Maximum Capture: Curiator’s Value in a Data-Starved Art Industry
Last week, ARTnews reported that Art Basel’s parent company, MCH Group, made a move into the startup domain by acquiring Curiator, the self-proclaimed “World’s Greatest Collaborative Art Collection,” for an undisclosed amount. But with the online art space still largely a work in progress (at best), the obvious question remains: What exactly does MCH plan to do with its new addition?
Functionally, Curiator is basically Pinterest with a different name, a slightly more appealing interface, and, most importantly, an exclusive focus on aggregating images of artwork. (In other words, no wedding inspo boards allowed.) What Curiator is NOT is a sales or monetization platform — at least, not yet. But no company acquires another without believing the acquisition will improve its bottom line in some way. It’s just a matter of how. And when I consider the potential interplay between MCH and Curiator, two possible answers emerge.
The first one is the more obvious of the pair — and also the less likely. Many industry observers will remember that Noah Horowitz, now the Director Americas for Art Basel, jumped into the driver’s seat of the online-only VIP Art Fair in 2010. The knee-jerk reaction would be to assume that MCH might be planning to use Curiator as the foundation for a Basel-branded reprise of the concept, with Horowitz’s past expertise to guide them.
The problem with this theory is that VIP was a raging grease fire. The fair’s chat function — designed to be the main line of communication between buyers and sellers — went down for much of its opening weekend in 2011, prompting the organizers to give full refunds to ticket-buyers while exhibitors like David Zwirner advocated for the return of their digital-booth fees. After sales at VIP’s 2012 encore stayed in a coma despite a smoother technical experience, the organizers pulled the plug. Not even VIP’s home page survives. Its URL was grave-robbed by a fashion blogger sometime between then and now, turning the inscription on the fair’s tombstone into an ode to off-the-shoulder tops and fringe bikinis.
Now, it’s fair to ask whether VIP’s cause of death was a flawed concept or simply bad timing. As the old Silicon Valley adage goes, being right too early is just as bad as being wrong. Personally, I’d argue that the idea of an online-only art fair is a contradiction in terms. From both a sales and professional networking standpoint, so much of the value in fairs comes from packing as many industry players as possible into a single compressed geographical space at the same time. A “fair” on the internet is just pure-play e-commerce with a short fuse, and pure-play e-commerce is now failing even in typical retail. Why would it ever succeed in a specialty market sector where sellers primarily create value through “exclusivity and the social prestige of ownership”?
Ironically, the quoted fragment in that last sentence comes from Horowitz’s 2009 book, Art of the Deal, where he intelligently deconstructs many of the socioeconomic factors underpinning the art market. His clear thinking on the page didn’t prevent him from taking the job at VIP a few years after the book’s release, but I suspect VIP’s ultimate fate will help prevent him and his current employer from making the same mistake with Curiator.
That leads us to the second, more nuanced theory about the startup’s utility to MCH. Even though Curiator is not a marketplace, Alex Greenberger at ARTnews points out that its founders have previously described the platform as a tool for helping users find art that they might want to buy. Since its curated collections double as quantifiable records of their members’ tastes, Curiator doubles as a repository of data on art lovers’ preferences and, just as importantly, their identities.
That information has value to all of MCH’s art-industry ventures, whether we’re talking about Art Basel, its recently acquired fleet of smaller regional fairs, or any other projects it has in development. Knowing what people like is useful. Once you know that, you can try to figure out why they like it — which in turn may be able to help you figure out what they might like next. And when you know who the people behind the preferences are, you can also try to figure out the relative importance of their individual choices to the overall marketplace. It’s not just about crowdsourcing raw opinions. It’s about being able to properly weight those opinions, too.
Other art-industry startups have already been doing broadly similar data-mining for years. Consider Artsy’s Art Genome Project, which seeks to break down the whole of art, architecture, and design into a set of discrete, quantifiable categories (or “genes”) that connect works across the centuries. But the project’s data can also be leveraged into recommendations for other pieces that might appeal to particular users based on their aesthetic interests. It’s the same principle as the “You May Also Like” feature on Netflix or Amazon, only applied to fine art. And while the Genome is presented as an educational endeavor, its output could someday translate into dollars and cents for the gallery/dealer partners actually selling inventory on Artsy.
Magnus Resch’s recently launched Magnus app provides another example of these unadvertised data benefits. Resch markets the app as a transparency tool, with some justification. By using Magnus to shoot and upload photos of artworks found in the wild — at galleries, in art-fair booths, at museums, etc. — everyday users receive the most recent known prices for those works in a matter of seconds, provided that Magnus’s database contains the relevant info.
But the app is not a one-way mirror. Every user can “like” whatever work they’ve just shot, as well as provide “additional details” about it, including the current price, the date of that price, and where the work was being exhibited. Magnus even specifically requests this information from users if they upload any pieces not already in its database. Filling in those blanks turns the app’s users into a worldwide network of unpaid operatives, continuously funneling useful market data back to Resch himself for whatever revenue-generating purpose he sees fit.
And then there’s Carlos Rivera, the man behind ArtRank, the data science-driven quarterly index designed to provide “actionable recommendations in accordance with optimal [art] market timing.” In an interview last year, Rivera described how one part of ArtRank’s algorithm involves scraping Instagram for likes and hashtags on contemporary artworks, along with the “saliency” of the people providing those data points. In his own words, “Saliency simply differentiates the importance of likes from relevant individuals in the art world versus, say, a robot you hired to like your Instagram photos.” Again, who you are matters as much as what you think. And your identity is right there on your account for all to see.
Rivera hasn’t just used this stealth data-collection strategy for ArtRank, either. He admits in the same interview that he and his team plowed what they learned from the site’s (currently on-hiatus) Buy Today feature into their latest venture, LevArt, an art-financing startup that allows collectors to borrow $5,000 to $1 million+ against qualifying artworks within 24 hours. As in these other cases, users provided data on a particular platform for one purpose, but the wizard behind the digital curtain transformed that data into something else entirely.
My best guess is that MCH acquired Curiator to be the wand in a similar magic trick. The bigger and more prevalent the platform grows, the more info it can funnel back to its parent company, and the better return on investment it provides — even if the site itself never directly monetizes anything. So look for MCH to begin pushing Curiator hard at every industry touch point it can, in an attempt to make the platform standard issue for casual fans and high-value players alike. Maybe they don’t know exactly how they’ll wring revenue out of the data yet. But as intelligence-gathering agencies the world over will tell you, maximum capture means maximum possibilities.
