Marketing automation is widely adopted among companies these days. Business owners realize how much time can be saved if you outsource all the repetitive task – delaying posts, starting and stopping ad campaigns, creating reports, and managing spreadsheets, to technology. In fact, according to a Forrester report, companies are expected to spend over $25 billion dollars by 2023. The growth rate estimated as a result of marketing automation is up to 13%.
Startups and small business can be wary about marketing automation as they don’t have high budgets to spare. However, as a matter of fact, you don’t need to use third-party software tools for marketing automation. Developers use Python for marketing automation – the programming language allows creating functional tools with little-to-no budget.
In this post, we’ll go over some tried-and-true applications of the programming language in marketing automation and lay down the benefits of using Python to learn how to automate marketing.
Python is a widely-used language in machine learning and AI development. It’s a go-to choice when it comes to designing any automated tool including marketing strategy software. There are a few reasons that contribute to Python’s popularity, namely:
- Extensive choice of libraries. Python is among the leading programming languages when it comes to ready-to-go code assets. The abundance of frameworks and libraries cuts development time and make the overall coding process easier.
- Simplicity. Python-written code tends to be simple and concise which improves its reusability and increases the comfort of collaborative editing. As most automating technologies use multi-layered workflows, it’s highly convenient for developers to not be worried about complex code infrastructure.
- The high quality of documentation. Python is one of the most improved languages when it comes to support – it has broad documentation, is supported by most development tools, and has a strong open-source community. Looking forward to using a language to automate marketing tasks, a developer can always consult his colleagues or find answers in official documentation.
All in all, Python is a solid fit for marketing automation tasks due to its innovative and simplistic nature. However, in order to know the right way to use the language, a developer has to have an idea for possible marketing automating applications that can be implemented with Python.
Small businesses and startups can rarely rely on advanced hardware or powerful technology in order to build a strong automation tool. However, there are more than a few simple and cheap applications that can nevertheless improve the workflow and handle mundane marketing tasks with no human observation
Let’s take a look at a few Python use cases for different types of marketing.
Search engine optimization has dozens of repetitive tasks marketers would happily outsource to a software solution. Good news is, Python is extremely handy for automating the following SEO tasks:
- Comparing canonical URLs and detecting indexation changes can be automated thanks to Python scripts;
- Data scraping and analyzing competitor pages. Moreover, you can even use a Python-based tool to react to any changes to a competitor’s website.
- Check headings and structured data and get alert as soon as a member of an SEO team changes meta-tags.
A/B testing gives marketers a possibility to test different versions of a website or an app to see which one results in a higher conversion and engagement rate. It’s a crucial marketing step – there’s no denying, however, that A/B testing every single feature of a product is mundane and can easily become a victim of human error.
Good news is, A/B testing, too, can be automated using Python. A developer would need to write a script considering the following values:
- Desired conversion rate;
- Baseline conversion rate;
- The number of visitors in testing group Number 1;
- The number of visitors in testing group Number 2.
A simple Python-based testing tool allows marketers to summarize the A/B testing sprint, calculate the conversion rates, and compare the difference between them.
While marketers tend to automate email marketing by using third-party tools like MailChimp, in order to ensure letters don’t go to spam, it’s better to send them manually. Obviously, sending thousands of letters on your own will get tiresome and waste a ton of time. Automating email marketing campaign with a Python tool is a solid idea. All you need is a base of emails as a CSV file and an HTML/TXT file with the email body.
You can even set up dynamic data values (a person’s name, location, etc) that’ll be changing with every email sent. Keep in mind that you’ll need to set up a mail server which can be time-consuming in order to run a script. Sending emails automatically doesn’t liberate you from restrictions set by an email client – via Gmail, you can only send up to 500 letters in 24 hours.
Marketers use Python automation for various research activities including market basket research. With the help of the association rule mining algorithms, you can understand why customers buy a set of products and how each item compliments each other. Here’s the brief description of the automation process:
- Gather the data on purchase time and the number of items bought;
- Transform the dataset into a transaction and unite all the items bought during the same purchase in one raw;
- Applying association rules, determine why customers get certain products together.
You can use built-in tools for Python to facilitate the creation of such a script. Mixtend library, for the record, is handy for analytics and analyzing the results.
It’s clear Python can improve the efficiency of marketing tasks by automating them. This way, a business owner or a manager can use free time to engage in tasks that require active thinking and advanced marketing skills.
However, staring marketing automation with Python is easier said than done. In fact, a developer needs to possess a wide set of coding skills in order to create a functional automation tool. Let’s take a look at what you should learn in order to create software that’ll take care of marketing tasks in your place.
- Repository management, mainly Git;
- Good command of Jenkins – an open-source automation API for Python;
- Sauce Labs knowledge for everything that requires cloud automation technology;
- A strong command of widely used automation tools like QTP;
- Automated database structure verification;
- Automated service verifications.
In case you already have a task you look forward to automating, be sure to look for tutorials online. Blogs like Towards Data Science on Medium are the places for developers to share their case studies on automation – there are dozens of posts regarding Python automation tools and practices that will help you learn programming and hone your craft.
Python might very well be the most widely used programming language for automation. Its applications in marketing are practically endless – from research to automated posting and conducting email campaigns.
While it’s true that there are third-party tools to automate various marketing tools, creating a custom Python script comes with its own advantages. It’s free of charge, easier to customize to your own needs, and all the data processed by the script is secure, with no risks of ending up in the hands of a third party. Also, using Python for marketing automation is certainly worthwhile as the language is actively developing and improving. Its applications are likely to broaden tremendously over a decade’s span – be sure to benefit from them!