Caroline Florence, author of our featured book “Data Storytelling in Marketing,” discusses transforming data into compelling narratives. She outlines a five-step roadmap for effective data storytelling, emphasizing emotion’s role in persuasion. Caroline offers advice for marketers to enhance their skills, sharing a De Beers case study to illustrate data-driven insights’ impact. Learn how to leverage data storytelling for more effective marketing communication and decision-making.
Episode Transcript
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Adrian Tennant: Coming up in this episode of IN CLEAR FOCUS:
Caroline Florence: Data storytelling is about creating a transformation in the end audience. So what are we needing them to buy into or to understand or think differently about relative to our position, an argument or a recommendation that we are making?
Adrian Tennant: You’re listening to IN CLEAR FOCUS, fresh perspectives on marketing and advertising produced weekly by Bigeye, a strategy-led, full-service creative agency growing brands for clients globally. Hello, I’m your host, Adrian Tennant, Chief Strategy Officer. Thank you for joining us. In today’s data-driven marketing landscape, the ability to tell compelling stories with data is becoming an essential skill. As marketers face an ever-increasing volume of information, the challenge lies not just in analyzing data, but in translating it into narratives that resonate with stakeholders and drive decision-making. This requires a unique blend of analytical skills, creativity, and strategic thinking. Our guest today is an expert in helping marketers develop these crucial data storytelling skills. Caroline Florence is a trainer and coach in data analysis, insight generation, and creating evidence-based narratives. As the founder of Insight Narrator, a training company building data skills with marketing and communications professionals worldwide, Caroline was included in the 20 Women in Data and Tech in 2023 for services to learning and development. She’s also been listed in the ESOMAR Insight 250 as a global innovator in market research, data-driven marketing, and insights. Caroline speaks regularly at conferences around the world on the value of insight. Her new book, published by Kogan Page, is Data Storytelling in Marketing: How to Tell Persuasive Stories Through Data, which is also our selection for the Bigeye Book Club this month. To discuss some of the book’s key ideas, I’m delighted that Caroline is joining us today from Cambridge in the UK. Caroline, welcome to IN CLEAR FOCUS.
Caroline Florence: Thank you for having me.
Adrian Tennant: Data Storytelling in Marketing is your first book. What inspired you to write it and who did you have in mind as your target audience?
Caroline Florence: So for over a decade now, I’ve been training and consulting with teams to help them use data storytelling, to think differently about how they communicate. So whether that’s internally with stakeholders or with external partners and stakeholders, and even end customers in terms of thought leadership. And as I’ve been working with more and more teams, I really felt that we could take those skills and ways of working and help more people. And a book is a really good opportunity to reach people with those proven techniques. And now I had lots of case studies that could really be helpful and make a difference to a task that’s becoming more and more part of everybody’s sort of day-to-day working week. So I’ve worked with both data specialists and data users across many different functions, but my background typically in terms of data is around the marketing function. And I’ve seen firsthand organizations trying to drive the democratization of data across organizations. And the impact that’s then having on the skills needed in teams that maybe traditionally wouldn’t have needed to develop data storytelling skills as a core capability. And marketing is one of those where it’s becoming more and more normal as part of what they do within the team. So I really envisaged that the core target would be those who are doing a lot of the communication day to day. So whether that’s brand managers, CRM managers, strategic planners, product managers, who are having to access that data and then help inform the decisions and actions either up or along or outside the organization. I also feel that senior marketing managers and leaders would be a good sort of secondary audience for the book, because as well as talking about specific skills, we also talk about that culture and the way of working within a marketing team, which is useful as a leader to think about how do you bring this into the function.
Adrian Tennant: Well, in your book, you outline a five-step roadmap for data storytelling. Caroline, can you give us an overview of these steps?
Caroline Florence: The roadmap was designed to really give the reader some structure to help identify the skills, the practices, the steps that maybe they personally need to develop, as well as helping give some structure to the practical hints and tips to help them improve their data storytelling. And the 5Rs approach focuses on the outcome a great data storytelling is looking to achieve. trying to get to a data story that is relevant, robust, refined, relatable and remarkable. And for each of these outcomes, we share three steps to achieve that goal. So, for example, for creating a relevant data story, the roadmap focuses on planning skills and helping the audience to determine what the knowledge levels, the needs and preferences are of the different people they’re communicating to, and what that then means for the data story itself. So by breaking it down into the steps, it’s really about giving the reader an opportunity to focus on the areas where they feel they’ve got headroom to grow as a data storyteller, as well as pick up some hints and tips to keep stretching things that they already do quite well.
Adrian Tennant: In the book, you discuss the importance of knowing what data to use and for what purpose. Can you elaborate on this and provide an example?
Caroline Florence: Yeah, so I think the reality is that data can easily be misused or distorted, so both intentionally or unintentionally. So it’s the responsibility for a good data storyteller to ensure that the approach that they’re taking their data is really conscious, robust. and deliberate in the way that they achieve that, the way that they look at the data and ensure their interpretation can stand up to scrutiny. So this means that they need to think about all the different plethora of data that’s available within that marketing team and know really what are the metrics that they are using in any given objective? What does this actually tell them? What does that mean in practice? And it can be hard when there’s lots of different experts out there with different data sets trying to influence that. And one of the examples we talk about in the book came from a conversation from a lady called Lizzie Harris, who is director of customer at an organization, a retail client called B&Q as part of the Kingfisher Group, large global retail organization. And she was talking about how marketing directors when they’re looking at evaluating performance of marketing campaigns, they’ll have econometricians coming in and telling them one thing and they’ll have their media planners, they’ve got great data scientists in their team telling them other things and they’ll have their internal teams And none of these things really knit together easily to say, well, it’s one plus one equals three in what we’ve achieved. And so being able to understand for what we’re actually trying to do, which of those measures is more important? How do I manage any conflicts between some of those different data sets? And what do I, as an individual within the marketing team, want to rely on as my lead indicators? The thing that I feel is going to be most important, given the objective of the campaign, given the end goal for the data story, what is it that I’m leaning on and why? And having some ability to make a hierarchy out of all of those different data sets that potentially are coming their way.
Adrian Tennant: Great point. Caroline, how can marketers improve their ability to interpret data and extract meaningful insights?
Caroline Florence: There’s two really key priorities for marketers looking to improve here and where it can make the biggest difference. The first is being really clear in their definition of what they’re trying to do and why. So rather than just starting to look at data, really have some clear parameters and understanding of what success looks like given the specific objective. It’s really hard to look at data without that context and get to the insight. So to determine a so what or now what in the data analysis, if you haven’t got some form of parameters in which you’re trying to operate. I also think at this stage, it’s really important to draw on existing data. So it could be from other campaigns or other things that have been done in the past, as well as that marketing knowledge to develop hypotheses that are going to guide some of that exploration. Otherwise you can be stabbing around in the dark, looking at lots of different data sources without really having a clear sense of what end you’re trying to influence with all of this. So that would be the first one. I think from the second is, again, coming back to that point about knowing what the different metrics do, aligning those measures to that specific objective, and thinking about the different data required to stress test the hypotheses you’ve come up with. So again, knowing what those KPIs are, knowing what might be lead indicators, what measures are more important for this particular goal, how these things all relate to each other can be really helpful in then, again, narrowing down the focus so that you’re not looking at everything and anything that might exist on the topic. And that will give a good kind of start point to really give a sense to compare and contrast and to also make meaning out of what they’re seeing in the data itself.
Adrian Tennant: Can you explain the difference between data reporting and data storytelling?
Caroline Florence: So this one comes up quite a lot, and I think there’s a lot of tools and platforms that have done a great job that do good data reporting that leverage that storytelling buzzword. And for me, they both have a role to play, but they are distinctly different. So for me, reporting is great for regular repeatable measurement. So where you’re looking to create some consistent formatting, really nice, easy-to-read graphs or tables that the audience can get familiar with, that they’re able to utilize and develop their own stories from. But even the most beautiful reports or dashboards are not really telling a story by just reporting all of that information. They’re informing the audience And it’s a focus on what the data is showing. Someone still needs to work out what the story is. So reporting is good for having access to layers of information right from the high level metrics to very detailed sub analysis. But it does require the user to be relatively data literate to be able to work out how to make sense of all of that and be willing and have the time and capacity to get their hands dirty playing around with it. So, while reporting for me is more about providing information, data storytelling is about then creating a transformation in the end audience. So, what are we needing them to buy into or to understand or think differently about? relative to our position, an argument or a recommendation that we are making. So, to persuade them, we need to communicate much more distilled, actionable insights and it’s going to always be more than just the what. It’s going to require the why, the so what, the now what. And actually from a structural perspective, we need to develop that story in a way that’s really compelling around whatever ask it is or the recommendation we’re making, rather than sort of more reporting logic in terms of how a dashboard or report might be set up. So for me, data storytelling requires the storyteller to be doing a lot more work in working out What is the most important message that needs to be landed? How do we structure the narrative in a way to ensure that stands out? Which reporting doesn’t necessarily require when it comes to communicating all of that information.
Adrian Tennant: So thinking about the end audience is critical.
Caroline Florence: Absolutely. It has to be front and center in terms of the story you’re telling and why this story, because you may end up with very different stakeholders that have slightly different responsibilities that you’re trying to influence around and different ways that you’re going to use that data to communicate to each of them.
Adrian Tennant: I’m curious, what do you think about the practice of every headline in a presentation providing an insight?
Caroline Florence: I don’t think there are always that many insights. So for me, this is about quality rather than quantity. The headline should still be useful in relating the data to the insight. So if we’re using graphs or visuals to demonstrate some of the data that validates that insight, then the commentary needs to make that really clear as to why this is important. But in itself, trying to make everything insightful when it doesn’t mean that people spend a lot of time wrestling with these things unnecessarily and spending a lot of time and energy trying to make what is just good data into something that it’s not. And it’s how it’s all weaved together and used illustratively to talk about key points of view that’s where it can be really valuable rather than every kind of page needing to be an insight itself.
Adrian Tennant: Let’s take a short break. We’ll be right back after this message.
 | Caroline Florence: Hi, I’m Caroline Florence, the author of Data Storytelling in Marketing: How to Tell Persuasive Stories Through Data. My book provides a practical guide for marketers to develop compelling evidence-based stories influencing decision-making and driving change. I share proven methods and real-world examples to help you create impactful data stories that resonate with your audience. breaking down key concepts, and explaining how to transform complex data into engaging narratives that inspire action. As an IN CLEAR FOCUS listener, you can save 25 percent on Data Storytelling in Marketing when you order directly from my publisher at KoganPage.com by entering the exclusive promo code BIGEYE25 at checkout. Shipping is always complimentary for customers in the US and the UK. I hope my book helps you use data storytelling to create more effective, persuasive marketing stories. Thank you! |
Adrian Tennant: Welcome back. I’m talking with Caroline Florence, founder of Insight Narrator and the author of Data Storytelling in Marketing: How to Tell Persuasive Stories Through Data. You discuss classic storytelling techniques in your book. How do these apply to data storytelling in a marketing context?
Caroline Florence: One of the advantages we have is that we’re naturally storytelling animals in any context. So this is something we intuitively do quite well. Our understanding of how storytelling works has developed again over centuries. So we know that there are tried and tested means to develop good stories and what helps with engagement and connection with audiences. So these classic formulas and techniques are useful for data storytellers because we can tap into what’s proven to work on that human level. And that’s still what we’re doing. We’re talking to other human beings and help provide a little bit more guidance to ensure more of a balance between that rational and emotional level. Data storytelling itself is not really new. We’ve used stories for millennia to communicate valuable information to others. It’s just now we have a lot of that information where before we might just be telling them where to avoid or what direction to go in. Now we’ve got all of this information and so many different stories we could tell from the data. it doesn’t mean that they are of equal value. So the frameworks can be really helpful in determining how to distill that data so that it’s supporting the narrative rather than overwhelming it. For me, that’s where the frameworks can be really helpful, because without them, it’s really easy for people to go round and round in circles and find themselves getting lost in all of the data and not being able to kind of see the wood for the trees.
Adrian Tennant: What role does emotion play in data storytelling and how can marketers incorporate it most effectively?
Caroline Florence: So for me, it comes back to the fact that emotion is key in any communication and humans need more than numbers and logic to be persuaded. They need to feel something as well. And yes, having the ability to rationally judge and say, that’s why I made a decision or took a call that was different. It’s especially true when we’re asking audiences to bind something new, different and challenging. If this is something that maybe is different to what they believe is standard. No amount of throwing lots of data at it is going to make them change their mind. So it’s really important for data storytellers to reflect on some of the core messages coming out of the data story and determine what do they want their audience to feel as a consequence of hearing those messages. So it could be actually, I’m reassured we’re on the right track. you know, things are working as they should be. It could be excitement because there’s this huge opportunity if we could just get it right. It could be nervousness, things aren’t really, you know, developing the way that they should be. It could be shock that something has really been disastrous. But actually determining that emotion can then help think around how do we position that story and tell that story in a way that is going to evoke that emotion rather than hiding from the difficult emotions that might come up and trying to over rationalize everything really to embrace those emotions is a way to make a connection with the audience And so this means the data storyteller needs to make some quite conscious and deliberate choices around how they’re bringing that data story to life. Sometimes it might be that the audience don’t really understand or are aware of the problem that this solution might be helping with. And so the story needs to really make sure they feel the fire of that problem. While in other circumstances, they might be really familiar with the problem and they’re looking for novel and interesting solutions of how we could approach that, in which case we don’t need to spend lots of time getting them to feel the fire because they’re already there. So it gives the data storyteller an opportunity to be flexible with how they bring that story to life. And for example, almost all data storytelling in marketing in particular is going to involve humans. So whether it’s human behavior, human choices, attitudes, responses to things, there’s humans behind all of those data points. And yet, When we’re looking at numerical data or lots of unstructured text data, it feels like the human has been removed from that. And actually bringing the human back into the story is a really powerful way for marketers especially to generate that emotional response so that their audiences are connecting with a customer or a prospect or with a user or whatever the end human is that we’re talking about. And so that can be a really nice way for marketers to bring that emotion back in and help make a connection between the end audience they’re trying to influence and the human being that they’re trying to understand.
Adrian Tennant: Caroline, how has the proliferation of data sources impacted the ways marketers approach storytelling?
Caroline Florence: So in some respects, I think it’s great. You know, we’ve got this plethora of data because it means more marketing roles have the opportunity to utilize that data to help them make decisions, to evaluate performance or inform their plans. But because of that range, because of that frequency of which it’s coming in, it does mean that there’s this never ending stream of information vying for the marketer’s attention and trying to make sense of that. If you don’t have a structured approach to it, it can almost feel impossible. And when it overwhelmed with that volume, it’s quite tempting to default to what you’re comfortable with. So the sources that you know and you’ve grown up with or you’re really familiar with, or to cherry pick data in isolation that is going to serve a particular purpose without having to feel like I need to look at everything that exists because that would just take too much time. I think the really great data storytellers and marketers are really able to cut through all of that noise. Some of that comes from aligning to the bigger picture and going back to those first principles about what are we actually trying to do here and why. But it’s also using their analytical thinking, their critical thinking to bring some clarity and meaning to any analysis. And I think finally, what marketers have to be much more comfortable, competent and confident with is saying, I’ve got all of this data, there’s certain different things I’m seeing, there’s patterns, there’s some consistency, there’s some inconsistency. Fundamentally having looked at all of this, this is what I think. There is still a judgment that needs to be layered over the top of it. And that’s where their experience, that’s where your marketing theory, all of those other things, which are also useful inputs into decisions, It’s leveraging the data alongside that. It’s another input, effectively, the data and trying to remember that the data is not going to do the job for you. Fundamentally, you still need to make a judgment on top of that. And so all of these are going to be hugely critical for them, but that ability to see the dots and how they join together to manage the uncertainty about it not being a perfect story and saying my best thinking given all of this data is we need to do X or we need to change that. That still requires the marketer to be able to cut through all of that data and make that call.
Adrian Tennant: Got it. We love case studies on IN CLEAR FOCUS. You have a ton of them in your book, but for right now, can you share an example of a particularly compelling data story you’ve encountered?
Caroline Florence: This one is one from the book, and I think it’s a really great example because when we talk about compelling, this is a good example of something leading to a real transformation in the market, within the way that a brand was operating and commercially successful use of data and data storytelling to really make a difference. So I talk about it in the book, but it comes from the global planning team for De Beers, the diamond company. And they were conducting some of their normal qualitative research that they were doing as part of some of their campaign development work that they do each season for different campaigns that they’re running. And they started to see this consistent sort of emerging trend appear. around women buying diamonds for themselves. So at the time, in the industry, no one was speaking to this audience. This was not who was considered to be diamond purchasers. It was pretty much predominantly targeted to men buying what they call tokens of love for partners who were assumed in most cases to be women. And predominantly the engagement ring is a key part of what they were targeting in terms of their audience. So the team knew that because no one was speaking to this audience and this trend was really emerging that there was a particular set of needs. There was a clear opportunity to do something different, but they were going to have to really influence the different audiences, both internally and externally to get them to leverage that opportunity because they would have to think really differently about this as a target group. So the first thing they did is not rely just on that trend. They went out and they triangulated that against lots of other sources. So they were building up a really robust story. So they were looking at that observation against wider macroeconomic data on female purchasing power, trend studies on the nature of modern relationships, as well as microeconomic factors in key markets and looking at competitors and what they were doing. And they started from that to be able to join the dots and be able to develop a proposition that would support this emerging insight. to then communicate that internally and with the wider industry to influence real change in the category. And this then meant for them creating a range of different data stories that were relevant for those data audiences. So in the book, we talk about the CEO really needing the data story to focus on the positive impact on the bottom line. This would require a very different potential set of products, ways of positioning, ways of talking to their retailers that they work with and to the end customer. So really seeing that there was going to be a return on investment for that direction. But for the jewelers that they work with around the world, they needed to get those people who are at the front line of selling to the purchasers to really understand the human angle and to understand the people that were going to be in this target so they could think differently about how they position, merchandise, sell diamonds to the target. And by utilizing all of that data, creating some really compelling stories, it led to the development of a whole new collection of products in terms of non-engagement rings and also a specific campaign that was focused on speaking to those women specifically and around their own empowerment for purchasing for themselves. And actually all of the data in that story helped the brand as a whole really inform how to speak to this audience, which was a new voice for the brand to be able to be talking in that way. And it led to some significant commercial success in a lot of their key markets. And actually as a category, it’s been expanded and much more of a focus in the industry as a meaningful commercially applicable group of people to now focus on rather than it being seen as something which is just emerging at the fringes. So I really like that example because it’s driven from some early insights and then layering on more data to evolve that story, to give it more credibility, to make it more robust, to then personalize and tailor that for the different audiences that needed to be influenced, but with that core trend staying the same at the heart of it. I think it’s just a really great example of the power of what it can do when done well.
Adrian Tennant: What skills should marketers focus on developing to become better data storytellers?
Caroline Florence: So if I was to suggest just one thing, it wouldn’t be so much as a skill, but a way of working, and that’s to step away from the reporting tools and find some space to engage the brain and think about what story is coming up to you when you’re looking at that data. What story is the data telling? It’s rarely going to happen looking at a screen and looking at lots of numbers and not to be scared about going around in circles a little bit or down a few rabbit holes before that narrative starts to become clear. I do think that most of the core skills that you need for good data storytelling exist in marketing teams. A lot of it is about building the confidence to apply these in practice. And that is the thing that I think can make the biggest difference. So that’s where frameworks are really useful and why I’ve included a lot in the book, because that can help with that practice and get people feeling more comfortable that they can do this with the skills that they already have. And like many things, practice is what makes all the difference. So I’m a big advocate of getting stuck in and trying things. and reaping better results than doing nothing, rather than waiting for a perfect opportunity to deliver the best data story that’s ever existed. And just getting their hands dirty and experimenting a little bit and seeing what works with the audiences and learning, replicating, scaling that to the different things that they do.
Adrian Tennant: Great. You’re the founder of Insight Narrator. Caroline, could you tell us a little bit about the clients that you work for and the services that you provide to them?
Caroline Florence: So the vast majority of what I do with them is training around these core capabilities. So that will be either remotely or in person doing workshops, training sessions around some of the skills and the frameworks that I include in the book. I also do consultancy around that. So for certain bits of output that people are creating, whether that’s a piece of thought leadership or whether that is a really important piece of communication will actually work with them on developing that data story. But the majority is around really upskilling people. And the bit that I most find rewarding in my work at Insight Narrator is seeing people be able to connect with the frameworks and realize that they can do this and actually have really quick wins quite immediately to say this connected with somebody or I really got that message across. And that gives that kind of really immediate gratification from my perspective, to see people can hit the ground running with this quite quickly.
Adrian Tennant: What’s the one thing you would like readers to take away from your book?
Caroline Florence: I think the key thing is that great data storytelling is possible without them having to be a data expert. They don’t need to be able to code dashboards or be able to use Power BI. They don’t need to have an in-depth understanding of lots of tools, lots of methods, all those different approaches. there’s going to be experts who can help them if that is needed. Where they have the opportunity here is to be able to bring the understanding of what needs to be done and their understanding of what good marketing looks like and that data interpretation together to really be able to create strong stories that are going to resonate with the different audiences that they might be talking to. So they don’t need to know everything that there is to know about data to be able to do this well.
Adrian Tennant: Great. Caroline, if listeners would like to learn more about your work at Insight Narrator or your book, Data Storytelling in Marketing, what’s the best way to do so?
Caroline Florence: So I’ve actually set up a website for the book specifically, and there are a number of resources that the listeners can access on there, including downloading a free chapter of the book itself, But there’s also links to other articles I’ve written on the topic and webinars where I talk about some of the skills covered in the book. So the website is datastorytellinginmarketing.com. And from that, there are lots of resources people can access.
Adrian Tennant: That’s perfect, we’ll include a link to those resources in the transcript for this episode and the show notes. And a reminder that IN CLEAR FOCUS listeners can save 25% on Data Storytelling in Marketing when you order directly from KoganPage.com using the promo code BIGEYE25 at checkout. Caroline, thank you very much for being our guest on IN CLEAR FOCUS.
Caroline Florence: Thank you for having me.
Adrian Tennant: Thanks again to my guest this week, Caroline Florence, the author of this month’s featured book, Data Storytelling in Marketing. As always, you’ll find a complete transcript of our conversation with timestamps and links to the resources we discussed on the IN CLEAR FOCUS page at Bigeyeagency.com. Just select ‘Insights’ from the menu. Thank you for listening to IN CLEAR FOCUS, produced by Bigeye. I’ve been your host, Adrian Tennant. Until next week, goodbye.
TIMESTAMPS
00:01: Promo for Bigeye’s Retail Revolution
00:59: Introduction to Data Storytelling
03:06: Caroline Florence’s Background and Introduction
05:33: A Five-Step Roadmap for Data Storytelling
06:53: Importance of Knowing What Data to Use
09:14: Improving Ability to Interpret Data and Extract Insights
11:12: Difference Between Data Reporting and Data Storytelling
13:40: Importance of Thinking About the End Audience
14:08: Every Headline Providing an Insight
15:05: Promo for Data Storytelling in Marketing
16:04: Classic Storytelling Techniques in Data Storytelling
18:06: Role of Emotion in Data Storytelling
21:18: Impact of Proliferation of Data Sources on Marketers
23:47: Compelling Data Story Example: De Beers Case Study
28:34: Skills for Marketers to Develop as Data Storytellers
30:08: Insight Narrator Services Overview
31:12: Key Takeaway from Caroline Florence’s Book
32:11: Accessing Resources for Data Storytelling in Marketing
