🔎 Who Uses Information and Insight Products? Understanding the Key Personas Behind Decision-Making
Get to know the people who will use your information and insight products before you rush into developing solutions for them
Hello friends!
I hope you enjoyed learning about the decision intelligence product ecosystem and the DNA of its products.
I’m sure you’re now curious to know what type of products need to be developed and when. This week’s article will take us one step closer to answering these questions with a few more pieces to add to our product development “puzzle”.
This week, we will learn about the common personas that use information and insight products and some of the misconceptions we might have about them. I won’t focus on data products this week since many are more machine-oriented than human-oriented.
Let’s dive right in and find some of the missing pieces we need in this puzzle.
🎬 Intro: Data users have different needs
A classic mistake information and insight product developers make is assuming all their product users are mostly data-savvy individuals such as data scientists, researchers, or executives making numbers-driven decisions who want all the possible bells and whistles in a solution.
I believe this could be at least partially explained by a cognitive bias called the “Curse of Knowledge”. In a nutshell, this cognitive bias occurs when a person with specialized knowledge assumes that others share that knowledge. After all, many of us who work on developing decision intelligence products have good analytical knowledge, and it’s easy to assume our intended users are just like us.
The reality is much more complex. Not everyone who relies on insights is eager to explore complex dashboards and reports. Some simply want quick, actionable insights, while others thrive on deep analysis.
Interesting evidence is presented in the Anthropic Economic Index that reveals that data analysis-related tasks are among the most common for generative AI use these days. We can assume there’s a mismatch between the data solutions these users were handed and their skills to work with them that led them to use generative AI for support.
It is crucial to understand the different personas that interact with information and insight products. If we assume all users are the same, we risk delivering overly complex or overly simplified solutions that don’t align with their needs and might require further solutions to interpret some of the output.
Consider an executive who needs quick, high-level insights. If they’re presented with a complex, detailed report full of raw data and technical jargon, they might ignore it entirely. On the flip side, an analyst who needs to dig into the numbers would find a generic, overly summarized dashboard frustratingly shallow.
By recognizing different types of users, organizations can ensure that their information and insight products are designed with usefulness and usability in mind, offering the right level of depth, transparency, and interaction.
This article explores the four key personas behind decision-making, why they matter, and how organizations can tailor their information products for maximum impact.
👩💻👨🏾💻The Four Core Personas of Data and Insight Products
First, let’s start by mentioning that user personas are usually something that you can only discover by talking to the intended users of your solutions. User research activities such as interviews and contextual inquiry (a technique to observe and fully capture someone’s typical workflow) can help you better understand who they are and what they need in an information or insight product. They would then typically fall into one of these four user personas:
1. The Information Consumer
This persona primarily acts on insights rather than analyzing trends and raw data. They rely on clear, digestible summaries of trends and insights that help them make decisions quickly.
Who they are: Typically they are users who are part of private or public organizations, including companies, NGOs, governments, and even the military or the police. Examples can be executives, managers, policymakers, business leaders, commanders, etc.
What they need:
High-level numbers, summaries, and key takeaways
Simple visualizations, such as KPIs, trends, and benchmarks
In certain roles, they’d need automated alerts and personalized reports
Example: A CEO reviewing a sales dashboard that shows simple revenue trends without needing to manipulate raw sales data or decipher complex graphs on a dashboard
Common mistake: Designing a solution that’s too complex and time-consuming for this persona to understand on their own or with a simple explanation from another colleague
2. The Information Analyst
Unlike consumers, analysts are deeply involved in data analysis, synthesis, and interpretation. They need the ability to explore, filter, and manipulate data to draw meaningful conclusions.
Who they are: Data analysts, financial planners, market researchers, product analysts, or anyone whose job involves detailed data interpretation and needs to dig into different data sources. Just like the first persona we looked into, they usually work in an organization.
What they need:
Access to raw data that can be further analyzed (in some instances)
Interactive dashboards with the ability to drill down into different levels of granularity
Tools for trend analysis, forecasting, and statistical comparisons
Example: A digital marketing analyst assessing customer shopping-related metrics across different channels (e.g. a mobile app, a website, physical stores etc.)
Common mistake: Creating an overly simplistic solution that doesn’t allow further digging, or creating an overly complex solution without proper documentation for an analyst to fully take advantage of.
3. The Hybrid Information User
This persona balances both consumer and analyst needs, sometimes requiring high-level insights, while at other times needing deeper exploration.
Who they are: Product managers, small business owners, domain experts, and consultants. They can be employees in an organization, or work for themselves.
What they need:
Dashboards that offer both summary views and the ability to drill deeper
The flexibility to switch between quick insights and more granular data
Customizable reports based on varying levels of expertise and business needs
Example: A product manager who needs an overview of user engagement trends to share with their business stakeholders every quarter, but occasionally needs to analyze detailed feedback data.
Common mistake: Not understanding the context and the workflow of this persona. This could lead to designing a solution that only covers part of this persona’s workflow.
4. The Personal Data Tracker
This persona uses insights to track personal progress and make lifestyle choices and improvements. They rely on simple, intuitive analytics rather than complex data manipulation.
Who they are: Individuals who monitor trends around their lifestyle such as fitness enthusiasts tracking their exercise progress, individuals monitoring personal finance trends, or hobbyists analyzing patterns in their interests.
What they need:
Intuitive and visually appealing dashboards that are embedded into the solutions they already use for other purposes (e.g. mobile banking app, fitness app, etc.)
Seeing simple trends over time (e.g., weekly fitness stats, monthly spending habits, sports stats, etc.).
Notifications and goal-setting features to encourage engagement and depending on the use case
Example: A runner using a fitness app to track their weekly mileage and pace trends
Common mistake: Designing a standalone instead of an embedded solution for this persona. Designing a solution that’s too complex for a non-business user.
In addition, it’s important to mention that there might be some sub-groups within these four personas. For instance, some personal trackers might want to access more detailed transaction-level data to track their spending a bit more precisely and to pinpoint unfamiliar transactions that might have been linked to fraudulent activity.
Also, information consumers, as well as personal data trackers could benefit more from insight products because, by definition, they spend less time analyzing data and their main concern is quick decision-making.
To better represent the four personas visually, let’s take a look at what they would look like in terms of depth of analysis:
ℹ️ Conclusion: Know your users and their needs
Not all users of information and insight products are the same, and assuming they are can lead to frustration, poor adoption, and ineffective decision-making. By identifying the core personas organizations can create user-friendly, and impactful information and insight products for them.
The key takeaway? Tailoring information to the right persona isn’t just about aesthetics or usability. It’s about empowering better decisions. As businesses and consumers continue to navigate an increasingly data-informed world, designing decision intelligence products with personas in mind will be the difference between data that informs and data that gets ignored.
What kind of persona do you most often design for? Share your experiences in the comments below 👇🏻
In the next article, I’ll present some interesting articles and data visualizations I came across recently.
If you know anyone who works on decision intelligence products or is interested in this space, invite them to subscribe to Signal to Product at this link (signaltoproduct.substack.com) or share this post with them.
If a friend sent it to you and you’d like to learn more about this fascinating space of decision intelligence products subscribe for free to Signal to Product now to get my articles, case studies, and more directly to your inbox.
©Yaron Cohen - 2025
Hi! Would love to know what research you based these four categories on?
Another great post Yaron! Keep championing user-centered choices, because THAT'S how data makes a difference. Thanks for sharing🤗