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Ordering satellite imagery and counting cars is just a weekend project. The last time I looked at ordering imagery, the main obstacle was the minimum order size
by 46Bit 2y ago
Ordering satellite imagery and counting cars is just a weekend project. The last time I looked at ordering imagery, the main obstacle was the minimum order size, so it'd actually scale better for monitoring every store car park than for looking at a single car park.
- avidiax 2y agoSo if Macy's parking lots have 11% more cars than the same time last year, is that a buy or a sell? Are people actually buying more, or are they more cash strapped and spending more time looking for value?
- aurareturn 2y agoYou’d have to have historical data to see if more cars mean more spending.
- baxtr 2y agoWhat if Macy‘s parking lots have fewer cars but they’re selling more and more online now?
- fragmede 2y agoyou buy data flow data from ISPs at all tiers, so even though they're encrypted, knowing how much traffic is going to Macy's.com vs JCPenney.com gives you information you can act on. We know this is being done, because of reports that say Netflix is X% of Internet traffic. The undredacted reports from those same data sources have much more detail. It's also why some apps that don't appear to have any business model are actually quite valuable.
- helsinkiandrew 2y agoHow busy are the car parks by their dispatch center? are the cars staying longer because people are working overtime? how many UPS trucks are visiting?
- baxtr 2y agoOk fair, so you need to have a model for every one of their revenue streams.
- jgtrosh 2y ago2024 answer: just train a predictive AI with that rarely measured data and avoid thinking about the innards of the black box.
- ttyprintk 2y agoIn terms of parallel construction, can you tell the difference between insider trading and confident-sounding tips from WallStreetBetsLM?
- lazide 2y agoIt’s an indicator they’re getting more traffic. Which you can then feed into your model to decide if it’s a buy or a sell, based on all other data. For instance, is the stock and/or expected earnings > 11%, while traffic seems to be only 11% - or vice versa.