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23 November 2018

What we learned at Web Summit 2018: Why adding a human touch to data is important

Today’s fast-paced, technology-driven society has drastically changed user expectations and led to a more demanding customer base. Businesses today face an entirely new set of challenges and expectations.

Luckily, data can give you valuable insights into your customers and prospects. It’s now relatively easy to create a profile of your best buyers, their life-time value, their buying preferences, etc. With the help of data you can now understand, meet, and even predict your customers’ expectations.

However, now that most businesses are driven by data, we see other challenges occurring. As tons of data are collected every day, it’s easy for companies or employees to drown in the sea of data they collect, or be intimidated by the pile of information coming at them. And how can we find the relevant data for the business question you want to solve? Moreover, how can your data team make sure the collected data is understood and thus used by everyone within your organization?

Why adding a human touch to your data is important

Numbers need stories and stories need numbers

Today the majority of companies collect data, however only a few use it to make strategic decisions.  So, what I learned at the Web Summit 2018 is that, to fully exploit the potential of your data, you need a qualitative human understanding of it.

In other words, you need to go beyond juggling numbers to understand what they’re telling you. And secondly, you need to make sure everyone within your organization understands and is able to work with the data you collect.

As Karthic Bala, Chief Data Officer at Condé Nast, said during the Web Summit: data represents real stories. And when you start to play with your data, you can start to see how each data point is related to another. The data patterns you discover, can help you create the story behind the collected data. Hence, by understanding what type of relationships to look for, you can find those stories sooner, and benefit from them to make strategic decisions.

Humanized data, what's in a name

The meaning of the term ‘humanized data’ is twofold: on the one hand we can say that lately there has been some criticism of the fact that when using data you might lose sight of the humans behind it, and that each data point is not just a number but a record of a human interaction. So, if we talk about humanizing data in this context, it addresses the question of how data can get in touch with the human interaction behind it.

Let’s clarify with an example mentioned during the Summit by Elaine Rodrigo, Chief Strategy and Insights Officer at Danone: Danone has developed a social listening tool ‘Radarly’ to discover online trends and to discover how people lead lives that are always on. Afterwards, Danone leverages the outcome internally to test what they’ve noticed online. By doing this, the company does not just follow online trends, but they turn data into real life stories which are then used to drive innovation and to define a brand strategy.

On the other hand, humanizing data can also be understood as the practice of making it easy for audiences of all levels to understand and leverage data. For example, if the user interface of your business intelligence dashboard that gathers all your data is disorganized, cluttered or incomprehensible, it will simply not be used by the people who need to use it.

As
Karthic Bala said, he once built a dashboard for the editors at his previous company ‘Everyday Health’ and asked them to spend 10 minutes every day on it. However, when he came in the office in the morning, he saw that his team looked at the dashboard for 10 minutes, closed it and continued with their day-to-day tasks without using the data. So, what happened was that the editors just did not understand how to use their dashboard. Conclusion: when building a dashboard, you need to connect with the right end user, otherwise they will just not use it.

The importance of humanized data

Why should organizations make an effort to humanize data? The answer is simple: mountains of data are worthless if you can’t pull out valuable insights from it. As machines become smarter every day, they get better at collecting and analyzing data than humans today. However, it doesn’t stop there. Adding a human touch to your data is required to make sure that the insights you have gained identify relevant and actionable information, meaning that you still need your data analysts to interpret the data and translate it into plain and actionable language.

Secondly, humanizing data will give employees a sense of how important it is to understand data, which will make it more likely they will use and work with it. So, when you can be sure the user interface of your dashboard is understood by business owners, managers or your creative team, it will allow them to better understand the collected data and use it in their decision-making processes.

How to transform data into understandable and actionable insights

Whether you are a marketer, an advertiser or a business owner, you want to be in a situation where you optimize everything you do. Hence, collecting data is the most important thing you can do to capture your customers’ needs. However, if you let your collected data remain as numbers, it will only bring you limited value. You need to find a common language to understand what is going on in the world and to make it understandable not only for your data experts but for everyone within your organization.

Turning data into understandable and actionable insights might seem complicated, but the following tips will already take you a step further:

  • Bring all your data to one place: Your common connector to make smart business decisions is data, but it doesn’t help if your data is spread out within your organization or applied in silos within departments. So, the first step you need to take is to blend or connect your data sources correctly. Only by breaking down silos and bringing all your data to one place can you start playing with it.
  • Build a team and identify strategic partners: Transforming data into understandable insights is not an easy process, so you probably can’t do it all yourself. You need to build a team of people with various skills. It is quite possible that you won’t find them all internally, so don’t be afraid to identify strategic partners who can help you in this process.
  • Add a human touch to your analytical processes: Machines today are better at gathering and analyzing information; however, they are not able to understand the nuances of the human mind. As companies collect huge amounts of data every day, a lot of insights remain undetected. Why? Because machines are not yet ready to take into account the physical and psychological context in which these data points where collected. You therefore need to apply common sense to your findings. You need a human interpretation of your data points  only then you can improve the accuracy and quality of your insights.
  • Connect with the end user when building a dashboard: Not all people are used to applying a data-driven mindset, so it’s possible they won’t work with the dashboards you created. In order to avoid this, you need to make sure that the people that need to use a dashboard on a day-to-day basis understand it and can work with it.  They need to make it their own, otherwise they will simply not use it.       

Here are the key characteristics you need to keep in mind when building a dashboard:

  • The whole display needs to fit on a single computer screen
  • It must only show the most important KPIs
  • Interactivity can be used, but should not be required to see underperforming KPIs.
  • It is automatically updated and is most effective when it is done on a daily basis.
  • It is usually custom-built and requires a high investment in UX/UI design. 

So, what I can conclude from the Web Summit is that in order to fully exploit the potential of your data you need to look behind the numbers. Rather than relying on machine-based interpretations, you need to interpret your findings from a human perspective. Secondly, you need to make sure your insights are translated within your organization in plain and understandable language and that dashboards that display those insights are understood by the people who need it most. Only companies that make data humanization a priority will be able to differentiate their brand, increase sales and achieve growth. 

The right business expert with in-depth knowledge available in-house

Still not entirely sure how to proceed after reading this article? No worries, for every data challenge, we at Quanteus Group can bring the necessary in-depth expertise by leveraging both the technical and business know-how of our different entities to offer you an end-to-end solution:

  • The House of Marketing puts its spike in data-driven marketing and is here to help you distill the right insights from your data to drive your strategic marketing decisions;
  • Our BrightWolves consultants use their deep financial, quantitative and analytical skills to support CEOs & CFOs in defining their corporate strategy by leveraging data;
  • HighMind designs and builds data-driven solutions that fit your needs and have a solid technical foundation that can be integrated in your architecture. These solutions are the glue between your business goals and technical reality;
  • Upthrust’s UX/UI team is trained to design custom-build, understandable and appealing dashboards which deliver you and your team the best possible experience.

But moreover, our consultants are always guided by a team of experienced experts. To deliver your solutions, we will always build a team that has a combined skill set to guarantee the perfect talent mix for your project.

Want to know more about data analytics?

Wondering what ‘data analytics’ means and what can marketers gain from it? How do marketers use data analytics and how well are they using their tools? And which data skills should marketers have now, but also in the future?

Register for our 3-part article series and discover the full interview with marketing professor Koen Pauwels on data analytics for marketing. 

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References: Brandingmag, DentsuHumanising Data, InteqnaPSafeSAS Blogs, Social Marketing Fella and Zurb.

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