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After covering the play-by-play from Snap’s recent Partner Summit, it’s time to look back and connect some dots for AR strategic implications. A few themes threaded throughout the procession of announcements, such as Snap’s continued evolution as a developer platform.
But another key theme we detected was an ambition to drive local commerce. As background, AR is inherently conducive to local commerce, as geo-anchoring aspects of the technology provide a foundation for utilities like local search and discovery via location-relevant AR content.
This is a key principle behind the AR cloud, and all its versions — everything from the Mirrorworld to the Magicverse. For example, Google wants to build an Internet of places — revealed through Google Lens — by indexing the physical world just like it indexed the web.
The payoff for all of this is monetization potential — through advertising, affiliate revenue or other models — to facilitate local offline commerce. It’s often forgotten that brick & mortar commerce (at least in normal times) accounts for a commanding majority of consumer spending.
Crowdsourcing AR
Back to Snap, how did it inch towards some of these local commerce endpoints? The first and most obvious example was its Local Lenses. Building from Landmarkers, it now wants to enable shared and persistent AR experiences in a broader set of physical locations.
This is a computational challenge in spatially mapping all these streets & surfaces (sort of like how Street View has visually mapped local places for AR navigation). Snap will accomplish this through a crowdsourced approach that utilizes data from existing and ongoing snaps.
As background, world-immersive AR needs spatial maps and point clouds in order to properly place graphics in the right place. This includes spatial understanding (surfaces, contours); and semantic understanding (knowing the difference between Bill’s Bakery and Tom’s Tavern)
Most AR players are working in different ways to solve this challenge, including actively scanning the world (Google and Apple) and crowdsourcing that spatial mapping data (Niantic/6d.ai and Facebook/Scape). As noted, Snapchat will mostly take the former approach.
If all goes well, the outcome will be an ability to leave persistent AR graphics on local spots. The use case that Snap has promoted is more about fun and whimsy, including “painting” the world with digital and expressive graffiti (paging Dr. Fink). But it could also include storefront UGC.
Visual SEO
Further evidence for a local commerce play comes from Snap Map. Erstwhile used for social discovery, it now has a commerce-oriented outcome: business listings. In other words, Snap Maps’ 200 million users can now search and discover local businesses using the same tool.
This notably brings a local search use case to Snapchat for the first time. Sort of like Apple’s forays into local search and mapping, Snap will rely on third-party partners in various vertical areas to assemble listings data (Foursquare, TripAdvisor, Uber Eats, and Postmates).
But most notably, it will offer SMB advertising on a self-serve basis (like Niantic). This is easier said than done — as our analyst coverage from a previous life informs — given deep-rooted challenges around how SMBs buy (or don’t buy) advertising on a DIY basis.
Tying this back to Local Lenses, one wild card is what we’ve been calling visual SEO. Just as local businesses apply rigor to local listings management for web search, a sub-sector could develop around optimizing data to show up prominently and correctly in visual search results.
But first, it will have to be seen if Snapchat’s user base is interested in using it for local search, including offline transactional intent. If so, this could be a powerful new competitor in local search, especially among Snapchat’s demographically-attractive Millennial and Gen-Z users.
Mini-Apps and Machine Learning
Next in our conspiracy theory for Snap’s local commerce ambitions is Snap Minis. These new HTML 5-based apps will live in Snapchat’s Chat section and include micro-functionality like casual games and utilities. It’s similar in concept to Apple’s subsequently released AppClips.
Launch partners include Coachella (coordinate and plan a festival experience); Headspace (launch meditation sessions and send to friends); and Movie Tickets by Atom (choose showtimes, watch trailers, buy tickets) — all demonstrating a wide range of use cases.
With that in mind, minis could be developed to discover, plan, and transact local activities such as dining out. The model here is what WeChat has done in China. It’s similarly a chat-based app that’s become a launchpad for micro-apps and transactional features for local commerce.
Along the same lines, Snap ML lets developers import their own machine learning. Launch partners include Wannabe shoe try-ons and Prisma’s artistic selfie renderings. but could evolve into lots of local search and commerce use cases that tap into Snap’s Scan tool.
So like Google Lens, this could identify local storefronts. With a training set of local imagery, an ML-fueled tool could allow Snapchat users to point their phones at a restaurant to get business info or user-generated content, then reserve a table or invite friends via mini-apps.
Of course, this is all speculative in terms of Snap’s intentions. And the current state of the world isn’t very conducive to local offline commerce. But in a long-term sense, Snapchat’s Lenses are inflecting among shelter-in-place masses while it plants seeds for local commerce’s return.
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