Reasons to Use Python for Marketers

Author

Kevin Urrutia

Category

Marketing

Posted

January 27, 2023

Digital marketing has become so sophisticated and data-oriented powered by numerous business intelligence tools in the present-day marketing field. Modern marketing strategies are highly influenced by deeper data analytics based on rich data, artificial intelligence, and creative marketing ideas. The main goal of a successful marketing strategy is to achieve a marketing return on investment MROI greater and faster, which is impossible without using the technologies like Python, Java, or PHP for marketing automation and data analysis.

Many companies hire Python developers to support their digital marketers, but that solution is not viable due to the high cost in the fiercely competitive marketplace. The best solution to overcome all glitches in the effectiveness of digital marketing strategies is to learn coding skills in Python or other powerful languages.

Python in Marketing Strategy

A modern marketing strategy includes numerous components like social media, SEO, paid search, content marketing, ads, video, and others. It would be best if you had the technical expertise to understand the crux of all those components and analyze the data achieved by them. According to the Digital Vidya information, Python and R languages are the most popular ones used in the data analysis field.

According to the CodeAcademy information, Python is at the top of all other big programming languages like Java, PHP, and others. The enrollment to learn to programme in Python has also increased rapidly during the past few years. To have a deeper insight into the marketing strategy, you should develop your custom code to analyze the data collected in digital marketing to find the fault lines, take corrective measures, and launch the right campaign.

Valuable Tips on How to Automate Marketing in Python

The main components for automating marketing campaigns include data mining, competitor price monitoring, SEO indexation, and other tasks. Python is a straightforward programming language that can help you automate your marketing strategies with short and simple coding.

Let’s have a look at a few handy tips on how to automate marketing in Python:

#1 Automate Data Collection

Marketers gather data from multiple sources repetitively for processing and analysis. So, data collection should be fully automated to generate an extensive data file. The main points in collecting data may include:

  • Automate SEO indexation through a python code that can trace the changes in ranking
  • Try to automate the price changes of the competitor products with a Python code
  • Gathering survey data, chat chains, and other commercial data files
  • Collecting email and SMS responses
  • Top marketing trend information gathering

#2 Automate Repetitive Data Formatting

Once the raw data is collected from multiple sources, you need to format that data in such a way that the real data looks in sync with the data processing requirements. The main activities of repetitive formatting tasks include:

  • Text string matching functions
  • Number matching functions
  • Marking/tagging data source, location, time, and other attributes of data
  • Encrypting PDF files repeatedly
  • Formatting functions for PDFs and web ads like splitting, watermarking, and other such parts

#3 Automate Customized Error Checking

The software or the Python module your company uses for data mining should accept specific criteria and fields. Any typos or other errors in the data that are mandatory for your organization should be automated to improve efficiency and save valuable time.

#4 Automate Massive File Operations

The massive operations on the files, like copying, editing, or removing the files based on specific criteria such as timestamp, data strings, changes in files, and other conditions, should be automated through Python codes. This will improve the efficiency of data processing.

  • Reading the file properties and their attributes.
  • Tracking of modifications made to the files in comparison with the timestamps
  • Always develop the custom code, the way you work and based on your marketing skills
  • Automate the filling out of forms, naming renaming files, and formatting sheets

#5 Automate Data Mining Process

The data mining process plays a pivotal role in all types of marketing in the marketplace. The data mining components may vary from company to company. Automating the primary functions related to big data processing is always a good idea.

  • The custom code should be developed for all data mining-related tasks to find valuable information.
  • Create a shortcode for the repetitive marketing tasks rather than doing them manually.
  • Making information summary as an automated task
  • Highlighting the new trends in user behaviors

Why Use Python for Marketers?

According to the IEEE Spectrum ranking of the top programming languages in 2018 information, Python sits at the top of the list. Marketers, data scientists, prominent data engineers, and machine learning developers extensively use Python language in their respective fields.

There are numerous advantages of using the Python programming language in the digital marketing field. Those benefits are listed below:

  • It is cheaper to learn Python than to use readymade data analytics tools in the market
  • It is straightforward and easy to understand for even a novice programmer
  • It has a large number of libraries for data analysis
  • It is an open-source programming language without any fee to use
  • It is powered by a large community to support
  • It is an interpreted language which does not require compilation
  • Its code is cross-platform portable
  • It is an object-oriented language with high performance
  • It is widely used in marketing, so new marketing-related features are counting

Top 5 Reasons to Use Python for Marketers

Python is extensively used in automating different tasks used for digital marketing campaigns nowadays. The main objective of using Python as an automation code development is to improve marketing efficiency and effectiveness to create a competitive advantage over competitors.

Let’s figure out a few important reasons for using Python in the modern digital marketing field.

#1 Large Number of Data Analytics Libraries

Python language is powered by numerous data analytics-related libraries that are extensively useful for digital marketing professionals. Examples of such tools include NumPy, Pandas, StatsModel, SciPy, and others. These tools are large-scale libraries for data mining, analyzing, converting, cleaning, processing, summarizing, visualizing, and reporting. Many other libraries can help you get a deeper perspective on the user data that you, as a marketer, are interested in. Present-day digital marketing is useless if the meaningful information behind it does not correctly drive it. That information can efficiently be achieved using the Python language’s power.

#2 Increased Data Mining Efficiency

By using the Python programming language, marketers achieve massive efficiency in data mining. The traditional data mining processes mostly use excel sheet processing, which has its limits and performance. For instance, processing an excel sheet of about 100 MB of data at a better speed and performance would be difficult.

But Python code can do it in a few seconds without sweating. Thus, Python increases the efficiency of data mining processes commonly used for getting insight into marketing campaigns and launching new campaigns.

#3 Improved Search Engine Optimization (SEO)

Search engine optimization, or SEO, is one of the core components to make your marketing campaign a success. Many SEO-related matters, such as 404 errors, meta tags, descriptions, robot text files, content duplication, faulty navigation maps, and others, can easily be detected through a custom Python code for automating the SEO process. A better ranking index of the website can help improve the visibility of your website and business.

Once the SEO faults are detected, it is easy to remove them instantly before they can damage the search engine ranking badly. Using the best white-label SEO rules recommended for a high-ranking index is critical, which can be achieved by getting a deeper perspective on the website’s technical and content-related issues in the early stages.

#4 Efficient Use of Big Data

According to the Research and Markets predictions, the global market of big data will grow by over 14% CAGR for the next three years from the present value of about $65 billion in 2018. The total volume of big data will cross 44 zettabytes by 2020. Python plays a vital role in skimming the valuable information from this good heap of data. Developing customized Python codes to combine, process, analyze, and visualize the big data makes the big data so beneficial for marketers.

#5 Effective Campaign Monitoring

One of the most critical bottlenecks in making digital marketing campaigns successful includes the monitoring and course correction of the marketing campaigns. Python custom codes can make life so easy in real-time monitoring the ads, effectiveness, clicks, checkouts, conversion rate, and other parameters.

This monitoring can help the marketers make the campaigns more focused on the desired segments by correcting the fault lines in the campaign components. A good Python code can monitor Facebook, Google, YouTube, and other ads in real-time by using the APIs of social websites.

Final Takeaways

After having discussed the different technical and commercial aspects of Python and digital marketing, we have come to conclude that:

  • Programming skills are essential in the modern digital marketing field
  • YouTube course on learning Python
  • Python leads all other languages in data analytics and digital marketing
  • The top 5 valuable tips out of the many include automation of data collection, processing, mining, and repetitive tasks that are time-consuming and less productive.
  • The top 5 essential reasons for using Python for digital marketing include extensive data handling, automatic campaign monitoring, data mining efficiency, SEO automation, and powerful libraries of the platform.

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