Episode Ten: The Importance of Being Curious

Using Customer Data to Inform Business Decisions

We caught up with Sarah Moore, Data Intelligence Director at Sky at the Women in Data Conference following the presentation of her ‘Twenty in Data & Technology’ award. Tune in to hear more about Sarah’s career in data and why she believes customer data is vital to inform business decisions and strategy.

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The Power of Data Podcast

Episode X: The importance of being curious

Guest: Sarah Moore, Data Intelligence Director, SKY
Interviewer: Louise Cavanagh, Communications Director, Dun & Bradstreet

Louise 00:00
Welcome back to the power of data podcast. I'm Louise Cavanagh from Dun and Bradstreet. Today we're at the Women in Data conference at the O2 in London, and I'm joined by Sarah Moore, who's the data intelligence director at Sky. Firstly, Sarah, congratulations on being one of the 20 in data in technology.

Sarah 00:16
Thank you,

Louise 00:16
You’ve been at Sky for about 12 years. I know you've got a degree in maths and stats. So data &analytics is kind of in your DNA. Could you tell us a bit about your career journey and how you ended up in a data role?

Sarah 00:28
I can. I kind of fell into it a little bit. I know that's a really bad thing to say at a conference or on a podcast like this. I chose maths because I enjoyed it, bizarrely. I was always that kid at school who liked solving problems. It kind of felt natural for me to do that university. I actually changed my degree a few times at university and ended up with maths and stats. I joined a bank, HSBC, straight out of uni worked in credit risk. It was fascinating at the time I got out just before the financial crisis happened, not to blame! Then I joined Sky. What I really liked about joining sky and as you said, I've been there for 12 years, is it's a choice for customers. And actually, data plays a massive story how you use all of the information, the viewing information that we collect. I've done quite a few different roles at Sky as well. So I haven't just sat still for 12 years, but there's been about five different roles within those 12 years. I started off as a lead analyst looking after churn and really thinking around what was making customers stay at Sky, what was kind of making them think differently about Sky. I was there for some of the launches of their key projects such as HD, broadband etc. And then I moved on to what was one of the most fun times actually, which was a capability project building, at the time, what was Europe's biggest viewing panel for TV. Up until then, Sky had really been at the behest of BARB, which is the industry standard for how we collect viewing information. It's a research panel. We built over half a million consumers onto one platform to sit there and say, using second by second viewing data, what are they watching. I did a lot of work around how we could use that to really drive the strategy for Sky. It was the first time we could actually see not just what people were buying, but how they were consuming what we bought.
So using it to understand how we could make customers stay at Sky for longer, what really resonated with them and engaged with them, how we could use it to think about some of the content rights that we were purchasing at the time, entertainment, drama, all of those things, but really all of the mechanics that went behind it as well. So not just how we use it from a customer point of view or business point of view, but the mechanics around how you actually get that to work day in day out so you can drive value at scale. So I did that for a good four years and then I had the opportunity to move over to Now TV. So for those of you don't know Now TV is part of the Sky family. It is our version of a streaming service. I look after that in UK, Ireland, Sky Austria, Sky x, and Sky Espana. But essentially really looking after how we use data, setting the vision, setting the strategy, really thinking about how we use that to drive some of the business decisions that we make, whether they be customer ones or actually within the teams themselves. And that's quite fun, I get to not only think about the mechanics of how we collect it, working with our technology teams, really thinking about how we can make it faster, better, more scalable, how we launch it across different territories, but also really think about it from a customer perspective. And really think about champion challenging the business with the customers voice. And I always like to say that the data flowing through all of our products and systems, it's really our customers voice without them actually having to talk to us. And it's quite nice to be able to represent that on behalf of Now TV.

Louise 03:51
It's very interesting, because I did maths, not at degree level, but A level, and then you talked about credit risk which is obviously Dun & Bradstreet’s core business and then I worked at the BBC with BARB so although quite a different career paths as I’m in Comms but lots of similarities there as well! Really interesting. And what you said about the importance of that customer data and unlocking the value for customers themselves, but also the business. It's just fascinating and shows how data is just at the core of, of a business and successful strategy. And I think we've answered one of my questions that was around the sort of customer intelligence piece. But what do you see as the key trends that we've seen in the data and analytics space over the last few years? And what do you think the key challenges and opportunities have been with things like AI and machine learning coming in? And what sort of difference that's made for those roles that you've had at Sky and elsewhere?

Sarah 04:36
So when I first came out of uni, it was very standard data structures e.g. SQL and all of those things. What you could do with them was great, but it was limited. You could do business decisions, but you really couldn't get it all into the customer journeys. And I think that's the big change that I've seen over the last 10 years. The power that we've got behind the processing right now. The cloud compute that we get enables us to just push the edge a little bit more. Five years ago, I would have been looking at it from an inside perspective, storytelling, which is hugely important helping shaping the business decisions. Now I get to look at it from how do I help the customer make decisions as well, which I think is a big shift from where we were 5 to 10 years ago. Examples of that, because what does that actually mean in reality? It means actually taking the business out of some of these decisions ever so slightly, not all the time, but ever so slightly. Looking at all of the customer journeys that a customer gets to contact us through, whether that's in our service, whether that's in our marketing, so below the line, direct emails, etc. Whether that is in the product itself, so how they interact with the apps that we have, actually physically consuming TV, or using the broadband, all of those ways that we can talk to the customer, we can change what we put in front of them, we can help direct them on a different journey. And all of that helps us make sure that they're engaged and helps us make sure that they're getting the value that they want out of the product that they're paying for. And it's really interesting, because whenever we go into consumer closeness groups, a lot of the things that come up is really around value. It's around what does this mean for me? And what we see a lot of is in today's world, that's not just around price. It's around, am I spending enough time using this? Is it worth the money that I'm spending on it for me? And that's all around how you engage those customers. So I think with machine learning, with AI, yes, we could have built a model that we would have sent out via direct mail or an email 5-10 years ago. Now what we do is we get to play in real time into those products to actually get the customer to interact when then choose to, rather than when we choose to.

Louise 06:41
It's fascinating, all the sort of the tech behind it. And that instant, real time, data coming through. It's just only going to go that way. So in the future as well

Sarah 06:50
Proper geek out, I love it.

Louise 06:52
Well, obviously we're here at the Women in Data conference today. So it'd be remiss of me not to talk around that. What's been your experience of diversity in a data related role, and in your industry, do you think there are barriers or things that businesses can do to help support women coming through in those roles?

Sarah 07:09
Yeah, so we talked about University earlier. And I have to say it was a fairly male dominated degree that I did. I didn't think anything of it at the time if I'm being honest. And when I came straight out of uni, again, quite male dominated, especially in the leadership roles. I was quite lucky that when I joined Sky, my bosses in the first few years were female. So I never actually questioned whether females could get into more managerial roles. Maybe I didn't see them as much in the leadership roles, but I could see that you could do it. I find what's interesting, though, is the role model. And I think it's so important to have the diversity in those leadership roles. Two things. Don't underestimate what you can learn from different experiences around the room. Not everyone has trod on the same path. In fact, every single person has trod on a different one. And they've all taken a slightly different approach from that. And whether that's about being female, whether that's around ethnicity, whether that's just around your personality preferences and how you communicate with each other, you can learn something from that. And I think it's really important to role model that because I find it amazing how many times I've looked up into the kind of the roles above me. And I consider whether I can picture myself doing that well based on the people I see in it, and how they act and how they behave. And interestingly, I, I don't think I've ever questioned the fact because I'm female or woman. But I always have thought about it from an introversion point of view. I tend to be the quiet one in the room. Back in the day, I would have been that person sitting in the background, head stuck in a piece of code. That was my safe space. I quite enjoyed it, frankly. And when I looked up, all the leaders were very engaged and vibrant, like sometimes a bit ‘jazz handsy’. And I always pictured myself doing that and I couldn't quite see that element. And I think that's what's really important in all of this. It's around whatever path you choose. How you can pitch yourself in that and having role models that display slightly different characteristics, I think is hugely important in that.

Louise 09:06
That's really good advice. Again, things mirror my career in that I was the introvert but now probably people can't shut me up.

Sarah 09:28
Exactly right! It's something you can teach yourself. I'm still an introvert at heart, I go home, I sit and I have my quiet time, and I'm okay with that. But I've learned how to manage it.

Louise 09:39
It's the perception isn’t it and the expectations that is really interesting. I know, we haven't got much time because you've got a busy day today at the conference. Just as a final question to finish I just wondered, what would your advice be for anyone thinking of going into a data related career, particularly for women, but I think anyone would find advice really useful.

Sarah 09:41
Two things, two things. The first one is be curious. Don't be afraid to ask questions. I'm not going to say that there's no such thing as a stupid question because we've all sometimes had them. Not all the time. However, if you don't know you should ask. And one of the things that you get to do with the data is you get to query as like a creative license every single time you look at it, but also it's with the businesses, it's with the customers and focus groups as well. So be curious, ask questions, and don't lose sight of the softer skills. Everyone always thinks that you have to focus on the technical, I need to learn the latest bit of Python, I need to learn how to build gradient boost modeling, or random forest, or the next level of kind of data engineering. That's great, and it will get you quite a long way. However, coming back to this is about our customers voice. A big part of this is how we tell the story and how we make a difference in those decisions. And if you can't influence others to actually take that gamble with you on something that potentially they're not that comfortable with and they don't quite understand. You're never going to make that step change. So really don't lose sight of the softer skills, be curious, ask questions, build those relationships and those networks. Because those are the things that help you step change how the customers and how the business uses information that we're collecting.

Louise 11:00
Thanks very much, Sarah. Thank you for your time today. It's been really interesting if somewhat short, I wish we’d been able to have a longer chat. And congratulations again on your award.

Sarah 11:08
Thank you very much. Very exciting.

Louise 11:10
Excellent. And we'll see you next time on the power of data podcast.