Post by account_disabled on Mar 4, 2024 23:28:51 GMT -5
The term big data generically indicates a collection of data so extensive in terms of volume, velocity and variety that it requires specific technologies and analytical methods for the extraction of value or knowledge. It is used to refer to the ability to analyze or extrapolate and relate an enormous amount of heterogeneous, structured and unstructured data, with the aim of discovering the links between different phenomena (for example correlations) and predicting future ones.” In other words, when we operate on the web, search for something on search engines or access an app, we leave traces of our actions, choices, preferences and interests.
These behaviors of ours generate a whole series of data and information: big data. They are heterogeneous in nature, both structured data, coming for example from the database, and Hong Kong Telegram Number Data unstructured data, such as email addresses obtained from profiles. They are measured in zettabytes, or billions of terabytes, and can refer to: information obtained from the web, social media and apps, such as the sites consulted, the most clicked contents, the time spent on a page; more classic and generic information, such as age, gender, place of residence, places frequented. But what are they for? Big data is very useful to companies because they have the task of extrapolating and obtaining as much information as possible , increasingly detailed and precise, in order to identify the real needs of their buyer personas and, consequently, create tailor-made strategies.
If you are thinking of adopting a data driven strategy within your company, for example, you might consider adding a marketing analyst to your team who takes care of data analysis. How to adopt a data driven strategy in your company To answer the initial question “ Is it worth adopting data driven marketing for my company? ”, the answer is “yes, you should”. Of course, building a data driven strategy is not a simple and immediate job . It takes time and effort! The first thing to do? Try to group the mass of data collected in a logical sense, ordering it based on priorities and therefore evaluating which are really important and which are not. And then, we need to measure and analyze them, in order to understand which path to take. Even here, however, it takes time to review the mass of data and to extrapolate useful information from them.
These behaviors of ours generate a whole series of data and information: big data. They are heterogeneous in nature, both structured data, coming for example from the database, and Hong Kong Telegram Number Data unstructured data, such as email addresses obtained from profiles. They are measured in zettabytes, or billions of terabytes, and can refer to: information obtained from the web, social media and apps, such as the sites consulted, the most clicked contents, the time spent on a page; more classic and generic information, such as age, gender, place of residence, places frequented. But what are they for? Big data is very useful to companies because they have the task of extrapolating and obtaining as much information as possible , increasingly detailed and precise, in order to identify the real needs of their buyer personas and, consequently, create tailor-made strategies.
If you are thinking of adopting a data driven strategy within your company, for example, you might consider adding a marketing analyst to your team who takes care of data analysis. How to adopt a data driven strategy in your company To answer the initial question “ Is it worth adopting data driven marketing for my company? ”, the answer is “yes, you should”. Of course, building a data driven strategy is not a simple and immediate job . It takes time and effort! The first thing to do? Try to group the mass of data collected in a logical sense, ordering it based on priorities and therefore evaluating which are really important and which are not. And then, we need to measure and analyze them, in order to understand which path to take. Even here, however, it takes time to review the mass of data and to extrapolate useful information from them.