Original Summary

We almost built a shipping optimization platform for Morocco. Here is why we didn't, and why I'm glad. The spark: Morocco runs on cash on delivery. Merchants ship through a mess of carriers, big national ones and small regional players, and prices change from one city to the next. We looked at that price gap and thought, what if we auto route every order to the cheapest carrier? Plug in all their APIs, and add a WhatsApp confirmation step on top, because with COD you need the customer to confirm they still want the product before you ship, or you eat the return cost. So we built the hard part first to test the idea. The messy reality: carriers don't use the same names for cities or destinations. So we wrote an algorithm to map matching locations across carriers, then ran an AI agent over the leftovers it couldn't match. Once we had a clean price map, we generated 10,000 orders and ran the routing 10 times. The result that killed it: across 10,000 orders, the best case savings came out to about $120. The platform was cheap to run, so we would have charged around $20 a month. But $120 saved on 10k orders is nothing, and 10k orders a month isn't even a big merchant. The savings just didn't add up to anything worth paying for. And the worse part wasn't the money, it was the hassle. Routing across carriers means several shipping companies showing up at one merchant's door through the day, and staff sorting parcels per carrier. We were basically asking merchants to take on more chaos to save pennies. Nobody signs up for that. The lesson: we proved that carrier prices in Morocco are too close together for routing arbitrage to ever pay. The whole save money angle was dead, and we found that out in a spreadsheet instead of after a year of building. Killing an idea with data feels bad for about a day. Then you realize you just saved yourself a year. Happy to answer questions. If anyone wants to dig into the numbers or the mapping approach, I'm around.   submitted by   /u/documy [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SaaS
  • 发布时间：2026/9/17 21:13:49