Before diving into the world of data-based marketing, let’s start with an intriguing story: This morning, I entered a parking lot. 

What’s intriguing about it? Let’s ask the sentence itself, a marketer, a programmer, a legal expert and a data analyst. 

Entering the parking lot: The same situation, different interpretations 

The mundane and everyday situation of entering a parking lot can give rise to different stories with various perspectives: 

The legal expert would tell us that entering the parking lot is a contractual event. The sign at the entrance of the parking lot presents specific conditions for entry, such as the price and limitation of liability for valuables. Pressing the button to receive a parking ticket constitutes acceptance of these terms. When there is an “offer” and there is “acceptance,” a contractual event occurs: the formation of a parking entry contract. 

The programmer would describe a chain of digital events that occurs upon entering the parking lot. The entrance camera captures the license plate, identifies it, and transfers the information to a computer that prints the parking entry ticket with the car details and entry time. Later, this data will be used to calculate the price to be paid upon exiting the parking lot. 

The marketer would explain the reason I chose to park specifically in this parking lot, even though there are other parking lots on the same street. They would talk about the signage that caught my attention, perhaps the smooth entry experience it conveyed, and of course, the price or its calculation method compared to competitors. 

The data analyst would see my story as a treasure trove of data that can influence the parking lot’s operations and business success. The accumulation of data obtained from parking entry, including vehicle type, arrival time, departure time, parking location, and actual payment, allows for the identification of returning customers, management of peak hours in the parking lot, targeted subscription offers based on parking patterns, and more. And all of this before I even mentioned I paid through an app and what data flowed through my smartphone as a result. 

Data-Driven Marketing: Training the Data Muscle 

In the movie “Steve Jobs – The Lost Interview,” Jobs recommends that everyone learn programming or law. “Not to become a programmer or a lawyer,” clarifies Jobs, “but to learn different ways of thinking about the world.” As is often the case, he is right. The world can be interpreted in various multidimensional ways, and if you learn how to think in a particular manner and practice that thinking in your daily life, you will start to see the world differently, just like Neo in “The Matrix” that suddenly sees the world in zeros and ones and understands it differently. 

black screen with green codeing

Every organization, regardless of its size, possesses data. The question is what to do with it: how to collect, organize, and consolidate it, and most importantly, how to analyze it and use the insights in an actionable way. Data-driven marketing is a broad term that can be interpreted in many ways. Even targeting audiences on social media platforms is based on data owned by those social networks, and anyone promoting content on Facebook is essentially marketing with data. However, there is a distinction between marketing using data, and data-driven marketing. It’s not the same thing. 


Data-driven marketing implies dedicating continuous efforts to deeply understand the consumer standing in front of us, their exact needs, and what will advance them in their consumer journey, and to deliver the right content to them in the right place and at the right time. One prominent example of data-driven marketing is Denon, a manufacturer of audio products, which utilizes data as a foundation for their consumer journey management. For instance, if you try to connect a Denon device to a wireless network and encounter difficulties multiple times, you may receive a mobile video tutorial that accompanies you through the installation process. 

Another story about Denon and another brand they jointly own, Marantz, is the story of selling digital speakers with an amazing conversion rate of 60%. How did that happen? The company’s data analysts decided to explore the names users give to their wireless speakers after connecting them. One of the data points they decided to investigate was what the names could teach them about the locations of the speakers in users’ homes. And indeed, one name stood out above all others: BATHROOM. 

The immediate insight was that many users want to listen to music in the bathroom, and if the company offered a dedicated speaker for the bathroom, there would be high demand for it. The company found that they already had plans for manufacturing a waterproof wireless speaker specifically designed for the bathroom and decided to expedite its production. When direct mail was sent to customers who had a speaker defined as BATHROOM, 60% of them decided to purchase it. 

This kind of thinking can be trained, as data expert Gil Kohavi defines it: “Data is a muscle, and the organization needs to train it constantly.” 

The technology exists: The thinking needs training  

The tools used to collect, aggregate, and categorize data are fundamentally technical and technological. Even marketing automation systems are technology-based systems. However, if there is no data-savvy person accompanying the operation, and data thinking that permeates the organization up to the management level, these systems will become a white elephant or a mountain that gives birth to a mouse. In this sense, not the data will win, but the person in charge of data. 

How can your organization start training? Like in a gym, first, you need to understand what basic data you already have and what data you still lack, and then build a suitable training and measurement plan. 

First, understand what data you are already storing, what data you are missing, and strategically decide how your data mining mechanisms will work and how you will synchronize between different information systems. Secondly, establish a data team that includes representatives from different departments in the organization, who will be responsible for asking interesting questions that concern the organization, and build a plan on how to ask smart questions about the data and derive insights from the answers. Finally, build a content system that will enable you to leverage the information and insights to integrate into the consumer journey and marketing funnel. If you have done all of this, you are definitely engaged in the field of data-driven marketing.