Video Transcript
Dyani Marvel:
I am very happy to be here with you to have this opportunity to share some of the subject matter from the strategic creativity course that I developed. And I teach in the IMC Professional Program. So I really hope that you enjoy the time that we have together. So let me start by briefly telling you a little bit about me and my background.
I am a passionate marketer. I love marketing over the 20 plus years I’ve been in marketing. I have had the pleasure and the good fortune, and having worked in a variety of industries, with organizations of all sizes on a multitude of brands. You’ll see them scrolling at the bottom and in a wide range of marketing functions. And also, if you you’ll see on the right side here these images. I am also a northwestern double alum. I got my undergraduate degree from the middle school of journalism, and I also got my master’s degree in the integrated marketing Communications program. So I am a big fan, and so happy to be here today.
So let’s talk about data. Most of the data we use as marketers is used to understand and analyze the business industry, customers, initiatives, and more. We use it as information to help guide and inform decision making. We use it as information that can help improve customer experience and return on investment. It’s used to segment customers, optimize campaigns. We use it to build personalized experiences, evaluate efforts, and so much more.
But I’m here to talk about how data can. And I would argue that it should be used as inspiration as well as a source and a stimulus to spark great creative ideas, whether that is creative ideas on how to build a marketing strategy, pricing a campaign or a piece of creative. We need creative ideas for many different components of marketing because we’re talking about inspiration. I want to start with examining the definition of inspiration. This is one of those terms that can be difficult to describe, and one where there are a variety of perspectives. But here’s one definition that I feel rings true to the type of inspiration we encounter in marketing.
Inspiration is a motivation from an external source that causes a person to have an idea, or to produce something creatively. And here, highlighted in bold at the pieces that I feel are really critical. Motivation. External source causes and idea. And what we can do is we can use data as that external source. So I’m going to talk about how we can all allow data to be the motivation source that compels and causes great creative ideas.
But before we do, let’s first start with making some distinctions in nomenclature. In terminology related to how we use the word data. The terms here, data-driven, data-informed, data-inspired are similar, may even seem interchangeable, but there are distinct differences that we can make between them. And when we do that, and we truly understand how they’re different, we can drive the power, the power, and the effectiveness of each.
So I took these terms: data driven, that informed that inspired, and I plug them into Google. Trends, looking at the last 5 years of search data. And if you’re not familiar with Google Trends, it is a tool you can use that represents search interest relative to that period of time. So numbers or points that are at the top represent the highest search interests. Those at the bottom are the lowest or not enough information to register.
So I did this to gut check and validate my own hypothesis on the popularity of the terms, and I’m almost certain that most of us here can guess which color represents which term, because there really were no surprises. As we can see, data-driven is the most widely used term. It’s often used as an all encompassing term to describe data being used to make any decision so when that is involved. We usually talk about being data-driven. I know I personally have used the term very broadly and very generally
Data-driven is followed in popularity by data-informed, and last, we have data-inspired. But again, we can distinguish the terms. And let’s talk about how we’re going to start with distinguishing between the two most popular references. First, data-driven and data-informed.
A data-driven approach can be described as one where the data makes the decision for you. There’s a focus on statistical analysis, data truly and singularly drives the decision in comparison. A data-informed approach is one where you don’t. Just do what the data says, but instead, you apply a layer of interpretation before you make a decision. Data informs you. But it’s not the only driver. When you take a data-driven approach, you are relying on quantitative data an example of a data-driven decision might be the decision on which email headline and move forward with based on the results of an A/B test. So if you’re doing that within any platform the decision is made. The remainder of the emails are sent out. Other uses may be personalization. If you have personalization on your website optimization. If it’s done automatically. If you have programmatic buying or dynamic creative data-informed approach can leverage both quantitative and qualitative, data a data informed decision might be where you need to determine a next product iteration. You analyze product testing results plus you take into account other information before making a decision like, what is your budget, or what is the competitive offering? Other examples of data, Informed decisions are making decisions on creative campaigns and executions, product launches product, pricing, budgeting, etc. And, in fact, I personally believe that we are actually being more data informed most of the time than actually being data driven.
Now a data-driven approach leverages data. Only a data-informed approach takes the data into consideration, but a human makes the decision. So it is both the data and the human involved. In this approach a data, a data-inspired approach is completely different. A data-inspired approach brings together different. Sometimes they may be disparate types and sources of information to make connections, to tell a story. And we’ve levers the data to inspire ideas. All data types could be utilized and a data inspired approach can be used when we are problem solving during ideation. When we’re working on creative concepts. If we’re exploring innovation, and so much more.
With this approach data is used. It’s there, it’s used, but it’s used to spark, and it’s used there for inspiration for the ideas. But the story comes from the human, comes from us. And looking at all three, we have clear distinctions. So let’s look at them through the lens of the type of decision you may be trying to make, or what you’re trying to accomplish.
If you’re looking to make a decision between options, be data-driven. If you’re looking to make a decision, but it’s a little bit more complex, it may need additional inputs. Additional interpretation to be that informed. But if you are looking to find inspiration for ideas. This includes creating solutions for business problems. Then you can be data-inspired. So let’s now dig a little deeper into being data-inspired. A key to that inspiration is the bringing together of the many different data sources to aid in the process of stimulating ideas. There may be some transactional data you pull in, social media reviews, customer profiles that you review. Then you may layer in information from Google Trends. I love Google Trends like we did earlier in the presentation. The goal here is to collect data from a multitude of sources and uncover and determine relationships and themes shared amongst them that help to tell the story that can spark the creative ideas.
We can think of data in rings. The data closest to the center is that data that is directly related to the problem or challenge that you have on-hand. This is our starting point, and this could be anything we might analyze and summarize this data, get a good understanding of what you’re trying to solve for, or what question that you may have. Then we expand outward to add in more data to the initial information we are absorbing.
Our next ring may be product or customer data. Then we might expand out further to look at our industry in whole. We may look at trends and competition. We may look at adjacent or complementary products. Here we may expand even further and explore general human truths, trends pop culture, and add all of these things to our repository. And then we take all of this, all of this data, and we work to find the story. Now, so the flow from initial data to final inspiration may look a little bit like this. So it’s very simplified, but it may look like this. So you start with the initial data that you’re given. You analyze it. You summarize it in examining the data. Maybe you find something interesting, something you didn’t expect. It’s an outlier. It’s like, Why is this happening? You ask questions about it.
So you begin to explore the data. You look a little bit deeper. You try to understand, “Hey? Why might this be happening? What are some other pieces to the puzzle?” Then you begin to search for, and you add additional data sources. You review this information. You absorb this information. Maybe some connections are starting to form here.
But maybe you want your … maybe you’re an overachiever, maybe you’re a hard worker, and you want to add even more data. So you search for, you add more data to your sources. You review. You absorb that information. Now. Finally, some things are starting to come together. You’re starting to make connections. You’re starting to uncover things, and you’re starting to develop a story.
And then inspiration strikes. And you get this amazing data-inspired idea. That’s very simplified, of course. So bringing together multiple information sources is the critical component for that inspiration. So you may wonder how many data sources do I need? Right? Well, there is no set number of data sources required to uncover the relationships and find the story. It really is going to vary. So inspiration can come from 10 sources in person can come from just two sources. Every situation will be different. So don’t try to lock yourself into a number. The same is true for time, so you may wonder how much time is inspiration going to take. Well inspiration, you know we can take it. It we can’t tell, but like a number of sources, each situation will vary. There’s no set time. And when we are working to motivate something like inspiration, sometimes we really do need to be patient and let the process run its course.
There’s a little bit of some tips later on the presentation that kind of hit on this. So here’s another kind of quick and very simplified example of how we pull data in for inspiration. In this example we have a new product that is launched, and sales have gone into the market, but they have a leveled off, and it hasn’t had the trajectory we want. Unfortunately, many of us may have been in this position before, so we need a decision on how we’re going to increase sales specifically as a marketer, how’s marketing going to help to do that? So the question is, what kinds of data might we pull in to be use this inspiration in a situation. So I’m actually dealing with a situation very similar to this in my job right now. But we have some products not exactly where we want, and we are actually in the process now of pulling together all of the data to try to make this story. So some examples of some data we may pull in for this might be transactional data. Okay, let’s look at the transactions and see what’s happening. Maybe product reviews — our customer saying something about a product that we are not aware of.
Let’s scrub through social media. It’s a great place to get the voice of the customer. That’s just raw and unfiltered. Right? You may look at Google Trends. Is it something happening there with customer search searches? Are they searching for something else. It’s not as popular as their seasonality here, and we pull all of those pieces together to try to uncover the connections that can get us to some insights that can help spark creative ideas. Now I realize some of you may be saying, “Well, I already do this.” You know, and if you are fantastic. So what you’re doing is you’re practicing data inspiration, and you should continue to do so.
So now let’s get a little more specific with an exciting real-world example that I am so excited to share. So in this example, which is for Burger King in the years 2019 data served as an inspiration for an idea. It was also a major driver in the creative and in the execution. So first, I want to say that there are. There’s some information here that I know. They use this some that I am making some assumptions here with it’s all caveat-ed with that. But here’s some data that I would assume was taken into consideration, as that idea was being developed. So if we take a look at the top half this information is information that you would typically find within your organization.
We have category data. This category data tells us Burger King is a challenger brand, and that it trails KFC and McDonald’s in global market penetration shares and sales. We have geographic market data. This tells us that Latin America, particularly Mexico, has been a battleground, and Burger King has a major presence, 1.6 versus 29.7, and we have product data, which demonstrates that whopper. The Whopper is Burger King’s and number one product with over 2 billion. So in 2019.
Now, if we look at the bottom data, this is where that disparate data comes into play, right? Not necessarily our product, but it is part of the data repository we have that can help tell a story. So we have some local geographic data here and trends. This is from Tom Tom’s traffic report, and we learn that Mexico City, the largest city in Mexico, has some of the worst traffic in the world. In 2017 it earned the distinguished title of being the most congested city in the world.
The report also noted that drivers in Mexico spent an average of 66% of their time in traffic, a lot of time. Then we have a human truth that we all might agree with: People get hungry while they’re in traffic, especially if you spend as much time in traffic as they do in Mexico City. So now we can take all of this information and data, the insights, and this resulted in an inspiration for the Traffic Jam Whopper campaign. What Burger King did was they used real time data to locate customers stuck in traffic and deliver a Whopper.
So as noted earlier, data was not just the inspiration for the idea. It was also heavily integrated into the execution. But I will say that data-driven creativity does not mean that it has to be in your execution. But they did it in this one, and I think it was really cool. So Google Maps APIs were used to identify traffic jams, locate people in traffic, push notifications to the Burger King App were sent to people in traffic that were near Burger King, and there was personalized messaging on digital billboards that were located along the busy roads close to a Burger King restaurant. And this campaign was an amazing success for Burger King. They saw a 63% increase in deliveries. 44% increase in app downloads and Burger King again. This is a challenger brand became the number one fast food app in Mexico City.
So not only a creative idea, but an impactful one as well. And if you’d like to learn a little bit more about this campaign, I’m going to leave this up for a second. You can scan this with your phone, and this will take you to a video summary of the traffic jam, Walker. And there are other iterations after this of other types of initiatives and campaigns where they use data. But truly, if you look at all of those different pieces that came together and out of it, it inspired an idea, and that is really the joy of this process.
So now let’s talk about some ways to help data serve as inspiration. So the key really is to look beyond the typical uses of data. A lot of the time we are looking at data to validate or we analyze data for standardized uses. We use templates and dashboards and reports, and when we do that we really can keep data in this very narrow view. So, in order for data to inspire, we have to be more intentional, we have to be willing to break out of the traditional ways of looking at data, and truly look at data differently. To look at data differently. We have to look at data, to tell a story. To answer a why. And this may mean that you may have to dig. It may not be on the surface. It may not be apparent, as first data can expose truth. It can expose those hidden gems. It can help us to see the bigger picture. We can use it to discover, trans challenge beliefs.
And we can use it to examine those interesting outliers that always seem to pop up. So it’s really about, “Hey, I’m gonna look at data into different ways,” not just to give you that information, but it’s to be able to do all of these different things. And even if you take these as a list when you look at data to say, hey, am I seeing any one of these things? I can just help to get your mind and spawn your mind in that area. Another critical step for data inspiration is to prepare, prepare to be inspired by data.
Now, the first few items here that I’m going to discuss are actually tips for how to prepare for inspiration in general. We’re just discussing it today in respect to data. So the first step and being inspired is to be intentional about your goal to be inspired now with data, since it’s not a traditional source of inspiration. It’s not a beautiful picture or a bird, or walk in the park that may come a little bit harder for us. So we have to be more intentional, and have that level of intention to be on higher****
also to increase the likelihood of inspiration from data occurring, you have to prepare your mind, making sure that you have an open mind in an open attitude that you’re willing to explore data in a different way than you normally and typically do that way. When inspiration does strike, you will be ready for it, but that the heart of this is really the need to look at that it differently. You are looking for the story, not just the information. I’ll say that again: We’re looking for the story, not just the information.
Now, one helpful practice to aid and inspiration is allowing for incubation. Now, during the course we actually talk about all of the processes and all the stages in the creative process. Incubation is one of the stages in the creative process, and the creative process is one which traditionally is used by creative types for idea generation. But we can also use the creative process to help us generate ideas for marketing problems. The incubation stage occurs. After information has been collected and absorbed at this point you should step away from the situation and internalize the information you let it just sit and simmer in your mind.
Even though you may not think you’re actively, maybe you may not be actively thinking about this, your subconscious will actually be working in making connections. To those who may not be familiar with this, this may sound ... It may sound like a waste of time, but it actually really works. And sometimes just step, just stepping away and sleeping on something for one night can allow those mental connections to be made. Incubation should hopefully lead to this next page, which is called illumination. And these are often referred to as light bulb moments. This is when an idea begins to emerge out of the subconscious work of incubation and into the conscious.
So an idea, or possibly multiple ideas may come to mind. It may even feel like a "eureka" moment to some people when this happens. So if you’ve ever had that, and all of a sudden you’re doing something unrelated, you’re making a sandwich, and you have a great idea about how to do something at work. That’s what’s happened. This has set in your mind, and it’s incubated, and then it’s come out. So this is one of the hardest pieces to do, because I think a lot of us like to get into rooms.
Do some brainstorming, solve on the spot. Get some ideas. But truly, allowing yourself that time to say, "hey, let’s just think about it for a night, and come back and let things kind of simmer can be extraordinarily helpful."
Now. I’ll close out, and I know we only have 30 minutes, but we’re efficient here with briefly sharing some of the benefits and the limitations of that inspiration. So I hope the presentation has proven that a data-inspired approach can be very beneficial, and being a catalyst for creative thinking and creative problem solving. And there are other benefits.
These benefits include the capacity to account for the larger picture. to account for culture, shifts, and other contacts and problem solving. It can reveal connections that you might not typically see, or that you haven’t seen before, and that can help in identifying new and unique insights. It can reveal trends that can be leveraged for business strategy.
And the data-inspired approach can encourage new ways of thinking about a business, thinking about a product or thinking about a problem. And of course there are also limitations. including the fact that it’s not an exact science and data is not traditionally used for inspiration, for creative ideas or ideation. So this may mean that it takes getting used to. There may be people in your organization, or maybe yourself. That was a little resistance to change as humans. We like consistency, so change is a little bit difficult. In addition, inspiration may not be automatic as we talked about that need to kind of sometimes let it sit sometimes for more information in, so there may be there may need to be some work to find meaningful insights there, or there may need to be time to just allow ideas to emerge.
And last, but not least, a damage of an approach is not appropriate for all situations, so we can’t just plug it in. We do have to be selective about. When does it make the most sense?
So in the effort. But I believe the effort in determining how data inspiration can work is so much worth the effort. Given all of the potential benefits. We have such an incredible wealth of growing and evolving data at our fingertips, and we have an unlimited number of ideas just waiting to be inspired by all of that great data. So be inspired.
I am very happy to be here with you to have this opportunity to share some of the subject matter from the strategic creativity course that I developed. And I teach in the IMC Professional Program. So I really hope that you enjoy the time that we have together. So let me start by briefly telling you a little bit about me and my background.
I am a passionate marketer. I love marketing over the 20 plus years I’ve been in marketing. I have had the pleasure and the good fortune, and having worked in a variety of industries, with organizations of all sizes on a multitude of brands. You’ll see them scrolling at the bottom and in a wide range of marketing functions. And also, if you you’ll see on the right side here these images. I am also a northwestern double alum. I got my undergraduate degree from the middle school of journalism, and I also got my master’s degree in the integrated marketing Communications program. So I am a big fan, and so happy to be here today.
So let’s talk about data. Most of the data we use as marketers is used to understand and analyze the business industry, customers, initiatives, and more. We use it as information to help guide and inform decision making. We use it as information that can help improve customer experience and return on investment. It’s used to segment customers, optimize campaigns. We use it to build personalized experiences, evaluate efforts, and so much more.
But I’m here to talk about how data can. And I would argue that it should be used as inspiration as well as a source and a stimulus to spark great creative ideas, whether that is creative ideas on how to build a marketing strategy, pricing a campaign or a piece of creative. We need creative ideas for many different components of marketing because we’re talking about inspiration. I want to start with examining the definition of inspiration. This is one of those terms that can be difficult to describe, and one where there are a variety of perspectives. But here’s one definition that I feel rings true to the type of inspiration we encounter in marketing.
Inspiration is a motivation from an external source that causes a person to have an idea, or to produce something creatively. And here, highlighted in bold at the pieces that I feel are really critical. Motivation. External source causes and idea. And what we can do is we can use data as that external source. So I’m going to talk about how we can all allow data to be the motivation source that compels and causes great creative ideas.
But before we do, let’s first start with making some distinctions in nomenclature. In terminology related to how we use the word data. The terms here, data-driven, data-informed, data-inspired are similar, may even seem interchangeable, but there are distinct differences that we can make between them. And when we do that, and we truly understand how they’re different, we can drive the power, the power, and the effectiveness of each.
So I took these terms: data driven, that informed that inspired, and I plug them into Google. Trends, looking at the last 5 years of search data. And if you’re not familiar with Google Trends, it is a tool you can use that represents search interest relative to that period of time. So numbers or points that are at the top represent the highest search interests. Those at the bottom are the lowest or not enough information to register.
So I did this to gut check and validate my own hypothesis on the popularity of the terms, and I’m almost certain that most of us here can guess which color represents which term, because there really were no surprises. As we can see, data-driven is the most widely used term. It’s often used as an all encompassing term to describe data being used to make any decision so when that is involved. We usually talk about being data-driven. I know I personally have used the term very broadly and very generally
Data-driven is followed in popularity by data-informed, and last, we have data-inspired. But again, we can distinguish the terms. And let’s talk about how we’re going to start with distinguishing between the two most popular references. First, data-driven and data-informed.
A data-driven approach can be described as one where the data makes the decision for you. There’s a focus on statistical analysis, data truly and singularly drives the decision in comparison. A data-informed approach is one where you don’t. Just do what the data says, but instead, you apply a layer of interpretation before you make a decision. Data informs you. But it’s not the only driver. When you take a data-driven approach, you are relying on quantitative data an example of a data-driven decision might be the decision on which email headline and move forward with based on the results of an A/B test. So if you’re doing that within any platform the decision is made. The remainder of the emails are sent out. Other uses may be personalization. If you have personalization on your website optimization. If it’s done automatically. If you have programmatic buying or dynamic creative data-informed approach can leverage both quantitative and qualitative, data a data informed decision might be where you need to determine a next product iteration. You analyze product testing results plus you take into account other information before making a decision like, what is your budget, or what is the competitive offering? Other examples of data, Informed decisions are making decisions on creative campaigns and executions, product launches product, pricing, budgeting, etc. And, in fact, I personally believe that we are actually being more data informed most of the time than actually being data driven.
Now a data-driven approach leverages data. Only a data-informed approach takes the data into consideration, but a human makes the decision. So it is both the data and the human involved. In this approach a data, a data-inspired approach is completely different. A data-inspired approach brings together different. Sometimes they may be disparate types and sources of information to make connections, to tell a story. And we’ve levers the data to inspire ideas. All data types could be utilized and a data inspired approach can be used when we are problem solving during ideation. When we’re working on creative concepts. If we’re exploring innovation, and so much more.
With this approach data is used. It’s there, it’s used, but it’s used to spark, and it’s used there for inspiration for the ideas. But the story comes from the human, comes from us. And looking at all three, we have clear distinctions. So let’s look at them through the lens of the type of decision you may be trying to make, or what you’re trying to accomplish.
If you’re looking to make a decision between options, be data-driven. If you’re looking to make a decision, but it’s a little bit more complex, it may need additional inputs. Additional interpretation to be that informed. But if you are looking to find inspiration for ideas. This includes creating solutions for business problems. Then you can be data-inspired. So let’s now dig a little deeper into being data-inspired. A key to that inspiration is the bringing together of the many different data sources to aid in the process of stimulating ideas. There may be some transactional data you pull in, social media reviews, customer profiles that you review. Then you may layer in information from Google Trends. I love Google Trends like we did earlier in the presentation. The goal here is to collect data from a multitude of sources and uncover and determine relationships and themes shared amongst them that help to tell the story that can spark the creative ideas.
We can think of data in rings. The data closest to the center is that data that is directly related to the problem or challenge that you have on-hand. This is our starting point, and this could be anything we might analyze and summarize this data, get a good understanding of what you’re trying to solve for, or what question that you may have. Then we expand outward to add in more data to the initial information we are absorbing.
Our next ring may be product or customer data. Then we might expand out further to look at our industry in whole. We may look at trends and competition. We may look at adjacent or complementary products. Here we may expand even further and explore general human truths, trends pop culture, and add all of these things to our repository. And then we take all of this, all of this data, and we work to find the story. Now, so the flow from initial data to final inspiration may look a little bit like this. So it’s very simplified, but it may look like this. So you start with the initial data that you’re given. You analyze it. You summarize it in examining the data. Maybe you find something interesting, something you didn’t expect. It’s an outlier. It’s like, Why is this happening? You ask questions about it.
So you begin to explore the data. You look a little bit deeper. You try to understand, “Hey? Why might this be happening? What are some other pieces to the puzzle?” Then you begin to search for, and you add additional data sources. You review this information. You absorb this information. Maybe some connections are starting to form here.
But maybe you want your … maybe you’re an overachiever, maybe you’re a hard worker, and you want to add even more data. So you search for, you add more data to your sources. You review. You absorb that information. Now. Finally, some things are starting to come together. You’re starting to make connections. You’re starting to uncover things, and you’re starting to develop a story.
And then inspiration strikes. And you get this amazing data-inspired idea. That’s very simplified, of course. So bringing together multiple information sources is the critical component for that inspiration. So you may wonder how many data sources do I need? Right? Well, there is no set number of data sources required to uncover the relationships and find the story. It really is going to vary. So inspiration can come from 10 sources in person can come from just two sources. Every situation will be different. So don’t try to lock yourself into a number. The same is true for time, so you may wonder how much time is inspiration going to take. Well inspiration, you know we can take it. It we can’t tell, but like a number of sources, each situation will vary. There’s no set time. And when we are working to motivate something like inspiration, sometimes we really do need to be patient and let the process run its course.
There’s a little bit of some tips later on the presentation that kind of hit on this. So here’s another kind of quick and very simplified example of how we pull data in for inspiration. In this example we have a new product that is launched, and sales have gone into the market, but they have a leveled off, and it hasn’t had the trajectory we want. Unfortunately, many of us may have been in this position before, so we need a decision on how we’re going to increase sales specifically as a marketer, how’s marketing going to help to do that? So the question is, what kinds of data might we pull in to be use this inspiration in a situation. So I’m actually dealing with a situation very similar to this in my job right now. But we have some products not exactly where we want, and we are actually in the process now of pulling together all of the data to try to make this story. So some examples of some data we may pull in for this might be transactional data. Okay, let’s look at the transactions and see what’s happening. Maybe product reviews — our customer saying something about a product that we are not aware of.
Let’s scrub through social media. It’s a great place to get the voice of the customer. That’s just raw and unfiltered. Right? You may look at Google Trends. Is it something happening there with customer search searches? Are they searching for something else. It’s not as popular as their seasonality here, and we pull all of those pieces together to try to uncover the connections that can get us to some insights that can help spark creative ideas. Now I realize some of you may be saying, “Well, I already do this.” You know, and if you are fantastic. So what you’re doing is you’re practicing data inspiration, and you should continue to do so.
So now let’s get a little more specific with an exciting real-world example that I am so excited to share. So in this example, which is for Burger King in the years 2019 data served as an inspiration for an idea. It was also a major driver in the creative and in the execution. So first, I want to say that there are. There’s some information here that I know. They use this some that I am making some assumptions here with it’s all caveat-ed with that. But here’s some data that I would assume was taken into consideration, as that idea was being developed. So if we take a look at the top half this information is information that you would typically find within your organization.
We have category data. This category data tells us Burger King is a challenger brand, and that it trails KFC and McDonald’s in global market penetration shares and sales. We have geographic market data. This tells us that Latin America, particularly Mexico, has been a battleground, and Burger King has a major presence, 1.6 versus 29.7, and we have product data, which demonstrates that whopper. The Whopper is Burger King’s and number one product with over 2 billion. So in 2019.
Now, if we look at the bottom data, this is where that disparate data comes into play, right? Not necessarily our product, but it is part of the data repository we have that can help tell a story. So we have some local geographic data here and trends. This is from Tom Tom’s traffic report, and we learn that Mexico City, the largest city in Mexico, has some of the worst traffic in the world. In 2017 it earned the distinguished title of being the most congested city in the world.
The report also noted that drivers in Mexico spent an average of 66% of their time in traffic, a lot of time. Then we have a human truth that we all might agree with: People get hungry while they’re in traffic, especially if you spend as much time in traffic as they do in Mexico City. So now we can take all of this information and data, the insights, and this resulted in an inspiration for the Traffic Jam Whopper campaign. What Burger King did was they used real time data to locate customers stuck in traffic and deliver a Whopper.
So as noted earlier, data was not just the inspiration for the idea. It was also heavily integrated into the execution. But I will say that data-driven creativity does not mean that it has to be in your execution. But they did it in this one, and I think it was really cool. So Google Maps APIs were used to identify traffic jams, locate people in traffic, push notifications to the Burger King App were sent to people in traffic that were near Burger King, and there was personalized messaging on digital billboards that were located along the busy roads close to a Burger King restaurant. And this campaign was an amazing success for Burger King. They saw a 63% increase in deliveries. 44% increase in app downloads and Burger King again. This is a challenger brand became the number one fast food app in Mexico City.
So not only a creative idea, but an impactful one as well. And if you’d like to learn a little bit more about this campaign, I’m going to leave this up for a second. You can scan this with your phone, and this will take you to a video summary of the traffic jam, Walker. And there are other iterations after this of other types of initiatives and campaigns where they use data. But truly, if you look at all of those different pieces that came together and out of it, it inspired an idea, and that is really the joy of this process.
So now let’s talk about some ways to help data serve as inspiration. So the key really is to look beyond the typical uses of data. A lot of the time we are looking at data to validate or we analyze data for standardized uses. We use templates and dashboards and reports, and when we do that we really can keep data in this very narrow view. So, in order for data to inspire, we have to be more intentional, we have to be willing to break out of the traditional ways of looking at data, and truly look at data differently. To look at data differently. We have to look at data, to tell a story. To answer a why. And this may mean that you may have to dig. It may not be on the surface. It may not be apparent, as first data can expose truth. It can expose those hidden gems. It can help us to see the bigger picture. We can use it to discover, trans challenge beliefs.
And we can use it to examine those interesting outliers that always seem to pop up. So it’s really about, “Hey, I’m gonna look at data into different ways,” not just to give you that information, but it’s to be able to do all of these different things. And even if you take these as a list when you look at data to say, hey, am I seeing any one of these things? I can just help to get your mind and spawn your mind in that area. Another critical step for data inspiration is to prepare, prepare to be inspired by data.
Now, the first few items here that I’m going to discuss are actually tips for how to prepare for inspiration in general. We’re just discussing it today in respect to data. So the first step and being inspired is to be intentional about your goal to be inspired now with data, since it’s not a traditional source of inspiration. It’s not a beautiful picture or a bird, or walk in the park that may come a little bit harder for us. So we have to be more intentional, and have that level of intention to be on higher****
also to increase the likelihood of inspiration from data occurring, you have to prepare your mind, making sure that you have an open mind in an open attitude that you’re willing to explore data in a different way than you normally and typically do that way. When inspiration does strike, you will be ready for it, but that the heart of this is really the need to look at that it differently. You are looking for the story, not just the information. I’ll say that again: We’re looking for the story, not just the information.
Now, one helpful practice to aid and inspiration is allowing for incubation. Now, during the course we actually talk about all of the processes and all the stages in the creative process. Incubation is one of the stages in the creative process, and the creative process is one which traditionally is used by creative types for idea generation. But we can also use the creative process to help us generate ideas for marketing problems. The incubation stage occurs. After information has been collected and absorbed at this point you should step away from the situation and internalize the information you let it just sit and simmer in your mind.
Even though you may not think you’re actively, maybe you may not be actively thinking about this, your subconscious will actually be working in making connections. To those who may not be familiar with this, this may sound ... It may sound like a waste of time, but it actually really works. And sometimes just step, just stepping away and sleeping on something for one night can allow those mental connections to be made. Incubation should hopefully lead to this next page, which is called illumination. And these are often referred to as light bulb moments. This is when an idea begins to emerge out of the subconscious work of incubation and into the conscious.
So an idea, or possibly multiple ideas may come to mind. It may even feel like a "eureka" moment to some people when this happens. So if you’ve ever had that, and all of a sudden you’re doing something unrelated, you’re making a sandwich, and you have a great idea about how to do something at work. That’s what’s happened. This has set in your mind, and it’s incubated, and then it’s come out. So this is one of the hardest pieces to do, because I think a lot of us like to get into rooms.
Do some brainstorming, solve on the spot. Get some ideas. But truly, allowing yourself that time to say, "hey, let’s just think about it for a night, and come back and let things kind of simmer can be extraordinarily helpful."
Now. I’ll close out, and I know we only have 30 minutes, but we’re efficient here with briefly sharing some of the benefits and the limitations of that inspiration. So I hope the presentation has proven that a data-inspired approach can be very beneficial, and being a catalyst for creative thinking and creative problem solving. And there are other benefits.
These benefits include the capacity to account for the larger picture. to account for culture, shifts, and other contacts and problem solving. It can reveal connections that you might not typically see, or that you haven’t seen before, and that can help in identifying new and unique insights. It can reveal trends that can be leveraged for business strategy.
And the data-inspired approach can encourage new ways of thinking about a business, thinking about a product or thinking about a problem. And of course there are also limitations. including the fact that it’s not an exact science and data is not traditionally used for inspiration, for creative ideas or ideation. So this may mean that it takes getting used to. There may be people in your organization, or maybe yourself. That was a little resistance to change as humans. We like consistency, so change is a little bit difficult. In addition, inspiration may not be automatic as we talked about that need to kind of sometimes let it sit sometimes for more information in, so there may be there may need to be some work to find meaningful insights there, or there may need to be time to just allow ideas to emerge.
And last, but not least, a damage of an approach is not appropriate for all situations, so we can’t just plug it in. We do have to be selective about. When does it make the most sense?
So in the effort. But I believe the effort in determining how data inspiration can work is so much worth the effort. Given all of the potential benefits. We have such an incredible wealth of growing and evolving data at our fingertips, and we have an unlimited number of ideas just waiting to be inspired by all of that great data. So be inspired.