13 Technical Marketing Skills You Can Learn (Even If You’re Not Technical)

Marketing has evolved beyond creativity and communication—it’s now deeply intertwined with data, automation, and digital technologies. The ability to harness technical skills is becoming increasingly essential, even for those who don’t have a technical background. Fortunately, AI tools like ChatGPT, automation platforms, and user-friendly programming languages make learning these skills more accessible than ever.

If you’re a marketer who wants to stay ahead, mastering a few fundamental technical skills will give you a competitive edge. Whether it’s using application programming interfaces (APIs) to collect data, automating workflows, or analyzing content performance, these skills can elevate your marketing efforts. Here are 13 technical marketing skills you can learn—even if you’re not technical.

1. Call an API to Collect Tons of Marketing Data

Application programming interfaces (APIs) allow marketers to gather large amounts of data from different sources. APIs help automate data collection, integrate tools, and improve decision-making. Whether you’re pulling search rankings from Google Search Console or analyzing engagement metrics from social media platforms, APIs streamline these tasks.

Getting started is simple. Many APIs, such as Twitter’s API, provide documentation to guide you through making your first request. Tools like Postman help visualize API responses, while ChatGPT can assist in writing basic scripts.

2. Write SQL Queries to Analyze Blog Performance

Structured Query Language (SQL) is a powerful tool for retrieving, filtering, and analyzing marketing data. If your blog drives organic traffic, SQL lets you track page performance, identify top-ranking content, and measure audience engagement.

A simple SQL query can pull data from a Google Search Console database, showing which keywords drive traffic. By learning basic SQL commands like SELECT, WHERE, and JOIN, marketers can extract valuable insights without relying on developers.

3. Automate Workflows with Zapier or Make
   

Marketing automation is essential for efficiency. Tools like Zapier and Make enable marketers to connect apps and automate repetitive tasks, such as posting on social media platforms or updating CRM data.

For example, you can create a Zap to automatically send email notifications whenever a customer submits a form. With a few clicks, you’ll reduce manual work while improving productivity.

4. Write Google Apps Scripts to Automate Sheets

Google Apps Script enhances Google Sheets’ functionality, allowing marketers to automate reporting, clean data, and integrate with APIs. A simple script can extract data from an application programming interface, format it, and update reports automatically.

For example, a script can fetch Twitter mentions daily, filter relevant conversations, and summarize brand sentiment—all without manual effort. ChatGPT can help generate and debug scripts, making automation even easier.

5. Clean Messy CSVs with Python and Pandas

Marketing data often arrives in messy CSV files. Python’s Pandas library makes it easy to clean, transform, and analyze this data. With a few lines of code, you can remove duplicates, standardize formatting, and filter out irrelevant information.

For example, you might have a CSV of customer data from multiple social media platforms. Pandas allows you to merge datasets, identify trends, and create structured reports for campaign analysis.



6. Visualize Trends with Looker Studio or Python Libraries

Raw data isn’t useful unless it’s visually digestible. Looker Studio (formerly Google Data Studio) and Python libraries like Matplotlib and Seaborn help create compelling data visualizations for marketing insights.

For instance, you can use Looker Studio to track traffic sources and campaign performance across multiple platforms. With Python, you can generate trend charts that highlight customer behavior over time.

7. Scrape Public Data with BeautifulSoup or Scrapy

Data scraping allows marketers to gather competitor insights, monitor trends, and collect valuable information from the web. Using Python libraries like BeautifulSoup or Scrapy, you can extract pricing data, keyword rankings, and content ideas.

For example, scraping product reviews can reveal sentiment trends, helping marketers refine messaging and strategy. While web scraping should always follow ethical guidelines, it’s a powerful way to stay ahead.

8. Learn Python for Automating Routine Marketing Tasks

Python is one of the most versatile languages for marketing automation. From scheduling posts across social media platforms to analyzing customer sentiment, Python simplifies complex workflows.

For instance, a Python script can automatically fetch keyword rankings via an application programming interface, compile the data, and generate a report. With ChatGPT’s assistance, even non-technical marketers can write basic Python scripts.

9. Build Dashboards with Notion, Airtable, or Retool

Dashboards help marketers organize and analyze data in one place. Tools like Notion, Airtable, and Retool allow users to create custom dashboards without coding knowledge.

For example, an Airtable dashboard can track content performance, social media engagement, and customer feedback in real time. These dashboards enhance decision-making by centralizing critical marketing insights.

10. Learn How to Use Pivot Tables in Google Sheets

Pivot tables are invaluable for analyzing large datasets. In Google Sheets, they help marketers summarize complex data sets, identify trends, and generate reports quickly.

For example, you can use a pivot table to compare engagement metrics from different platforms, helping you identify which channels drive the most traffic. Mastering pivot tables enhances data-driven decision-making.

11. Use RegEx to Extract and Clean Marketing Data

Regular expressions (RegEx) are a powerful way to clean and extract structured data from unorganized text. Marketers can use RegEx to filter URLs, clean email lists, or extract keywords from messy datasets.

For instance, if you’re working with URL data, RegEx can quickly filter pages related to specific campaigns. Tools like Google Sheets’ REGEXMATCH function make it easy to integrate RegEx into daily workflows.

12. Master Advanced Formulas in Google Sheets

Advanced Google Sheets formulas simplify data manipulation and reporting. Functions like ARRAYFORMULA, QUERY, and REGEXEXTRACT help automate calculations and filter complex data sets.

For example, the QUERY function allows marketers to pull insights from campaign data across different social media platforms, reducing the need for manual analysis. Learning these formulas can significantly improve productivity.

13. Learn to Prompt LLMs Like a Pro

Large language models (LLMs) like ChatGPT are changing how marketers work. Knowing how to craft effective prompts can help generate marketing copy, analyze sentiment, or automate research tasks.

For instance, a well-structured prompt can summarize customer feedback collected from various platforms. By refining your prompts, you can maximize AI’s potential and integrate it seamlessly into your marketing strategy.

Conclusion

As digital marketing becomes increasingly technical, mastering a few essential technical marketing skills can set you apart. Whether it’s using application programming interfaces to collect data, automating reports with Python, or leveraging Looker Studio for visual analysis, these skills will future-proof your career.

The best part? You don’t need a computer science degree to get started. AI tools like ChatGPT, low-code automation platforms, and user-friendly programming languages make learning more accessible than ever. Start with one skill, experiment, and gradually build your technical expertise—your future self will thank you.

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