Data v’s insights. How audience intelligence drives marketing efficiency.
Welcome to the first episode in the second series of ‘Know your audience’ mini-cast.
Paul and James re-introduce the concept of audience-first marketing, and how data can be used for a better understanding of audiences. They also talk about how understanding an audience, whether a large FMCG or just a smaller startup, means you need multiple data points. Discussions dive into the difference between data and insight, where the two diverge, and how even James confuses them from time to time.
Dr James Piecowye: Hi, my name is James Piecowye
Paul Kelly: I’m Paul Kelly
James: And welcome back to ‘Know your audience’ – a new season.
Paul: Yeah, fresh episodes hot out of the oven. Yes, we’d like to say (maybe) that’s where we do podcasts?
James: That’s exactly where we do in these micro mini podcasts. It’s all about really getting to practically no practical, (Paul: insights), insights. There we go!
Paul: Yeah, for marketers, and I guess people who are dealing with business growth, or needing to know what people are doing out in the real world at scale. And that’s what audience-first is about. That’s what we talked about at length in series one, drop back and listen to it if you haven’t yet.
And in this series, if we’re going to call it that, all these fresh episodes, what we’re going to start to do I think, is really go a little bit deeper into what numbers are, what data is, and how you can understand audiences, and particularly, I guess, through a marketing lens, and how we can really start to build traction.
James: I like that word. Traction. I like traction, how to build traction.
Paul: Yeah, and get make things more effective. Whether you’re a small brand, maybe a coffee shop, or a shawarma shop. Shawarma yeah, even better, I’d love shawarma right now. And what we could do; and or you’re the biggest brand in the world…..
James: You’re selling shoes, you’re selling cars, you’re selling or whatever. Electric boats!
Paul: Everybody has to sell or market to an audience. And what this is about is doing that more efficiently, more effectively, or perhaps even coming up with products that better suit your audience. And that’s what audience-first is about. That’s what we talked about at length previously.
James: So let’s, let’s, let’s pause, pause, stop, stop, (Paul; collaborate), because you are listening. And I’m saying to you, the person who has us in their ears, the speakers or other speakers are in their car or playing in their shop or bedside listening on the big screen.
You did allude to season one (Paul: I did) on this podcast, and I’m going to put you on the spot (Paul: that’s come previously), it has come previously. And you can go back and listen to them all because they are there. And they quick, quick, easy, simple to get into.
Paul: Your commute to work would be made infinitely better by listening to them.
James: Somebody right now is saying, Oh, I haven’t listened to those, but I’m listening to this now; And I will go back and listen. But Paul, can you tell me what that first season was all about? Can you put it into a nutshell? That’s what they’re saying? And I’m thinking, that would be really interesting to hear.
Paul: Yeah, look. So the first series was all about looking at audience-first as a concept and how the actual notion of looking towards the people who are consuming your product, service, (insert, whatever here) can be reached more efficiently and effectively.
And then, how you can use the insights from those people themselves to make things either, (like I said) marketing more efficient, or your product better, or new products tailored to your audience a lot better. We looked across the whole range of what that actually could mean.
James: Doesn’t all marketing suggest its audience-first?
Paul: Correct. Yeah, I think the difference, I guess, with this concept is really borrowing strongly from the ‘creator economy’ where there’s creators out in the world today who have amassed audiences, in the hundreds of millions.
James: Creators, like the people who are micro influencers, people who are doing YouTube videos, people who are doing stuff on tick tock, or Insta?
Paul: Yeah, people who are making content that people love that formed a community. I mean, most people, if not all people, probably, YouTube is a great thing, because it’s more accessible, I guess, platform for everybody. There’s creators on there that everybody knows everybody deals with on a daily basis, or watches, maybe not daily, but occasionally even
James: No, no; everyone is sitting in their office cubicle, they’re sitting in a car, they’re on the metro, that everyone’s looking at tick tock, they won’t admit it. You’re looking at it. They’re looking at their YouTube videos, they’re looking at the Insta Stories.
Paul: And people create that content, no matter what that content is, it’s been created and people love that content. They then become an audience of that content. I guess in the way traditional media, you know that radio stations or TV stations and things like that before have been strong in that.
That’s certainly democratized. Now, what we looked at before and what audience first is, is about looking at that, that audience what they love about that, what that person’s creating, and you get much richer insights. Because it’s digital at social, we’re able to sort of see the commonalities between those audiences.
James: And that’s where the algorithms and things that you’re using with Sila give them, give you, the data that leads to the insights.
Paul: Yeah, yeah, exactly. And I think what we touched on in the first series as well, lucky or smart, whichever one you want to choose, at DA, but we’ve got Sila, which is our AI enabled consumer intelligence platform.
But you don’t necessarily and that’s what we talked about in series one, is that you can do this, some of this stuff yourself, you don’t need to get out the advanced tools. Okay, you know, it’s great that we’ve got it and it gives us (I guess), an edge in being able to say this stuff.
James: Edge is the key right today? With whatever we’re selling with whatever we’re trying to get people’s attention with. Yeah, sure, I can go and I can look at how many people are looking at something or how many hits they have, or how many likes they have. And I can go and I can look, read through the comments. But D/A has got a tool that is going to enrich that data that I’m looking at and help me to actually make sense of it. And a little bit more economical (when I say economic economical with my time) economical with your time, and a little bit more economical way.
Paul: Yeah, yeah, exactly. And time is everything right. And I think, you know, when you start to sort of go up the marketing chain a lot, I guess a lot at the bottom of it is about experimentation. But then as you go up, I guess, you know, there needs to be stronger targeting. And you need to be able to speak the same language as your audience, whether that’s a physical language, so being English or Arabic, or it’s just the same sort of slang and things like that.
James: That’s actually an important point you just brought up, is that one of the key things that you’re dealing with in we’re dealing with here, and we talk audience first, is we’re talking while this is a global phenomenon, and these ideas are applicable, globally. Really, we’re also zooming in on the Middle East in this part of the world, this region. So we’ve got language that we’re dealing with in Arabic, is the language.
Paul: Yeah. And even then it’s not homogenous, right.
James: Exactly. Big problems. Different dialects and what people say
Paul: Yeah, and things mean different things to different people. And it’s, I guess, a similar situation, a lot of people who, perhaps native English speakers, you’re from Canada, I’m from Australia, we can say similar things, but they mean completely different things. And it usually comes down to slang. But in this circumstance, we have different dialects and all that sort of thing. That’s something we’re going to touch on in this series is really to delve deep into why getting a deeper audience understanding is really key to giving you an edge across competitors, but also making your dollar go further or you’re doing more your Riyal or whatever that currency is making it go further. That’s the whole point of this right is to is to push up margins, and things like that, especially in a really competitive environment, you don’t want to have to constantly be expanding marketing spend on media spends and that type of thing.
James: So here’s the thing, I like to think that I’m fairly intelligent, you know, I’ve got an advanced degree or two under my belt, I do a lot of reading, I’ve read your white papers, I’ve read other white papers. There’s still terminology that when I read it, I know what the words mean, I get the idea. But when I start applying it in an audience first scenario, sometimes the question that I have is, okay, well, what exactly are we talking about in terms of what’s within this term? So data is one of them. And when I’m looking at what we’re talking about, with, with surveilling, listening, watching, interpreting audience impressions of things, what does data mean, in that context?
Paul: Wind back, I guess. There’s a huge difference. And it’s something that, you know, you shouldn’t ever conflate data with insight. Oh, I see. I always do that. So because data is just a set of facts, you know, whether that’s how many kilometers or miles or depending on the lexicon, how far you’ve driven in a day or something like that through to how many, you know, eyeballs have seen a particular piece of content, they’re just data points, you know, it’s just numbers. It’s just information. It’s Yeah, exactly. And the difference between that, and getting insight from that is when it’s really the analysis part, you know, so data can actually mean anything. It’s just any pages piece of information that can help you make a decision, I guess. That data, those data sources can, you know, in our context rely on the digital world, so social media, the web, etc. in anybody’s listening, well, that could also be sales information, it could be footfall, it could be customer loyalty, all those sorts of things. When you put them all together, that’s when some magic happens. And you’re able to develop an insight into how people are behaving or how they’re responding to a product or how people perceive your business and that type of thing. And how we look at it, in our sense, is that data can provide us with a rich basis for analysis and, you know, Sila is AI-focused; uses natural language processing and a number of different AI models to make. (James; all simultaneously?) Yeah, yeah, yeah. And what that does and you know, people out there, there’s so much ……
James: We hear the word AI and instantly, Will Smith comes to mind.
Paul: Yeah, and it’s not and it’s just, it’s just completely, you know, it’s all BS, without turning this into an adult-only podcast, or mini cast? The idea is that AI helps us sort through information. (James: So it’s a sorting tool?), yeah, it processes information it learns, and at its depth, it can learn from itself, learn to collect information the single human could never do.
So you’re sitting at a computer, like imagine, everybody’s had nightmare experiences with Excel, and giant sheets with, you know, instead of 1000s of rows it will go into millions, you just wouldn’t physically be able to go through all that information to get it, you know, to analyze it, you know, there’s just no possible way there isn’t a possible way. It just would take you years, right. That’s what the machines do. That’s what AI’s primary function is.
James: So it groups the stuff, it doesn’t tell you about processes, it puts it together so that you can (Paul: get an output) And you can make inferences.
Paul: If you apply that same thinking to a Tesla, for example, it’s the same thing it’s looking at, for instance, the surroundings, processing all of that information, and then giving you a recommendation. Or maybe it’s on a recommendation, the information processed. So these cars are around you park like this. This is the speed limit. This is the lane, you know, even less advanced cars. Newer cars now have Lane Keeping technology and things like that. That’s all to an extent AI in the sense that it’s processing information, giving it to you learning from your behavior, and making things better. And practically, that goes from fridges now to everything, yeah, anything that’s robotic, I guess, as we might call. And I think a lot of the time AI is used by a lot of people to confuse and to, you know, be a trending topic and all that sort of thing. And I think it’s just really boiling and simplifying it down. It’s a tool that enables us to understand large and vast amounts of information more simply, quickly, almost instantaneously. And without much intervention.
James: But it doesn’t negate the need to be able to do that interpretation. It doesn’t know exactly, you have to have someone like yourself or marketing teams, or who can then look at all of this data that has been grouped and organized to say…..
Paul: Apply it to a situation. Yeah, and that’s where, you know, the human part becomes really important. It’s forgotten. People talk about AI taking people’s jobs, what it’s doing is taking away, I guess, the less, the more mundane, I guess, processing, data entry processing, all that sort of stuff, which, you know, just changes the job of the future, it doesn’t necessarily change.
James; It’s giving you more time to do the job. You’re not doing the grunt work, you are literally able to look at that data and, and ask better questions. I think that becomes key and we talked about in the last podcast.
Paul: Yeah, audience, first of all, that sort of thing is just about asking questions about your challenges and getting to the bottom of it. And AI is, is the thing that helps us with that, in our context, with Sila, what it is, is a bunch of models that basically can process language and images, at a huge amount of scale, to give us a set of information that we can then help people make decisions, better decisions about their marketing efforts, their outreach, their creative, their advertising placements, their media, all that type of thing.
James: I think one of the things that you just mentioned, when you talked about Sila, it takes a look at all the outputs that people are doing, for instance, it might go through an influencers’ Instagram, but it’s not just looking at the words, it’s looking at the images. And to me, that becomes the gold of using these AI tools. Because me as that one person who’s going to go through one person’s account, and I’m going to read the comments, I’m gonna look at things, I’m going to look at a picture, then I’m gonna look at another picture. I’m not necessarily going to be able to group the likeness of them and think about okay, well, what’s in that picture? What’s the context of that? Yeah, what’s the location of that picture?
Paul: And the key, with what you said there is context. And people, I guess users, mostly are rightfully upset, (not upset, that’s the wrong way to)…. apprehensive, I guess, about what they share, and the data, and stuff like that. But the truth is that you sign up to any platform, you’ve given away public information. Yeah, it’s public information effectively, you know, within reason, obviously, there are privacy settings that you can apply. But your experience gets altered on that particular platform, whatever it is, they’re all the same. And so I think from that perspective, then we really need to think about, what’s important to the context of what people are doing. So if you just use language, for example, if you just look at using, for instance, we’re talking this through marketing or social media or that type of analysis, that type of consumer intelligence, if you’re just using words, you miss a lot of contexts and, and that’s, that’s a limitation of social listening tools and things like that is that it’s usually keyword-based, which we, I think we touched on in the previous series with biases, particularly. And using keywords to search for things, becomes difficult. So if you have an extra layer of information that provides context to those words and can understand, you know, things like sarcasm, and things like emotion and content, dialect, yeah, and then you get understanding. Yeah. And if you don’t have access to that information or that kind of tool, it’s about knowing that that’s the limitation. And using that, sort of, you know, as I said, something like social listening, as a, one of the tools in your arsenal, you know, it’s not the tool, it can never be the tool, but it will help you. For instance, with trending information or trending topics, that type of thing. That’s where it really comes to the fore, but not necessarily, for really understanding consumers.
James: That’s what we talked about in the previous set of podcasts. If you haven’t heard them, give them a listen. They’re bite-sized, they’re enjoyable, they’re funny, they’re informative, they’re entertaining, and they’re educational. And they lead into where we are right, I know that they are everything to everyone.
That leads nicely into where we’re going in this set of podcasts that carry on because we want to deep dive a little bit more into where we’re going to go next; messaging and how we need to think about the messaging that we are creating across our platforms, how we can use data that we’ve gotten from what people are saying, to influence our new sets of messages that we are delivering to thus also influence audience knowledge for the better.
Paul: Yep, that’s where we’re going. And who also takes him the listeners also through, you know, the things that we’ve touched on is so really sort of demystifying some data science points as well. We’ll have a couple of guests on, through the series. And we’ll also talk through, I think, in more specific detail about, you know, concepts like dialect, and I have some Arabic speakers in the podcast to really sort of shine a light on how that type of stuff can really impact the type of information you’re getting.
James: I’m James Pickaway.
Paul: I’m Paul Kelly
James: And this is ‘Know your audience’.