Writing reports, answering the same question several times, creating and using generic and inefficient email lists, repetitive tasks, results that don’t meet expectations… Sound familiar? We understand! Our sincere welcome. We are glad to have you here. In this post, we’ll discuss how your Digital Marketing ploys can benefit from using Artificial Intelligence (AI).
Not only will you have the opportunity to extrapolate the basic understanding of the definition of the AI concept, but also access to practical tips on how to use it to your advantage. If you do this, the chances of reducing the rough work in your department, increasing the time available for other demands and improving results (such as customer conversion rate) will increase. Check out!
You must have heard of AI. It is a phenomenon so present in our lives, yet so enigmatic, that we practically ignore the depth of its existence. Therefore, it is imperative that we start with the basics.
We can define artificial intelligence as a man-made problem-solving capability. Want a simple example? The operating system (OS) of a computer — Windows, macOS, Linux. The ability to solve problems is a common activity both in the professional world and in everyday life. It is always necessary:
This ability also implies, therefore and generally, the need to understand some basic principles (such as how much to pay each employee, and what the company’s budget is) and the potential to learn to get more successes than mistakes. Among other factors, of course.
For a long time, man has been looking for ways to automate his work. Inventing mechanisms that operate alone, even partially, for the execution of a task that does not require creativity. Like the hydraulic innovations in Classical Greece.
Fast-forwarding to modernity, around the middle of the last century, some brilliant minds, such as Alan Turing’s, got together to create, among other things, AI. They also created computational machines and algorithms (mathematical sequences to solve problems in stages). In that context, that of World War II, many of these innovations were aimed at cryptography and how to decrypt them.
So AI has been used for approximately seventy years. Over time, it acquired widespread use, being offered to civil society, in the form of the first OSes available on computers sold at the time.
Today, the application of AI is so common that some famous personalities draw attention to the subject, stating that it is necessary to take it easy and regulate the market, since the laws surrounding it are still very precarious.
Some pertinent examples of AI employment: Google, which has algorithms and virtual robots. For defining rules according to which sites will appear in a certain order on your results pages; as to check, one by one, rule by rule, who will appear where. Virtual assistants on mobile devices that help users complete tasks. Cookies, which collect usage information so that their holders can offer more accurate advertisements, etc.
Have you made any connections so far about how you can apply AI in Marketing to get better results? Because we’re getting there, you’ll see. First, let’s just remember what is Digital Marketing? It is the specialty of planning and executing value exchanges using the Internet. It extrapolates products and services for money, and can involve different entities: companies, the public, personalities, causes, etc.
As we discussed in the introduction, you are probably aware that there are some repetitive tasks in this area. Wouldn’t it be great if we could optimize them? With AI, we can! That is why, from now on, we will bring some examples that illustrate this possibility.
Machine learning is another of many terms used lightly, precisely because of its complexity. It is just a single part of AI. It concerns the ability of an artificial intelligence to learn to be more efficient. How? By analyzing a large sample of data, for example.
What fits here are social media. Most of them, if not all, have one or more algorithms responsible for understanding what type of content you, the user, prefer, in order to offer more of it and, therefore, increase your time spent in that space.
Leads are people most interested in the product or service your business has to offer — potential customers. To qualify them is to identify the characteristics that make up this profile and also that of the ideal customer, the one willing to pay for your offer. Do you know who does this? Some E-mail Marketing and/or Digital Marketing services. How?
During this process, the platform’s AI, through machine learning, identifies which leads have the greatest buying potential, qualifying them. That is, the platform intelligently saves the resources (in this case, time and money) that you have to invest in converting interested customers into buyers, identifying the patterns that make up this profile. An example of what we are talking about: more than 90% of visitors who access a website for the first time are not there to buy. Ever wondered if you wasted your precious marketing resources and time trying to convert them?
As in the process of qualifying leads, targeted advertising consists of, by using data and information collected from past efforts or studies, planning these ads thinking about the characteristics of the ideal customer. Google and Facebook Ads, for example, are management platforms for ads in their respective media. Similar to what we have been describing about machine learning and lead qualification, in the case of Google Ads, the tool has features that help increase the efficiency of your advertising and sales efforts:
In the case of the referred platform, in particular, you work with a pre-established budget. But one of the metrics that matter a lot to this value is the cost per click (CPC), which can be drastically reduced through the mentioned features. In a way that campaigns reach and convert more people into customers.
It is normal, in the day-to-day of the company, to come across questions, both from the public and from leads who are about to purchase. They are evaluating, among other issues, whether we are, in fact, valuable. A large investment of work (time and effort) is required to meet these demands. In this context, chatbots emerged, the next level of question and answer pages. These AI-powered assistant robots use machine learning to understand:
These four examples do not exhaust the applications of AI in Digital Marketing, and we can also mention:
But we say goodbye here. We hope to have resolved your doubts and remain at your disposal for further clarification. Remember: today you learned about Artificial Intelligence (what it is, how it emerged and it’s uses until today); and its applications in Digital Marketing (machine learning, lead qualification, targeted advertising and chatbots).
Lastly, we ask that you join this debate with us! Share this post on social media and let’s find out what else we can talk about. Till the next time!
Writing reports, answering the same question several times, creating and using generic and inefficient email lists, repetitive tasks, results that don’t meet expectations… Sound familiar? We understand! Our sincere welcome. We are glad to have you here. In this post, we’ll discuss how your Digital Marketing ploys can benefit from using Artificial Intelligence (AI).
Not only will you have the opportunity to extrapolate the basic understanding of the definition of the AI concept, but also access to practical tips on how to use it to your advantage. If you do this, the chances of reducing the rough work in your department, increasing the time available for other demands and improving results (such as customer conversion rate) will increase. Check out!
You must have heard of AI. It is a phenomenon so present in our lives, yet so enigmatic, that we practically ignore the depth of its existence. Therefore, it is imperative that we start with the basics.
We can define artificial intelligence as a man-made problem-solving capability. Want a simple example? The operating system (OS) of a computer — Windows, macOS, Linux. The ability to solve problems is a common activity both in the professional world and in everyday life. It is always necessary:
This ability also implies, therefore and generally, the need to understand some basic principles (such as how much to pay each employee, and what the company’s budget is) and the potential to learn to get more successes than mistakes. Among other factors, of course.
For a long time, man has been looking for ways to automate his work. Inventing mechanisms that operate alone, even partially, for the execution of a task that does not require creativity. Like the hydraulic innovations in Classical Greece.
Fast-forwarding to modernity, around the middle of the last century, some brilliant minds, such as Alan Turing’s, got together to create, among other things, AI. They also created computational machines and algorithms (mathematical sequences to solve problems in stages). In that context, that of World War II, many of these innovations were aimed at cryptography and how to decrypt them.
So AI has been used for approximately seventy years. Over time, it acquired widespread use, being offered to civil society, in the form of the first OSes available on computers sold at the time.
Today, the application of AI is so common that some famous personalities draw attention to the subject, stating that it is necessary to take it easy and regulate the market, since the laws surrounding it are still very precarious.
Some pertinent examples of AI employment: Google, which has algorithms and virtual robots. For defining rules according to which sites will appear in a certain order on your results pages; as to check, one by one, rule by rule, who will appear where. Virtual assistants on mobile devices that help users complete tasks. Cookies, which collect usage information so that their holders can offer more accurate advertisements, etc.
Have you made any connections so far about how you can apply AI in Marketing to get better results? Because we’re getting there, you’ll see. First, let’s just remember what is Digital Marketing? It is the specialty of planning and executing value exchanges using the Internet. It extrapolates products and services for money, and can involve different entities: companies, the public, personalities, causes, etc.
As we discussed in the introduction, you are probably aware that there are some repetitive tasks in this area. Wouldn’t it be great if we could optimize them? With AI, we can! That is why, from now on, we will bring some examples that illustrate this possibility.
Machine learning is another of many terms used lightly, precisely because of its complexity. It is just a single part of AI. It concerns the ability of an artificial intelligence to learn to be more efficient. How? By analyzing a large sample of data, for example.
What fits here are social media. Most of them, if not all, have one or more algorithms responsible for understanding what type of content you, the user, prefer, in order to offer more of it and, therefore, increase your time spent in that space.
Leads are people most interested in the product or service your business has to offer — potential customers. To qualify them is to identify the characteristics that make up this profile and also that of the ideal customer, the one willing to pay for your offer. Do you know who does this? Some E-mail Marketing and/or Digital Marketing services. How?
During this process, the platform’s AI, through machine learning, identifies which leads have the greatest buying potential, qualifying them. That is, the platform intelligently saves the resources (in this case, time and money) that you have to invest in converting interested customers into buyers, identifying the patterns that make up this profile. An example of what we are talking about: more than 90% of visitors who access a website for the first time are not there to buy. Ever wondered if you wasted your precious marketing resources and time trying to convert them?
As in the process of qualifying leads, targeted advertising consists of, by using data and information collected from past efforts or studies, planning these ads thinking about the characteristics of the ideal customer. Google and Facebook Ads, for example, are management platforms for ads in their respective media. Similar to what we have been describing about machine learning and lead qualification, in the case of Google Ads, the tool has features that help increase the efficiency of your advertising and sales efforts:
In the case of the referred platform, in particular, you work with a pre-established budget. But one of the metrics that matter a lot to this value is the cost per click (CPC), which can be drastically reduced through the mentioned features. In a way that campaigns reach and convert more people into customers.
It is normal, in the day-to-day of the company, to come across questions, both from the public and from leads who are about to purchase. They are evaluating, among other issues, whether we are, in fact, valuable. A large investment of work (time and effort) is required to meet these demands. In this context, chatbots emerged, the next level of question and answer pages. These AI-powered assistant robots use machine learning to understand:
These four examples do not exhaust the applications of AI in Digital Marketing, and we can also mention:
But we say goodbye here. We hope to have resolved your doubts and remain at your disposal for further clarification. Remember: today you learned about Artificial Intelligence (what it is, how it emerged and it’s uses until today); and its applications in Digital Marketing (machine learning, lead qualification, targeted advertising and chatbots).
Lastly, we ask that you join this debate with us! Share this post on social media and let’s find out what else we can talk about. Till the next time!
Writing reports, answering the same question several times, creating and using generic and inefficient email lists, repetitive tasks, results that don’t meet expectations… Sound familiar? We understand! Our sincere welcome. We are glad to have you here. In this post, we’ll discuss how your Digital Marketing ploys can benefit from using Artificial Intelligence (AI).
Not only will you have the opportunity to extrapolate the basic understanding of the definition of the AI concept, but also access to practical tips on how to use it to your advantage. If you do this, the chances of reducing the rough work in your department, increasing the time available for other demands and improving results (such as customer conversion rate) will increase. Check out!
You must have heard of AI. It is a phenomenon so present in our lives, yet so enigmatic, that we practically ignore the depth of its existence. Therefore, it is imperative that we start with the basics.
We can define artificial intelligence as a man-made problem-solving capability. Want a simple example? The operating system (OS) of a computer — Windows, macOS, Linux. The ability to solve problems is a common activity both in the professional world and in everyday life. It is always necessary:
This ability also implies, therefore and generally, the need to understand some basic principles (such as how much to pay each employee, and what the company’s budget is) and the potential to learn to get more successes than mistakes. Among other factors, of course.
For a long time, man has been looking for ways to automate his work. Inventing mechanisms that operate alone, even partially, for the execution of a task that does not require creativity. Like the hydraulic innovations in Classical Greece.
Fast-forwarding to modernity, around the middle of the last century, some brilliant minds, such as Alan Turing’s, got together to create, among other things, AI. They also created computational machines and algorithms (mathematical sequences to solve problems in stages). In that context, that of World War II, many of these innovations were aimed at cryptography and how to decrypt them.
So AI has been used for approximately seventy years. Over time, it acquired widespread use, being offered to civil society, in the form of the first OSes available on computers sold at the time.
Today, the application of AI is so common that some famous personalities draw attention to the subject, stating that it is necessary to take it easy and regulate the market, since the laws surrounding it are still very precarious.
Some pertinent examples of AI employment: Google, which has algorithms and virtual robots. For defining rules according to which sites will appear in a certain order on your results pages; as to check, one by one, rule by rule, who will appear where. Virtual assistants on mobile devices that help users complete tasks. Cookies, which collect usage information so that their holders can offer more accurate advertisements, etc.
Have you made any connections so far about how you can apply AI in Marketing to get better results? Because we’re getting there, you’ll see. First, let’s just remember what is Digital Marketing? It is the specialty of planning and executing value exchanges using the Internet. It extrapolates products and services for money, and can involve different entities: companies, the public, personalities, causes, etc.
As we discussed in the introduction, you are probably aware that there are some repetitive tasks in this area. Wouldn’t it be great if we could optimize them? With AI, we can! That is why, from now on, we will bring some examples that illustrate this possibility.
Machine learning is another of many terms used lightly, precisely because of its complexity. It is just a single part of AI. It concerns the ability of an artificial intelligence to learn to be more efficient. How? By analyzing a large sample of data, for example.
What fits here are social media. Most of them, if not all, have one or more algorithms responsible for understanding what type of content you, the user, prefer, in order to offer more of it and, therefore, increase your time spent in that space.
Leads are people most interested in the product or service your business has to offer — potential customers. To qualify them is to identify the characteristics that make up this profile and also that of the ideal customer, the one willing to pay for your offer. Do you know who does this? Some E-mail Marketing and/or Digital Marketing services. How?
During this process, the platform’s AI, through machine learning, identifies which leads have the greatest buying potential, qualifying them. That is, the platform intelligently saves the resources (in this case, time and money) that you have to invest in converting interested customers into buyers, identifying the patterns that make up this profile. An example of what we are talking about: more than 90% of visitors who access a website for the first time are not there to buy. Ever wondered if you wasted your precious marketing resources and time trying to convert them?
As in the process of qualifying leads, targeted advertising consists of, by using data and information collected from past efforts or studies, planning these ads thinking about the characteristics of the ideal customer. Google and Facebook Ads, for example, are management platforms for ads in their respective media. Similar to what we have been describing about machine learning and lead qualification, in the case of Google Ads, the tool has features that help increase the efficiency of your advertising and sales efforts:
In the case of the referred platform, in particular, you work with a pre-established budget. But one of the metrics that matter a lot to this value is the cost per click (CPC), which can be drastically reduced through the mentioned features. In a way that campaigns reach and convert more people into customers.
It is normal, in the day-to-day of the company, to come across questions, both from the public and from leads who are about to purchase. They are evaluating, among other issues, whether we are, in fact, valuable. A large investment of work (time and effort) is required to meet these demands. In this context, chatbots emerged, the next level of question and answer pages. These AI-powered assistant robots use machine learning to understand:
These four examples do not exhaust the applications of AI in Digital Marketing, and we can also mention:
But we say goodbye here. We hope to have resolved your doubts and remain at your disposal for further clarification. Remember: today you learned about Artificial Intelligence (what it is, how it emerged and it’s uses until today); and its applications in Digital Marketing (machine learning, lead qualification, targeted advertising and chatbots).
Lastly, we ask that you join this debate with us! Share this post on social media and let’s find out what else we can talk about. Till the next time!
