. Right, but it's a very basic level of segmentation. But you have improved, you know, that coffee quite dramatically, sorry, the satisfaction quite, quite dramatically from the consumer side. So that's what I would recommend is, you know, even if you can't get to the one to one personalization, you can still get to a segmentation level, you know, personalization.

Tom Ollerton 26:21

So what does the future hold for personalization, I remember, 10 years ago, every presentation at a conference would have Tom Cruise in Minority Report in that scene where he walks through a mall, shopping center, as we call them here. And there's a poster thing. It's even a Guinness poster, and it says, hey, look, I remember his name, but he says, Hey, Tom Cruise, that's your nice cold Guinness. And like, you know, just think about the Castle or the GDPR level of compliance, you'd have to go through to make the ad work, you know, they would have to, you'd have to like sign into the shopping center and agree that their OS can track your identity. And then you'd have to sign up on the Guinness site. Like, that kind of personalization probably won't happen, certainly not in an advertising context. So where do you think it's gonna go?

Narsingh Dixit 27:11

I think we're, if you think of an equilibrium, right, you know, it always swings, you know, one way and the other. I mean, this analogy works for anything from politics to what have you. And I think, marketers, and you know, companies in general, have a lot of free rein, we're kind of seeing the pendulum swing the other way now, but it's, you know, more legislation, more law, more restrictions, more autonomy. But the thing is, consumers are actually very receptive to personalization when it's done right. You know, it's just, they don't appreciate when it goes wrong. And ultimately, I think there's going to be, you know, more desirability to, you know, want that personalized information. Because really, we've spoiled consumers, right? We've given them the instant gratification of having more optimized content, having more optimized creative, having more optimized advertising, you know, being tailored to them. And I wonder, right, this is just more of a speculation here, I wonder if that's going to see that shift back where, you know, they do start to appreciate and start to, you know, want those moments of personalization and tailoring. But I do feel that the future is going to be one to one communication. And we're kind of seeing this with the emergence of web3 with the decentralization of businesses and relationships in general, where, you know, you know, if adidas has an NFT tomorrow, you know, I have to purchase that NFT directly from Adidas and build that one to one relationship with the business. So that one to one, again, going back to ownership of data, I think that's going to become a key theme again, where you know, you're going to own the data, you're going to own the relationship, you're going to have as much information as you can derive from that relationship to be able to provide a better service or solution to that consumer.

Tom Ollerton 29:11

Well, unfortunately, we've come to the end of the podcast now. So if someone wanted to talk to you about personalization, your experience and your views, how would you like them to do that?

Narsingh Dixit 29:21

Yeah, I think, you know, LinkedIn is probably the easiest way to connect with me, you know, very open, just kind of a brief introduction, and you know, more than happy to connect and chat with people there.

Tom Ollerton 29:35

And what makes a great outreach message to you?

Narsingh Dixit 29:39

Honestly, I would just say, you know, an intro, you know, what you're looking for and how you feel that that information will be beneficial, you know, having you know, I do like to be generous with everything that I've learned and you know, all the experiences that I've had, so even if you're looking simply to learn and have a quick coffee chat, I'm also hoping to share you know what I can and hopefully inspire the next you know era of marketers.

Tom Ollerton 30:06

Narsingh, that is a lovely offer. Thank you so much for your time.

Narsingh Dixit 30:10

Thanks a lot Tom.

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