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Summary

Ever wonder how your phone seems to listen to you? Or how Spotify knows what tunes you need just at that moment? You ever wondered how Supermarket loyalty cards can sometimes give you AMAZING deals?? It’s all in the data that you are generating by doing, or sometimes NOT doing certain things that are just habit for you.

Transcript

Okay, quick question, do you ever feel like your phone is listening to you? You know, like one of those things where you mentioned holidays once and suddenly your news feed is wall to wall adverts for budget airlines, sun cream and that one inflatable Flamingo that you definitely don’t need. You know, nothing beats a Jet2 holiday! Here’s the secret. It’s not always your phone listening. It’s your data. Every click, every like, every scroll, every sigh that you make, is being hoovered up, is being logged, and it’s been fed into algorithms that shape what you see next.

Good afternoon, everybody. This is Duke. This is episode two, talking about the fundamentals of data. So episode one where I introduce myself and introduce the idea to you of what data is and what data could actually be, because there’s a lot of misconceptions, a lot of myths about it. And over this first mini series of podcasts, I’m hoping to clear up some of the myths and help to get you to understand how you can get data to work for you. Now, just to give you a little bit of a spoiler of what’s coming up next is that once we’ve got through this little mini series, you’re going to be talking about actually different skills that anybody can actually take using free software that is available to absolutely everybody to not only control your data, but help it to help you make decisions. So that’s where we’re heading. That’s where we’re going. But we still got a lot to talk about, about what data is and what data isn’t. So just as a summary, this episode is about how data follows you around in every day of life. We’re going to look at maybe some boring stuff, like receipts and bills. We might look at some fun stuff like Spotify and and apps. And I’m also going to sort of dig into the the wild west of data. I’m going to talk a bit about social media. And just a bit of a spoiler, your feed isn’t random. It’s engineered sometimes very cleverly. Sometimes it feels like it was programmed by a drunk cat, but we’ll come on to that a little bit later.

So let’s start a bit small. Let’s think about a receipt. I don’t know about you guys. I don’t know if anybody else does this, but if you go, you go to a shop, and the shop cashier, or the self service till, or whatever it is that using it gives you a receipt. It offers you a receipt. I don’t know. Is it British of me to just go and take that because I would feel rude if I didn’t take it. Does anybody else do that? So I end up actually gathering all of these receipts, and then they get stuffed into a drawer. Actually, more commonly, they just get stuffed into my wallet at the at the end of it, and then maybe once a month or so, I’ll go through the I’ll go through my wallet, and I’ll have a quick scan through the receipts and decide whether or not I need to keep it or not. Usually the answer is not, and they get thrown away and discarded. But every now and then, I’ll stop and I look at one of the two receipts, and I’ll think about the information that actually gets stored on there, the data that’s stored on there.

I’ve been shopping today. I’ve been grocery shopping today. So I’m holding a receipt in my hand of the supermarket that I went to. And literally, from the top, you’ve got data. It’s the name of the supermarket brand that I’ve gone to. That is data. Specifically, it names the store that I’ve got that is data. Now you might think, Okay, well, I mean, it’s pretty obvious where I went. So is that necessary? It then goes into it, then asks me for then tells me, sorry. It tells me a VAT number, VAT number, and this is where it starts to get difference, because that VAT number is something that can change. That is what we call a variable. That’s something that that can actually be altered at some point. Then you’ve got things that will change every single time I go to the shop. What comes next will change every time. It’s what I bought. It’s the order in which I bought it in. It’s how much of each item I actually bought and how much I paid for it. It’ll also tell me whether or not I took a multi pack deal on it, if I got a discount, if I got a saving because I bought more than one, it’ll also tell me later on, how much I paid in total, how much I actually saved in promotions like multi save, multi pack, if I used a voucher that would be stored on there as well.

It’s giving me how many loyalty card points that I’ve earned. I’m going to come back onto loyalty cards in a second, and then it tells me how I paid, and it gives me a load of other different numbers, which includes the last four digits of my card number, but something called a pan sequence number, and authorisation codes and merchant numbers. And these are all data points. It then goes on and gives me a barcode with a random series of letters and numbers and a date and a time and even a number of the store and the number of the checkout that I actually used. This is all data now you as a person, as a consumer, might not use that, but you better believe that the supermarket will be using that, and they’ll be using it quite a lot.

Receipts might seem simple and receipts might seem boring, but one receipt is boring. 100 receipts tell a story, and that 100 receipts could tell you all sorts of things. I mean, it could tell you that maybe you’re keeping Gregg’s in business, or maybe they’re telling you that you like a particular brand of food.

Think about budgeting apps that actually sit on your phone when you spend money. It may be tracked on one of those budgeting apps that you could see. Those budgeting apps, they don’t invent data, they don’t create data. They just make the data easier to see. I’ve got a bank account with Monzo, for example, and Monzo literally, if you choose to use it, literally, categorises your spending into colour coded charts. Now, do I need Monzo to tell me that Deliveroo has replaced home cooking? Probably not, no, but seeing in a graph just hits differently.

And businesses love this.

Your bank doesn’t just track your transactions, it looks for patterns, and those patterns can be used for things like fraud detection systems to spot if your card has maybe been used in two countries within an hour. The loyalty cards that you get on your supermarkets I mentioned earlier, they don’t just reward you with a free coffee. They track what you like when you buy it, how often you switch brand. That’s why your points are so generous! Because the company gets a full psychological profile of your spending habits. Your three free cappuccinos are basically just a thank you for letting them peer into your caffeinated soul.

I’ll tell you a true story. Couple a couple of Christmases ago, I went to my my local supermarket, and there was a particular brand of bourbon that will remain nameless, that they had brought out a flavoured version that I had tried once. I liked it, and I thought that’s pretty good. But you know that stuff’s not cheap. If you want a big bottle of it, you’re talking £40 a pop at least. But for this particular Christmas, they were charging £16 for it on one condition that you swiped your loyalty card on the on Checkout, and that sort of got me thinking, and I’m like, Okay, wait a minute, £40 for a bottle, £16 if I happen to swipe a card. Now, I don’t know what the markup is on these things that don’t work in retail, but I could be pretty sure that the markup is not £34 or £24 on a £40 bottle, that even if they are not, even if there is a markup on there, they are not making much profit. You multiply that by the dozens of bottles in that specific store multiplied by the hundreds of stores that exist Countrywide, and how much money are they actually losing by giving such a high discount on this particular bottle of bourbon, and that’s where I started investigating and that’s where I started looking into this.

Now you may be surprised to know this, but that information on your receipt, you multiply that by everybody who shops in every single store, that data becomes So, so valuable to the supermarkets, because do you know what they do with it? They sell it back to the manufacturers at quite a high cost, because they can go to the manufacturer of that bourbon and say, do you know so many people actually bought your bourbon? And we can tell you because they tracked it on their loyalty card. We can tell you what they bought with it, whether or not they like particular snacks, and how much of those snacks that they bought. We can also tell you whether or not they came back and paid a higher price for the same bourbon because it was no longer on deal.

What can that bourbon company do with that data? All sorts of things. Think about their sales strategies. Sales start to drop off a little bit, and they just like we happen to know, because we have bought the data from the supermarket to say that people who buy that bourbon also like a particular brand of peanuts, for example. So we are now going to team up with that brand of peanut. So we are going to create a deal that our consumers couldn’t, can’t constantly resist. And there we go. They’re selling honey again.

So next time you actually scan your loyalty card, whether it’s a club card for Tesco or your miles and more, or whatever they call it now, for Morrisons or your nectar card, think about, oh, yeah, brilliant. I’m getting a fantastic deal. But how is that data being turned into profit for your supermarkets and also for the manufacturers? As time goes on, you start going down that rabbit hole, and things start to get a little bit interesting.

Let’s talk about something maybe a little bit more entertaining, because Spotify. Spotify is a perfect example. It sort of tracks what you listen to, when you listen to it, how often you listen to it, whether you skip after 30 seconds, even the time of day that you actually play certain tracks. And that’s why your ‘Discover Weekly’ feels oddly personal, because it’s not guessing, it’s predicting what you want to listen to.

The same goes for your phone apps, so like step counters that you might have on your phone, or a sleep tracker, if you play games on your mobile, your gaming stats that little batter says, Congrats, you’ve hit 10,000 steps. That is the app analyzing your personal data set and spitting out encouragement. It’s basically. Like Pavlov’s dogs for humans, except instead of drooling at a bell, you’re a walking laps of your living room at 11:59pm just to hit your target.

Even the screen time app is data in disguise. It doesn’t shame you because it cares. It shames you because you’re more likely to pay attention and slap your behavior in slap its behavior in your face. Yeah, people do change habits where they’re confronted by their own numbers.

What I’m saying to you is that data works.

Let me move on to social media. Now this is, this is the big one, because these, these companies that you use, and I’m talking about, I’ll name them, Facebook, Twitter, X, whatever you want to call it, Blue Sky, Instagram, all the big names, Netflix, Spotify, actually counts as sort of like a social media because you can, well, maybe not Netflix, but Spotify, you can comment on it now. You can, you can feed back. And that information sort of counts, as I would say, probably social media, certainly in this particular case.

So let me, let me just be really, really clear, social media data, if receipts that I’m talking about that that receipt from the supermarket is like small potatoes, social media data is an all you can eat buffet. What I asked you on the last episode to start to think about what is data and what data isn’t, and what I’m starting, hoping that you’re going to pick up is that data can be absolutely anything, any interaction, any nuanced sort of behavior, can be quantified and can be tracked. So if we’re talking about social media, I’m talking about X, I’m talking about Facebook specifically, this is what actually gets tracked. This is what they track. So any pages or groups that you follow, every like or follow, goes into a profile about you and your interests. You join a group about gardening, you can expect the compost apps like a football page, and you’ll start seeing ticket promotions that all sort of starts to make sense.

But what about the people that you’re in contact with; the direct contacts. These platforms map your social graph. In fact, the databases that Facebook do use for a big part of their data is known as a graph. So who you message, who you interact with on a news feed, who you like posts of who you comment on, who’s you have a full conversation about the meal that they have just posted.

All of that information actually gets tracked. But even if you never post, even if you never like anything, even if you never make a single comment on that person you’ve had a crush on since you were 15 years old and still hoping that, even though they’re married now, that one day they’ll they’ll see you for the person that you are, every single time that you go onto that social media site, every single time you look at a photo, every single time you scroll that is all data.

So how long you hover on a post, whether you click See More, whether you scroll back up after passing something, that pause; that’s data. So every time you interact with something, every time you like something, every time, every time that you type a comment, and whether you actually post it or not, that’s still being tracked. That’s still data.

And I think about the adverts that actually show up on these sites like Tiktok and Instagram. Whatever this is, this is where it gets really quite clever or maybe quite creepy, depending on which way you look at it, because advertisers can target you with insane precision. And for example, they can say, show this video to people who have recently looked at camping gear, follow outdoor pages and live within 25 miles of, I don’t know, leads. You don’t see random ads. You see ads that have been algorithmically likely to interact with you, to engage with you, and that you are more likely, statistically, more likely, to click on.

I’ll give you some examples. At the moment, my partner and I have been talking about gardening. So my partner has been Googling, like flowers. She’s been looking at, I don’t know, supermarket superstores like B&Q and whatever. And I’ve been talking about how I can quickly and efficiently and clean the weeds up from the garden. And then yesterday, all of a sudden, I am seeing three different branded adverts for those little blow torch things that I can use to get rid of weeds, which definitely appeal to a little bit of my masculinity, I guess. But I probably be never, be too scared to actually use because I don’t want to burn my little tootsies as I’m out in the garden, so it knows how I’m going to click on those. And I did. I actually clicked on and I’m thinking, oh my god, that that is, that is the social media taking my likes into account, taking my family’s likes into account because it knows that we’ve been talking about it on social media, and providing me an advert that it knows that I’m going to click on. So all of this stuff, the pauses, the hovers, the likes, the half typed and deleted comments, or the full conversations that end up going on a feed. All of that information creates your personal Feed, Facebook, Instagram, Tiktok, none of them show you a raw Chronological list anymore.

And I’m old enough to remember when Facebook used to do that. It would literally just list you everything that had happened in order you’d be able to see everything. And I remember when it changed and so many complaints coming through about I don’t hear from my friends anymore. I don’t know what my friends are posting. All I see is adverts for the for the latest incontinence pads. I don’t know whatever it is that you’re seeing.

These are all deliberate, engineered situations by the social media companies based on your data. Every single thing that you do is the more and the more data that you generate, I should say, feeds right back into the cycle. It’s a never ending loop. You scroll. The App learns what you hold, what holds your attention, and then it serves you more of that, and then you scroll more. This is something I’ve actually said to so many people. I made the mistake of interacting with a Flat Earth post one day, the post that was done that I was convinced it was parody. I was actually convinced they can’t be serious. The person who posted this, and I went in there, and I scrolled through the comments, and I realized that actually it wasn’t parody, that they were very serious.

And then I did the the carnal mistake is that I actually commented on it. And since that day, I have literally had almost every single day I’m getting 10, 20 Flat Earth posts, because the social media site knows that I am interested in that comment, whether I’m interested in it because I it actually interests me, or if I’m interested in it because, literally, I couldn’t face palm so hard, that’s still an interaction. So Facebook keeps giving me that data because they think that I want to see it.

So next time you’re actually scrolling through and you’re thinking that, Oh, wait a minute, this. This is pretty cool stuff. I gotta keep scrolling. I’m going to keep scrolling through and through and through that rinse and repeat and congratulations. You’re trapped into the dopamine Casino. Just consider that. The kicker is that even your non data is data, even if you don’t click on something that’s also logged. You’re not just telling the algorithm what you like. You’re teaching it what to avoid as well. So the next time your feed feels oddly accurate, it’s not magic, it’s maths, it’s statistics, and it’s a terrifyingly detailed profile of your habits, your interests, and probably your dog’s favorite chew toy. So have a think about that. Have a think about how much data you as a consumer are generating every single day. We’re talking about your receipts from when you go and shopping. We’re talking about whenever you you click on something on Spotify or Netflix, and we’re talking about that session of doom scrolling that you spend after dinner. And you’re just having a look to see what, what, what your friends are up to, and you end up actually finding out about the latest scientific theory on badges. So what I want you to do have a think about that, and maybe think about your boring data sets. Think about your receipts. Think about your your fun data sets, like your Spotify, or your or your or your gaming stats or Netflix or whatever, and then have a look at your social media feed. Do you go through it? Just have a look on it for 10 minutes and write down what you see. Just give me a little bit of an insight as to what you actually see, stick it in the comments on the YouTube video, and we’ll have a bit of a chat about the differences that what different people see.

And what I’m going to touch upon on the next the next podcast is actually why people see so many different things, and how that can actually affect you psychologically, and then what you can do about it. So compare your three data sets. What are the data sets say about you? Is it is it accurate, or is it hilariously wrong? Do you receipt say responsible adult, while your Tiktok suggests you’re a 14 year old into memes and slime videos?

I want to hear about it. Let me know about like, the ridiculous mismatches your eerily accurate ads, or even the moment your feed knew something about you before even you did. And then I’ll share the best ones on the on a future episode. So next time I said, we’ll talk about actually tidying up your data, and we’ll actually talk about how you can take control over the data that provides that you’re providing to these to these companies, should you wish to for the record.

And I do say this to absolutely anybody. I don’t care how much data Google has about me. I don’t care how much data Facebook has about me, because it is able to provide me things that I find useful. I know I’m probably not going to go and buy that blowtorch, but I might! It was useful for me. It was something that was relevant to something that I am particularly interested in at this point. And that’s why I’m more than happy for my data to be given. Because every now and then, something is provided for me through a doom scrolling session that actually is useful. Something will appear on my Android phone, on an on an advert which is related to the things that I have been searching on. I’ll be like, you know, that’s exactly what I’m looking for, Google. Thank you very much.

But not everybody likes that. So if you do want to take control about that, we’ll touch upon how to tidy up your data a little bit. And we’ll also actually talk about tidying up the data that you are actually gathering on a day to day basis. So things like tidying up your files and your computers, hiding up the data that that creates for receipts or your your browser bookmarks, or if you have like a finance app or a budget tracking app, how you can actually tidy that up a little bit.

The other thing that I’ll talk about on the next one is that companies actually have the same problem. I work with companies and people who work with data on a day to day basis, and you may not be surprised to know that that as efficient as that whole Clubcard thing sounds about all of that data that is gathered and then sold back to manufacturers you’re it’s not as simple as it looks, and actually tidying up data is something that companies will pay people a lot of money to do.

So it’s a bit of a scarier skill, because this is a much bigger scale, but it’s actually not actually that different. So that’s what we’re going to do. But this has been episode two. So this is data in your daily like life, if it’s provided for you, then go and blame the algorithm because you’ve interacted with something else that has set that has decided that I should be long in your feed. So Go and shout at them, not me. Otherwise, on the other hand, please feel free to comment and interact and let us know what you’re thinking, and I will speak to you in a couple of weeks about tidying up your data. This is Duke, signing off.