Price Automation for Ecommerce: How We Solved a Margin Problem with an AI-Powered Automation

Artificial intelligence is everywhere. Every week, new tools appear that can generate text, images, videos, or even complete applications. However, in my experience, the most valuable uses of AI are rarely the most eye-catching ones. More often, they are the solutions that help solve everyday business problems (such as price automation) that have been affecting a company for months without receiving much attention.

In fact, one of the most interesting projects I have worked on recently started with a much simpler — and much more important — problem: an ecommerce business was losing profit margins without realizing it.

This happens more often than you might think.

Months earlier, the company had carefully calculated its selling prices. Margins had been defined, discounts had been configured, and prices had been adjusted to ensure that every product maintained the required level of profitability. The problem was that supplier costs had changed over time. Meanwhile, the store’s selling prices remained unchanged, and certain discounts were starting to dangerously reduce profit margins.

A pricing mistake repeated hundreds of times can cost a business a significant amount of money, even if nobody notices it day to day.

Reviewing Prices Manually Was Possible, But Not Sustainable

The most obvious solution was to review product prices one by one manually.

That meant checking the supplier’s current price, comparing it with the existing retail price, calculating the available margin, and verifying whether the product would remain profitable even when discounts were applied.

The challenge was the amount of work involved. The store contained a large number of products, multiple variations, different sizes, and country-specific pricing conditions. Reviewing all that information manually would have required many hours of work, and the process would also need to be repeated regularly to remain useful.

That was the moment when the real question emerged:

Does it make sense to spend hours on a repetitive task when technology can do it for us?

We needed to stop spending time on a process that a machine could handle much more efficiently.

Price Automation Started as a Practical Solution, Not an AI Project

When people hear the term price automation, they often imagine large and complex systems. In reality, this project started with a very simple goal: eliminating a repetitive manual process.

I began developing a tool capable of connecting both to the supplier’s API and the ecommerce database, automatically comparing information from both sources and identifying products whose prices required updating.

To speed up development, I relied on tools such as ChatGPT and Claude, particularly for understanding the API documentation, generating parts of the required code, and helping solve technical issues throughout the process. And there is something important I think should be said honestly.

AI was incredibly helpful.

But it was not a case of “one prompt and done.”

The Hard Part Wasn’t Programming — It Was Defining the Problem

UnOnce we successfully retrieved the core data, new questions quickly emerged:

• What profit margin should be considered acceptable?
• How should discounts affect the calculations?
• Are there differences depending on the country where the product is sold?
• Should problematic products be highlighted automatically?
• What information does the person reviewing the data actually need?

What started as a simple price comparison gradually evolved into a much more useful decision-making tool. We spent a couple of afternoons refining it until it became genuinely practical.

I think this is worth mentioning because there is often a perception that artificial intelligence can turn any business need into a perfect solution within minutes. My experience has been quite different. AI can dramatically accelerate development, but people still need to think, make decisions, and refine the solution.

In price automation projects, business judgment remains the most important component.

What AI Really Contributes to Projects Like This

When discussing artificial intelligence, it is easy to fall into one of two extremes.

Either believing it can do absolutely everything.

Or believing it is useless.

My experience sits somewhere in the middle.

AI was a huge help throughout this project. It allowed me to move faster, solve technical challenges, and build the tool in far less time than would have been possible a few years ago.

However, AI did not identify the original business problem.

It did not decide which metrics mattered most. It did not define the criteria used to evaluate profitability. And it certainly did not design the business logic behind the solution.

All of that still depended on human expertise and business understanding.

That is why I believe the real value of artificial intelligence is not replacing people, but helping us create better solutions for real business challenges.

Conclusion: Many Repetitive Tasks Can Be Automated
The most valuable lesson from this project is not that “AI can build apps.”

It is something far more practical.

Many companies still rely on manual processes that consume time, introduce errors, and gradually affect profitability. Sometimes these processes have existed for so long that nobody stops to question whether they should continue working that way.

This price automation project is simply one example of a broader principle: when a task is repetitive, based on structured data, and requires constant review, it is worth asking whether it can be automated.

And no, the answer is usually not five minutes and a single prompt.

But meaningful results do not require building a massive platform either.

Sometimes a few hours of focused work and a clear understanding of the real problem are enough to create something genuinely useful.

If you have identified repetitive processes within your business or believe certain tasks could be automated to save time and reduce errors, feel free to get in touch with us and tell us about your situation. In many cases, the best solutions are not the most complex ones — they are simply the ones that solve the right problem.