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Artificial intelligence has pervaded every aspect of our lives, driven in large part by the remarkable popularity of generative AI applications. Among these, ChatGPT stands out as the app that boasts the most rapidly expanding user base in history, sparking extensive discussions around the boundless possibilities and future potential of this cutting-edge technology. Naturally, with such fervour comes a fair share of misconceptions and misinformation circulating.  

In his influential 2004 paper, John McCarthy defines artificial intelligence (AI) as “the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable." The goal of AI is to develop a machine that can think like humans and mimic human behaviours. But let's debunk the myth right here - AI isn't a looming menace ready to overthrow the industry (or take over our jobs) - no matter what the media is trying to tell you. Instead, it's a game-changer, a potent tool reshaping our sector in ways we could barely have imagined a few years ago. ChatGPT, or more broadly, Large Language AI Models (LLMs), have become ubiquitous in our lives. LLM (Large Language Modelling) is an AI technology that efficiently processes and condenses vast amounts of information. LLM excels in tasks such as summarising and creating analytical models, but it does not possess the ability to think or discern between good and bad, it doesn't make any judgment, nor can it validate what it creates. Hence, human supervision is necessary to evaluate the accuracy and significance of the AI-generated output.

Imagine AI as an e-bike for your brain. It equips you to go further, quicker, and with less effort. However, just as the cyclist needs to pedal to propel the bike forward, human intervention is indispensable for AI to perform at its best.  

However, AI does come with its share of shortcomings. While AI has groundbreaking potential to overhaul the way we work, it is not designed to replace human intellect but to augment it and help us be better at what we do. While it's great at crunching colossal volumes of data, businesses need clear and actionable strategic advice, not basic data digests. Moreover, AI falls short when grasping sarcasm, irony, and other nuanced linguistic expressions. In such instances, humans still need to peruse the text to decipher the intricate layers of communication. Emotional interpretation, negotiations, imagination, and vision of the future are still strong qualities of humans, underlining the irreplaceable role of human understanding and contextual interpretation in harnessing the full power of AI.

Impact of AI on insights and analytics

Here at boobook, exploring new methodologies and learning about innovative technologies has always been in our DNA. Over the last year, we’ve been exploring working with AI, and we believe it offers great assistance in the process of gathering, creating, and presenting insights.  

One of the biggest advantages of AI is that it revolutionises the data analysis process by eliminating the risk of human error and bias. Additionally, AI automates the time-consuming tasks of data cleaning and preprocessing, freeing up valuable resources.

AI can greatly assist the industry in multiple ways:

1. Efficiency Increase

By harnessing the power of AI-powered algorithms, organisations can analyse vast amounts of data faster and more accurately than ever before. This capability reveals hidden patterns, trends, and correlations, providing invaluable insights and expanding organisations’ research capabilities in several groundbreaking ways. Let’s take a look at its various applications:  

• Predictive analytics leverages AI algorithms to forecast market trends, consumer behaviour, and product demand.  

• Natural language processing (NLP) algorithms can quickly analyse qualitative information from sources such as focus group transcripts, survey responses, social media posts, reviews, etc.  

• Sentiment analysis enables a nuanced understanding of public sentiment toward products or brands by analysing online content, social media, and customer feedback.  

• Price optimisation, on the other hand, uses AI algorithms to analyse pricing dynamics, competitor strategies, and market conditions.  

• Another critical application of AI in data analysis is demand forecasting. By analysing historical data and external factors, AI models facilitate accurate predictions of future demand patterns for products or services.  

• Additionally, AI aids in fraud detection by identifying anomalous patterns in transactions and user behaviour, enhancing risk management, and ensuring the integrity of research-related financial processes.  

• AI also enables 24/7 focus groups and interactive questionnaires, allowing businesses to gather real-time insights and feedback from their target audience.

• Furthermore, chatbots powered by AI technology provide instant and personalised support to customers, enhancing their experience and streamlining communication.

• The capabilities of AI extend beyond text-based data analysis. Image and video analytics have become increasingly sophisticated, enabling businesses to extract insights from visual content such as images and videos.  

2. Inspiration

AI has the potential to inspire innovation and creativity within the industry. It can generate fresh ideas, identify emerging trends, and offer novel perspectives that fuel growth and progress. For example, you can use AI tool to add value for more profound segmentation. By asking questions such as “Who is your ideal customer?” and “How is your ideal customer feeling?” you can get interesting output when consulting on how to connect with that segment.  

3. Summarization

AI-powered systems excel at generating accurate and concise summaries of large volumes of information. This capability saves time and effort by distilling complex content into easily digestible formats. Numerous tools are available to help you efficiently grasp the core message of any text, but it’s crucial to prioritize the use of closed-loop mode apps to guarantee data confidentiality.

The future-proof MI professionals: Embracing opportunities & acquiring relevant skills

​​The adoption of AI is bound to open up new opportunities for professionals in all industries, and experts in the insights industry also have to rethink how they allocate their time and the skills needed for success. With AI taking care of routine and repetitive tasks, professionals can dedicate their time to interpreting data and extracting meaningful insights with confidence.  

Additionally, AI can also be a valuable tool that allows more coaching and enablement. By automating specific processes, professionals can devote more time to mentoring junior team members and nurturing their growth. This shift allows for a more strategic approach, where professionals can focus on driving innovation and strategic initiatives instead of being weighed down by mundane tasks.

Furthermore, the integration of AI reduces the technical benchmark required for entry-level professionals. With AI handling tasks that traditionally demanded hard technical expertise, junior profiles can contribute more effectively to data analysis and insights creation.  

Even though the benefits of AI are straightforward, professionals are concerned that their jobs are at risk of being replaced. However, it's not actually AI itself that poses a threat, but rather those who are adept at utilising it. Let's discuss new strategies and essential skills that will help future-proof MI (Market Intelligence) professionals to ensure their continued relevance and success:

1. Embrace and engage: Rather than fearing the rise of AI, MI professionals should embrace it as a valuable tool in their arsenal. Learning about AI algorithms, machine learning, and data analytics will broaden your skill set and enhance your ability to work effectively with AI tools.

2. Prompt engineering: One of the critical skills for a future-proof insights professional is the ability to ask the right questions to an AI-using machine. AI can provide vast amounts of data, but it's up to humans to determine which questions to ask to extract meaningful and actionable insights.

3. Insights / Consultancy / Storytelling: At Boobook, we understand the power of storytelling, as we know this is an essential tool to bridge the gap between raw data and strategic, meaningful decision-making. By conveying information concisely and engagingly, insights professionals can demonstrate their value and assist organisations in making effective choices.

4. Advising on AI adoption: By understanding the capabilities and limitations of AI, MI professionals can guide, inform and give the needed nuance to decision-makers on how to use AI tools effectively. This includes identifying the right AI solutions, evaluating their potential impact, knowing their strengths and weaknesses, and meeting ethical considerations.

5. Be extra critical of information sources & validation: AI is only as good as the data it is fed, so ensuring accurate and trustworthy information is mandatory. MI professionals should meticulously cross-reference multiple sources, verify the credentials of their data providers, and analyse the validation methods used.

6. Prioritise and validate: Typically, AI splits out way too much information without stressing and prioritising insights. Not all data is equally valuable, and not all insights are similarly relevant. By identifying and prioritising the most critical data points and insights, you can save time and resources while maximising the impact of your analysis.

7. Make insights actionable: MI professionals should be experts in data analysis and possess a strong sense of business acumen. By interpreting data in the context of the organisation's goals and challenges, you can effectively communicate the implications and recommendations to decision-makers.  

8. Specialise: By deepening your knowledge and understanding in a particular niche, you can position yourself as a valuable and sought-after expert, with AI assisting you in that particular niche.

Unlocking the potential of AI in the insights industry

This year, generative AI has quickly gained momentum, leaving many people feeling challenged to keep pace. Ever since ChatGPT burst onto the scene in November 2022, it has been the talk of the town, attracting businesses eager to seize its immense value. The innovation adoption curve of AI may have had a slow start, it’s growing rapidly, and we are seeing new and exciting applications of it every day. This fast change is not easy to grasp, and for some, it might be just a bit overwhelming. However, it’s important we don’t see AI as a threat but as a liberating force for the industry. It's high time we realise that AI is not designed to replace human intellect but to augment it and help us be better at what we do. By dispelling fears, embracing opportunities, and leveraging AI for insights creation, professionals can unlock the full potential of AI and drive innovation in their fields.  

Do you know why some stories are compelling and some aren't?  

The “why” we are attracted to some stories depends on many factors. Today, we roam through so much content on a daily basis, jumping from one meeting to another while exploring the vast lands of the online world. This makes most of us linger in the middle between being overwhelmed with lots of data and information and having little time to read a full article, process it and share it. The sixty-four-thousand-dollar question is how can we create content that will be captivating, easy to understand, and meaningful?

I have read and done many business presentations. Yet, I learn new things about storytelling every time I need to tackle a new project. I’m deeply passionate about data and storytelling: capturing people’s attention and making sure they remember the most important elements is a fun skill once you know how to do it right. 

So, how can you do it right? In this article, I’ll share some guidelines that I learned over the years that helped me improve and polish my storytelling expertise. However, before disclosing my “secrets”, I’d like to emphasize three things: 

1. When talking about storytelling, I refer to conveying business insights to an audience, meaning how to approach storytelling in a business context. Don’t ask me to tell you a joke or talk about my holiday in a very appealing way. Though there are definitely parallels between personal and business storytelling, they aren’t the same thing.

2. There is only one objective of storytelling in a business context: you want your audience to remember the key insights, ideally 3 to 4 elements. If these are not clear for you or presented in a confusing way, they will also be confusing for your audience. 

3. Good storytelling and choosing the right narrative have become increasingly important as we transitioned from in-person to online meetings and presentations. Capturing an audience behind a laptop is even more challenging!

Ready to mesmerize your audience? Here is how to tie a bowline knot with storytelling! 

1. Know your audience

It’s such a marketing cliché, but your audience is the best starting point. You must know who you are telling stories to. In the consulting world, we are telling a story in order to achieve a certain goal. That goal could be to define a pricing strategy or a customer targeting approach. In order to answer the client’s needs, first, you have to know who is listening to that story.

To understand your audience better, ask yourself the following questions: 

1. What does my audience need? 

2. What are their burning questions? 

3. Why should they care? 

4. How in-depth do they want to go? 

5. What is their attention span? 

TIP: Think about a few major issues or questions your client wants to solve and build your story around them.

2. Keep it simple, keep it short

This is by far the most difficult tip to execute!  

After 25 years of presenting to various audiences, I’m still struggling to follow the KISS principle (Keep it simple, stupid). Usually, there are so many interesting things and you’d love to share ALL of them with your audience. At boobook, considering we need to delve into many numbers, we also get all kinds of useful insights. This is where you need to be more like a ruthless editor - cut the unnecessary and focus only on main takeaways. So again, start from the most burning questions, and think twice before you share everything you find interesting. Your client might not find it equally interesting. 

TIP: Edit, edit, edit. The longer the story, the more details are shared, the less likely people will remember it.

Simplicity refers not only to what is presented but also to how. Slides created in PowerPoint (or in any other similar tools) slides are a great assistant to prepare your presentation. If done correctly, your storytelling will be more engaging through the combination of visuals and words. This can help the audience to remember the key elements. If you are wondering what I mean with “correctly”, it’s where simplicity does come in again.

Clients sometimes ask us to include fancy charts or infographics. Even though I like these elements from a design perspective, if they take more than 30 seconds to understand or explain then they are rather pretty and complex than informative and simple. 

TIP: Keep your text concise with bold and short insights. Back your statements only with just enough data needed to understand the key insights.

3. Be bold

This point is closely linked to critical questions to which your audience is looking for an answer. In our industry, we often use terms such as summaries, conclusions, insights and recommendations. There are definitions for each term and when to use what, but at the end of the day, what a client wants is to have clear guidelines on what to do next - regardless of how you want to label it. 

I believe it matters less if something is written as a conclusion, insight or recommendation, as long as your audience gets actionable points they can start applying immediately. That final input needs to hit the core, and making bold statements of what are the next steps is a good way to do it. 

TIP: Don’t beat around the bush. Avoid vague and soft statements. Bold, clear, and often provocative insights will have the best effect.

4. “Translate” complex concepts

“What does this mean for you?” is a question I use a lot when I try to see from the perspective of a client. While every presenter knows his or her topic insight out, as well as the materials he/she presents, the audience might not understand it immediately. Talk in short, direct sentences. Yes, even if you are convinced your audience is full of smart people. Getting lost during a presentation happens easily, and if that happens you risk losing your audience interest and engagement. 

TIP: Use plain English, no matter the audience profile or background. Break down complex concepts into smaller “biteable” pieces of information. 

5. Repeat and connect

Last but not least - my favourite tip I use all the time. A good story is built on a good flow and good flow means that you continuously build further on what you told or presented previously, meaning: continuously connect the dots. This helps to gradually build up the story, enhance the dynamics in it as well as reinforce the information shared so far.

TIP: Throughout the presentation, continuously recap and link the insights into one cohesive story.

These tips barely scratched the surface of the science behind storytelling. To keep consistent and follow the tips mentioned, I will leave you with only a few recommendations. However, if you are hungry for more advice and you want to upgrade your storytelling skills, feel free to reach out and book a coaching session in storytelling with me!  

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The need to extract meaning from dynamic datasets in a fast and flexible way is becoming increasingly urgent. By making use of the potential of internet browsers, new data visualisation tools and software packages allow us to do so. However, because of the field’s rapid evolution, we risk overlooking some of the basic aspects of data visualisation: your goal(s), striking a balance, finding inspiration, effective annotation, and interaction and animation.

First, the bad news. As data visualisation expert Andy Kirk states, “There is never a single path towards a ‘best’ solution. The inherent creativity and individualism of design work ensures that.” That’s why the following insights serve as ground rules only, and focus mainly on the most important aspects of data visualisation.

1. Define and refine your goal(s)

Whether it is a bar chart, a pie chart, or a complex interactive visualisation, it’s important to remember why you want to visualise your data in the first place. Frequently revisiting, restructuring and refining your goals will help you decide if visualisation is a good idea, and whether the data you have is sufficient to do so.

Additional contextual data may help you accomplish the task more quickly or more thoroughly — that’s why the buzzword big data was invented. Big data will also help you define the most important variables and values, as well as enable you to know more about the characteristics of your data and your users before making decisions on what is important to display or what colour palette to choose.

2. Find the right balance

In any attempt to visually represent a dataset, you will naturally be making many choices. Essentially, you’ll need to balance effectiveness and expressiveness by conveying information about your data using the appropriate visual marks — e.g. dots, lines, shapes — and assigning visual attributes that efficiently add the intended meaning to your visual components.
Making conscious and goal-driven decisions with regards to that balance will help you create a (not the) best solution. For example, you should not use size variation to express different categorical values, and quantitative differences should not be visualised with hues. The writings of computer science professor Tamara Munzner are great references when it comes to aspects of data visualisation techniques that touch on this balance.

3. Get inspired

A quick internet search for rankings of perceived accuracy from Cleveland & McGill will help you decide which visual variables and, by extension, which chart types are ideal to present your principal values. Want to dive deeper? Check out the work of Colin Ware, Director of the Data Visualization Lab, or look online for Garner’s whitepaper on integral and separable visual dimensions.
In trying to strike the right balance between these characteristics, you will find yourself at the complex intersection of statistics, graphic design and cognitive psychology. So, staying up-to-date with what happens within these fields and expanding your awareness of relevant concepts will certainly help you to make faster and more effective decisions. Viewing submissions for contests like the Malofiej awards or following blogs like Information is beautiful are also great ways to keep up with the times.

4. Use effective annotation

Another, often underrated, aspect of data visualisation is known as annotation. Annotation isn’t just about making efficient use of typography; it also calls for the smart use of titles, introductions, labels, captions, grid lines, axes and units. However, it is just as important to omit unneeded grid lines, labels, etc. — don’t simply stick with the software defaults — an important ground rule that applies to any aspect of data visualisation.
Edward R. Tufte has some useful things to say on this topic, and Noah Iliinsky, UX Architect at Amazon Web Services, and Julie Steele, Director Communications at Silicon Valley Data Science, recommend: “Minimise noise, maximise signal”. Annotation should thus be well-balanced, show what is necessary for correct interpretation, exclude anything that’s unnecessary and blend harmoniously with visual marks and channels. A best practice here is to visually send the annotation layer to the back.

5. Add interaction and animation

This is a great segue to interaction and animation. Together with bottom-up oriented visualisation tools, interaction and animation offer lots of opportunities to make interpretation more efficient. The ability to manipulate the visualisation in response to user-initiated changes and the capacity to select, zoom, scroll, or reduce a dataset on the fly allows you to go far beyond what is easily constructible within a spreadsheet or standard presentation application. These features will help you present your story in an intuitive way so that it sticks with your audience. And, when approached consciously and intelligently, it should also help you appreciate the beauty and power of the endless possibilities available to craft excellent static visualisations of your data.

It’s not so hard to choose wisely

I hope that my brief take on data visualisation will help boost your confidence in applying some of these techniques to your current project and/or make it easier to choose between different implementations. In the end, it’s all about picking the option that suits your data without getting overwhelmed by choices and solutions you don’t need. Want to know more about how we can help you with your data visualisation goals?
Don’t hesitate to get in touch!