The Thought Leader's Voice Podcast

Unleashing the Power of Data Storytelling

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Join us for an insightful journey into the world of data storytelling with Caroline Florence, a distinguished trainer, coach, and founder of Insight Narrator. Based in the UK, Caroline has been recognized among the Twenty Women in Data and Tech in 2023 and listed in the ESOMAR Insight 250 in 2021 for her innovative contributions to market research and data-driven marketing. With her expertise in data analysis, insight generation, and data storytelling, Caroline is a sought-after speaker at global conferences. 

In this episode, we delve into Caroline’s new book, Data Storytelling in Marketing: How to Tell Persuasive Stories Through Data, and explore the essential elements and strategies of effective data storytelling. 

Key Takeaways

  • Transform Data into Persuasive Narratives: Learn to craft compelling data stories that drive decisions. 
  • Strategic and Tactical Applications: Discover how data storytelling adds value across organizational functions. 
  • Integration in Marketing and Communications: Enhance your marketing efforts with powerful data storytelling techniques. 
  • Emerging Trends and AI in Data Storytelling: Stay updated on the latest trends and AI innovations in data storytelling. 

Full Transcript of Podcast with Caroline Florence

Rachael: Hello and welcome to the Thought Leaders Voice. I’m Rachael Kinsella, Editorial and Content Director at iResearch Services and your host for today’s episode on data storytelling. 

I’m particularly excited to be joined today by Caroline Florence. Caroline is a trainer and coach in data analysis, insight generation, data storytelling and activation, based in the United Kingdom. She’s the founder of Insight Narrator, a training company building data skills with marketing and communications professionals worldwide. Caroline featured in the 20 Women in Data and Tech in 2023 for her services to learning and development and was also listed in the SMR Insight250 in 2021 as a global innovator in market research, data-driven marketing and insights. She regularly speaks at conferences around the world on the value of insight and data storytelling. And she’s about to publish a very exciting book on data storytelling. Welcome Caroline, it’s lovely to have you here today to talk about a subject that we’re very passionate here at iResearch. 

Caroline: Thanks for having me. Yeah, it’s great to talk about this topic. It’s very close to my heart, as you say, with the book coming out and definitely a skill I’m seeing is on the up in terms of demand for people being able to apply to their business as usual practices. 

Rachael: Yeah, absolutely, that’s a trend that we’re really seeing, and we’ve been talking about it a lot recently to look at how firms can gear up for the need for skills and capabilities in data storytelling and the value that it adds. So it’s ideal timing to be speaking to you today about this topic in a bit more depth. So I guess to get us started, could you tell us a little bit about the book? It’s called Data Storytelling in Marketing: How to Tell Persuasive Stories Through Data, and I love that that’s actually in the title, persuasive stories being the operative phrase. And again, as you said, it’s a trend that we’re really seeing to develop across our client base and in the conversations that we’re having with other industry professionals. I believe it’s launching in a couple of weeks’ time? 

Caroline: Yeah, so the book is out everywhere apart from the U.S. on the 3rd of June and then later on the 28th of June in the US, and it takes all of my experience working with teams, helping them develop robust but insightful and compelling data stories and I’ve tried to take all of that and turn it into a practical guide. So, enabling those who work in marketing, who work in communication roles to be able to create data stories that both stand out from the crowd, so that they’re engaging and cutting through, but that they also stand up to scrutiny and that robust work is done behind the scenes. 

And there’s lots of different applications for data storytelling. So we’ve talked about it in the book in its broadest sense, so whether it’s data storytelling to communicate internally to senior stakeholders to help get endorsement for the marketing plan or to approve budgets. Externally, we’re seeing a lot working with partners in the supply chain, so helping sell in the plans to ensure buy-in and activation around marketing activity, but also directly to customers through thought leadership, through their marketing campaigns and the book takes all of those different scenarios and looks at data storytelling with some nice practical case studies and examples to give a best practice roadmap really to create data stories that are not just informative, but truly are influencing decisions, actions, behaviours. 

Rachael: That’s fantastic. It’s such a crucial part of thought leadership, without robust data, without evidence-based content and developing that storytelling element. You can’t really call it true thought leadership and there’s so much more demand for that across different types of organisations now. Certain industries have been doing it very well for many years, but then as you say, there’s a skills gap there in terms of how to tackle it, how to weave it into the marketing and communications process and how to use it within thought leadership programmes to actually drive action and to be robust and backed up by evidence and facts. 

So obviously in this world of misinformation, there’s nothing more important than having those evidence-based arguments and having those facts at your disposal, but being able to tell them in a compelling way that’s going to differentiate you from the competition and from everyone else who’s talking about the same hot topics. So it’s great that you explore all of those different elements, which are all linked together, but warrant coverage in their own right throughout the book and having those compelling case studies from people who have been there and done that or have been trying out different methods so that we can learn from what they’re doing. 

 
And that’s a big part of what we’ve been doing recently, sharing best practices across the industry, who’s doing thought leadership well, who’s actually using data storytelling well in these various different guises across marketing and communications and also commercially through business development, which is an often overlooked area. So I think, you cover this in more detail in the book, but in your opinion and based on the conversations you’ve had and the research you’ve done over the years and for the book, what would you say are the key differences between sort of evidence or news-based content that’s citing statistics and it refers to facts and actual data storytelling? Because I think people don’t often see the difference and quite often are unsure about those definitions. 

Caroline: Yeah, it comes up a lot. I was talking with a team yesterday, we’re kicking off a programme of work and absolutely this grey area between “is this a report or is this something that needs to work as a data story and how are those different?” So having some distinction really helps. 

For me, there’s a couple of clear distinctions. I think primarily and firstly it’s their purpose. So for me reporting evidence, inciting facts and statistics, it’s predominantly designed to inform the audience, to give them the facts for them to then determine what they do with that, whether they believe it, whether they utilise that as part of their knowledge on a topic or they completely ignore it. Data storytelling however, it’s about the persuasion of that audience. So it’s about trying to create a transformation in the hearts and minds of the audience. We’re trying to get them to buy into a particular argument, example, way of thinking about a topic and the evidence is part of that in terms of driving their understanding, in terms of influencing their understanding, but it is a part of it and it’s bigger than just the data alone. 

Reporting data does have an important role to play, I still think, in communicating really important insights. It’s useful in organisations for tasks like ongoing performance measurement and actually were informing people and keeping people up to date on progress is important, so management information and things like that. But it does really have its limitations. I mean I’ve lost count of the number of organisations I work with or spoken to that are drowning in dashboards and reports that very few people are actually really using, that they understand that data in there and are utilising it for informing their decision making. So having all of this data and reporting on it is just not enough to have data-enabled decision making. 

I think what sets data storytelling apart from reporting is it is more than just the data observations themselves. It’s that synthesis of those different sources. It’s that applied understanding, expertise and context that leads to an interpretation of that evidence and a judgement ultimately, because never anything is 100% certain, even with evidence. So that we’re generating some really clear and insightful messages, but they’re derived from the data. They’re not just reporting the facts as they are. 
 
Rachael: Yeah. I think you really hit the nail on the head there that it’s those layers of evidence and it’s the combination of those different sources and different types of research that actually come together to build the stories and to create that compelling, persuasive argument. So layers of secondary research that are clearly evidenced, backing it up with qualitative analysis and discussions alongside the stats and the quantitative measures. And bringing that together and reading into the data and looking at the context, as you say, to build that picture and then actually be able to use those stories to persuade and to drive action or drive a conversation or move things forward.  
 
So it’s quite active, as you say, that rather than just reporting on the facts and right, well, yes, these are important statistics and we need to know about them, or drowning in the dashboards, which is, again, a conversation that we have with a lot of people that they’ve got all this marketing data, but they’re not quite sure what to do with it or they do research, but then they’re just drowning in the statistics and are not quite sure what to take from it and how they can build the narratives. And obviously, that’s where we come in and we say, well, we look at it as a whole and bring together those different layers of research to tell those stories, build the narratives and then create something compelling with it. And also knowing what to do with it, how to represent it visually, how to be able to activate it, which we were talking a little bit about in our opening discussion, that knowing how to use it through marketing and communications campaigns and also from a business development context, how that can be used by sales teams, by business development colleagues to, again, create compelling arguments and drive action commercially and in terms of relationship building with different clients and potential clients. 

 
So, there seem to be a lot of use cases for data storytelling across the organisation. Could you talk us through perhaps some of the examples that you’ve discussed or that you’ve come across in your research where organisations have been using data storytelling in different ways across different departments or different parts of the organisation? 

Caroline: Yeah. So, really good example of something I was involved with last year. So, the organisation itself and the marketing team, they’re not government, they’re sort of non-government, but they are operating within the food and drink sector and they are supporting a number of different initiatives in terms of whether it’s food security, whether it’s around sustainable nutrition, whether it’s just in terms of helping the sector to be able to manage and mitigate some of the difficulties they’ve faced, certainly over the last few years with the costs of living and rising costs for all organisations. 

 
And their marketing department were really keen that they were providing multiple partners and stakeholders that they had with the most up-to-date, the most robust, the most forward-looking insights around some of the key trends that are going on within the food and drink sector to then be able to inform what does that mean for what they’re doing and whether that is around their relationships within the supply chain, through thinking about their marketing and activation activities within the retail environment, traditional communications and so on. 

And actually, moving into a much more thought leadership space, and one of the things that came out of lots of the discussions around developing the data stories was firstly, how do we create a true thought leadership where we’re using this data to give fresh, new perspectives that the audiences don’t already have available to them? If you think about communicating to one of the big retailers, they’re absolutely swimming in their own data. They see all of that behavioural data live coming in around their sales. What can you be doing differently to talk about some of the bigger trends, some of the things that maybe they won’t have access to, to encourage their manufacturers to be able to have some really good conversations around how we support category or how do we support specific products and talking to category teams and buying teams. 

One of the things that the organisation was really keen to do is not just create thought leadership from the marketing team, but be able to bespoke those stories for the different conversations that would need to happen and to empower and enable sales teams, ultimately, a lot of them would be, or maybe category teams within manufacturers to be able to utilise that thought leadership to have specific relationship-based conversations. So some of those trends would obviously be more important than others and having the capability to firstly understand the data behind the thought leadership, but be able to manipulate it enough on an individual basis to have really strong conversations around specific plans and specific activities. So it ended up being not just a marketing job, it also touched into capability in terms of business development and sales and also in terms of just general PR for the sector, multiple purposes from multiple studies they were doing on some really hot topics. 

Rachael: I think there’s a number of key points to come out of that. Firstly, thought leadership and data storytelling are valuable across the organisation. They shouldn’t just be coming out of marketing, they shouldn’t just be used by marketing. Actually, there are very real applications for sales, for category teams, for product development, because it’s all driving those conversations and conversations with different tailored audiences. 

So again, the opportunity there is huge and many organisations aren’t aware of that or don’t know where to start in terms of realising those opportunities. Actually, if you’ve got those evidence-based conversations that not manipulated the data, but manipulated the way of presenting it so that you can tell those stories and build those robust narratives, then that’s a really valuable thing, surely, for different layers of the organisation, for different departments to use and potentially a way to bring the organisation together internally so that they can be aligned on not just on messaging and how they’re representing the brand and how they’re taking those conversations forward, but actually, we’ve got the facts here, we’re sort of, we’re informed, we’re up to date with what’s happening in the industry, what’s happening with our customers and our clients and we’re able to represent that and to articulate it better because we’ve got this storytelling capability. And I feel like that’s a very powerful thing and there’s more and more demand for it. We’re certainly seeing that and that’s a growing trend. 

So, it kind of points to the importance of data storytelling and thought leadership and this sort of combination of different layers of research and insights and ways of sharing that and activating it and using it across the organisation from a commercial perspective, but also from a cultural perspective because it’s allowing the organisation to communicate internally better, to communicate with their various different external stakeholders better and that’s all the more important in the current difficult times with geopolitical pressures, with environmental pressures.  So, I feel like it’s a very powerful, often undiscovered tool that companies can use. Was that something that you were finding in your conversations that companies were sort of kind of coming to that realisation of the value and the importance of data storytelling? 

Caroline: Definitely, I think a lot of the organisations that I speak to and I work with and that I interviewed, some of their representatives in the book, they’re drowning in data so that they know they need a process to be able to turn that into an asset and make sense of it all, to join those dots, to determine what matters most, especially when things are contradictory, distilling those into clear messages that everybody can be buying into and then personalising some of those messages for the different audiences in terms of how they’re positioned. 

One of the quotes I refer to in the book, I think, sums it up really nicely is taken from a five-year study that was cited in a book called Good to Great: Why Some Companies Make the Leap… and Others Don’t, by Jim Collins. And it’s 20 odd years old now. But one of the things that they looked at as part of that study was access to data. And there was this myth, certainly probably going back 10, 15, maybe even 20 years ago, that good to great companies are the ones that have all this access to data. And actually, they concluded it’s got nothing about the access. And actually, access is less of an issue now, given everybody is swimming in the stuff. And quality is a different issue, but having access to good data is not the thing that makes a difference.  
 
And they found no evidence to suggest that it was access that made these organisations be great in terms of their performance. And actually, most of the organisations have virtually identical access to the information, so it was not in having it, it’s in what you do with it. And a really nice quote around, it’s turning information into information that cannot be ignored. And for me, that’s what data storytelling does. It’s not about access to that information, it’s turning it into information that is powerful, is an asset, cannot be ignored. 

One of the key enablers for that you just pointed to before, and I think came out in that example that I gave, is the role of cross-functional collaboration in generating the story in the first place, and getting those consistent perspectives from different parts of the organisation, different levels of understanding, and then buying into this collective sense of, okay, this is what the overall story is, these are some of the underlying sub-stories that are more relevant to some audiences than others. And that consistent approach of, okay, this is what the story that we’re going out with, so that we don’t need to kind of keep spending time telling people what the story is to be consistent. They’ve all bought into it.  
 
And the one thing that came up consistently in the interviews was the power of collaboration in utilising multiple brains, whether they’re data specialists and marketers working together, or marketers working with contact strategy teams, or business development, or sales teams, whether we’re bringing even in from a thought leadership for some sectors, bringing in policy teams, all of those different strands coming together to help join the dots is such a powerful way of working to create data stories that cannot be ignored. 

Rachael: That sums it up really nicely. I really like that and it cannot be ignored. And that’s more important now than ever. And also, that’s what we feel thought leadership is all about. It’s that collaboration. It’s bringing together those minds, those opinions and insights from across the organisation, from across industries, across industry, getting perspectives from different sectors and different audience groups, and then bringing that together and making sense of it and distilling it, as you say, into those compelling messages that cannot be ignored, that can drive action, that can mean something rather than just making a comment. And that’s true thought leadership, and it’s action leadership as well. As IBM say, they kind of take it the next stage further, and they refer to it as what’s actually action leadership? How is it evolving from thought leadership? And how are people acting upon the insights that are being presented? 

So I think that sums it up really nicely. And the importance of collaboration, whether that’s, as you say, across the organisation itself, whether it’s externally with policymakers, trade bodies, membership organisations, that bringing together of knowledge and sharing it and making sense of it. Because, again, as you’ve alluded to, everyone’s drowning in data, we’re swimming in it, pretty much everybody has got the same type of tool to use to access data now. 

And most companies, large or small, have got certain levels of access to data that’s needed for regulatory requirements or for management information or whatever the case may be or to inform the marketing activities, but actually being able to make sense of that data, and then in the same way that maybe 10 years ago, it was the norm just to push out a survey, and then write up a report, just based on the survey findings with with very little other information or no other layers of research in there, that didn’t create compelling arguments, it was just out there. 

And yes, these are the statistics you can refer to, and we’re informing you on this particular topic. Whereas now, organisations have the ability to create those compelling, persuasive arguments to be able to drive action leadership and make use of their thought leadership through data storytelling, by combining the different insights, the different layers of research, the different knowledge from different individuals or different organisations. And that’s a powerful position to be in. So the more people that know about it, the better, and the more skills that are available in  the work that you do, and in training and learning and development and addressing that those skills gaps, the better that people realise what a vital part of the business that the data storytelling makes up.  
 
And I also like how some of the examples that you’ve discussed, look at how data storytelling can be used both strategically overall, and tactically. So it could be used for particular campaigns for particular audience groups or conversations and very tailored, but it can be used looking at the bigger picture, looking at the overall business strategy, informing a company on position and bringing together the evidence-based arguments. Have you got any more examples of that perhaps from a B2B context that you could share from from your research? 

Caroline: Yeah, so one of the things that I talk about in the book is what I call T-shaped storytelling. So that need for the sort of horizontal layer, consistent what I call metadata stories. So those bigger strategic stories that look at what’s going on in the market or the customer world, and they’re needed to help all teams really be able to understand the metrics they’re being measured against how they can influence them to be truly customer centric, they need to understand needs, behaviours, preferences, trends, to design product services, operational practices, marketing. They need to understand all of those elements at that bigger picture to inform those more strategic decisions. 

But then on a tactical basis, whether it’s related to a specific trend or theme or a particular activity that’s being measured, both have their their place. I think too much time personally is that especially in marketing teams is spent on those shorter term tactical data stories, everything’s very project related and moving on to the next thing rather than thinking about the bigger picture in terms of where all this sits in the journey. 

 
But I think certain teams are becoming much clearer in kind of using this for more strategic purposes. I’m definitely seeing from a B2C perspective for thought leaderships becoming important, certainly a corporate level in terms of thinking about brand reputation and purpose and so on. But definitely in the B2B sector, I think lots of different sectors are becoming much more aware of the need to be able to demonstrate that expertise to be able to be known for having an opinion on something to be able to cut through. 

 
One of the examples I talk about in the book from a B2B perspective really is looking at the pharmaceutical industry, and how very traditional in the way that they have to sort of sell in a market around some of their products, certainly in certain markets, heavily regulated markets, but actually being able to do more than just talk about the product benefits relative to the competition when they’re going in and talking to healthcare professionals and actually becoming much more consumer and end patient savvy in their storytelling to be able to inform these healthcare professionals that are so super busy, don’t have the time will have their brand preferences that potentially they’ve been prescribing for years cutting through that short window that they have using data storytelling to bring in that patient experience to be able to talk more about the lived experiences of patients to be able to bring that alongside obviously the quantifiable benefits from their clinical trials and that synthesis again into their thought leadership. I’m seeing that becoming much more of a hot topic, something that pharmaceuticals have to be able to do in those relationships to be able to cut through in what is a really challenging audience to just get their attention in the first place. 

Rachael: They’re able to present a fuller picture of their differentiation against the competitors. So it’s not just selling in the benefits of the products but actually they’re looking at lived experience, they’re looking at patient needs and patient experience which brings it to life in a completely different way and as you say is very different to the way that these products were traditionally marketed, and that’s quite an exciting use case I think. Is that one of the trends that you’re seeing evolving being able to give more of a rounded view of the situation or of human experience or what’s going on in the industry through data storytelling? 

Caroline: I think the will is there definitely. The activation of that is very variable. Because there are lots of issues that get in the way of doing that, not least skills and capabilities to be able to join those dots, to be able to find the right sources, to still be able to have those robust stories but actually also some of the practical things around accessing the data when it sits in different parts of the organisation, the time and the headspace just when everyone is so busy to sit down, to work out what it means to collaborate together, to invest time and energy in creating the materials and the content off the back of those stories in a way that is maybe not comfortable for some people because it’s just not the default, it’s not the way that we’ve done things in the past. 

And I think there is this disconnect between knowing that things can be done better and that data storytelling can play a role in that and that could be a really powerful asset and add lots of value and this sense of I don’t know where to start and stop with it. So access, volumes of data, time, all of the real life pressures that get in the way, even if you’ve got the skills and capability, it’s hard to have it prioritised against all the other million things that need to be done. 

Rachael: Of course, yeah, that’s key and it’s a steep learning curve for organisations regardless of size, regardless of industry, as you say everyone’s so busy, they’ve got regulatory pressures, they’ve got financial pressures, everything else going on. So actually selling in internally the importance of allocating that time and budget to be able to collaborate, to be able to sit down and make sense of this and how it’s going to add value, looking longer term as well, so not being sidelined by those shorter term pressures and those tactical programmes that you were discussing earlier. So I think it’s very important to raise awareness of that and look at how organisations can start to implement those hubs to be able to focus on it or bring in the help they need for training and addressing the skills gap or to be able to work with other organisations to help them to get started and to get that out there. So that’s a very important point because it doesn’t just happen automatically or naturally in busy lives. 

Where do you think AI fits into this? Do you think it’s friend or foe? Obviously, we can’t not talk about AI when we’re talking about data and volume of data and making sense of it. 

Caroline: Yeah. And it came up in all the conversations that I had. I do personally believe it has a clear role to play and absolutely can be a friend, I think. When it comes especially to the time pressures, I think there’s a huge advantage to being able to utilise that and I’m seeing some great initiatives that some organisations are starting to do, but it also has its limitations and it can’t do everything for us. 

I think the main opportunities I see around saving time for some of the key elements of the data storytelling process, so especially things like creating some of the initial visualisations and charts from a wealth of data to just to be able to get it into a format that is easy for the human to process rather than it being a huge data set and to do that quickly and accurately in a way that is so time consuming for the human and no value add, for me that’s an obvious one. And that then gives the freedom and time to be doing the thinking around actually how do we now use all of this data that’s been sort of had a first level of processing through the AI to then think about what the story is and how do we influence others. So I think that has a huge benefit. 

I think there’s also some benefits around given the need to have all of these multiple sources to use AI to pull out some of those themes quicker and easier in a way that is harder, especially if you’ve got five other things you’ve got to do within the hour for a human to sit and work out and actually get some of the nuances from some of the large data sets that might be missed. I think it gives a good starting framework, especially if you want to get extra validation, so you’re going to be looking to do secondary research, you’re trying to google what do we know about a topic, you’re going to end up with a long job trying to kind of filter all of the information that’s out there, so I think it can give a better framework. 

And actually, there’s lots of evidence to suggest when it comes to self-research and doing additional surveys that AI is as good as a lot of people when it comes to writing good questionnaires and surveys; and so I think it can help people with some of that as well.

So there’s a case study that I include in the book, it’s a number of organisations have formed part of and it’s actually been published and showcased quite a bit now in different conferences, looking at pitting the AI and the human together with a particular task to create both internal data stories that were going to senior management as well as creating thought leadership in terms of marketing content off the back of the work. 

And yes, in terms of creating content quickly, the AI hands down is going to be faster, but the level of insight was quite limited in terms of the key themes that were picked out. It was quite surface level in terms of the real understanding of the data and wasn’t actually that accurate at meeting some of the criteria that were set around some of the thought leadership and so on. So quite bland and not that insightful, but helpful in terms of distilling things very, very quickly to be able to work from. So for me, I absolutely think it can be a friend, but the human is still going to be crucial for ensuring we’re not just telling any old story that we can. There’s so much data that you can literally make a story about anything. 

So that relevance to the context, to the needs, the objectives, to the things that really matter the most. I don’t see any improvement or any form of comparison yet in terms of what it’s able to do. I think, again, this comes up time and time again when people talk about AI and it being a foe, I guess, is just the understanding of the inputs being used by the tool. So the training data, the limitations, the potential for bias, ensuring things are ethical, accurate, reliable, all of those things is still going to need that level of human sense checking. 

But also crucially, a lot of the data storytelling skills, some of the things that we talk about in the book around knowing what story we’re going to tell and why is going to be super important. The more we rely on these tools, because framing the queries appropriately to ensure that we are incorporating the right context, the issues, the target audience needs, all of that from the knowledge base that we’re mining from is going to be absolutely critical. 

And just that cross-referencing, yes, the AI can synthesise and pull from those different sources and it’s going to be more and more pulling on synthetic data. But it’s that human expertise, it’s the subject domain knowledge, it’s all of those extra layers that the human brings that can ensure that we’re confident with the stories that we’re going out with. 

 
Rachael: I agree. I think it’s a very useful tool in terms of bringing together those different sources, being able to do that quickly, being able to frame some initial thinking and themes and start to build that framework and then in some of the data analysis aspects. But you very much need that human input and that human lens to be able to, firstly, sense and fact check everything and ensure, as you say, it’s accurate, free from bias, that it’s relevant and it hasn’t just made it up. But also that in being able to differentiate and to be able to take that either contrarian viewpoint or to be able to look at it in a different light compared to competitors or whoever else is talking about that topic in the market. That relies on human insight, on someone who’s synthesising all of those different sources and creating those narratives and building the stories ready for telling. 

So that’s always going to be a really important part of the puzzle and AI, I think, would be a great tool for enabling that and supporting and helping to, particularly on the research side and scoping. But actually, the insight and the narratives are going to come from humans and careful checking and sort of having that sense checking mindset is going to be all the more important as well as more and more people are using the same tools or same approaches to start doing their insights work or to start on thought leadership programmes. And it’s interesting that that seems to be a theme that people have discussed throughout your conversations for the book as well. 

Caroline: Yeah, absolutely. And this whole idea of having different angles and different perspectives on things is going to be critical from a point of difference perspective. It’s not thought leadership if it’s not being thought about. 

Rachael: Yes, absolutely. Very important. We’d like to highlight that point. Are there any other key trends that you’re seeing emerging in data storytelling, some interesting ones that you’d like to share? 

Caroline: I think some of the key themes that we talk about in the book and starting to emerge, I think some interesting ones about where people have maybe invested in what they thought were good data storytelling tools that would do the job for them. And realising that actually, no, that isn’t data storytelling. It’s just giving me beautiful outputs and that that alone isn’t going to be what makes the difference. I think, no disrespect to organisations promoting and running these tools, they’ve made a really good industry out of talking about data storytelling. But it does require more than an ability to mine the data and make it into a beautiful graph. And so, I think teams are beginning to realise that the skills and capabilities of the teams and the ways of working together, collaboration and so on, starting to realise that. 

I think one of the other trends that is starting to emerge as people realise, especially with a drive towards more data literacy and data culture across different functions, is the need for real engagement strategies for these teams when dealing with their data stories. Not that we can produce them and they will tell themselves that there is still the need to have a communication plan that goes alongside that, whether that’s externally to customers or internally to be able to implement stakeholders. And that just creating great data stories isn’t enough. There’s the whole telling of those stories. 

And alongside that, much more alignment, I guess, with the thinking around internal comms and the skills that lie in internal comms teams around, okay, message development, different media, different ways of communicating this, rather than thinking we’ll do a great data story, but it will be in a report. It will still look and feel a bit like they always have done. Yes, it might be a better story and it might have more synthesis and great validation, but it still looks like a report. And therefore thinking more creatively about different ways of bringing that to life, whether it’s using more journalistic skills in terms of the way things are communicated, using more sort of social media tools that might be available to people around the content, video in particular, much more normalised and being used in thought leadership, as well as just more cross-functional ways of engaging with the content itself. So giving the audience an opportunity to not just generate the content, but respond to the content, making it feel a little bit more interactive. 

So I think there’s a lot of thinking going on around the different tools and means to be able to tell the story. I think where there is still this gap is around getting to the right story in the first place. And lots of books and models that talk about data storytelling say the importance of getting to the main message and then everything follows from that. But the process of getting to that main message is far more complex than I think often it is, given it’s due and the critical thinking skills needed to do that well and accurately. 

 
Rachael: Yeah, that’s another really important point. Defining and refining that message, getting to grips with that, getting decided on that, and then looking at engagement internally, how it’s going to be used, how it can be used, and getting aligned on the messaging and the approach internally before anything goes out externally. And then, of course, engagement and activation externally, how you’re going to tailor it to target audiences, how you’re going to use it across different channels and as part of the marketing and communications mix. 

 
There’s so many factors that go into it, all strategic at the outset, that need to be decided and defined as early as possible so that you’ve got a roadmap to follow and that you can make the best success of it once you actually do go to market. As you alluded to earlier, with the reliance on short-term tactics and campaigns and traditional ways of getting reports out quickly and focusing on particular types of content or particular channels, a lot of it can get lost and just, right, we’ll just get it out and not give any more thought to it. Whereas actually how you’re going to use it and what are the best ways of using it needs to all be decided and almost implemented internally first before you actually embark on those programmes. 

And that’s when we have conversations with clients and at industry events, that’s something that comes up very often, that it’s that internal activation that’s lacking and internal engagement. And that’s a key part of the puzzle, that if you get that right, everyone’s on the same page and it’s an awful lot easier to get that out to market in the right way and to make the most of it because obviously everyone’s on message and it’s reflecting more accurately externally. But also you’ve got far more chance of getting those conversations going, of getting the commentary and the insights out there. 

So that’s a really key part and I think it’s an ongoing trend that companies are trying to address. And the ones that are getting it right are actually doing data storytelling well, they’re doing thought leadership well and they’re rolling it out across their campaigns, whether they’re marketing or comms or specifically PR or if it’s for business development purposes. And that’s quite exciting, really, if we can keep banging the drum for the value of data storytelling as part of that commercial puzzle, then I think companies are really reaping the rewards that are engaging with that and doing it well. 

Caroline: Yeah, I agree. You need a process for it. It needs to have a way that it is working to enable you to be proactive with the stories you’re going and in control of how those are then managed and supported rather than feeling data storytelling is a we’re reacting to data that’s out there and then having a position on and it’s constantly we need to have a position on this. And there’s a fact that came out here from an industry body or from a regulator and now we need to have PR around that and actually having some of those data stories to draw on that are consistently understood, that are evolving over time, that are proactively generated as part of the process will make that feel more seamless, I think, rather than we’re reacting to any data point that’s put out there by others to feel like that we have to be on top of everything. 

 
Rachael: Yeah, that’s also really key, proactivity rather than being reactive and just reacting to stories or jumping on particular topics, actually carving out a niche or finding those topics that are meaningful to the organization that you can have a voice on, even a space that you can own by having a particular take on it. If it’s backed up by evidence, if it’s backed up by the data and you can represent that accurately in a compelling way, that’s going to just help differentiate the company and set you up as a thought leader, which is what everyone wants to do. 

So that proactive approach and strategic approach and then building the process off the back of that is so important at the outset. And again, it’s an area that’s quite often missed and sort of comes up that this is where we’re struggling or this is one of our key challenges. Brilliant. 

Thank you so much, Caroline. I think we’ve covered a lot of ground today. Really looking forward to the book coming out and you sharing the insights and the discussions that you’ve had with all different types of organization and sharing those case studies. And I hope to continue the conversation with you as more and more trends emerge and as we see data storytelling really come into its own. I predict that in the year ahead, it’s going to be more and more at the forefront of organizations’ minds and how to do it well. So, I imagine you’re going to be busy with the training and sharing your insights in the year ahead. 

Caroline: Thank you so much for having me. It’s always great to talk about this topic. So, thank you for sharing your thoughts and for allowing me some time to share some of the insights from the book. 

Rachael: Thank you, Caroline. Speak again soon. 

Caroline: Brilliant, thank you. 

Guest Speaker Details

LinkedIn profile: https://www.linkedin.com/in/carolineflorence/

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