Introduction:
The intersection of digital marketing and the unique challenges of marketing baby formula presents both opportunities and complexities. With over 15 years of experience at Reckitt, I’ve navigated these challenges head-on, focusing on retail media and e-commerce.
Journey to Digital Marketing Excellence:
My journey began as a graduate selling to retail pharmacies in Australia. From there, I transitioned into operations, account management, and trade and shopper marketing. About ten years ago, I pivoted to e-commerce and digital marketing, launching Reckitt’s first direct-to-consumer business model.
E-Commerce Evolution and Learning Curve:
E-commerce within the CPG (Consumer Packaged Goods) industry has grown exponentially. My career took a global turn as I focused on direct-to-consumer e-commerce, necessitating continuous learning and adaptation. I honed my skills with platforms like Google, Facebook, and Shopify, ensuring I stayed ahead in the rapidly evolving digital landscape.
Data Clean Rooms and Their Impact:
Data clean rooms have revolutionized our understanding of consumer behavior and media attribution. These secure environments allow for the compliant matching of first-party data with retail media data, enabling highly targeted marketing strategies. My experience with data clean rooms has been particularly impactful in the complex baby formula market.
Case Study: Baby Formula Marketing on Amazon:
In a case study using Amazon Marketing Cloud and data clean rooms, we optimized our marketing strategy for baby formula. By focusing on targeting, budget optimization, and setting media, we achieved significant improvements in purchase per dollar spent, purchase rate, and ROAS (Return on Ad Spend).
Key Takeaways and Future Trends:
From my experiences, the key takeaways include the importance of delivering the right creative to the right audience at the right time, and the role of AI and automation in scaling marketing efforts. Marketers need to be data-fluent and understand the interconnectedness of marketing, sales, and supply chain data.
Conclusion:
Continuous learning and innovation are crucial in digital marketing. I encourage you to connect with me on LinkedIn, subscribe to my podcast, and explore the evolving world of digital marketing and data science.
Hosted by: Imteaz Ahamed
Video Transcript
Speaker: 00:00:00:00 – 00:00:22:05
This is Imteaz. Say hi.
Imteaz: Hi.
Speaker: He is awesome. We met at this conference over here on what was it because you were packaged goods, right?
Imteaz: Yeah.
Speaker: And we just happen to be both looking for lunch and we start talking. And he’s an expert in data and digital and AI and he says we need somebody to speak. And I said, Hell yes.
Imteaz: 00:00:22:05 – 00:00:46:10
So he works for a company called Reckitt, which makes everything from Lysol to baby formula. Yeah, that’s pretty cool. So he’s going to give you a whole thing on what he’s doing and all the stuff he’s talking about. So ask questions, but let’s give another round of applause. Good morning, everyone. So in terms of what we’re going to go over today, I’ll give you the agenda first and then we’ll cover specifics.
Imteaz: 00:00:46:12 – 00:01:08:01
So who am I? How did I get here? What is retail media, which is what I really focus on right now for a job? What is a data clean room and how does that impact how we do marketing today at a global CPG? Thirdly, I’ll show you a case study in terms of how we’re using a data cleaner.
Imteaz: 00:01:08:03 – 00:01:37:04
And then I’ll give you some takeaways from that. So firstly, who is Reckitt? Reckitt is a multinational CPG. We have a whole heap of brands across multiple categories. So if you think about the business, there’s three parts to the business. One is infant nutrition, so baby formula, which is where I work. We also have a household cleaning business, so we make everything from finished dishwashing tablets to earwig to Lysol as well.
Imteaz: 00:01:37:06 – 00:02:01:21
And we also have a personal care and health care business as well. So everything from Mucinex, Dell, some airborne, etc.. Okay, So in me in particular, I’ve been with the company since I was 20 years old. I started it in Sydney, Australia, and have moved across the world with Reckitt.
Imteaz: 00:02:01:21 – 00:02:08:13
So in terms of my experience, I started on the field as a grad with Reckitt.
Imteaz: 00:02:08:15 – 00:02:29:22
Then I moved into sales operations, which means looking at the field teams that we have selling our products in to customers all across Australia. I then moved into account management, which means maintaining our business relationships with the likes of Woolworths and Coles back in Australia. And then this thing called and a bit of trade and shopper marketing in there as well.
Imteaz: 00:02:30:00 – 00:02:54:08
But then this thing called e-commerce pops up for about nine or ten years ago, which was relatively new to the CPG space. And I was kind of pushed into that role by my senior leadership in Australia, not because I knew anything about digital marketing or e-commerce, but because I was good at PowerPoint and Excel. So, you know, right place, right time and right opportunity.
Imteaz: 00:02:54:10 – 00:03:24:11
From there I was the first e-commerce manager in Australia and we launched new business models. So, you know, Reckitt is traditionally a B2B, so we sell to other retailers who then sell on to other customers or our consumers. I was then setting up new business models like direct to consumer e-commerce. So how do we cut out retailers and then shipped directly to consumers and then market directly to consumers using things like Facebook and Google?
Imteaz: 00:03:24:13 – 00:04:00:18
Then I got shipped to the UK where in a global role. So in global, we look at, you know, how how can we support multiple markets from cross market learnings and scale up things that are working and then scale things that aren’t working. So if, for example, China is very, very advanced when it comes to e-commerce, if you think about Alibaba and Teamviewer, etc., how do we take some of those learnings from China and then apply them into other markets as well from a global role?
Imteaz: 00:04:00:20 – 00:04:38:08
I transitioned into specializing in direct to consumer e-commerce, which is where I’ve been for about four years of my career thus far, both in looking after Europe from a regional role as well as moving to the US at the height of the pandemic in March of 2020, looking after baby formula in that time as well. So, you know, in this transition that I’ve had from going to school at the University of Sydney, studying commerce and marketing and then transitioning into a sales career and then transitioning into an e-commerce career through the DTC experience.
Imteaz: 00:04:38:08 – 00:04:59:14
I’ve also had to pick up a lot of technical stuff when it comes to understanding software and understanding how to use technology. And now I look after performance media, and what Performance Media is, is looking at media, but specifically within Amazon, Walmart, Target, and how do we actually directly market to consumers on those platforms and get them to purchase.
Imteaz: 00:04:59:16 – 00:05:26:08
So it’s not DTC anymore. It’s looking at total e-commerce marketing, but at the retailers in particular. So that’s my corporate experience on one half of a slide on the right hand side. Beyond corporate, I am I have a podcast called Applied Intelligence where I talk about generative AI and the applications of that within the CPG space.
Imteaz: 00:05:26:09 – 00:05:51:03
I also do some stuff with the Harvard Business Review in terms of contributing into generative AI content. I have some passions around startups as well. There’s a thing called startup buzz. You guys should Google that. Everyone should do the startup competition. I’m not going to go into a detailed today, but it’s basically a hackathon on a bus where you build a business in 72 hours, launch it, pitch it, and then get going from there.
Imteaz: 00:05:51:05 – 00:06:04:18
So even if you don’t do the business, the whole learning experience that you get from that process is super valuable to anyone doing growth marketing marketing today. Okay, cool. So
Imteaz: 00:06:04:18 – 00:06:19:18
If you think about the CPG category or the CPG industry vertical over the last, let’s call it 5 to 10 years, it’s gone through two massive shifts. The first one is in distribution.
Imteaz: 00:06:19:19 – 00:06:41:14
If you think, let’s say 20, 30, 40 years ago it was all about brick and mortar sales. If you’re talking about CPG goods, every category was being bought at a physical retail location over the last ten years. E-commerce has taken off, Amazon has taken off here in the US. Alibaba and the likes have taken off everywhere across the world.
Imteaz: 00:06:41:16 – 00:07:11:01
But now we’re coming to a place where from a marketing point of view, we’re thinking not just about the digital retail, where a lot of the growth has come from over the last few years. But we’re thinking about the holistic journey of consumer when it comes to where are they actually shopping from. Right. So when the pandemic kicked off, you know, people like Instacart or companies like Instacart, by the way, the two founders of Instacart bet on startup us as well.
Imteaz: 00:07:11:03 – 00:07:41:01
Fun fact, but we’re thinking about the holistic consumer journey. What are those digital media all marketing that are touching the consumers along that journey and where are they actually shopping it? Where are they actually making that purchase? So we don’t just care about, you know, did they purchase online or did they purchase in offline? What are those touchpoints in that consumer journey that we can actually expose media to and we actually can influence to make them buy our brand versus somebody else’s brand?
Imteaz: 00:07:41:03 – 00:08:09:07 The second piece here is that digital revolution when it comes to media. So, you know, 50 years ago, reach and frequency media across television, print, radio, you didn’t really know who you were marketing to or who those actual consumers were. You just knew the audience titles. So, you know, people who watch the news at 7 p.m. have a certain demographic profile.
Imteaz: 00:08:09:07 – 00:08:31:06
That’s what you were buying from a media point of view. Digital kind of changed that with the likes of Facebook and Google in terms of getting clearer signals, in terms of who people are. So someone who’s typing in baby formula on Google is obviously very interested in buying baby formula or interested in understanding what baby formula is about.
Imteaz: 00:08:31:11 – 00:08:56:18
We didn’t have those signals when we were doing analog media before and now this. This third wave is retail media, which is, you know, an interaction of both media and shopping in the one place. So Amazon is not just a shop. It’s not just a place where you buy stuff. It’s also a place where you’re being influenced to buy stuff as well through media.
Imteaz: 00:08:56:18 – 00:09:21:14
And Amazon owns lots of things like Prime video. There’s a football free V, etc. and is becoming a much bigger media organization and not just a retail destination as well. And similarly, I think, you know, if you think about retailers like Walmart, this is why they’re doing media partnerships with the like some of Paramount plus Roku, etc. as well.
Imteaz: 00:09:21:14 – 00:09:40:15
So retailers are evolving and digitizing their not just their store footprint, but also the media footprint and how they influence consumers. So delving deeper into what a what a retail media network is,
Imteaz: 00:09:40:15 – 00:10:13:19
If you think about the major retailers here in the US, all of these retailers have a wealth of first party data. They have transactional data on who is purchasing what at their physical stores as well as their digital stores and even more on digital, right When you’re signed into your Walmart app or your Amazon app, they know everything about who you are, where you live, what frequency you are buying certain products, what frequency you are seeing certain ads before you’ve actually made that purchase.
Imteaz: 00:10:13:19 – 00:10:42:02
So for us as a CPG, there are certain media tactics that we play across the retail media ecosystem, starting with Page Search. So when you’re typing in baby formula, for example, on Amazon or you’re typing in any product category that’s relevant to one of my brands, I’m trying to actively make sure that my product appears at the top of the page.
Imteaz: 00:10:42:02 – 00:10:50:20
So you click it. The higher up on the page that you are, the more likely you are to be clicked on, the more likely you are to win that search. Right.
Imteaz: 00:10:50:20 – 00:11:10:13
The second part of it is targeted display and video ads as well. Similarly, on Amazon, when you’re making that search or when you’re interested in a particular category and you haven’t converted, you’ll start to notice that those ads, those visual ads are following you around the Internet trying to get you to convert.
Imteaz: 00:11:10:15 – 00:11:34:17
So the retail media network has seen the signal that you have searched that you did not purchase within a certain timeframe. So companies that are actively advertising to you, trying to make you convert into that brand. And then thirdly, what is this actually doing for us as a CPG is giving us a whole heap of customer insights that we never had before, right?
Imteaz: 00:11:34:19 – 00:12:01:16
So again, remember I told you, you know, we’ve always used to be a B2B type company. We’ve always had retailers maintain that relationship with consumer when it comes to transaction and purchase that data now is way more accessible to us than it was ever before. So we’re actively mining that data and trying to find use cases and uses of that in order to continue to grow our brands.
Imteaz: 00:12:01:18 – 00:12:24:22
And then finally, is data clean rooms. And we’re going to go into more detail in the following slides. But basically what’s happening now is there’s a framework or a technology available for us for brands to take their first party data. So the data that we have on our customers match it in a compliant way with retail media data and then activate that accordingly.
Imteaz: 00:12:24:22 – 00:13:12:16
And we’ll go into detail in, in the case study. So what are clean rooms and how do they work? So on the right hand side of this chart over here you have retail media network. So data clean rooms are places where ad publishers. So Google met Facebook as well as Amazon now, as well as Walmart Connect. They’re sharing their aggregated data rather than their customer level data with advertisers such as myself whilst exerting strict control because you can’t Walmart when you’re signed up to Walmart or when you’re signed up to Amazon in the privacy agreement, you’re agreeing that sorry, Walmart is agreeing that they’re not going to share your data with somebody else in a
Imteaz: 00:13:12:16 – 00:13:44:07
Very explicit manner. Right. There’s privacy controls in place. So in terms of that first party data to match that compliantly with a brand advertiser such as myself, it’s that data is actually put into a clean room. What that means is all of your AI, all of your personal information is hashed in a way that I can’t identify who you are, but I can use certain signals and understand certain behaviors that you have on that platform to match up to my data.
Imteaz: 00:13:44:09 – 00:14:15:02
So say, for example, I want to look at over the last 30 days, I want to see people who searched for Nike shoes but did not purchase. Okay, so keyword Nike shoes did not purchase. I can go into the data clean room and create an audience of people that search for that keyword that did not purchase. And the data clean room will give me back an audience of 2000 or 20,000 identities.
Imteaz: 00:14:15:06 – 00:14:41:21
I don’t know who these people are, but I know that they had a certain behavior on that retail media network and then I can advertise against them. Okay. So from there, we see how different datasets match up and look at any inconsistencies between the two to understand if we’re over serving ads, if we’re giving too many ads away, or what activity do we actually need to run.
Imteaz: 00:14:41:23 – 00:15:05:08
So the three ways that you can use a data cleaner, one is through measurement. So you can look at historical performance of your ads within that retail media network. You can use it also for media planning. So if I change the media tactics that I’ve done, what happens? It’s like a scenario planning situation and then you can also use it on the fly.
Imteaz: 00:15:05:14 – 00:15:34:11
So from a media activation point of view, which is where the case study is going to head go, I think I’ve covered this one. So to make it really easy, a dairy clean room is akin to a middle school dance. So one on the left side and left hand side. Here you have your own or your brand or the advertiser’s first party data on the right, right hand side there you’ve got someone else’s first party data, right?
Imteaz: 00:15:34:13 – 00:16:06:18
And there is a heavily chaperon temporary interaction happening in between them. Okay. So after you’ve done that interaction, everyone goes back to the wall and remember, who owns the gym isn’t as important as you know what you’re dancing to in the music, what the music is, right? So this is a very new way for advertisers or CPGs for us to match our data with other people’s data in a compliant way and activate against it.
Imteaz: 00:16:06:20 – 00:16:38:09
Okay, guys, if you have any questions throughout my slides, please, please feel free to ask as well. So the retailer that’s leading data clean room activation here in the US is Amazon. Amazon has a product called Amazon Marketing Cloud and in this case study, we’ll go over some of the things what we’ve done with them. So the objective of this initiative was to shoot more bulls eyes with our media.
Imteaz: 00:16:38:11 – 00:17:00:11
Right. If you think about the baby formula category, if you don’t have a baby, you’re not interested in this category. So there’s no point of me exposing my ads to people that don’t have a baby. In the US, there are 10,000 babies being born every day, and then there are 10,000 babies leaving this product category every day. There’s only 1% birth rate growth in the US.
Imteaz: 00:17:00:13 – 00:17:34:00
So like and breastfeeding is increasing. So from a volume point of view, there’s no volume growth in this category. It is all about how do I acquire more customers from other people’s brands as well as how do I extend that lifetime value within people that are built. My brand as well. So in terms of the how, what we did was create weekly cohorts from our own database, from our own first party data that we have, and we put them into Amazon Marketing Cloud and delivered sequential ads to these consumers.
Imteaz: 00:17:34:01 – 00:18:04:02
And we measured the difference in conversion versus control groups. Previously, we also built lookalikes within the Amazon audience layer as well to find shoppers that had similar sorts of behaviors as well to further get to more consumers. So in terms of how we activated this, so we did a specific we did some specific campaigns around our infant vitamins portfolio.
Imteaz: 00:18:04:04 – 00:18:29:14
So consumers that fell into the audience behaviors that we were looking at would deserve display creative across. We started with our vitamins range, then we moved onto baby formula as well. But to give you some perspective of some of the ads that people were looking at, and then what were we optimizing and testing against? So as a performance marketer, I really want to drive two things.
Imteaz: 00:18:29:18 – 00:19:06:18
One is I want a direct purchase. I want more people to buy my brand. And secondly, I want to optimize against cost, which means I want to spend less money acquiring those customers into my brand. Right? So the way this works is across these three vectors or these three levers, we were either upgrading or downgrading things to find the optimal way to acquire new customers, 10,000 babies every day, acquire more of those customers in the most cost effective way possible.
Imteaz: 00:19:06:20 – 00:19:30:04
Okay, so how do you kind of do that? So firstly, you start with audience. Who is the right audience to target? So you go into the data clean room, you look at what are these behaviors that people display when they’re shopping on Amazon, for example? Search is a very good one, right? Because if you searched in the last 30 days for baby formula or you’ve searched in the last 30 days for a bit.
Imteaz: 00:19:30:06 – 00:19:53:06
Sure. Go ahead. So it’s just about what is the right budget to spend? How do you what’s the process for that? Like, how do you find the right budget if it’s not? You start with a seed budget. You start with $10,000 a week, for example, and you see the performance against that. And if you want to scale that up or down, you can.
Imteaz: 00:19:53:08 – 00:20:13:17
So you just start somewhere. Obviously, it needs to make sense for that category right? So if you’re in $1,000,000,000 category, you’d spend a lot more money than if you were in a category. And if your brand is only like $1,000,000 big or $10 million big, your advertising budget would be significantly different versus someone who’s, you know, shipping billions of dollars worth of product.
Imteaz: 00:20:13:17 – 00:20:24:08
Right? So you’ve just got to pick a number that kind of makes financial sense for you to start with. And then based on that performance, you can scale up with that.
Imteaz: 00:20:24:10 – 00:20:53:10
So you start with audience. So what are those signals that you can take out of that retail media network? So search is one of them. But you could also think about things like, you know, if someone’s buying Lululemon gym pants, they might also be interested in sweatshirts from Lululemon, for example. So you’ve got to think about what are those correlations between behavior on a platform and then create that audience and then test against it.
Imteaz: 00:20:53:12 – 00:21:20:01
Right budget. So to your question, you start with something and you say if you need to scale up or down. But also what’s very cool about this is the machine is actively making decisions on do I spend my entire budget today like that $10,000 if I’m spending, let’s say, $20,000 a day right now? Do I spend all of it today, or do I hold on to some of that budget and optimize for total sales?
Imteaz: 00:21:20:06 – 00:21:44:01 Right. So it’s not just about spending your marketing dollars today. It’s also thinking about what’s the best way to spend my dollars so I get the maximum return. And then finally is settings. So when you’re setting up Amazon campaigns, you can do things like frequency caps. So what a frequency cap is, is the number of times somebody is exposed to an ad, right?
Imteaz: 00:21:44:06 – 00:22:12:09
So let’s say for a particular category, if you are exposed to nine or more ads, anything above nine doesn’t increase conversion anymore. So why would we want to do a frequency of 24 that has no impact? So I can cut down my frequency and cap the number of times that the same person sees the same creative and save money and, you know, share my ad to somebody else.
Imteaz: 00:22:12:11 – 00:22:34:20
So the machine was doing all of this stuff for us to look at how the model actually works. So on the left hand side there, we have our CDP. A CDP is basically a database where all of our first party consumer information sits. The second part is we looked at Amazon ads, we looked at how our historical campaign performance was happening.
Imteaz: 00:22:34:22 – 00:23:04:12 And then within our media platform. So we used a specific software to buy our media. We’re looking at the audience reports. All of this information was fed into our ad optimization model, which processed all of this information, created new campaigns for us. It served those ads into Amazon ads. It monitored the performance of those ads in real time, and then that information gets sent back into the optimization model.
Imteaz: 00:23:04:14 – 00:23:34:06
And it continually optimizes on the fly. So it’s using machine learning to do all of those three things that we talked about in the previous slide in real time on the fly with real budget at all times, right? So instead of me having to have multiple performance media managers sitting there like updating certain budgets down, weighting budgets, looking at which audiences to create and a number of things that they could be doing.
Imteaz: 00:23:34:11 – 00:24:07:11
The machine is doing that for us because machines are better at process driven tasks versus humans. Right. Any questions on this lot? So, all right. So what did it achieve? So across the key metrics that we were tracking for this particular case study, we saw significant improvement on the first KPI, which is purchase per dollar spent. What purchases per dollar means is for every dollar that I spend, how many transactions did I get from that?
Imteaz: 00:24:07:12 – 00:24:36:07
Right. So, you know, in the benchmark periods, we were getting very low conversions per dollar spent versus when we were looking at the cumulative performance. In the case study, we significantly improved against the baseline in terms of purchase rate, which is similar to your conversion rate in terms of total sales coming across from a conversion point of view that increased as well.
Imteaz: 00:24:36:09 – 00:25:15:08
And then finally, when we look at the return on ad spend, which is your sales divided by your ad spend, it significantly improved as well. So across from a result point of view in performance media, this is exactly what you want to see. You want to see higher sales and you want to see lower cost, right? Because typically when you scale spend, especially in the old world of traditional media, your performance drops very quickly because you’ve already if you’ve already if you’re already spending too much money, spending that next dollar might not necessarily be a good thing.
Imteaz: 00:25:15:10 – 00:25:31:09
This model kind of showed us on some of our paracatu diaries. We were already spending too much money. It didn’t improve our sales, but it cut our marketing in half, meaning that I could take that savings and then spend it somewhere else.
Imteaz: 00:25:31:11 – 00:25:57:03 So to some takeaways. So by using a clear data clean room, you can deliver that right creative to that right audience at the right time. You can optimize your media and optimize what ads you’re showing to everyone in real time. And you can do all of that through AI and automation at scale as well. So what does that mean for you?
Imteaz: 00:25:57:05 – 00:26:24:05
So if I was in your shoes, what I would be focusing on right now is how and understanding how data flows through multiple things or multiple pieces within an organization, across sales, across marketing, across consumer insights, across all of these things. So improve your data fluency. I would also learn how to start small and cheap and then walk away if it doesn’t
Imteaz: 00:26:24:07 – 00:26:48:16 And this is something I learned by doing Startup, by the way. But this project that we started off initially, we didn’t know if it was going to work. It was a very big risk that it wasn’t going to work, but we thought, What’s the cheapest way to get started? What is the smallest category that we can kind of get, you know, throw a little bit of money that wouldn’t hurt us to get started with and see if it works.
Imteaz: 00:26:48:18 – 00:27:13:10
And then you can scale up from there and ask for more money from the business. And then finally always be learning, which is, you know, this stuff didn’t exist when I was when I was in college. I also I also took a data science course through Harvard Online a couple of years ago because, you know, when I studied marketing and commerce, data science wasn’t really a big thing back then.
Imteaz: 00:27:13:10 – 00:27:21:03 Right? But now it’s a very important thing to learn as well. Cool. That’s it for me. Any questions?
Imteaz: 00:27:21:03 – 00:27:47:02
What what’s the project on this topic? What was my project? Okay, so this is back in 2014 before Pokémon Go made air. Like augmented reality a thing. So Mike, my team, we made this thing called Spec See Me, which is custom designed 3D printed glasses using augmented reality from your webcam laptop.
Imteaz: 00:27:47:04 – 00:28:16:04
So yeah, so we actually had built a functioning product. I had a girl on the team. She was 20 years old. Atlassian had already hired her. She found out right then had some open source software allowing you to put glasses on someone’s face, you know, within the browser. This is like nine years ago. This is like revolutionary at the time, another person who was a mechanical engineer, he found In-Browser CAD.
Imteaz: 00:28:16:06 – 00:28:51:08 So we were customizing the look and feel of the glasses. Another person on the team who was building e-commerce sites, so he built a functioning website and then a go from Spectrum PR, who managed the PR for Samsung in Australia, and she did all of our content marketing. She got us into 3D printing news and we did all of this with dodgy wi fi traveling from Sydney to Melbourne, which is about 700 miles and back in in three days.
Imteaz: 00:28:51:10 – 00:29:14:20
So, you know, if you want to build stuff using technology, it’s very accessible now to do and with such a pity with all of these no code solutions as well, I think it’s really important to understand the problem you’re going to solve for consumer or your target market more than it is the technology. The technology now is just becoming even more and more accessible.
Imteaz: 00:29:15:02 – 00:29:39:00 It’s I don’t want to say it’s not important to learn code or not important to learn data fluency or data science. But the bigger challenge that we have is how do we actually create stuff that’s going to get used and make money and add value? Yes, I’m going back to that slide that has like three different circles.
Imteaz: 00:29:39:02 – 00:30:04:16
Yep. In terms of like jobs and how that works through your team. Like, yeah, that one like, is the oldest a one person job? Like how does it flow through like your company? Great question. So there are two teams that were really instrumental in making this happen. One was my performance media team and the second team was our data partner.
Imteaz: 00:30:04:18 – 00:30:37:13 So an external agency that we worked very closely with. So we had three dedicated data scientists, a business analyst and like a project manager who kind of orchestrated all of the technical stuff or the data science, building the product, understanding and connecting the APIs and the data points. And then a commercial person or a marketing person who had to clearly define the problem that we were trying to solve and what the output kind of needed to look like.
Imteaz: 00:30:37:17 – 00:30:53:07
Right? So again, you know, the technical stuff, there’s a lot of technical people out there in the world. But clearly defining the problem that you’re trying to solve is the tricky stuff which, you know, everyone in this room can do.
Imteaz: 00:30:53:07 – 00:31:09:17 Like how do you determine when to change the parameters of the benchmark? Okay. Good question. And this comes down to studying your category and studying your brand and studying your competitors.
Imteaz: 00:31:09:17 – 00:31:32:20 Right. So, for example, if your competitor comes in and start spending twice as much as you do for no apparent reason within their particular category, you have to respond to that. Right. But you need to know that they’ve done something. So on a monthly, bi-weekly, and then quarterly basis as well, we monitor our market share.
Imteaz: 00:31:32:22 – 00:32:08:23
We look at how are our brands performing against all of the competitors and the total market. And if there is a significant change, we determine what do we need to do about that. And to your question, I think you go, when you have like an industry that’s a very defined like customer life. Yes. How much of like when you’re looking at data, like deciding how to go on, how much it is focused on like new customer acquisition, the 10,000 babies entering like every single day versus, you know, trying to take you with your competitors And like any market share that way.
Imteaz: 00:32:09:04 – 00:32:44:08
Sure. Great question. By the way, because I’ve worked in the baby formula category is very different to most of CPG, right. If you think of CPG toilet paper, yogurt, all these other different categories where, you know, promo price your for your traditional full pace, play a huge part of your purchasing decision. Right? Baby for me is different because you’re buying this one category for nine months and you’re spending between 400 to 1200 dollars in nine months.
Imteaz: 00:32:44:08 – 00:33:15:13
That’s a lot of money versus toilet paper an average household might spend, I don’t know, 120 to $150 on toilet paper on an annual basis, which is completely different and is heavily influenced by who’s on promo that week, for example. Right. So it comes down to understanding the shopping behaviors that we talked about. What what is that path to purchase in terms of choosing the brand that you’re going to go with or and what priority does brand have?
Imteaz: 00:33:15:15 – 00:33:38:04
What priority does media have in that equation to actually make a purchase? Right? So let’s say I’m picking on and this is a hypothetical example. I don’t know is the toilet paper category in the US that well, but let’s say media doesn’t matter in that equation, right? It doesn’t matter who is doing as many display ads as possible.
Imteaz: 00:33:38:06 – 00:34:10:23 The customer only cares about who is on promotion. This week. Yeah. Then promotion is more important than media. So then you have to change your strategy and really, you know, compete against your competitors who might be on promotion, promotion every single week and then determine how do I differentiate myself against everybody else. Maybe for this completely different, highly emotional category doctors, health care professionals, your midwives, everyone has a huge part to play in terms of making the decision of which brand you’ll pick for your baby.
Imteaz: 00:34:11:01 – 00:34:48:16
So yeah, the answer is it depends. do you mostly target or focus on getting new or find new customers? Or is it like, what’s your customer base stick with that? Is the experience I don’t know about big. Yeah. Because that the only time you use this formula then you’re just more so your experience is that once a customer has become a customer because they stay for nine months or they experiment with different, you spend money and and keep keeping them the so this is like the general customer behavior within baby formula.
Imteaz: 00:34:48:17 – 00:35:13:23
So you get when you, when you’re at hospital and if you’re having feeding issues, the hospital will typically give you a formula. And all of the companies are trying to be that formula of choice, that hospital, because that’s the first interaction that we have. We also we all do sampling programs as well. So we actually sample products to to to the home as well.
Imteaz: 00:35:14:01 – 00:35:36:04
So we want to be that brand that’s there at that moment of need. Right. Secondly, what happens is one in three babies in the US has a feeding issue, which means digestive issue, cow’s milk, allergy intolerance to something whatnot, and one in three babies are switching within them in the first, let’s call it 60 in the first 60 odd days.
Imteaz: 00:35:36:04 – 00:36:07:10
Right. And sometimes people switch twice, depending on the severity of the food allergy or intolerance to the formula. After that, after baby is comfortable with the formula. Switching behavior is not there anymore. It’s a very high, highly loyal category. So for us, even though you might have a nine month baby who can still drink formula for another three months or another six months, once you’ve bought the same formula for 90 days, another switch.
Imteaz: 00:36:07:12 – 00:36:24:00
I don’t need to market to you anymore. I’m not going to convince you to buy anything else again. Comes back to understanding your category dynamics and understanding how your consumer is buying into your category and what can you actually do to change that.
Imteaz: 00:36:24:00 – 00:36:36:10
all right, how awesome is this? All right. So let’s spend about 20 minutes on a project and you guys can get out of here for the holiday segment.
Imteaz: 00:36:36:12 – 00:36:50:06
All right. There you go. And then you can log to show us. So, yeah, if you guys want to learn more or reach out anything, please do.
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