Podcast S1. Episode 4: What do social media metrics tell us?

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What do social media metrics tell us?

With measurement being defined by the platforms that sell us the real estate, it is becoming increasingly difficult to find commonality within metrics. Naming conventions are being misrepresented with newer formats replacing old. And so the big question becomes, do marketers truly understand the metrics they are performing against? 

In this episode, Dr. James Piecowye and Paul Kelly take a step back and explore what we actually can learn from social media metrics.

LISTEN HERE:

TRANSCRIPT

Dr. James Piecowye: Welcome to know your audience, a marketing minicast that explores how knowing an audience can unlock greater insight. In this episode, we take a step back and explore what we actually can learn from social media metrics. And what are the pitfalls to be aware of?

We’ve been talking about audiences, we’ve been talking about old school ways of thinking about those audiences. We’ve touched on social media and its role in giving us more data points to think about our audiences. Can you take us back a little bit, and give us that primer on how we need to start thinking about measurement from social media so that we can actually start making sense of what it is we’re learning from that data, and how it helps us, doesn’t necessarily nullify what we’ve already got from our old school thinking. 

Paul: First of all, I think it’s particularly over the last five to six years, there are industry-standard definitions and things like that. And it’s gotten a lot better, you know, from that earlier time, there’s still, I think, a fundamental problem, that measurement is defined by the platforms that create the tools that you buy the stuff from. I’m not suggesting that there is any form of like fraud or anything like that. But regularly, regularly, the two biggest platforms being Google and Facebook, face actions and have to refund customers because of misreported metrics, particularly around video views in advertising campaigns, and that gets into the many, many, many millions of dollars in terms of the waste. Then you have{questions}, ‘did someone actually see that ad’? ‘That played, yeah, sure, but was the browser open while I went to get a cup of water?’ Or ‘Was I getting a phone call as I was scrolling?’ And ‘Did the ad play, ok sure, and  it reaches somebody, but did someone actually see it?’ And I think, you know, that’s, that’s the important stuff to think about with all of this. And when it gets back to those basic definitions, I mean, it’s talking about impressions, or how many times somebody might see an ad or a piece of content, the reach that that then generates, and how much of a unique audience saw that versus repetition, repeated audience. Engagement, which is on something like Instagram would be a like or comment messaging, or on other platforms, you know, like Twitter, it’s engaging with that content with like, are we retweet or are those types of things. And those numbers form the nucleolus of everything to do with social media, whether it’s particularly in the organic space, you get a whole extra layer when you pay for that reach. So you know, your time viewed and all that sort of stuff comes into play, which it does, you know, anyway, on YouTube as a creator, but as a third party, trying to observe trends and information and things like that. You use those basic core metrics, you know, but what about the depth? And this is the challenge, I think, to me, the most important part of any piece of content or an ad or anything is whether anyone paid attention to it. And I think it’s the most valuable way we have of measuring anything, but there are no clear metrics on what attention is. 

James: Is this the piece that; ‘have I paid attention to that piece of content?’ And again, I’m thinking about old school here. I’m thinking about the advertisement that’s up, in our case, we’re in Dubai, on Sheikh Zayed Road. I know, my reach. I’ve got a sense of engagement, maybe, but whether anyone paid attention to it? I don’t know. And I wonder, in a sense, do marketers really want to know? 

Paul: Well, that’s a great question. I think probably not to an extent because, I mean, if you went to a marketer at the end of the financial year, and the results are in and sales were up, it’s like, what part of the mix worked? I don’t know. No, I don’t, know.

And, you know, I know something’s working. But don’t ask me what. 

And I think that’s a necessary part of the mix. But we can be smarter about how that’s deployed. Because there’s a significant amount, particularly in the digital space, a significant amount of waste comes through of ads not seen ads engaged with wrong audiences, particularly looking at the engagement, it could be completely off from your target. What happened? Where did that miss, and that doesn’t need more granularity, it just needs smarter intelligence about what it is and the problem that I think a lot of us have, you know, and there’s a lot of other ways to measure things; You can, you know, direct response surveys and things like that offers sometimes, you know, you can measure all, but really, whether a successful campaign was successful or not, is usually measured in sales sometime after the event or otherwise via survey. And there are some inherent problems with surveys and things that I know we’re going to touch on later. But we do have this other way of thinking about everything where we can measure an impact of a campaign by you know, or a brand or how they tried to affect certain behavior by watching people and how they behave in their own environment.

That’s what social media has afforded us to is a great way of observing at scale

James: This is new like this is relatively new, this ability to observe those people and how they’re interacting with the reach and engagement, we now have another layer of data we can put on top of that’s afforded to us through social media. 

Paul: Yeah, and I think this is what is most interesting about the use of social media from a marketing perspective, and you’ve got the reach side of things, but you’ve also got an observational side of things. And that that’s really important. Because you know, as humans, ourselves, we have a lot of inbuilt biases that just control the way that we think and talk. And we love to think that we’re not biased. But we are, this conversation will have biases in it. And everything does. And one of the greatest ways that I can explain that is just simply by the use of Google, when you Google something, you’re predetermining the results of what you’re going to be getting, even when you’re asking a question, because you frame that question with a specific sentence or keywords in mind, to get those results back to you that score against that. So it’s just constantly reinforcing what it is. So you might be looking for like; how do batteries work, for example, and that might give you an example of those batteries, and how it works and everything like that. But actually, what you might be more interested in is how direct current works, you know, or something like that. And that line of inquiry you’ll get, you’ll get there eventually, but you’re not necessarily getting the results that you’re asking for, because you’re putting in the words, to begin with. And so it’s giving back that thing, and this is what we get. This is like a, I guess, confirmation of a little bit of confirmation bias and action. But it’s also not necessarily – social media is great at reinforcing our own beliefs already without introducing us necessarily to something new. So we’ve created this thing called ambient feedback at D/A and then what that is, it is something that we where we can observe people behaving at scale without necessarily introducing anything like keywords, or specifically targeting groups of people or anything like that just watching mass behavior at scale across different social media platforms. And what that does is it enables us to then look at how people are responding to things without necessarily saying, you know, how are people eating cereal? It might be necessary to look at a time of day, and what goes on during that time of day, and then coming back down from there. And what that is, is without introducing a set of keywords or a set of predefined responses that we’re looking for, we get a better answer to what we’re seeking. And it all comes down to how people behave in their everyday life.

James: So it’s unconscious behavior. 

Paul: Yeah, which is like based on you know, the system one system two thinking Daniel Kahneman, Nobel laureate, well-defined principle now that 95% of our day in our being is guided by our subconscious, it’s learned behavior, or its behavior, it’s survival behavior, or it’s all those sorts of things are breathing is a great example of that. The minute you start to think about breathing, it becomes difficult and then all of a sudden, you come back – and just challenge anyone who’s listening to this right now just to think, to concentrate on their breathing. And that’s obviously why it’s such an effective technique, for instance, for calming people down and things like that; relieving stress and all that sort of thing, because when you become conscious of that, and you’re creating a control mechanism, and that 95%, that can be anything from putting a seatbelt on, for instance, that’s an example of learned behavior, and not necessarily an unconscious behavior, and that falls into the 95%. And then the 5% is when we’re really conscious, and where we have to think. So a math problem is a great example of that, or any kind of issue where we’re faced with having to make a decision that’s in that 5%, but literally, 5% of our day, is to do with that sort of thing. Even when we’re at work, there’s a sort of a level of autopilot going on. And when people do audience, for instance, surveys, and what I’m talking about here is research surveys and things like that, it is only natural that we as humans will try and give the answer even – this is a sort of subconscious thing – even if you’re trying not to give the answer that you think the person might want to give, might want to hear from you. Do you still give that answer? And so if I ask you, are you environmentally conscious? Are you worried about the environment or something like that you’re that person {response} ‘very worried’. ’Recycle everyday’ and everything and then, you know, you go into, you might observe their behavior, and actually, that person is driving 10 meters to the shop, are they buying, you know, 65 bottles of plastic, you know, every day and not recycling, wasting, you know, littering the beaches and all those sorts of things. 

It gives us room to say what we think and its part of social desirability bias where we want people to think of us what’s society will want us to do, you know, so the environmental one is the best example of that. And by asking people surveys and not necessarily observing how they behave, we don’t, when we do this research, we’re getting this kind of obfuscated kind of answers that are like, they’re hazy, it’s a bit, you know, it’s a bit like looking through a steamed up sort of window, because you get some real answers. But also, you get some answers that are not necessarily that real. And that’s why you know when you can observe people in there, 95%, then you’re better able to sort of draw a picture of what behavior patterns might be an interest in a product, or whether a brand campaign made an impact, you know, by changing behavior is a great one, you know, getting someone to switch from processed food to organic food, for example, or that type of thing, like, you can start to see that pattern of behavior through intelligent observation. 

James: So essentially, you start to see a scenario where your data collection becomes more relevant to understanding your audience from what we’ve had in the past, which is very singular in nature and very broad. 

Paul: Yeah, and it brings another dimension to numbers. So you’re better able to form an audience, you better able to understand that audience at a much, much bigger scale than the representative samples that were used to have, like, nationally significant representative sample of 800 people like, is it? –  and who defined, you know, I know statistics to find that and, you know, I’ll probably be lynched on my way out of here by research firms and things like that. But and there is a definite place for that. But if you don’t ask someone, and a great example could be instead of me asking you, are you aware? Or are you worried about the environment? And is your behavior this? What do you think your neighbors do? For instance, when people remove themselves from that situation, and they observe other people, we tend to think the worst of other people. And so the real reflective behavior of ourselves comes through in our answers. So our answer might be well, I don’t really like, you know, that they drive into the shops or, you know, you might not even know that, but you’ll say that about other people when it’s actually your own behavior. And that, but, you know, you can’t come into somebody and ask them that question, either. And so what you need to do is start to build this array of information, these different data points without necessarily saying; ‘how do people like going back to the cereal’ example how are people eating cereal? maybe nobody talks about, what the cereal is, but, what happens around them? What’s the context of that moment in someone’s day, that’s going to help them make a decision to buy your cereal by the brand of eggs, or, you know, whatever it is, we’re talking about breakfast. And that’s where it becomes really, I think, a unique opportunity is to understand an audience without actually intervening in in their day, and asking them questions that, you know, we might get some great answers to, but on the whole, you know, you should never really ask a consumer about what they prefer, because it’s always never going to be what’s the truth? And that’s because, like, for all the reasons I’ve mentioned, it’s just better to observe than ask. 

James: The takeaway from this episode is that social media does have its pitfalls when it comes to understanding content and measurement. But it also offers us as marketers and researchers, an unprecedented opportunity to understand consumer sentiment without intervening in the data collection, thus enabling more authentic analysis with less researcher-generated bias. 

You can get in touch with me across the socials @jamescast or [email protected] thejamescast.com 

Paul: And get in touch with me both through d-a.co or otherwise, email me at [email protected]

Thanks for listening.