AR continues to evolve and take shape. Like other tech sectors, it has spawned several sub-sectors that comprise an ecosystem. These include industrial AR, consumer VR, and AR shopping. Existing alongside all of them – and overlapping to some degree – is AR marketing.
Among other things, AR marketing includes sponsored AR lenses that let consumers visualize products in their space. This field – including AR creation tools and ad placement – could grow from $2.78 billion last year to $9.85 billion by 2026 according to ARtillery Intelligence.
Factors propelling this growth include brand advertisers’ escalating affinity for, and recognition of, AR’s potential. More practically speaking, there’s a real business case. AR marketing campaigns continue to show strong performance metrics when compared with 2D benchmarks.
But how is this coming together? And what are best practices? These questions were tackled in a recent report by ARtillery Intelligence, containing narrative analysis, revenue projections, and campaign case studies. It joins our report excerpt series, with the latest below.
When it comes to emerging technologies, some companies are in a unique position to accelerate adoption. That can often happen by tapping into large established networks or user bases to expose and distribute the technology in question. It’s a classic incubation play.
In AR, Apple is a good example of this, given its work to seed user demand and developer interest through ARkit and other mobile means. Snap has likewise popularized AR lenses by integrating them into the existing and popular activity of social multimedia sharing.
But greater impact could come from the web’s most traveled destination: Google. Can it use this position to incubate AR and expose it at scale? It’s already begun to do so by planting AR throughout its well-traveled touchpoints and search engine results pages (SERPs).
More specifically, Google continues to enable search results to come to life in 3D and AR. To define these two terms, 3D is when searchers can spin a 3D graphic (often on a desktop interface), while AR offers the same effect but overlayed in one’s space (on smartphones).
This is the Way
Google’s AR efforts have played out so far with topics that are conducive to visualization. These include educational subjects like a human skeleton or members of the animal kingdom. These use cases and categories will continue to broaden as Google tests the waters.
We’ll also see this moving towards more monetizable searches. In Google fashion, it’s gaining organic traction before it flips the monetization switch. The latter could involve things like characters to promote shows & films like it recently did with Disney’s The Mandalorian.
Another way monetization will play out is Google Swirl, as demonstrated in the Bollé Brands case study we recently covered. This 3D/AR format lets advertisers develop interactive search results. In early tests, these campaigns show strong engagement versus benchmarks.
For example, Nissan’s Swirl ad let users control a virtual car and see features like lane-assist. It achieved an 8x engagement delta over rich media benchmarks. Adidas’ Swirl ad let users zoom in and spin its shoes, achieving a 4x engagement delta over 2D benchmarks.
10 Blue Links
All of the above represents an ongoing evolution of the SERP from its “10 blue links” origins. After years of expanding into the “knowledge graph,” 3D models are the next logical step. They’re also a way to future-proof search for a more camera-forward era.
Moreover, search could represent a developing AR ad channel. In addition to already-established channels such as social media apps, and web AR, a sizable portion of paid AR distribution could take place in search. After all, it’s the web’s most prevalent launch point.
And Google’s broader AR efforts don’t end there. As we examined last week visual search is a promising segment of the AR world. This involves using your phone to identify real-world objects and products (Google Lens) and navigate the world visually (Live View).
These efforts will continue to develop in Mountain View with a combination of computer vision, machine learning, and the knowledge graph that Google has spent 20+ years building. This puts it in an advantageous position to gain AR user traction and revenue, in that order.
We’ll pause there and circle back in the next report excerpt to continue the narrative on AR marketing…