Digital marketing has become the new trend and new businesses that don’t adopt it are likely to get phased out. However, you can’t just engage in digital marketing for the sake of it, as you won’t compete favorably with others.
Data-driven marketing is the most effective approach for modern-day digital marketers. However, digital marketing is an ever-evolving space and reading the best marketing books might not be enough and you must arm yourself with other tools.
Can you use Python for digital marketing? Python, a multipurpose programming language, has become one of the biggest marketing tools for digital marketers today. In this article, I will explain why every digital marketer should learn Python and the different ways to use Python in digital marketing.
Why marketers should learn to use Python
A survey conducted in 2023 shows that more than 49% of the respondents use Python as their preferred programming language.
Its popularity is not by sheer luck. The following are some reasons why every digital marketer should learn to use Python.
Easy to learn
Most ‘common’ people fear programming languages and tend to think it is only for ‘nerds’. However, Python is beginner-friendly and is easy to learn, even for non-techies.
Compared to other languages like C#, C++ and Java, it is easier to learn Python. You will also need fewer lines of code to build programs using Python than the languages mentioned above.
This language also has simple functions and syntax like ‘find’, allowing you to use everyday expressions to create scripts and solutions.
It is a multipurpose language
You can use Python for data analysis, data science, AI, frontend, backend development, and more.
When you start learning this programming language, you will want to keep discovering new things. You can always repurpose your code to perform different functions and achieve varying goals.
Has a big community and many libraries
The ease of learning Python and its diversity have made this language attract a big community. As such, you will likely find people who share ideas on using Python for digital marketing and the best practices. As a digital marketer, learning digital marketing will be the best approach.
In some cases, you don’t have to create everything from scratch, as various libraries exist that speed up your processes. You can use libraries such as NumPy, Matplotlib, Tweepy and Pandas for various digital marketing purposes.
The different ways to use Python in Digital Marketing
Marketers in the digital realm face various challenges like competition, ads becoming expensive and determining which ads perform best and under which circumstances.
These experts have to look for solutions to improve their marketing campaigns. When used with other tools, Python can solve some of these challenges. This is how you can use Python as a digital marketer:
Web scraping
Web scraping allows users to harvest vast data from websites or APIs with a few clicks. For instance, you can scrap for trending news in your niche and use it to build marketing campaigns.
Instead of manually checking what your competitors are posting on their websites and socials, you can simply create a script that scrapes for that data and sends you a report. As a digital marketer, you can also scrap the internet to collect data on consumer behavior.
Digital marketers can scrape for price updates in niches where pricing is a key marketing factor. This approach allows digital marketers to note price changes and discounts their competitors offer and adjust accordingly.
However, always ensure that you scrape data ethically. Remember to observe the existing data processing regulations to be on the law’s good side when exercising web scraping.
Workflow automation
A typical digital marketer can be overwhelmed by researching, analyzing competitors, creating content and posting on various platforms. Luckily, such an expert can automate some of the tasks with Python.
A good example is creating a script that scrapes trending hashtags, creates good content around them, and posts automatically on social media. This approach will ensure you remain trendy and create authority within your space.
A digital marketer may also, from time to time, deal with loads of files and folders. Sorting such data manually may take a lot of time. Python allows marketers to gather, sort and group large datasets and files into meaningful formats.
SEO
A digital marketer may churn out content that never reaches the intended masses. Poorly optimized content is just a waste of time. You have to understand the search intent of your target customers, the keywords they use and how they interact with the content.
With Python, you can automate keyword research, look for trending topics and auto-generate optimised content for social engines. You can also use scripts created using this language to analyze backlinks and determine which are performing well.
You can also use Python to ensure that different website pages are always online. You can create a custom script that analyzes how web users interact with your website and send a notification if they encounter any errors.
Campaign monitoring
You may have heard people say that marketing is all about numbers. However, you can never know your campaigns’ performance unless you monitor them. Traditional marketing may be hard to monitor as you cannot determine how many people buy your product after seeing a billboard or an ad on TV.
You can have different digital marketing campaigns, from emails and social media to ad campaigns. Python allows you to create custom scripts that check the effectiveness of clicks, your social media posts, ads, checkouts and the bounce rate. This approach will help you make informed decisions about what to focus on, improve, and drop.
You can also use Python scripts to generate reports in various formats. You can use the same tool to analyze the reports for proper planning.
Personalization and customer engagement
Every customer who comes to your shop is unique. Identifying customers’ interests, traits, and habits manually is not easy. You can use Python to learn about your customers’ interests and provide personalized experience.
To achieve this, you can collect data when users sign up and store it in a database. You can also collect data over time as they interact with your store. You can use Python to analyze these past customers now and offer them tailored offers and personalized content based on their interactions with your products. A simple message with the customer’s name whenever one login can make a customer feel appreciated.
Predictive Analysis
The ideal digital marketer should use the current data to forecast the future. However, some of the datasets might be abstract and hard to analyze. You can create Python scripts that analyze current market data and trends and know what to expect in future.
For instance, based on historical data, you can predict how users are likely to interact with social media content. You can also predict the conversion you will likely make at different pricing points based on historical data.
Work with APIs
Application Programming Interfaces (APIs) make interacting with different programs and applications easy. For instance, if you are an investment consultancy business, you can fetch real-time trading data from the New York Stock Exchange and London Stock Exchange through APIs and display them on your website.
You no longer have to collect data manually; APIs can do it automatically through Python scripts. Most APIs also have different endpoints that ensure you only collect data that suits your needs. As a digital marketer, you can opt for free and paid APIs depending on your needs and niche.
Analyze customer feedback
Modern customers are looking for products that address their pains. However, analyzing and understanding customers’ feelings about different products may be very involving. Millions of competitors may offer similar products, and you want to know how customers perceive such products.
You can collect customer feedback and analyze it using Python scripts. For instance, you can create a script that scrapes the internet for a keyword related to your niche and only picks positive reviews with words such as ‘amazing’ and ‘awesome’. You can also create another script that scrapes only for negative reviews.
This approach will let you know what people love about competitor products and what you can improve.
Data visualization
Some of the data marketers collect can be hard to analyze or make sense of unless offered in visual formats. Digital marketers can use Python to represent data in visual forms, such as charts and graphs, to learn patterns and trends and provide insights.
Python has various libraries, such as Matplotlib, a 2D plotting library, which you can use to generate static visualizations. You can also generate dynamic and interactive visualizations using a library such as Plotly. The choice of a library to use will depend on the nature of the data you need to analyze.
Conclusion
Digital marketers deal with vast amounts of data. At the same time, they must ensure they clearly understand their customers. Python is an awesome tool for digital marketers as you can use it for data visualization, scraping the web, business intelligence and analyzing competitors, among many other uses.
