How to use data analysis to sell more?
Posted: Tue Apr 22, 2025 4:36 am
In recent years, there has been increasing talk about the importance of measuring and analyzing the data and results of each strategy, team or company as a whole.
You, like me, already use several data measurement and monitoring tools on a daily basis, whether they are more complex and detailed platforms such as a marketing automation tool or even the routine Facebook to monitor updates on our friends list.
In this article, I will explain how the data analysis process will help you sell more and increase your company's revenue.
But what is data analysis?
When we talk about analyzing uruguay mobile database data, we are talking about the process that consists of transforming a set of data, whether structured or unstructured, with the aim of being able to verify, understand and transform a specific set of data into information .
For example, let's suppose you have a spreadsheet listing all active prospects in your sales funnel and in that same spreadsheet you have a column listing the origin of each one and the stage of the funnel they are in.
At first, the spreadsheet is just a set of data. But once you organize, filter, and analyze all of that data, you realize that only a small percentage of leads make it to the proposal or quote stage. That’s a piece of information.
Data analysis can be done both to identify a problem or bottleneck, as well as to obtain better details about it or to find answers and solutions, enabling what we call data-driven decision-making .
Furthermore, it is possible to make behavioral predictions, optimize future investments and predict financial and economic crises by analyzing data from the population or specific clusters.
An article published in 2015 by the international research group Gartner predicted that by 2017 “most analysts and business professionals will have access to self-service tools for data preparation and analysis” and this scenario is already present.
But to make the right decisions, it is essential that all this data is consistent and true. Only then is it possible to generate useful reports .
How to generate a useful report?
It may seem extremely redundant, but with the large volume of tools and processes that are part of our daily lives, it is very common to come across reports that are rich in data, but that cannot be used to make decisions.
And when we talk about making decisions, we are talking about it in a very broad way. We can use reports to redirect investments, understand behaviors and detect purchasing patterns, and even identify alerts and red flags in customers who are close to canceling a service, for example.
But before we even begin the process, we need to define an objective or a question to be answered. This way, we can direct and filter the exact data that will help us understand and respond to each step more assertively and with less noise.
Using the same example we mentioned earlier, let's assume that the objective is to detect the main bottleneck of the sales team within the stages of the sales process.
You, like me, already use several data measurement and monitoring tools on a daily basis, whether they are more complex and detailed platforms such as a marketing automation tool or even the routine Facebook to monitor updates on our friends list.
In this article, I will explain how the data analysis process will help you sell more and increase your company's revenue.
But what is data analysis?
When we talk about analyzing uruguay mobile database data, we are talking about the process that consists of transforming a set of data, whether structured or unstructured, with the aim of being able to verify, understand and transform a specific set of data into information .
For example, let's suppose you have a spreadsheet listing all active prospects in your sales funnel and in that same spreadsheet you have a column listing the origin of each one and the stage of the funnel they are in.
At first, the spreadsheet is just a set of data. But once you organize, filter, and analyze all of that data, you realize that only a small percentage of leads make it to the proposal or quote stage. That’s a piece of information.
Data analysis can be done both to identify a problem or bottleneck, as well as to obtain better details about it or to find answers and solutions, enabling what we call data-driven decision-making .
Furthermore, it is possible to make behavioral predictions, optimize future investments and predict financial and economic crises by analyzing data from the population or specific clusters.
An article published in 2015 by the international research group Gartner predicted that by 2017 “most analysts and business professionals will have access to self-service tools for data preparation and analysis” and this scenario is already present.
But to make the right decisions, it is essential that all this data is consistent and true. Only then is it possible to generate useful reports .
How to generate a useful report?
It may seem extremely redundant, but with the large volume of tools and processes that are part of our daily lives, it is very common to come across reports that are rich in data, but that cannot be used to make decisions.
And when we talk about making decisions, we are talking about it in a very broad way. We can use reports to redirect investments, understand behaviors and detect purchasing patterns, and even identify alerts and red flags in customers who are close to canceling a service, for example.
But before we even begin the process, we need to define an objective or a question to be answered. This way, we can direct and filter the exact data that will help us understand and respond to each step more assertively and with less noise.
Using the same example we mentioned earlier, let's assume that the objective is to detect the main bottleneck of the sales team within the stages of the sales process.