Steam Spy, the PC gaming sales-tracking mainstay loved by some developers and loathed by others, was recently presumed dead by its creator, Sergey Galyonkin, after an update to Steamās privacy defaults. It is now coming back, but itāll be different.
The old Steam Spy estimated a PC gameās sales by sweeping publicly viewable Steam profiles and taking stock of their game collections. That technique was blocked in early April when Steamās architects at Valve made it so that usersā profiles no longer automatically show which games players own. The new version of Steam Spy will get around that by embracing machine learning to predict sales based on ācoincidental data.ā
In a blog post, Galyonkin explained that heās in the process of switching Steam Spy over to a model rooted in machine learning. He confessed, however, that despite a wealth of data to feed his algorithm, itās ānot very accurateā at this point.
āI have the data for around 70 games from different developers, and for 90% of them, the new Steam Spy is within 10% margin of error,ā he wrote, pointing out that the siteās estimate for Frostpunk (252,000 units sold) was basically on the money (250,000 units sold). āBut I also saw some crazy outliers, where the difference between the estimates and the real data could be fivefold.ā
If thereās a chance the data could be that inaccurate, why bring Steam Spy back at all? Galyonkin credited his decision to āover 200ā³ messages from developers explaining how Steam Spy impacted their operations. He mentioned an indie company from Berlin that got government funding for its game with the help of Steam Spyās data, and though he didnāt name the developer in the post, he told Kotaku that it was inbetweengames, creator of noir tactical game All Walls Must Fall
Praise for Steam Spy has always been buffeted by wariness. Earlier this month, many developers were relieved to see it seemingly go, because it empowered armchair analysts (and some harassers) with data they perceived to be accurateāeven when it wasnāt. In theory, a new, less accurate model could exacerbate that problem. Galyonkin, though, still thinks Steam Spy is worth bringing back from the brink.
āArmchair analysts do not need Steam Spy data,ā he said in an email. āTheyāre fine with whatever is available: [concurrent players], the number of reviews, even a user score.ā He noted that, in his opinion, the most important number for most players is concurrent users in a given game, because that helps them decide if multiplayer games are worth purchasing. Valve, he added, already makes that number public.
As for why developers can still benefit from Steam Spyās reanimated bones, Galyonkin claimed that theyāre already happy to shell out serious cash for services that he thinks are even less accurate.
āRelatively low accuracy doesnāt prevent developers from paying $30,000/year for [an] AppAnnie subscription,ā he said, referring to a popular app analytics service, ābecause having an estimate is usually better when making decisions than having no data at all. Analysts can work with data when they know itās not entirely accurate as long as they are aware of the limitations and caveats.ā
Galyonkin is still fine-tuning the new algorithm, and many of Steam Spyās old features arenāt even back online yet. Country stats, for example, are off the table right now. Things are early, in other words, and there are still options on the tableāsome of which involve collaboration with other interested parties.
āI have some offers from people with more recent knowledge in the field of machine learning,ā he said. āI hope theyāll help me improve the algorithm.ā
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