Citizen Data Scientists: How Everyone Can Make Sense of Data

You either love it or hate it, but data is here to stay. If it scares you, you can try to ignore it. If it comforts you, you probably want to crunch it. But the fact is: these days, every single action generates data. Just think about a random day in your life: your GPS route when driving to work, paying at the grocery store, the number of products you’ve sold at work, and so on. There is so much valuable information hiding in that data, which helps make our lives much easier. Whether it’s finding the fastest route to work, keeping an eye on your personal finances, or understanding what enabled you to sell so many products!

For a long time, BI specialists, data scientists, and other data experts were the answer to making sense of all that data. But today, everyone wants to be data-savvy, and find new insights without needing a Ph.D. in data science. Luckily, new emerging tools are opening up ‘citizen data science’: a way for anyone to make sense of their own data.

What is a citizen data scientist?

Citizen data scientists are on the rise. But what are they exactly? As Gartner puts it:

In other words, this is someone who has no background in data science or programming. However, they have a strong business background and combine that expertise with user-friendly technologies to make sense of their data and make smart business decisions.

These business users are widespread across any organization, with some of the most common roles being:

• Sales & marketing;
• Customer service;
• Human Resources;
• Operations & Logistics;
• Project/product management;
• Finance, accounting, or administration;

However, the ability to turn data into insights yourself isn’t only of value in a business context. Also individual consumers rely on data to make better decisions in their private lives.

What insights are data consumers looking for?

The main reason data consumers are looking to access data insights is to become smarter. Data can help them figure out what their ‘next best action’ is, which makes their lives easier.

But which insights are they looking for specifically? Let’s illustrate a couple of common use cases for citizen data scientists.

• E-commerce/retail: Think of a salesperson analyzing sales volumes on their webshop, or a marketer who wants to understand how users buy on their website. Both teams can use that website usage data to optimize which products they will put in promotion, and where to promote them on their website.
• Logistics: Think of a logistics planner who plans the delivery of packages. He’ll want to give his truck driver the shortest & fastest route for delivery, and load packages with the same destination area on the same truck. A big-picture data overview can help them optimize the logistics process, save money and make life easier for their truckers!
• Digital Marketing: A marketer wants to analyze the results of their digital campaigns and website data to understand which messages or channels are most efficient within their go-to-market strategy.
• Consumers: And it goes further than only business. Individual consumers may want to keep track of their personal financials to spend & save money more effectively or monitor their medication intake through remote patient caring systems. It can go as far as optimizing your car usage for less CO2 etc,… By giving consumers the ability to analyze their data at any given moment, they make better choices.

These are just a couple of scenarios where business users and consumers are taking matters into their own hands, and making their data actionable without the help of a data scientist.

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So, more people want to analyze data themselves…

I can hear you thinking: “Why make it difficult? Just ask a data scientist or data expert to give them the right insights.”

Well, there are multiple reasons why data consumers are taking over the steering wheel:

1. Business people need data in their day-to-day operations. In many business roles, performance is measured through KPIs, and more and more business decisions are made based on what their data tells them. They heavily rely on their data to take the next step and find the road to business success.
2. There’s a shortage of data scientists. Simply put, there aren’t enough data scientists to keep up with the demand for insights. Besides, with the amount of data growing every day, data scientists are indispensable for more complex analytical tasks, like data cleaning, data modeling, AI and ML algorithms. This leaves less time to tackle business analysis questions. And simply, given the shortage, the business analysis would be a suboptimal use of their time.
3. Technology finally allows them to take control. Before, business users simply couldn’t analyze their data because they didn’t have access to the right tools or knowledge. Technology has paved the way for democratizing data science. Drag & drop tools make it easier than ever to slice & dice any business data, and take away the complexity a business user would have needed a data scientist for.
4. Business users enrich the data by putting it in context. Just like a business user doesn’t know how to code, a data scientist doesn’t know the business side of things. A data scientist might spot a drop in revenue for a specific product, but only the salesperson knows that this is because they ran a heavy sales promotion on the article. Putting things in context will yield much richer and deeper insights.

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Why should SaaS product owners & B2C service providers care?

New technology allows business users and consumers to take ownership of their data. They can now make relevant data-driven decisions without being dependent on technical staff.

From the point of view of an end-user, a consumer, or an employee, this is revolutionary. But why should you care about it as a technology product vendor? And why should you even encourage it?

First of all, B2B SaaS companies will help drive positive change in the organization of their end-users. Equipping users with the tools they need to analyze their own data will:

1. Alleviate the work of their data experts. They can now focus on more innovative, core analytics techniques like AI and ML, which will be the true game-changers in the field of data;
2. Make their business users data-smart. Business people will feel encouraged by your technology to use data in decision-making. It will help them work more efficiently and take action faster, making them feel truly empowered;
3. Position your product as innovative & supportive. Opening up your data to your users creates trust & connection with your users, resulting in better customer loyalty;

Likewise, B2C apps can give consumers ownership over their consumption data. Just think about the many banking and fitness apps that exist. What if users of those apps could get the possibility not only to do data exploration their own financial or health data, but even to create their own “infographics”, completely personalized to their needs?

People love knowledge, and therefore they love data. So the more knowledge you give at their disposal, the more your product will stick.

Final notes

New emerging technologies enable anyone to look at their data critically, whether in a B2B or B2C context. No business user should only be limited to a single data snapshot created by a data scientist with less business context. Let them explore and create their own view on the data, based on the expertise and context they bring to the table. Let them spit to the bottom of their data until they find the exact insight they need, without writing a single line of code.

As a result, your platform or app users will get much richer insights and become a truly data-driven organization. And for your SaaS platform or consumer app, it means more engaged users and very likely, business growth.

Do your users want more tools to become data-smart? Talk to our product experts to discover how you can add data exploration to your SaaS product!