How to turn your Big Data into a Machine Learning process that sells like ever

From small services to big retailers, businesses will keep increasing their investments in technology to enhance their performance and profitability. To do so, a clever digital strategy combining the correct tools, resources and intelligence is essential to improve customer experience, reduce sales frictions and optimise budget.

How technology can help you with this challenge?

Among media channels, social media, SEO, content marketing, CRM and every known digital marketing asset, there is one thing behind them which must be controlled to achieve the desired success: data.

Your data is your driver for understanding and improving your business processes, allowing you to save money and time.

In this post, we explain how you must treat your data, how rich it is for your company, how it can make your business a lot more profitable, and how you can leverage an artificial intelligence strategy based on the information you constantly generate.

Quick Big Data Overview

If you want to deeply know your customer journey, increase retention, stimulate reorders, reduce purchasing process frictions, find new clients and identify market trends you must rely on Data.

Luckily, whether you run a small business or a big company, there are a lot of tools and platforms from which you can collect and manage your data.

But the headaches might start when you have too much data collected, and start missing what metrics you should focus on. This magnitude of information is well-known as Big Data. Big Data is a larger and complex set of data from new data sources, stored in a server or cloud.

It is generally distinguished by three characteristics: increasing volume, variety of data and transfer speed.

In addition, Big Data can help you improve your decisions and sales conversion allowing you to consult it at any time in real time. That’s why a good infrastructure is necessary to provide you with speed.

It also allows you to log information according to your query fields, ensuring its integrity and becoming a source of reliable information for your business.

Through your Big Data, you can mine a variety of rich information that helps you create a personalised relationship with your customers, turning your sales process and experience better than ever.

Use of Big Data for Artificial Intelligence and Machine Learning

Before talking about Machine Learning, let’s quickly understand the role of Artificial Intelligence for Marketing and Sales and how it relates to Machine Learning.

If we go to Wikipedia, it says:

“AI (Artificial Intelligence) is intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals including humans. Leading AI textbooks define the field as the study of “intelligent agents”: any system that perceives its environment and takes actions that maximise its chance of achieving its goals. Some popular accounts use the term “artificial intelligence” to describe machines that mimic cognitive functions that humans associate with the human mind, such as learning and problem-solving.”

AI (Artificial Intelligence) is composed of several different technology branches, such as computer vision, Natural Language Processing, Robotics, Deep Learning, Expert Systems and many others, including Machine Learning.

The use of Machine Learning for Marketing and Sales is an AI process that helps you identify patterns within your Big Data.

By identifying those patterns, Machine Learning helps make predictions and improve them over time.

There are many different tools and systems that you can rely on to deploy a Machine Learning strategy, such as Data and Cloud services, automation platforms, content optimisation and personalisation tools and several other solutions that can integrate into your channels.

Once you have these processes up and running well, you can automate the understanding of your customers steps throughout the purchasing journey, allowing you to personalise your messages and help with the decision-making process.

A Machine Learning process helps you reduce time and costs by creating an automated relationship and experience according to each customer’s profile, especially when combined with the right platforms and expert creative team.

Our process at Cadastra

Whether you still haven’t put it in place or are not happy with your current Data and Machine Learning strategy, Cadastra may be the right partner for you.

At Cadastra we understand that having a lot of data is a good problem and converting them into information is an opportunity. That’s why we add knowledge and execute actions to generate results and capture value.

Our goal is to transform the reality of companies by structuring and democratising data. In an extremely dynamic world, with changes almost daily, the need for rich and accurate information is growing at an exponential rate.

Therefore, we help organisations obtain next-generation data with the necessary experience to know what, how and when to measure what is relevant.

Check how our Data Hub will help you by combining Data Engineering, Data Science, Data Strategy and Analytics in an agile framework process:

The first step of the process is to deeply understand the Analytical Maturity of your company. We have developed a technology that identifies when the organisation is in its analytical maturity called Business Analytical Score (BAS).

Through this score, we can monitor the evolution of organisations and how they use data internally for decision-making so that we can evaluate, plan, execute and assist our clients in the analytical maturity of the organisation, no matter the industry or sector.

As the next steps, the team puts together a strategic plan with an action roadmap and goals. This plan is based on an agile framework with lifetime cycles that never end.

The agile lifecycle is based on stages such as planning and mockup, data measurements, systems integration, database construction, dashboard and analytics review, tests and optimisations and planning again.

Depending on the Analytical Maturity of your company, to achieve every desired goal, our Data Hub team is also ready to help you first improve necessary or must-have digital assets, like:

• Review or setup of Digital Analytics tools
• Integration of platforms and tools
• Mobile and Web Analytics measurements
• Data repository infrastructure setup (Data Lake)
• Data Science
• Data Marketing

With everything well-balanced and under control, we guarantee we will find the best standards for your campaigns to add our creativity and increase your KPIs according to your targets.

So, let’s take a look at your Big Data?

From small services to big retailers, businesses will keep increasing their investments in technology to enhance their performance and profitability. To do so, a clever digital strategy combining the correct tools, resources and intelligence is essential to improve customer experience, reduce sales frictions and optimise budget.

How technology can help you with this challenge?

Among media channels, social media, SEO, content marketing, CRM and every known digital marketing asset, there is one thing behind them which must be controlled to achieve the desired success: data.

Your data is your driver for understanding and improving your business processes, allowing you to save money and time.

In this post, we explain how you must treat your data, how rich it is for your company, how it can make your business a lot more profitable, and how you can leverage an artificial intelligence strategy based on the information you constantly generate.

Quick Big Data Overview

If you want to deeply know your customer journey, increase retention, stimulate reorders, reduce purchasing process frictions, find new clients and identify market trends you must rely on Data.

Luckily, whether you run a small business or a big company, there are a lot of tools and platforms from which you can collect and manage your data.

But the headaches might start when you have too much data collected, and start missing what metrics you should focus on. This magnitude of information is well-known as Big Data. Big Data is a larger and complex set of data from new data sources, stored in a server or cloud.

It is generally distinguished by three characteristics: increasing volume, variety of data and transfer speed.

In addition, Big Data can help you improve your decisions and sales conversion allowing you to consult it at any time in real time. That’s why a good infrastructure is necessary to provide you with speed.

It also allows you to log information according to your query fields, ensuring its integrity and becoming a source of reliable information for your business.

Through your Big Data, you can mine a variety of rich information that helps you create a personalised relationship with your customers, turning your sales process and experience better than ever.

Use of Big Data for Artificial Intelligence and Machine Learning

Before talking about Machine Learning, let’s quickly understand the role of Artificial Intelligence in Marketing and Sales and how it relates to Machine Learning.

If we go to Wikipedia, it says:

“AI (Artificial Intelligence) is intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals including humans. Leading AI textbooks define the field as the study of “intelligent agents”: any system that perceives its environment and takes actions that maximise its chance of achieving its goals. Some popular accounts use the term “artificial intelligence” to describe machines that mimic cognitive functions that humans associate with the human mind, such as learning and problem-solving.”

AI (Artificial Intelligence) is composed of several different technology branches, such as computer vision, Natural Language Processing, Robotics, Deep Learning, Expert Systems and many others, including Machine Learning.

The use of Machine Learning for Marketing and Sales is an AI process that helps you identify patterns within your Big Data.

By identifying those patterns, Machine Learning helps make predictions and improve them over time.

There are many different tools and systems that you can rely on to deploy a Machine Learning strategy, such as Data and Cloud services, automation platforms, content optimisation and personalisation tools and several other solutions that can integrate into your channels.

Once you have these processes up and running well, you can automate the understanding of your customers steps throughout the purchasing journey, allowing you to personalise your messages and help with the decision-making process.

A Machine Learning process helps you reduce time and costs by creating an automated relationship and experience according to each customer’s profile, especially when combined with the right platforms and expert creative team.

Our process at Cadastra

Whether you still haven’t put it in place or are not happy with your current Data and Machine Learning strategy, Cadastra may be the right partner for you.

At Cadastra we understand that having a lot of data is a good problem and converting them into information is an opportunity. That’s why we add knowledge and execute actions to generate results and capture value.

Our goal is to transform the reality of companies by structuring and democratising data. In an extremely dynamic world, with changes almost daily, the need for rich and accurate information is growing at an exponential rate.

Therefore, we help organisations obtain next-generation data with the necessary experience to know what, how and when to measure what is relevant.

Check how our Data Hub will help you by combining Data Engineering, Data Science, Data Strategy and Analytics in an agile framework process:

The first step of the process is to deeply understand the Analytical Maturity of your company. We have developed a technology that identifies when the organisation is in its analytical maturity called Business Analytical Score (BAS).

Through this score we can monitor the evolution of organisations and how they use data internally for decision-making so that we can evaluate, plan, execute and assist our clients in the analytical maturity of the organisation, no matter the industry or sector.

As the next steps, the team puts together a strategic plan with an action roadmap and goals. This plan is based on an agile framework with lifetime cycles that never end.

The agile lifecycle is based on stages such as planning and mockup, data measurements, systems integration, database construction, dashboard and analytics review, tests and optimisations and planning again.

Depending on the Analytical Maturity of your company, to achieve every desired goal, our Data Hub team is also ready to help you first improve necessary or must-have digital assets, like:

• Review or setup of Digital Analytics tools
• Integration of platforms and tools
• Mobile and Web Analytics measurements
• Data repository infrastructure setup (Data Lake)
• Data Science
• Data Marketing

With everything well-balanced and under control, we guarantee we will find the best standards for your campaigns to add our creativity and increase your KPIs according to your targets.

So, let’s take a look at your Big Data?

From small services to big retailers, businesses will keep increasing their investments in technology to enhance their performance and profitability. To do so, a clever digital strategy combining the correct tools, resources and intelligence is essential to improve customer experience, reduce sales frictions and optimise budget.

How technology can help you with this challenge?

Among media channels, social media, SEO, content marketing, CRM and every known digital marketing asset, there is one thing behind them which must be controlled to achieve the desired success: data.

Your data is your driver for understanding and improving your business processes, allowing you to save money and time.

In this post, we explain how you must treat your data, how rich it is for your company, how it can make your business a lot more profitable, and how you can leverage an artificial intelligence strategy based on the information you constantly generate.

Quick Big Data Overview

If you want to deeply know your customer journey, increase retention, stimulate reorders, reduce purchasing process frictions, find new clients and identify market trends you must rely on Data.

Luckily, whether you run a small business or a big company, there are a lot of tools and platforms from which you can collect and manage your data.

But the headaches might start when you have too much data collected, and start missing what metrics you should focus on. This magnitude of information is well-known as Big Data. Big Data is a larger and complex set of data from new data sources, stored in a server or cloud.

It is generally distinguished by three characteristics: increasing volume, variety of data and transfer speed.

In addition, Big Data can help you improve your decisions and sales conversion allowing you to consult it at any time in real time. That’s why a good infrastructure is necessary to provide you with speed.

It also allows you to log information according to your query fields, ensuring its integrity and becoming a source of reliable information for your business.

Through your Big Data, you can mine a variety of rich information that helps you create a personalised relationship with your customers, turning your sales process and experience better than ever.

Use of Big Data for Artificial Intelligence and Machine Learning

Before talking about Machine Learning, let’s quickly understand the role of Artificial Intelligence in Marketing and Sales and how it relates to Machine Learning.

If we go to Wikipedia, it says:

“AI (Artificial Intelligence) is intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals including humans. Leading AI textbooks define the field as the study of “intelligent agents”: any system that perceives its environment and takes actions that maximise its chance of achieving its goals. Some popular accounts use the term “artificial intelligence” to describe machines that mimic cognitive functions that humans associate with the human mind, such as learning and problem-solving.”

AI (Artificial Intelligence) is composed of several different technology branches, such as computer vision, Natural Language Processing, Robotics, Deep Learning, Expert Systems and many others, including Machine Learning.

The use of Machine Learning for Marketing and Sales is an AI process that helps you identify patterns within your Big Data.

By identifying those patterns, Machine Learning helps make predictions and improve them over time.

There are many different tools and systems that you can rely on to deploy a Machine Learning strategy, such as Data and Cloud services, automation platforms, content optimisation and personalisation tools and several other solutions that can integrate into your channels.

Once you have these processes up and running well, you can automate the understanding of your customers steps throughout the purchasing journey, allowing you to personalise your messages and help with the decision-making process.

A Machine Learning process helps you reduce time and costs by creating an automated relationship and experience according to each customer’s profile, especially when combined with the right platforms and expert creative team.

Our process at Cadastra

Whether you still haven’t put it in place or are not happy with your current Data and Machine Learning strategy, Cadastra may be the right partner for you.

At Cadastra we understand that having a lot of data is a good problem and converting them into information is an opportunity. That’s why we add knowledge and execute actions to generate results and capture value.

Our goal is to transform the reality of companies by structuring and democratising data. In an extremely dynamic world, with changes almost daily, the need for rich and accurate information is growing at an exponential rate.

Therefore, we help organisations obtain next-generation data with the necessary experience to know what, how and when to measure what is relevant.

Check how our Data Hub will help you by combining Data Engineering, Data Science, Data Strategy and Analytics in an agile framework process:

The first step of the process is to deeply understand the Analytical Maturity of your company. We have developed a technology that identifies when the organisation is in its analytical maturity called Business Analytical Score (BAS).

Through this score, we can monitor the evolution of organisations and how they use data internally for decision-making so that we can evaluate, plan, execute and assist our clients in the analytical maturity of the organisation, no matter the industry or sector.

As the next steps, the team puts together a strategic plan with an action roadmap and goals. This plan is based on an agile framework with lifetime cycles that never end.

The agile lifecycle is based on stages such as planning and mockup, data measurements, systems integration, database construction, dashboard and analytics review, tests and optimisations and planning again.

Depending on the Analytical Maturity of your company, to achieve every desired goal, our Data Hub team is also ready to help you first improve necessary or must-have digital assets, like:

• Review or setup of Digital Analytics tools
• Integration of platforms and tools
• Mobile and Web Analytics measurements
• Data repository infrastructure setup (Data Lake)
• Data Science
• Data Marketing

With everything well-balanced and under control, we guarantee we will find the best standards for your campaigns to add our creativity and increase your KPIs according to your targets.

So, let’s take a look at your Big Data?