DATA INTERPRETATION: THE PATH TO REAL DECISIONS

In an increasingly digital world where users have more specific needs, marketing has found in the results of various tactics an ally for understanding people’s behavior, serving as a fundamental basis for predicting the path to follow.

In recent years, there has been significant progress in understanding the results of various actions executed in Digital Marketing. There has been a rapid advancement in building advertising strategies based on solid data, moving further away from decisions made by intuition. A new component has been added to this path: data interpretation.

What is data interpretation?

With this focus, greater attention has been given to the results, considering them as the union between qualitative and quantitative analysis. This allows for viewing demographic, geographic aspects, and even identifying consumer preferences in a numerical result. It facilitates the understanding of the audience and key points that will enable informed and especially realistic decision-making.

With the aim of making this interpretation more accessible and applicable in different result analysis spaces, in this first installment, we list a group of concepts that, from our experience, can be useful to understand why, for what, and how to be part of this new trend that data reporting and analysis areas face.

What are the basic concepts for data interpretation?

1. Metrics: These are numerical values that serve as the quantitative basis for analysis. They are essential for evaluating KPI performance and can range from the sum of two values to calculating averages.
   • Example: Two million users reached on Meta Ads or 300 comments on our Instagram Reel.
2. Dimension: After identifying the numerical result, we move on to categorize them. Through this classification, the representations of each numerical value can be understood, being a fundamental aspect of qualitative analysis.
   • Example: Of the two million users reached on Meta Ads, 1.5 million are men, 500,000 are women, 60% live in Bogotá, and the remaining 40% reside between Cartagena, Medellín, and Cali.
3. Insight: After the “raw” results and their categorization, we seek the truth that needs to be told, the idea that responds to a human reason.
   • Example: Identifying that the Meta Ads campaign is for an innovative sportswear brand in materials, leveraging post-pandemic trends, sports diversity in Bogotá, and the growing interest of middle-aged men in physical activity.

Steps to establish a good data interpretation:

1. Identify and generate recommendations: With knowledge of qualitative, quantitative results, and insight, it’s time to establish the possible path to reach the business objective, considering external factors.
   • Example: Build the buyer persona for the identified segment and include it in the brand’s strategy.
2. Find the opportunity: Look for an innovative proposal fueled by data, qualitative analysis, and recommendations.
   • Example: Alliances with content creators in sports disciplines and digital communication for men interested in comfort and durable materials.

There you go, we now know the basic concepts! This is the first step in data interpretation. In our next article, we will break down how to transform these interpretations into concrete actions, exploring effective strategies to turn information into tangible impact in decisions made from the data. Stay tuned for our next publication and get ready to unleash the power of interpretation in real decisions. 🚀