Digital Marketing vs. Data Marketing
Posted: Tue Apr 22, 2025 4:31 am
When digital marketing arrived, its big differentiator was being able to measure every step, every action. With it, we were able to know website accesses, banner clicks, Facebook Ads engagement… But what about Data Marketing, what’s the big difference?
Data-Based Marketing consists of cross-referencing information from the three data sources you saw in the image above – social data (social media and portals), company data and data from things – to obtain the most accurate information possible. If digital marketing gives you the data, Data-Based Marketing goes beyond the web, cross-referencing other sources and making you act based on this data.
Creating a strategy based on costa rica mobile database Data Marketing means intelligently reading all available data and thinking about actions based on that data, nothing else.
970x160px banner article ebook After all, what is Data Marketing?
How to work with data?
We now understand what Data Marketing is and its importance in digital marketing. Now let’s see, step by step, how to extract this data and transform it into clear information.
One important thing that should always be remembered is that you need to have a clear objective for the data analysis that you are going to do. This is because there is an infinity of information and if you do not know clearly what you want, the chance of getting lost is great. So keep in mind why you are analyzing that data and where you want to get with it.
Here at Buscar ID, we follow a 5-step process to create a useful report that truly gives you the foundation you need to create insights. These steps are:
Data extraction
The first thing you need to know is that data must be extracted constantly , at all times. Another important factor is to realize that there are 3 types of data:
data-types
Structured data is more related to the company. Semi-structured data is related to the world of digital marketing. Unstructured data basically includes data from social media, news portals and other media that do not have any information organization.
Here we come across a factor that usually requires a lot of work. The data is spread across different platforms and sources. Therefore, this step is usually one of the most time-consuming in the entire process.
Furthermore, large companies have several departments. Some of them are not open enough to share information about their sector, making deeper analysis difficult.
Data organization
After extracting all the information, it's time to clean the data, see which ones are relevant, check if they are correct and organize them. In other words, you will take all the data and create grouping clusters to help you understand which ones are related and complementary. Here, the idea is to classify what the data is giving us so that we can understand what we can actually get useful out of a given piece of information.
And one point is very important at this stage. Never, ever underestimate or ignore a certain piece of information right away , because it may not be useful to you, but it will be extremely important to others. Therefore, carefully evaluate what may or may not be interesting to the audience that will consume the information that is being generated.
The idea is that at the end of this stage you will be able to have data from various sources structured and organized.
Understanding the data
At this stage, you will begin to understand that range of data, see all the information that is there and start cross-referencing the data. Here we define how the information will actually be understood, that is, whether the arrangement of this data will be done visually or textually.
If you have the availability, it is interesting to involve User Experience professionals who have experience in Data Visualization so that they can help you transform the way you visualize this data, so that it is easy to read and understand.
The most important thing at this stage is to clean and group the data so that it can be understood and points towards your objective.
Data-Based Marketing consists of cross-referencing information from the three data sources you saw in the image above – social data (social media and portals), company data and data from things – to obtain the most accurate information possible. If digital marketing gives you the data, Data-Based Marketing goes beyond the web, cross-referencing other sources and making you act based on this data.
Creating a strategy based on costa rica mobile database Data Marketing means intelligently reading all available data and thinking about actions based on that data, nothing else.
970x160px banner article ebook After all, what is Data Marketing?
How to work with data?
We now understand what Data Marketing is and its importance in digital marketing. Now let’s see, step by step, how to extract this data and transform it into clear information.
One important thing that should always be remembered is that you need to have a clear objective for the data analysis that you are going to do. This is because there is an infinity of information and if you do not know clearly what you want, the chance of getting lost is great. So keep in mind why you are analyzing that data and where you want to get with it.
Here at Buscar ID, we follow a 5-step process to create a useful report that truly gives you the foundation you need to create insights. These steps are:
Data extraction
The first thing you need to know is that data must be extracted constantly , at all times. Another important factor is to realize that there are 3 types of data:
data-types
Structured data is more related to the company. Semi-structured data is related to the world of digital marketing. Unstructured data basically includes data from social media, news portals and other media that do not have any information organization.
Here we come across a factor that usually requires a lot of work. The data is spread across different platforms and sources. Therefore, this step is usually one of the most time-consuming in the entire process.
Furthermore, large companies have several departments. Some of them are not open enough to share information about their sector, making deeper analysis difficult.
Data organization
After extracting all the information, it's time to clean the data, see which ones are relevant, check if they are correct and organize them. In other words, you will take all the data and create grouping clusters to help you understand which ones are related and complementary. Here, the idea is to classify what the data is giving us so that we can understand what we can actually get useful out of a given piece of information.
And one point is very important at this stage. Never, ever underestimate or ignore a certain piece of information right away , because it may not be useful to you, but it will be extremely important to others. Therefore, carefully evaluate what may or may not be interesting to the audience that will consume the information that is being generated.
The idea is that at the end of this stage you will be able to have data from various sources structured and organized.
Understanding the data
At this stage, you will begin to understand that range of data, see all the information that is there and start cross-referencing the data. Here we define how the information will actually be understood, that is, whether the arrangement of this data will be done visually or textually.
If you have the availability, it is interesting to involve User Experience professionals who have experience in Data Visualization so that they can help you transform the way you visualize this data, so that it is easy to read and understand.
The most important thing at this stage is to clean and group the data so that it can be understood and points towards your objective.