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I'm confused what the author is trying to argue? 1. People don't want satellite data they want their problem to be solved So a company like Planet shouldn't (

• campchase 4y ago
  That is, indeed, exactly what I am arguing. Either: * Just sell data or; * Just sell applications powered by your proprietary source of data Do not: * Sell derived/refined data as a half-measure * Sell both applications and wholesale data at the same time If you feel like that doesn't make sense, you are not alone. Almost everyone in the industry disagrees with my views on this topic based on how they run their businesses. Satellogic is one notable exception. But I can't think of a single other provider that would agree with me.
  • campchase 4y ago
    Also, full disclosure, I work for a satellite imagery provider (https://umbra.space/ https://umbra.space/) where we're executing on the "just sell data" strategy, so I'm fully corrupted as far as seeing the Truth when my own ego and self interest is inextricably wrapped up in this debate.
    • RosanaAnaDana 4y ago
      Do yall have any plan to do work in the vis/IR space?
      • campchase 4y ago
        No, but I'm close with Albedo who is pursuing the same strategy in vis and IR: https://albedo.com/ https://albedo.com/
        • RosanaAnaDana 4y ago
          Great! Checking them out.
  • frakkingcylons 4y ago
    > Sell both applications and wholesale data at the same time Bloomberg comes to mind since they offer wholesale access to data in addition to all the terminal functions.
    • campchase 4y ago
      Interesting example! Planet sometimes describes themselves as "Bloomberg for Earth Observation" or something along those lines.
      • _puk 4y ago
        "Bloomberg for x.." strikes me as just the modern corporate version of "Uber for x..". I've heard so many founders try to describe their business as "Bloomberg for.." when trying to describe a mixed focus offering of products that I immediately hear alarm bells nowadays.
    • ackbar03 4y ago
      Bloomberg's main product offering is still the data feed though. The "application" part of it definitely makes it easier to use but a lot of trading desks build their own algorithms and pricers on top of that data for the functionality they really need. The built in stuff bloomberg has tends to be overly simplified
      • throwaway2037 4y ago
        This has not been my experience. My view of Bloomberg is two primary products: (1) Bloomberg terminal and (2) Bloomberg BPIPE. (1) is a desktop (and now mobile) application that trader, sales, etc. use to communicate, view raw data, and view derived data in "mini-apps" (price this bond under scenario X, etc.) The base cost is about 25K USD per year (there are local IT costs above the terminal license fees). There is a raw data access API for Excel, but very limited. They block your API access if you try to download too much data. The days of pricing any kind of volume of products from a Excel Bloomberg API is mostly gone. Also, you cannot run it on a server and just screen scrape / use data API all day long. (2) is a raw data feed service, akin to Reuters. Not well understood by industry outsiders: There is no "all you can eat data service" anywhere in finance. Period. Every primary data source is now carefully guarded with license costs and special rules (no redist, etc.). Some stock exchanges make more money selling data licenses than collection trading fees! I have no idea about BPIPE prices, but I assume expensive and per data source with nearly infinite granularity. About revenue: (1) Wiki says: https://en.wikipedia.org/wiki/Bloomberg_Terminal https://en.wikipedia.org/wiki/Bloomberg_Terminal If you believe it: 20K USD per terminal and ~325,000 terminals as of 2016. That is 6.5 billion USD per year. Nice. About revenue: (2) No idea. I cannot find any reliable published stats. Lastly: I regularly see people argue on HN about an open source version of Bloomberg. It is impossible for two reasons: (a) Network effect in the communication channels -- lots of people mostly use Bloomberg chat / email and hardly use data, besides the trivial. Most people on the buy side (money management, hedge funds, portfolio managers) join Bloomberg to talk to other people on Bloomberg. And: (b) data licensing.
  • dylan604 4y ago
    Who are you to tell a company what they can sell. If they want to sell the raw data so people can do whatever they want with it, then sound reasonable. If they also want to sell data with some analysis already applied so that other people can buy that data because they don't have in-house for it and just want pretty pictures to put in the deck, then why not sell that too? You don't always have to order the biggie fries and drink, you can just order the standard meal.
    • altdataseller 4y ago
      You can do anything you want. The OPs point is that it won’t be profitable/effective, that’s all.
      • deleted 4y ago
        [deleted]
  • RosanaAnaDana 4y ago
    I'm in complete agreement with this point of view, with about 22 years experience in the remote sensing space, ~10 of that in private industry. And its not just Planet that is hung-up on this same failed business model. Its also Hexagon, and a myriad of other earth-observation providers. Some are so difficult to work with its literally cheaper to go buy an airplane and a wide format camera and roll your own.
    • randomluck040 4y ago
      I would love to know more about the possibilities of Remote Sensing in the private industry. I‘m working in academia and have the feeling that I’m in an echo chamber all day every day and no insights at all. Any chance I can contact you or can you point me into a direction?
      • RosanaAnaDana 4y ago
        Sure, check my profile.
    • JumpCrisscross 4y ago
      > its not just Planet that is hung-up on this same failed business model There’s a new one like every picosecond.” It’s “delivery, but for dorm rooms” for space tech.
  • palata 4y ago
    Where does a system like https://picterra.ch/ https://picterra.ch/ lie? They seem to provide a way to tune algorithms for your images. Are those "algorithms nobody want", or is that helping niche use-cases (by allowing customisation)? Disclaimer: never actually used their system, just saw presentations about it, which show how one can train an algorithm to count... stuff.
    • campchase 4y ago
      Terrific company and interesting technology. I see them as an application making it possible for non-technical people to automate basic workflows. I’m skeptical that’s a big audience but low code/no code solutions in other industries have enjoyed surprising success, so I look forward to being pleasantly surprised.
    • jre 4y ago
      Hey, I'm the lead engineer at Picterra. Would be happy to answer any questions. What we are trying to do is indeed allow customers to build algorithms tailored to their use cases. We often joke that the reason our ML works is because we are overfitting to customer datasets/use cases. But I think that's somewhat true in the sense that we are not going for "worldwide trees counting" but more for "reliably count cars on these 50 parcels". It's also interesting to note that a sizeable chunk of our revenue is coming from companies with drone data where it makes even more sense to be specific to customer data (resolution, time of day, geo, etc...).
  • countvonbalzac 4y ago
    Thanks for the reply! I'm curious where you draw the line between derived data and a full application for something like modeling climate risk for insurance?
    • campchase 4y ago
      It’s blurry. Can you take an action based on information presented to you from within the software? Probably a sign it’s an application at that point and not just a data feed.
  • astrea 4y ago
    One thing that comes to mind for me is GasBuddy. They simply show me the raw data feed (price of gas at various stations). It's up to me to decide based on my MPG, distance, price, etc. what is worth fueling up at.
• RosanaAnaDana 4y ago
  I can get not how this might get lost if you are looking at it from outside the industry. Realistically, Planet should be in the business of selling pixels in mass. However, Planet has decided that isn't enough for them, they want more of the value add. This is built into their licencing/ ToS. However, their black box analytic solutions simply aren't good enough. They never have been and if they arent willing to give you a full chain of custody of every assumption a given algorithm uses, it never will be. Any solution that isn't completely translucent isn't good enough. If they wanted to be crushing it, lower the cost/ barrier to entry on the pixels themselves. Get it out into peoples hands and use more open, easier to build on licenses. Let people actually use the data. I've been on the other side of 5 failed attempts to work with Planet at large, medium, non-profit and startup scale projects, as early as 2016 and as late as 2021. They just don't get it. If your data isn't easy to use, I wont. If your license is going to prevent me from building what I need to from that data, I wont use it.
  • campchase 4y ago
    I’m sorry to hear that. Planet is a company I admire quite deeply. I think they are well aware of the difficulties folks like you have had working with them in the past and I’ve seen firsthand the lengths they’ve gone to remedy that once made aware. Their new product organization is very focused on taking things in a new direction that I have high hopes for.
• jandrewrogers 4y ago
  Having worked in the sensing analysis market for a long time, I would frame the recurring business problem as follows, and it applies to sensing data generally, not just satellite imagery: There is a large market gap between the sensor platform providers and the would-be end users of that sensor data. Business is constrained by the fact that the end users are not capable of consuming what is being produced and neither party in the transaction is really qualified to solve that problem. Sensor platform companies can't make their data more consumable because they only know their data, not the analytic nuances of the end users nor the other sensor modalities that the end user may be using. They try, with the hope of improving revenue, but it almost never comes off. The end users are experts in their analysis problems and application domains but usually have no skill or capacity to write custom performance-engineered infrastructure software to bring the sensor data into their domain. This software often has pretty hardcore computer science requirements and there is minimal tooling, certainly not in open source, to make this easier or more scalable. There is clearly a market opportunity, but neither of the obvious parties is in a position to address it even for their own immediate benefit. There are a few companies with expertise in building high-performance data tooling for analytic workflows across sensor modalities with enough application understanding to bring it into the end user's domain. There is a lot of commonality across application domains from the view of tooling requirements but you have to have expertise in several vertical domains to see it, so it is repeatable. These companies have neither the data nor the application but they bring them close enough together that they can "make the market" as it were. Currently this is a high-end contracting business rather than a general platform, so it doesn't scale. But if this tooling became part of a general platform, it would let the sensor data platforms focus on data collection without worrying about how to make the data more consumable for various application domains, which they were failing at anyway. The state of software tooling for these sensing data applications is primitive, overfitted for single data sources, and not nearly scalable enough. Most other problems in the sensor data market are consequences of this reality.
  • campchase 4y ago
    I think this is a fair summary. Don’t sleep on GEE, Orbital Insight, and Descartes Labs, though. All three have incredibly impressive platforms that can spin up new custom models and deploy them at scale very quickly. And Microsoft is starting to make a major push into the space with their Planetary Computer initiative. Early innings yet, though, I agree about that.