You know, Herman, I was looking at a specific high end networking switch the other day. In the United States, it lists for about four hundred dollars. I checked a local retailer here in Jerusalem, and after you account for the import taxes and what I like to call the because we can tax, it was closer to seven hundred. It makes you feel like you are living in a completely different economic reality.
It really is a different reality, Corn. And it is not just the price. Sometimes the model number is slightly different, or the internal firmware is restricted, and you are left wondering if you are even looking at the same piece of hardware. I am Herman Poppleberry, by the way, for anyone joining us for the first time, and you are listening to My Weird Prompts.
We are on episode six hundred fifty one today, which is wild to think about. Our housemate Daniel actually sent us a voice note about this exact frustration. He is looking for a way to pull a global inventory, to see those recommended retail prices, different part numbers across markets, and even things like hardware age and programmatic specifications. He wants a supply chain intelligence tool that lets him see through the marketing fog.
Daniel is hitting on a massive pain point in global commerce. What he is describing is essentially the holy grail for procurement professionals and hardware hackers alike. We live in a world where data is the most valuable commodity, yet companies go to incredible lengths to keep their supply chain data siloed and opaque. They want to be able to price differently in different regions without you knowing exactly how much you are being overcharged.
Right, it is the classic information asymmetry. If I know what the part costs in Taiwan and I know the shipping cost to Israel, I have more leverage. But if they give the part a different name or number in every region, that transparency vanishes. So, Herman, let us dig into this. Does a tool like this actually exist for the average person, or even for a small business?
The short answer is yes, but it is complicated. There is not one single search bar where you can type in a product and get every global detail for free. However, if you are looking at technical products, especially electronics and industrial components, there are some heavy hitters that get very close to what Daniel is asking for. The first one that comes to mind, and probably the most accessible, is a tool called Octopart.
I have used Octopart for basic price comparisons, but does it go as deep as Daniel wants? He mentioned programmatic specifications and different part numbers.
It actually does. Octopart is essentially a massive aggregator for electronic components. It pulls data from thousands of distributors like Digi Key, Mouser, and Arrow. What makes it powerful is that it maps different manufacturer part numbers to the same functional component. So, if a company like Kingston or Samsung has a specific memory module that they sell under one part number in the United States and a slightly different one in Europe, a tool like Octopart can often bridge that gap. It uses what they call a Part Grouping algorithm to identify these twins.
And what about the programmatic aspect? If Daniel wants to ingest this data into his own system to track trends over time, can he do that?
Absolutely. They have a very robust application programming interface, or A-P-I. You can feed it a part number and it will return a J-S-O-N file with everything from current stock levels across fifty different distributors to the technical data sheet. It gives you the specifications in a structured format, so you do not have to scrape a P-D-F manually. You can see the voltage, the tolerance, the packaging type, all of it. But here is the thing, Corn, it is primarily focused on components. If you are looking for a finished consumer product, like a specific brand of printer or a laptop, Octopart is not going to be your best bet.
That makes sense. Components are the building blocks. But Daniel also asked about hardware age. That seems like a much harder metric to track. How do you find out if the hardware you are buying is yesterday’s news or the latest revision?
That is where you move into the territory of what we call lifecycle management tools. There is a company called SiliconExpert that is legendary in this space. They do not just tell you the price; they tell you the risk. They track the years to end of life for millions of parts. They can tell you if a component is nearing obsolescence, which is critical if you are designing a product that you want to manufacture for the next ten years. They also track what they call cross references, which are those different part numbers Daniel was asking about.
SiliconExpert sounds like the pro version of this. I imagine that is not a free tool you just sign up for with a Gmail account.
No, definitely not. We are talking about enterprise level subscriptions that can cost thousands of dollars a year. It is designed for companies like Apple or Boeing who need to know exactly where every capacitor is coming from and how long it will be available. But for someone like Daniel, or our listeners who are deeply into technical procurement, knowing that this data is being aggregated is the first step. It proves that the data exists; it is just a matter of who has the keys to the kingdom.
It feels like there is a massive gap in the market for a consumer facing version of this. We have things like Honey or Camel Camel Camel for basic price tracking on Amazon, but those are very surface level. They do not tell you that the laptop you are buying in Israel has a slightly inferior screen compared to the one with the same name in the United States.
You are touching on a very real issue called regional S-K-U fragmentation. S-K-U stands for stock keeping unit. Manufacturers do this for a few reasons. Sometimes it is for regulatory compliance, like different radio frequencies for Wi-Fi or different power supply certifications. Other times, it is pure market segmentation. They know they can charge more in a certain country, so they give it a unique part number to prevent people from easily comparing prices or importing them from cheaper regions.
So if I am Daniel and I want to find these regional differences programmatically, how do I even start? If the part numbers are different, how do I tell a machine that Product A is the same as Product B?
This is where it gets really nerdy and exciting. You have to look at the specifications. If you can programmatically ingest the spec list, you can create a fingerprint for the product. Imagine a script that looks for a laptop with sixteen gigabytes of R-A-M, a specific processor model, and a thirteen inch O-L-E-D screen. If you find two products with different names but identical fingerprints, you have likely found a regional variant. There is a service called Icecat that is actually quite helpful here.
Icecat? I have never heard of that. Is it like a catalog for frozen goods?
Not quite. Icecat is an open catalog project that provides a global database of product data sheets. They work with thousands of brands to provide standardized specifications for millions of products. It is used by retailers to populate their websites. If you go to a tech site and see a beautifully formatted table of specs, there is a good chance that data came from Icecat. They have a global S-K-U mapping system that links different regional part numbers to a single master product record.
That sounds exactly like what Daniel needs. Is it accessible to an individual?
They have an Open Icecat level which is free and covers hundreds of thousands of products. For more detailed data, they have a professional version. But the key is that they provide this data in X-M-L or J-S-O-N formats. So Daniel could build a tool that pulls from Icecat to see that the S-K-U ending in U-S and the S-K-U ending in E-U are, in fact, the same physical device.
Okay, so we have Octopart for components, SiliconExpert for lifecycle and risk, and Icecat for consumer product specifications. But what about the actual price? How do we see the global R-R-P, the recommended retail price, versus what people are actually paying?
That is the hardest nut to crack because R-R-P is often a moving target. However, there are companies like Dataweave or Intelligence Node. They use machine learning to crawl thousands of retail websites globally every single day. They do exactly what Daniel is asking for. They track the R-R-P, the actual selling price, and the discount levels across different geographies. They can tell a brand, hey, your product is being sold for thirty percent less in Eastern Europe than in Western Europe, and here are the specific part numbers being used.
That sounds like a tool for the brands themselves to police their pricing, but a savvy consumer or a small business could use it to find the best deal.
Exactly. It is a double edged sword. The brands use it to maintain their high margins and catch gray market sellers, but if you can get access to that data, you can find the arbitrage opportunities. This is actually how a lot of the gray market importers work. They use these intelligence tools to find where the global inventory is highest and the price is lowest, then they buy in bulk and ship it to places like Israel where the local prices are inflated.
Let us talk about the hardware age piece again. Daniel mentioned wanting to know the age of the hardware. In the computer world, we often see old stock being sold as new, especially in smaller markets. Is there a way to check a serial number or a part number against a global database to see when that specific batch was manufactured?
For many products, yes, but you usually need the serial number, which you do not have until the box arrives. However, you can look at the manufacturing cycle. For components, we have what are called date codes. If you open up a piece of gear, every chip has a four digit code. The first two digits are the year, and the last two are the week of the year. So a code of twenty five ten means it was made in the tenth week of two thousand twenty five.
That is great if you already have the product in your hand, but Daniel wants to know before he buys. He wants a tool that tells him, hey, this inventory sitting in a warehouse in Tel Aviv was actually manufactured three years ago.
That is where you look at the revision history. Many technical products have a hardware revision number, like Rev A or Rev B, hidden in the S-K-U or the fine print of the listing. If you use a tool like SiliconExpert, you can see when each revision was released. If you see that Rev C came out in twenty twenty four, but the store is selling Rev A, you know you are looking at old stock. Another trick is to look at the E-D-I feeds.
E-D-I? That sounds like something from the eighties.
It basically is. E-D-I stands for Electronic Data Interchange. It is the old school way that big retailers and distributors talk to each other. When a distributor like Ingram Micro or Tech Data sends an inventory update to a retailer, that data often includes the age of the stock or the date it was received into the warehouse. While this data is not public, some high end supply chain tools like Panjiva or ImportGenius can give you a peek behind the curtain.
Wait, Panjiva? I have heard of them in the context of investigative journalism.
Exactly. They collect shipping manifests from customs agencies. In the United States, and several other countries, these records are public. You can search for a company name and see exactly what they are shipping, where it is coming from, and how often. If Daniel wants to know the age of the inventory in a specific region, he can look at the customs data. If he sees that the local distributor for a certain brand has not imported a new shipment in six months, he can be fairly certain that the stock on the shelves is at least that old.
That is incredible. So I could look up a local electronics brand in Israel and see which factory in China they are actually buying from?
Yes, precisely. You can see the volume, the weight, and sometimes even the specific part numbers listed on the manifest. If you see that a local brand is importing five thousand units of something from a specific factory in Shenzhen, you can go to Alibaba, find that factory, and see the original product they are rebranding. That is the ultimate way to find the real recommended retail price. You find the source.
This really highlights the importance of what we do here, Herman. Taking these weird prompts from Daniel and digging into the underlying systems. It is not just about finding a cheaper price; it is about understanding how the world actually works. The global supply chain is this incredibly complex, often intentionally confusing machine.
And it is getting more complex as companies try to localize their supply chains to avoid geopolitical risks. We are seeing more regional variants than ever before. For example, a laptop sold in India might have a different keyboard assembly and a different battery chemistry than the one sold in the United States, even if the model name is identical. Without a tool to compare the programmatic specifications, the consumer is flying blind.
So, let us get practical for Daniel. If he wants to build a dashboard today to get this global overview, what are his best steps?
Step one: Start with the Octopart A-P-I for any component level data. It is the most mature and easiest to integrate. Step two: Use the Icecat Open Catalog for consumer product specs. This will give him the mapping between different regional S-K-U numbers. Step three: If he is serious about the pricing data, he might need to use a web scraping framework like Bright Data. They have specialized tools for e-commerce that can bypass the geo-blocking that many sites use to hide their local prices from international visitors.
Geo-blocking for prices? That feels so anti-consumer.
It is very common. If you visit a French electronics site from an Israeli I-P address, they might show you a different price, or redirect you to a global site with inflated numbers. Using a proxy or a specialized scraper allows you to see the ground truth.
And what about the hardware age and the shipping data?
That is step four. He should look into the A-P-Is for ImportGenius or Panjiva. By tracking the Harmonized System codes, or H-S codes, for the products he is interested in, he can see the flow of goods into his specific region. If the H-S code for networking switches shows a massive drop in imports, he knows a shortage is coming and prices will likely spike.
It sounds like Daniel is basically trying to build his own private Bloomberg terminal for physical goods.
That is a great way to put it. And in twenty twenty six, with the A-I tools we have now, this is actually doable for an individual. You can use a large language model to parse those messy customs manifests or to normalize the specification data from different websites. The barrier to entry for this kind of supply chain intelligence has never been lower.
It is also a great reminder for our listeners. If you are feeling like you are getting a raw deal on a piece of tech, you probably are. But the data to prove it is out there if you are willing to dig. Remember the global chip shortage a few years back? If we had these tools then, would it have made a difference for the average person?
It would have made a huge difference. At the height of that shortage, there were actually plenty of chips, they were just in the wrong places. They were sitting in the wrong warehouses or being hoarded by companies that did not need them yet. A global, transparent inventory tool would have shown that. Instead, we had people paying five times the recommended retail price for graphics cards because they thought there were none left in the world.
Knowledge is power, especially in a market like ours where the information is so fragmented. I think Daniel is on the right track. He is looking for the programmatic, data driven approach to being a smart consumer.
Definitely. And hey, if you are finding these deep dives into the weird corners of tech and supply chains useful, we would really appreciate it if you could leave us a review on your podcast app. Whether it is Spotify or Apple Podcasts, those ratings really help more people find the show. We have been doing this for over six hundred episodes now, and the community feedback is what keeps us going.
It really does. We love hearing from you all. You can always find us at myweirdprompts dot com. We have the full archive there, and a contact form if you want to send us your own weird prompt. Maybe you have found a tool that we missed today, or you have a story about a crazy price discrepancy you discovered.
I would love to hear those stories. There is nothing more satisfying than finding a way to beat the system using a bit of data and a lot of curiosity.
Well, I think we have given Daniel plenty to chew on. From Octopart and SiliconExpert for the technical side, to Icecat and customs data for the consumer and brand side. The tools are there; you just have to know where to look.
And you have to be willing to get your hands a little dirty with some A-P-Is and spreadsheets. But for a nerd like Daniel, I think that is part of the fun.
Absolutely. It has been a fascinating discussion, Herman. I am definitely going to be looking at my next electronics purchase through a much wider lens.
Same here. I might even start checking the customs manifests before I buy my next router.
Haha, that might be taking it a bit far, but I respect the dedication. Alright, I think that is a wrap for today.
Thanks for listening to My Weird Prompts. We will be back soon with another prompt from Daniel.
Until next time, stay curious and keep digging.
Goodbye everyone.
Bye.
