PYTHON: Essential for AI Development. How to Leverage It for Marketing Efficiency

This article introduces the programming language "PYTHON," frequently used in AI fields such as machine learning and deep learning. It covers its features and practical applications, explaining why it is also useful for marketing tasks like data analysis. Furthermore, considering the growing demand for AI solutions, we will explore the future potential of PYTHON.

What is Python, the Essential Programming Language for AI Development?

Python is a programming language developed in 1991 by a Dutch programmer. Being open-source, anyone can build a development environment for free. Python's strengths compared to other programming languages include its ability to write concise programs with less code, the readability of code written by others, and its rich library ecosystem adaptable to various purposes.

Its high versatility makes it widely used for web application development across various fields. Familiar platforms like YouTube, Instagram, and Dropbox also utilize Python.

According to the "2021 Programming Language Usage Survey" conducted by Nikkei Cross Tech among IT engineers, Python ranked first among currently used languages, with over 30% of engineers employing it for some aspect of their work. Given its broad applicability, simplicity, and ease of learning, Python is undoubtedly one of the most popular programming languages today.

Python is also utilized in the AI field

Python is also widely used in developing software for machine learning and deep learning within AI. Reasons for this include its simplicity and ease of use, as previously explained, plus its strength in handling the advanced numerical calculations and statistical processing required for machine learning and deep learning.

Another strength is the abundance of libraries specifically suited for machine learning and deep learning development. For example, Google's "TensorFlow" and Facebook's "PyTorch" are libraries specialized for machine learning. Using these libraries allows for more efficient and easier creation of programs in the AI field.

How can Python streamline marketing?

Python is utilized in various scenarios, and its effectiveness is also anticipated in the marketing field. Automating and streamlining the data collection and analysis processes in marketing is one such application. While data collection and analysis are crucial in marketing, processing vast amounts of data consumes significant time and cost, making automation and efficiency key.

For example, introducing Python enables the automation of routine tasks. For data extraction and analysis, it becomes easy to list or graph large volumes of data, such as customer lists, monthly sales figures, or sales broken down by payment type (cash, credit card, electronic money). By creating a "web scraping" program to collect and extract information from web pages, tasks like "listing influencers from social media," "extracting popular product rankings from e-commerce sites," or "daily collection of news relevant to your business" become straightforward. Furthermore, it can automate "GUI operations" involving mouse and button clicks. This automates previously manual tasks, speeding up processes while reducing human error and ensuring reliable execution.

Additionally, it enables tasks like "extracting co-occurring terms via natural language processing to inform owned media planning," "analyzing trends in user reviews," and "using image analysis to evaluate ad creative effectiveness." Efficiently performing such data collection and analysis frees up resources, allowing you to explore new initiatives.

As AI solutions become more prevalent, Python's popularity continues to grow

Finally, let's consider Python's future potential and upcoming trends.

As mentioned earlier, Python is an extremely popular programming language due to its ease of learning for beginners, high operability, and the simplicity of program construction enabled by its rich libraries. Its adoption by many companies in Japan has also increased the demand for Python engineers. According to the "Programming Language Job Posting Rankings" released in 2020 by Levatech Career, a recruitment agency for IT engineers and web creators, Python saw a significant increase in job postings compared to the previous year in the full-time engineer market, ranking third after Java and PHP. Its applicability to marketing, combined with the abundance of self-study resources like learning sites and books, suggests that even non-engineers involved in tasks like data analysis will likely increasingly seek to learn Python.

Furthermore, Python's prominence stems from its applications in the AI field. As research and development in AI—centered on machine learning and deep learning—advances, Python, being well-suited for building the supporting programs, will likely see increasing demand. One reason for this AI research and development push is the pronounced trend of declining birthrates and aging populations in developed nations, including Japan, in recent years. More companies are considering AI implementation as a solution to challenges like talent shortages and the difficulty of training personnel.

Examples of AI utilization in the marketing field are also increasing. For instance, services that automatically generate creative content like logo designs and advertising copy. Alternatively, there are platforms that automatically learn and generate the most effective combinations of ad images and copy based on users, regions, timing, and other factors. Additionally, solutions supporting SEO efforts, identifying influencers aligned with a brand, and measuring user reactions to TV commercials and video ads are emerging. AI is expected to grow increasingly prominent in the marketing world. By entrusting some marketing-related tasks to AI, it is hoped that busy marketers' workloads will be reduced, allowing them to focus more on creative work and communication both within and outside the company.

PYTHON is a programming language that is easy to read, write, and handle, enabling efficient program construction using specialized external libraries. It excels particularly at high-speed numerical calculations and statistical processing, making it frequently used in AI fields like machine learning and deep learning. Learning PYTHON will allow you to leverage it in the AI×Marketing field, where demand is expected to grow significantly in the future.