C++ and Other Programming Languages an Internet Marketer Should Learn. How to Do My C++ Homework?

Today, we’ll talk about why C++, Python, R, and other programming languages are the best choice for learning if you are an internet marketer. If you have already started to learn one of them, you may face some problems. Nevertheless, there is a way out. For example, if you have problems with tasks in C++, you just need to google “do my C++ homework.” Thus, you will find a service where experts can help you with your assignment. It is a good option when you are stuck with a difficult topic. 

Data-driven marketing is becoming more and more relevant, so the demand for big data analytics is growing. There are a number of tools for working with information in the digital world, but the advantage lies in the hands of internet marketers and web analysts who know how to work with data directly using one or another programming language. In this article, we will consider popular and convenient languages, their features, and areas of application.

1. C++

It is a full-fledged powerful programming language that in marketing, due to its high speed, can be used for mathematical calculations with very large amounts of data. C ++ needs to be learned in industries where performance and reliability are a priority. Learning this language allows you to understand a large number of development methods and related technologies, but more from the point of view of OOP. C++ will seem difficult to a beginner, but learning another language after it will be much easier. Moreover, many modern programming languages are similar to C ++.

According to the September 2021 TIOBE rankings, C ++ is the fourth most popular in the world. This is largely due to the need to maintain legacy code and old projects, but, nevertheless, C ++ knowledge will be helpful for the internet marketer.

C ++ is focused more on opportunities and prospects than on achieving goals here and now. Of course, it will take a lot of time to reach the professional level, but for a marketer, a basic level will be enough. 

2. Python

This language is quickly gaining momentum, and in 2021, it took the second spot in the TIOBE ranking, behind only C. Python is quite a popular language, and many people want to write in it. It is not surprising because the language is easy to learn, and students study it in the first programming courses.

Python is accessible with its simplicity of syntax. You can start writing on it in a couple of weeks. It is also famous for its expressiveness and brevity: a program in Java will be 3-4 times larger than in Python.

Python is a universal language. Hundreds of convenient libraries have been created for it, allowing you to do literally everything: from creating simple games (Pyxel) to popular libraries for working with data (Pandas, NumPy) and neural networks (TensorFlow).

Python is arguably the most profitable for marketers today. Knowing the language at an acceptable level, you will be able to completely cover a number of tasks:

1. Receiving data through API services. Let’s say you need to compose a small report, receiving a certain dataset from several sources. For example, you need to bring conversions from Google Analytics, calls from the call tracking system, and Google Ads data. You can easily import your results into Excel, Google Sheets, or a database if you have some scripts written in Python.
2. Data processing. This is where the Pandas library comes to the rescue, which organizes data into convenient data frames (similar to tables) and allows you to operate on columns and rows, making massive changes.
3. Process automation. In Python, you can easily remove from your work most of the routine associated with advertising campaigns or working with tables, mailings, etc. As an example, you can set up automatic letters, collect data on balances from advertising platforms, check and install link markup, and more.
4. Parsing of information. If you need to quickly retrieve certain information from the web –  be it prices for specific products in an online store or any other text data contained in the body of a web page – you can use the BeautifulSoup library. 
5. Creation of chat bots. Using Python, you can create a bot in a social network or messenger. You need to pay attention to the fact that special services can further automate and simplify this process.
6. Machine learning. Using Python, you can analyze statistical data and make predictions based on it. For example, you can find out the likelihood that users will unsubscribe from your product soon. In this way, you can influence their behavior in time. Scikit-learn has many machine learning algorithms that allow you to build models and find anomalies or important patterns.
7. Where and how to study Python

• Python course at Codecademy
• Python for Data Science at Udemy
• Analyzing Data with Python course at edX

3. R

Compared to Python, R is a more highly specialized language: it is mainly used for working with mathematical and statistical models. In terms of features, R does not have as detailed and convenient documentation as Python, and it also has a smaller community and a more specific syntax. Even so, R is a great tool for working with data.

Python and R have similar capabilities. With R, you get:

• Automate routine Excel-related operations.
• The ability to parse data using the rvest package.
• Write scripts to access the API of different systems.

Like Python, R makes it easy to visualize results. For example, using the ggplot2 package, you can display graphs in a convenient form that show important anomalies.

1. Where and how to study R

• Statistics and R course at edX
• Introduction to R course at Datacamp
• Learn R course at Codecademy

4. JavaScript

In internet marketing, JavaScript comes in handy when interacting closely with sites. It is not as elegant and concise as Python, but it is just as powerful and versatile. Almost anything done in Python can also be done in JS. In general, JavaScript is an integral part of modern web development, so knowledge of it will come in handy.

Three digital areas where JS comes in handy:

1. SEO. Knowing JS, you will understand how search engines see the site. This is essential for search engine optimization.
2. Working with Google Tag Manager. You need JavaScript basics to write scripts for Google Tag Manager. The system allows you to install a container on the client’s website, in which tracking tags are placed and any other manipulations necessary for analytics are performed.
3. E-commerce. Knowing JavaScript, you will be able to understand the e-commerce setup on the client’s site, implement it, or make the necessary edits.
4. Where and how to study JavaScript

• Learn JavaScript course at Codecademy
• JavaScript for Beginners course at Coursera
• JavaScript Introduction course at edX

5. 5 reasons to start coding
6. “It’s effective”: automate your routine + save

Basic knowledge of programming languages allows the marketer to make a quantum leap in their profession. Copying and renaming files, dividing one large table into many small ones, and finding the right key phrases in a large data array are the simplest tasks for a programmer with a Junior level.

For those who are engaged in contextual and targeted advertising, programming skills make it possible to:

• Manipulate hundreds and thousands of ads without going into the web interface and without paying third-party services for their generation.
• Manage customer accounts: track balance, as well as start and stop advertising campaigns under the necessary conditions.
• Adjust rates according to the necessary conditions without resorting to bidders and automation services.
• Simplify the work with analytical data. For example, Python has analytical libraries with data visualization. You will be able to collect data from Google Analytics + CRM and bring it all together into a single informative graph.

Programming gives freedom for creativity. For example, you can create several scripts: to collect keywords and create new ads, launch campaigns, and send the results to the customer. And all these scripts can be connected into a pipeline, which can be launched by pressing a few keys. Moreover, you can automate everything to such an extent that this pipeline will be launched after filling out a form on the site, for example, to demonstrate the work of an entire department.

1. “It’s profitable”: get more money

Telling that you have practical experience in data science or are using simple neural networks to conduct automated A/B tests, you greatly increase not only the chance of being hired but also the increase in the salary. 

And if you work freelance or you have a small team of specialists, then firstly, the list of your opportunities will be supported by several rather expensive services, and secondly, you will speed up the processes, which means an increase in the cost of an hour of work.

2. “This is promising”: master a promising profession

One Microsoft employee said there would be a shortage of about a million programmers in the labor market over a five-year period. If you make the right decision, you can take advantage of this.

The demand for programmers has grown thanks to three areas: Big Data, Artificial intelligence (neural networks, machine learning), and IoT (Internet of Things). All of this applies to data science. 

Each of these areas will become relevant within five years, and some specialties will become as widespread as the SMM specialist and targetologist once were.

And since data science is a direction in IT, where work is done with large amounts of data, it is desirable that a specialist understands the area where this data comes from. The best specialists in data science have experience in digital marketing, biology, chemistry, physics, and any other areas. Data science and knowledge of programming languages is the next step in almost any brainwork profession.

3. “This is the future”: be ahead of your competitors

Once upon a time, a responsive website or multiple PPC ads were a competitive edge in the marketplace. Now everyone knows about contextual advertising, and Google introduced the mobile-first index at the beginning of 2019.

After a while, if AI consultant bots and neural networks for making decisions about the best time and ways of interaction with clients are not implemented in your projects, then you may find yourself out of work.

4. “This is useful”: learn to think consistently

Most marketers use primarily creative thinking in their work: selecting images for advertisements, writing headlines, calls to action, and sales copy. Each of these challenges requires being creative.

But marketing also consists of dry numbers that lead or do not lead to results in real businesses. The effectiveness of creativeness in marketing should be evaluated according to precise criteria: conversion rate, transaction frequency, and return on investment. Not every marketer thinks in the same way as a business owner, but without this, you cannot become a super-effective marketer.

Writing programs is the same skill as writing text. Some people in the world still do not know how to express their thoughts in writing. Just like people who cannot write by hand or in a messenger, they do not have some opportunities in their kind of activity. Likewise, marketers who do not know how to program lose sight of new growth points. Some people think that programming skill is “21st century literacy,” and to some extent, they are right.

When learning to write programs, you will also break down large tasks into small ones, as well as think algorithmically and sequentially, which will definitely make you more productive. 

Conclusion

A programming language is just a tool, not an end in itself. You should not be an adherent of only one, as this narrows the possibilities and the list of tasks to be solved.

Of course, you don’t need to learn a huge number of languages, frameworks, understand complex tools, and thoroughly study computer science. Decide what you need to disassemble at a level that is enough to solve specific cases. Answer the questions: what tasks you need to accomplish, what marketing tools you need to use – and choose the right programming language.