In today's digital age data is widely available to companies of all sizes and industries. However, simply having access to data does not necessarily translate to success. To truly take advantage of the wealth of information available online, companies need to understand not only the science of data, but also the art of interpretation, the “why” beyond the metrics.

One of the key challenges facing companies today is how to make sense of the vast amount of data available to them. While data science and analytics tools can provide important insights, they are only as valuable as the interpretation and action that follow. A recent study by McKinsey & Company found that only 20% of data projects actually make it into production, largely due to lack of understanding and buy-in from stakeholders.

This is where the art of interpretation comes in. Human vision and intuition when combined with data science can provide a powerful perspective that helps translate data into actionable insights.

1. The science of data : refers to the technical aspects of data collection, processing and analysis. It involves using algorithms to uncover patterns and insights from large sets of data. However, the results of these analyses are often complex and difficult for non-experts to understand and act upon.

2. The art of interpretation : involves taking the insights gained from data science and understanding how they can be applied to the specific business context. It requires human intuition, creativity, and critical thinking to make sense of the data and determine what it means for the business. It takes into account the business objectives, the brand purpose and vision, the audience mindset, values and the cultural relevance.

A recent study by Gartner found that organizations that effectively combine data-driven insights with human intuition and creativity are more likely to achieve a competitive advantage. In order to take advantage of this, companies need to invest in building a data-savvy culture, where all employees are educated on the basics of data interpretation and analysis. This will ensure that everyone in the organization has a shared understanding of the data and can work together to make data-driven decisions.

5 pillars to make data insights actionable :

1. Define a clear briefing process : By identifying and clearly articulating the problem or question at hand, companies can focus their efforts on finding relevant and useful information.

2. Build a framework for interpretation : such as the "4 C's" context, comparison, correlation, and causality.

3. Involve cross-functional stakeholders : bridge the gap between strategists, sales, marketing and tech teams in the process to ensure that the data is being interpreted from various perspectives.

4. Explore new territories : By investigating different audiences spaces, leveraging first party and third party data to uncover emerging signals.

5. Invest in data visualization tools and storytelling techniques : to present data narratives in a way that is easy to understand and communicate.

Best case :

Situation : A good example is the business case for AXA's "KNOW YOU CAN" campaign, which aimed to reposition the company as a brand that empowers its clients before life issues. I worked on this project as a data lead at Publicis Conseil, and it was the result of a close collaboration between the data team and the strategic planning team.

Task : The goal was to research and identify triggers surrounding the concept of a better life, such as health, family, and fulfillment.

Action : The research included a hybrid methodology, combining a panel study with social listening to understand the need for empowerment and consumer's triggers, as well as a search analysis on key questions related to a better life. Knowing how to interpret the data based on the emotional intensity of the topics expressed and the opportunity to preempt them as a brand helped our team to identify and select four key topics expressed by consumers for a better life: the need for change, the need to overcome obstacles, the need for support, and the pride in achieving goals.

Results : The campaign slogan "Know You Can" positioned AXA as an encouraging partner in life, featuring professional tennis player Serena Williams in the campaign. The campaign was launched globally, including online with videos featuring inspirational quotes from Williams and later with stories from Liverpool FC players. The campaign reached millions of people around the globe and helped reinforce the brand equity. The approach was also implemented as a repeatable data empathy methodology that was duplicated for other projects.

Data insights are not the final step in the process, but rather the first step towards taking action that drives business outcomes.

The human intuition brings the empathy and the values, while the machine intelligence brings the scope and the scale. Moving beyond the science of data to the art of interpretation allows for a deeper understanding of human behavior and creates strategies that truly connect with people.

By understanding the human story behind the data, companies will resonate with their audiences.

Seddik Cherif - Head of Insights at Twitter France