Marketers in eCommerce SEO face many challenges today:
- Indexing & crawling issues: Large eCommerce sites have thousands of pages, making it difficult for search engines to crawl and index every page properly.
- Keyword strategy: Competing with larger marketplaces such as Amazon, Walmart, and Target for high-value, conversion-based keywords today is difficult, since these global retailers offer nearly unlimited product selections online — far beyond what’s available in their physical stores.
- Technical SEO issues: Many eCommerce sites suffer from slow loading times, and complex product pages can be challenging to navigate and load properly.
Additionally, eCommerce SEO professionals navigate an ever-changing landscape, often dedicating countless hours to manual tactics, including:
- Optimizing XML sitemaps so pages can be indexed.
- Providing a list of recommendations to increase page load speed.
- Targeting and researching long-tail keywords for the correct pages.
- Implementing more internal links to specific pages, and redirecting broken links to new links that work.
I wondered if I could create an SEO tool that could speed up most of the day-to-day work for an eCommerce marketer. The idea crystallized when I read an article about how a fellow marketer successfully used AI to create a web tool despite having a limited development background. This sparked a realization — perhaps I can do the same. But my coding knowledge is minimal at best. So, where to start? Where all (or most) first forays into AI begin: ChatGPT.
Building a custom tool with ChatGPT & Cursor
First, I inputted a pretty simple prompt into ChatGPT:
The full response was too long and comprehensive to include here, but ChatGPT understood my request and got started enthusiastically:
With that answer in hand, I moved over to Cursor, an AI-powered code editor, to build the tool. I created a new project and opened Cursor’s initial dashboard. The magic happens in the right margin, which is the Chat Agent.
I copy-pasted my input from ChatGPT into the Chat Agent and pressed Send.
While code was automatically generated for the tool, it was somewhat buggy. I then prompted Cursor to resolve those errors and spent additional time prompting Cursor to refine the CommerceSEO Pro tool layout, with a specific request to adjust element placements. After an hour, I was able to evolve something basic to a fully functional interactive tool with intuitive navigation and properly formatted output.
I then saved this project and opened it in my browser to see a working dashboard with key metrics like backlinks, organic traffic, conversion rates, and keyword rankings.
Next, I gave Cursor the freedom to generate additional features. The results were remarkable.
One of the first features it developed was a keyword planner tool capable of tracking specific keywords and their search volume.
With more time, I could’ve connected this to the Google Search Console API to fetch real-time keyword data, but even this early stage showed how far AI can transform a concept into a real-world solution.
Another feature that Cursor developed: An AI product description generator. Enter any product details for a particular eComm site, and the tool will generate a product description, which could be used in several ways, such as changing meta descriptions, creating compelling product listings, or developing new social media content.
Inspired by what I had built so far, I came up with another idea, a tool that could help eCommerce marketers analyze competitor pricing. The concept was simple — allow a user to input a product category URL from a competitor’s site, then extract the following elements from an eCommerce product page:
- The total number of products
- Price range and average price
- A list of individual product links
I figured I’d give it a shot back on Cursor. This is the question I asked the Chat Agent:
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Cursor immediately came up with a functional tool called the Competitor Price Analyzer:
This tool was equipped with all the features I prompted it to incorporate, and it excelled in synthesizing the data. When I tested it on the Allbirds men’s shoe page, it extracted 12 products and calculated their prices — showing a price range between $98 and $145.
Even more impressive, this list provides links to the page in which the products appear so marketers can conduct deeper competitive research. I clicked on the Men’s Tree Runners – Rustic Orange product.
And it took me straight to the Allbirds Men’s Tree Runner page in a Rustic Orange color. Pretty impressive, right? The system I created automatically scraped and indexed URLs directly from allbirds.com, organizing them into a searchable database — all from my instructions and prompting to Cursor.
What can code as content do for your brand?
Creating the right marketing tool with AI can help you and your brand move faster, work more efficiently, and make decisions with a bird’s-eye view of comprehensive data.
Marketers who use code as content create value and drive traffic for their clients — but they also make it possible to fully build new tools using ChatGPT and Cursor to benefit their teams and others simultaneously.
Learning how to use code as content transforms the traditional content paradigm. It allows marketers to develop interactive solutions to problems and provide value to their consumers, going beyond using AI solely for blog and general content.
By leveraging AI tools to create functional code, marketers can develop tools that visitors can actively engage with rather than passively consume. You can now help your customers identify the right solutions for them, reducing the work on their end and your internal development teams, if necessary.
These code-based content assets can serve many purposes, such as demonstrating expertise, providing utility to potential customers, and creating unique digital experiences that competitors can’t replicate.
As website visitors interact with these code-based assets more often, they’re more likely to convert, share them with their colleagues, and return for regular use, extending the lifetime value of something that would otherwise be deemed a one-time content interaction.
By embracing code as content in your marketing strategy, you position yourself as a forward-thinking leader who delivers tangible value beyond traditional content formats. This approach not only differentiates your brand through interactive tools that solve real customer problems, but also creates sustainable engagement that traditional content simply cannot match. As your competitors continue producing static content, your code-based assets will create unique digital experiences that establish your brand as an indispensable resource in your industry’s digital ecosystem.
If you want to learn more about using code as content in your marketing strategy, get in touch with us today.
