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SheCanCode's Spilling The T
SheCanCode's Spilling The T
Data-Driven Marketing: Insights on AI, Analytics and Advertising
In this episode of Spilling the T, Seena Samani, Head of Data and Analytics at Mindshare UK, dives into the dynamic world of data and analytics within the advertising and marketing sector.
With a keen understanding of the role AI and machine learning play, Seena offers invaluable insights into the evolving landscape of data analysis. Whether you're considering a career in data analysis within the media sector or beyond, Seena's expertise and advice provide valuable guidance for navigating this rapidly expanding field.
Seena heads up the data and analytics department at the global media planning and buying agency Mindshare (part of WPP and Group M).
Her day-to-day role sees Seena lead Mindshare’s Marketing Science, Performance Analytics and Data & Technology teams, providing data, analytics and technology solutions for clients – including M&S, KFC, and Unilever, and Mindshare's internal teams.
Before joining Mindshare, Seena worked in a variety of senior data roles in the finance sector for brands such as Barclaycard and NatWest. Most recently, she was Global Head of Marketing Effectiveness Analytics at HSBC, where she was accountable for the optimal use of a $500m marketing budget across multiple markets.
SheCanCode is a collaborative community of women in tech working together to tackle the tech gender gap.
Join our community to find a supportive network, opportunities, guidance and jobs, so you can excel in your tech career.
Hello everyone, thank you for tuning in Again. I am Kayleigh Bateman, the Content Director at she Can Code, and today we are discussing data-driven marketing insights and advice. I've got the wonderful Sina Samani, head of Data Analytics at Mindshare UK, and she's here today to dive into the dynamic world of data analytics within the advertising and marketing sector. Welcome, sina, lovely to have you on here. Thank you so much for joining us.
Speaker 2:Hi, kayleigh, thanks for having me. Pleasure to be here as well.
Speaker 1:Thank you. This is a topic that I know our community are going to love. A lot of our ladies work in similar areas, so I know they're going to love to hear about your insights and your advice in this area.
Speaker 2:So, to set the scene today, can we hear a little bit about you and your background and your career journey so far, if that's okay? Yeah, so just I have over 18 years experience now in data analytics. I started off in sort of financial services retail banking in particular and then more recently have moved into kind of media advertising so Mindshare UK, as you mentioned. I wish I could say when I was at university that data analytics is where I wanted to be. In all honesty, I recall when I started in management sciences I went to a lab on visual basic coding and after the first lab I was kind of confident that this wasn't for me. Coding was definitely not something I wanted to do. So, having kind of been through that journey, it was actually when I graduated and I was speaking to recruiters and at the time I graduated, in all honesty, data analytics wasn't such a hot topic as it is today. So I wasn't aware of kind of careers and roles in this space. But from speaking to a graduate recruiter about what.
Speaker 2:I enjoyed doing the type of roles I was looking for. I ended up starting my first role as a campaign analyst at Global Bank, so that's how I got into data analytics. So just to explain my first role actually it was sending out direct mail campaigns to customers who take up the credit cards at the bank. So who knew kind of that existed. But for me what kind of drew me in was very much being able to use some of that numbers technicaly element but also apply that to the business. So so how does what we're doing make an impact on business results or um?
Speaker 2:you know, influence the sort of the activities we're doing and so forth, and it was the application, I think, data analytics that really kept me in. Obviously, I ended up getting coding skills to do my role at Edmund Progress, but that's, I'd say, how my journey started. And then, from that point on, I've done numerous roles within financial services at some of the top retail banks within the UK and then sort of the last few years've joined mindshare in the in the uk. So mindshare, for people who don't know, is a media planning and buying agency and my role here, as you mentioned, is heading up the data analytics team. So this involves everything from helping clients understand their data strategy, what their ad tech strategy needs to be, through to developing sort of BI, sort of dashboards, and then going into sort of advanced analytics, be it kind of metrics modelling, brand modelling and so forth, so really helping customers understand how their marketing investment is making a return for their business.
Speaker 1:Yeah, you know. I'm curious to ask you that you obviously now fully understand how to make an impact on a business with data. Was all of that clear at university? Or is that something that you know? Because we always hear that disconnect between what you're studying at uni and then when actually you hit the real world and you didn't realise that you know a lot of the jobs that exist in the tech sector. You almost weren't aware of them at university and you know people on here they say you know, I wish I'd almost known, or what it was like to work in the real world. But did you know that? Or was it kind of when you left uni? Then you realised that's when I could make an impact on a business with data analytics.
Speaker 2:Yeah, I did know that at university and I do believe that's changed a lot, certainly from the time I was graduating to today. Just to give a flavour when I was graduating, even at the careers fairs that we'd go to, no one was talking about data analytics or types of careers in data analytics, whereas I know, since being in the role, I've had opportunities to go speak to students, do sort of initiatives like this and be able to kind of bring that more to the forefront and show people what are the types of roles that exist in data analytics. So I feel that is changing and it's moving in the right direction. But certainly, you know, kind of 18, 20 years ago, when I was thinking about roles, looking at what's available, I wasn't aware.
Speaker 1:Yeah, yeah, because you said it was actually what attracted you to the role. And if you'd known that up front, you know you probably would have moved in that direction a little bit sooner. But you're right.
Speaker 1:And then yeah, yeah, you, you, you're, you're absolutely right. Um, it's always interesting to hear what draws people to certain roles, because tech is always seen as that um, uh, it can can be seen as a place that people don't want to go because it's just for technical coders and if you can't do, then there's nothing else in between. So, but usually when you speak to people that work in the tech industry, they always say actually, you know, you're just making an impact on business and on people's lives. And then when you actually figure out what it is that you're doing, it's not the nerdy getting into the data part actually that drives you, it's the making an impact and applying that to to a business. Um, so, yeah, and it's great to hear as well that you're now, um, spreading that news with students about you know actually what you do, um, and kind of bridging that gap between what you would have loved to have heard when you were a student. Um, can you explain the role data and the role that data analytics plays in the advertising and marketing sector?
Speaker 2:yeah, sure. So advertising and marketing is very big and vast, as it can appreciate. So, even if I take kind of the part that we as mindshare play. So you know, at Mindshare we're a media planning and buying agency, as I mentioned, and I actually see data analytics playing a role throughout the whole media planning and buying cycle. To give an example of that, if I think about our planners who are planning, you know how should we allocate media spend across the different media channels. They're using machine learning tools to help them do that in the most optimal way, for example, through a buying team. So they're buying these media channels. They're using kind of in-camping optimization bidding tools to help them do their job more efficiently.
Speaker 2:And then coming on to my team, so you know, we're using, we're looking at spend clients have done and the impact obviously that's made on business results for them. And again, that be it through kind of the BI reporting through to building econometrics, modeling these, machine learning and so forth. So for me, data analytics certainly plays a role across the whole media planning and buying cycle, certainly here at Mindshare. And, like I said, that's just part of the advertising marketing sector. And recently we've seen the rise of generative AI, for example, and that's having a huge impact in the content and creative side of marketing.
Speaker 2:And then, just going back to my experience being more kind of client side, brand side, you know we were using data analytics even at the time in my first role, to create propensity models to target the right customers with the right offers at the right time. Um, using kind of you know the fast enough data that we had around customers to look for lookalikes etc. So data analytics certainly, from my experience, plays a role across kind of the sector, in all the different pockets, kind of. I've touched on there yes, definitely, and especially myself.
Speaker 1:I've worked at several publishing houses where we've worked with media agencies, and it's always come down to that ROI and you know, proving you know why things are working, or or you know, even testing, and saying you know something isn't working and you know we'll move in a different direction. But, um, you're absolutely right, that's really changed as well. From back when, when you started, through to the type of data that that you can access now, and the way that people can have such an insight into, um, uh, how their businesses are working with, you know, third parties and agencies is so, so, so interesting. And you must have a really interesting day.
Speaker 2:To be honest, I bet your day is like completely different every single day it's 100% varied, something different every day, and that is actually one of the things I love about being in data analytics it is you're doing something different, it's always evolving, there's new innovations, new capabilities coming out, so you're constantly learning and for me, that really keeps me kind of engaged within the field.
Speaker 1:Yes, exactly and can you share some examples of how data and analytics have impacted advertising and marketing campaigns?
Speaker 2:yes, I can share two recent examples from here at MindShare.
Speaker 2:So the first one actually is with Cornetto.
Speaker 2:So the ice cream brand, and we wanted to help Cornetto kind of tap into weather-related demand as well as, obviously, increase of their penetration in the market as well.
Speaker 2:As you can imagine, it's a very heavily saturated market in terms of ice cream. So here what we did is we actually used daily weather data, stock level data and kind of geographic data to build a decision engine and then, based on that decision engine, we could synchronize the media and the message based on the sun, the stock and the surroundings on any given day. And what that led to is just us being able to be a lot more playful with the message that we were sharing with customers and when we were sharing that message, meaning that Cornettos they top of mind are the right type of these customers. And again, just going back to business impact impact, not only did we help increase penetration for Cornetto, but actually managed to reduce media spend in areas where the stock wasn't theirs, so really being kind of both efficient with the media that we have, but also help Cornetto become more front of mind for customers. So that was like one example of something recently.
Speaker 1:Yeah, and to just be able to prove with them why they should be working with you and why they should, you know, have a retainer with you or whatever it may be, to be able to prove you know, actually, the data that we use, um and and, and the insights that we found. You know they really work and they really have an impact on your brand. Um and and, uh, the difference, what the different ways. I suppose that you've helped them as well, not just with budget, but I'm assuming, lots of other um things as well throughout your campaign. It's so, so interesting. And, cornetto, what are you interesting brand to work with as well?
Speaker 2:yeah, uh. The other one actually that comes to mind is, uh, kfc, and again we did some. So KFC was launching a new sort of delivery app service and here it was very much about how do we drive sales through the delivery app compared to some competitive be it delivery uber, eats, etc. We have sort of regular reporting analysis for them and this actually helped us understand that, if we look at again the location of these stores, there was very different demographics around stores, be it where they in a rural location that's, the city business, retail park versus sort of again like there's something in the city center.
Speaker 2:And using sort of data around the demographics around the different store locations and and understanding you know, different makeup customers, again we were able to create sort of geo-based algorithms. So we used thousands of data around the stores, the geo around media, demographics, and then at a postcode level, we were really able to dial up and down with media data around the stores, the geo around media and demographics, and then at a postcode level, we were really able to dial up and down the media that we shared to help drive the right sales to the right stores. That needed our support and again, if we go back to business impact. It led to a 15% increase already in sales. So it just shows the value that data in these capabilities can add to the bottom line as well yeah, and kfc is a brand.
Speaker 1:They're very um clever brand. When it comes to advertising. Their adverts were always very relevant. They're very they're the type of brand that jumps on. You know everything quickly on social media and and um you always see them like picking up something um really quick and going with a trend.
Speaker 2:So to then look into that geographically and how that is is being consumed across the country in different different locations must have been so, so interesting to look at and break down yeah, and with both those examples, like sort of geo data actually has become more and more valuable, especially as we everything about cookies being phased out and it's just a different way of us being able to target media more sort of efficiently and more effectively as well for our clients, and we certainly see a rise and demand actually coming through from, you know, just in all different types of clients wanting to do more and experiment with this data as well.
Speaker 1:Yeah, definitely. You touched upon AI a little bit earlier and I wanted to dive into that. So how do you see AI and machine learning transforming the field of data analytics in the coming years?
Speaker 2:Yeah, that's a very good question. So for me, I feel AI and machine learning has been around for a very long time and has already had a huge impact within our field, especially in areas such as automation, predictive analytics and, I feel, kind of over time, the growth in of computational power means we can do more things, and faster, which has really helped already transform the field and we touched upon this as well. You know, generative ai things like chat, gpt have really made ai love mainstream um in recent years and has continued kind of to transform the field and has continued to transform the field. If I bring it back again to the industry I'm in at the moment, we've already used AI and machine learning for a very long time to remove manual-type consumer tasks, especially within the digital marketing area.
Speaker 1:And I feel like with generative AI.
Speaker 2:We're starting to experiment a lot more in this and I think we've only just touched the surface. I see a lot more potential of how this is um, so, so actually kind of it's been a long time and potential just growing. One of the things I do want to caveat is, you know, I feel those who are going to be sort of successful in terms of organizations, individuals, are going to embrace the change and just get on experiment, etc. But also understand the limitations. So making sure we address some of the challenges this brings up, be it around data governance, privacy, ethics and that's going to be equally as important as we sort of, you know start innovating and embracing some of these changes that are that come yeah, because for a lot of people it still sounds it's it's quite, um, quite a daunting area to, to, to think even, um, you know, placing your brand in the hands of ai, for instance.
Speaker 1:you know, you see all those those bad headlines at the moment at things that are not working and you still need some kind of human intervention there to to check everything. But I think the main thing and mostly people that have been on this podcast that have discussed the topic of AI and machine learning is that it is making things better and faster in so many ways and that it's still obviously, you know, having a human involved in everything. But the rate that the industry is moving and the way that data, ai and machine learning can really just improve things, especially in data analytics, I mean, the field must be moving at an incredible rate for you and that can really impact lots of brands for the better, definitely.
Speaker 2:Yeah, and I always come back to the thought that, you know, ai is only good as human using it. So, to your point, it absolutely does go hand in hand. It doesn't take away from kind of you know, even areas like creativity et cetera. It actually helps, support and complement us in this area. So it makes us I feel like stupid.
Speaker 1:Yes, yes, definitely. But again, you know something's. It must be so, so interesting about your job. And then the new things that are constantly coming along and that you are constantly learning. Um, I don't. I mean, you've been in this field for some time. I take it you never see kind of an end to it, because you know things just keep moving and that's a bit I know yeah yeah, it's a it's a good industry to be in.
Speaker 1:Um, we always say in the tech industry, we just wish more people knew that about the tech industry you know you'll never um, you'd never be bored, and you're always learning something, something very new. And, on that note, what advice would you give to somebody looking to break into the field of data analytics, particularly within the media sector?
Speaker 2:yeah, sure. So I believe there's many sort of paths and avenues leading to korean data analytics. So you know, be it through higher education, nowadays there's so many courses specific around data science, data data analytics, etc. So the availability of that is clearly one avenue in. But also, if we look at online courses and certifications, there's so much out there to learn Python or different coding languages, and all of this is a good way to get onto the ladder.
Speaker 2:So my advice here would be, if someone's interested, then definitely start being curious, start being start exploring kind of you know the vast amount of material already out there from a kind of training, educational perspective as well, and then, if you know someone's a bit further along and start to look for careers within media. So again, there's multiple ways in depending on your career stage. So organizations offer internships you know you're still studying graduate roles and just thinking about what we do here at Mindshare, wpp. Even for women who are, kind of you know, in their midlife career stage and looking to end or re-enter the media industry, you've got a visible start programme. So there's loads of different avenues in and, you know, if someone's interested in that, I'd really encourage them to look at the organisation's website, their jobs board, to understand the different sort of opportunities at different stages of their career, to kind of get in.
Speaker 2:And then, lastly, you know, what I've certainly seen in recent times is again so many kind of conferences and meetups and networking events in this space, and again a lot of them are free. Really take advantage of that just to connect with people already in the industry and to learn more again about, you know, the types of roles and careers to help, to help educate sort of people around again. What type of roles are out there, what's going to interest me and who do I need to speak to?
Speaker 1:yes, I love that and our community are going to love to hear that, because a lot of our ladies um, they transition at all stages of their career. You're absolutely right that more people should know that you can move into the tech industry at any time, any stage, and that those roles, a lot of those skills that you might do day to day, they align with lots of other industries as well, and that you know, you don't have to have that computer science degree and you don't have to do that from the age of 21. So then, come into the tech industry that you can, you know, learn and retrain, and, as long as you're open to constantly learning, as you said, the tech industry changes so often that you can, you know, transfer a lot of those skills into. You know the good companies know that as well. The good companies are looking for people that have good skills where they can transition into another role in tech.
Speaker 1:So you're absolutely right, and and networking as well, and going to those conferences and finding out the different roles and what's next is such a good part of finding out what's what's next for you, and that's what we encourage within our community as well to share stories and share what you're doing on a daily basis. I did you want to ask you quickly when, when people say that about you working in data analytics and what your role is like and you know how they might be able to come in do people have a stereotype of what your job is like? Do people think because you work in data, that's kind of that might be quite dry, or you know? Do you find that people look at you and think, oh, you work in data and then actually, when you tell them what you do and the impact that you have and what your day to day is like, do you find maybe they're a bit like oh, you know, I didn't know your day was going to be like that.
Speaker 2:Yeah, and again I feel like the understanding of data, analytics and types of roles and what people do is becoming, you know, kind of there's more and more knowledge around this space on it. You know kind of there's more and more knowledge around this space and but you're right that there is sometimes that view of it's all about kind of being hidden behind a computer or in a spreadsheet or amongst loads of data and actually I think people forget it is all about the application of that and the tools and the technology in helping try the change and impact and and just being able to kind of position in more of that way than clients and others really kind of opens people's eyes in that. Oh yes, this is how we're helping and impacting the business. You're not just kind of locked away in a dark room somewhere.
Speaker 1:Yeah, yeah, exactly that, and the more people that know that, the better to be fair, and the more people that know that, the better. Yeah to be fair. Um, and so we mentioned that obviously, the, the tech industry is moves um incredibly fast, and so is um, uh, advertising and media, um. So what emerging trends or technologies in data analysis are you most excited about?
Speaker 2:yeah, I feel like, um, this is almost the easy way out, but I'll go back to.
Speaker 2:I honestly believe we've just touched upon the potential from gen ai and this is one of the areas that really is exciting me and interesting me at the moment.
Speaker 2:Um, for example, you know already just having access to a tool where it's helped me summarize pages and pages of feedback for my team and actually helped pull that into a concise development plan. It just means I can spend time having better conversations with the team and what we need to focus on in the year to come, rather than having to spend less time reading through, say, pages of documents. So already just the impact of that on day-to-day life has been great. But one of the things I come back to is it does mean you need to re-skill and up-skill. So even for me now, thinking about how do I write prompts and how do I actually put what's in my head in terms of the image I want to create or be able to create, a tool such as this that helps summarize those documents is a new skill in itself. But again, it's exciting to learn this new skill and then see just how it helps. You know from the example of day-to-day life.
Speaker 1:Yes, yes, and again, you know it kind of touches upon your career development as well and where you would like to go, and you know whether or not that is role. But within the company that you work at as well, that you find yourselves with lots of opportunities to keep progressing in your career. And I suppose, if you know, perhaps if you didn't work in such an area, it might be more of a challenge to keep moving and to keep feeling like you're also progressing in your own career as well, also progressing in your own career as well. Um, if, if you know, perhaps you were perhaps a different company even, you know, um, I don't get that. You know at mindshare that you feel that there's lots of career progression and, um, that you do you put aside kind of time to to do that. How, how do you do you do that? Does the company put aside time for you or do you put aside your own time for mapping out your own career development?
Speaker 2:yeah, I think it sort of varies with individuals.
Speaker 2:Um, and again, you know that we give sort of um our employees the opportunity, for example, if they want to do some of the apprenticeship programs and to take part in that, which means you know you've got set time that individuals might carve out in their diary every week, whereas certainly for someone like me I like to plan it around what else is going on in my diary or take up, you know, and again, some of that's depending what sort of conferences, partner events, meetups are happening.
Speaker 2:Some of it is just taking time out to just experiment and learn and and play around with these new capabilities. So it varies a lot and, and you're absolutely right, the opportunities are fast, be it from kind of formal education, be it on job training, be it just going to these conferences, networking events etc. Um, but very much, I'd say, down to the individual, you know, in terms of how individuals want to learn and kind of incorporate this within sort of day-to-day yes definitely because I wanted to ask you that how do you stay updated with the latest developments and trends in data analysis and technology?
Speaker 1:but you mentioned it there. I suppose it is very personal, down to how you learn with me, and also a mix to to keep you um feeling like you want to keep learning. You know, you said you you attend events and you might do, you know, some online learning or you might join a network and learn something from other people, um, but I suppose it's just it's that when you come into the tech industry, you kind of embrace the fact that you're going to be continuously learning throughout the, the whole of your um yeah, the whole of your career, um. Are there any particular networks or communities that you that you like to go to, and especially for learning as well? Is there any kind of um online learning communities that you, you um love to go to to see, you know, the new developments?
Speaker 2:yeah, it again, like you said, very so I enjoy a lot of times just reading different publications that come out of organizations. Um, so, certainly within the marketing space, you know you've got companies like the ipa, walk, etc. Who are talking a lot around marketing, advertising and just learning about the industry and what's happening wider than data analytics is great because that helps you understand how you use data analytics to apply to the wider industry challenges. Even just being on LinkedIn and following top voices in the industry and just hearing about what they're talking about or, you know, watching what they're showing in terms of content, for me is a great way of just learning and hearing different voices, different opinions to help kind of shape your own way of thinking.
Speaker 2:Podcasts, you know I definitely, when I'm going out for a walk or something, I enjoy just putting on a podcast again, listening to different sort of podcasts and be about kind of my personal development, but also, you know again, also within the marketing industry. That's kind of the different ways I'm learning. And and then you know I keep going back to just take being involved in conferences, part of events, being part of the discussion and being part of the conversation, hearing how others are using and applying data analytics. It's all kind of great ways to learn on the job and through other people as well. So definitely different ways that I'm kind of absorbing and taking in information and I feel that works well for me definitely, definitely and especially at conferences.
Speaker 1:You're right, um, we know you used to go to conferences to to cover news stories, for instance. When you'd sit in the keynotes you would hear future trends, what's happening, and then that's nice to hear, but that people always used to say that that is kind of two to three years ahead of what actually people were saying on the show floor. So then you would go and meet people, network and you might have some lunch, and then you would speak to people that are there actually doing it and they would say, yeah, I love the keynote, but that's like two to three years in the future. So you'd get a real balance as well, not just by sitting in a keynote, but just chatting with people over lunch to you know what they're actually doing day to day and then what you could be doing in the next you know couple of years in the direction to move in. Um, so you're right, just hanging out of a conference for a day can can really inspire you as to what you you know where you want to go next.
Speaker 2:No, absolutely, um, no, absolutely, yeah. If I could give kind of one key takeaway, for me it's definitely stay curious, keep learning in this space, embrace the developments that are coming in or some call it chaos, but you know that's the best way to kind of really learn and understand how you can apply this new technology, this new capability to make a difference and an impact to what you're doing or who you're working for.
Speaker 1:Definitely we are almost out of time, but I wanted to ask you one question out of curiosity If it was 18 to 20 years ago, is there something that you would have said to your younger self when you were starting out? Is there one thing that you wish somebody had said to you?
Speaker 2:I definitely wish I'd stayed with the visual basics code, um. But you know, for me it's very much about and this is why I encourage everyone to take the opportunity it's just about helping sort of people in education and at different stages of their careers understand the breadth of roles out there, and I definitely think that there's a role out there that you know works for every individual and their interest. It's just how do you can navigate all the noise and and try and find those roles that fit for you, for the company. So for me it's very much about, yes, being just a lot more open and curious again to investigate different roles, opportunities and learning opportunities as well.
Speaker 1:Yes, I love that. That is brilliant advice to. Yeah, definitely hear what lots of companies are doing and how you know there are lots of jobs out there and they're not all for everybody. But just, you know, being curious I love the fact that you said that earlier. Being curious about what's coming up and what works for you is such such good advice for our community.
Speaker 1:So, sina, I could keep talking to you about this subject, for a lot, lot longer, but we are already out of time time, so thank you so much for taking time out of what sounds like an incredibly busy day and interesting day to come and have a chat with. Uh, she can code today.
Speaker 2:Thank you so much for that thank you, kaylee, it's been a pleasure thank you to everybody listening as always.
Speaker 1:Thank you so much for joining us and we hope to see you again next time.
