Case Study: Panera Drives ‘Craveability’ with AR

AR continues to evolve and take shape as an industry. Prominent sectors include industrial AR, social, gaming, and shopping. But existing alongside them is AR advertising. This includes paid/sponsored AR lenses that let consumers visualize products on “spaces & faces.”

Advertising is one of the most lucrative AR subsectors, estimated to reach $1.41 billion last year and $8.02 billion by 2024. These figures measure the money spent on sponsored AR experiences with paid distribution on networks like Facebook and Snapchat.

As our research arm ARtillery Intelligence examined in a recent report on AR advertising, adoption drivers include brand advertisers’ growing affinity for AR. Its ability to demonstrate products in 3D resonates with their creative sensibilities, transcending common 2D formats.

To continue the narrative and “show rather than tell,” part II of that report features case studies that map to various stages of the consumer purchase funnel. What do AR ads look like today, what’s the concrete ROI, and what are strategic takeaways for campaign execution?

Evoking ‘Craveability’

After case studies that focused on upper-funnel AR ad campaigns, we now continue to the mid-funnel. These campaign strategies include AR-based games, experiences that link to a product page; experiences that drive high “dwell-times”, or other indicators of consumer engagement.

The latest example of an AR ad campaign that hit these marks comes from M7 Innovations. The creative agency executed an AR campaign for quick-serve restaurant Panera, along with 3D-model photogrammetry work with Qreal. The use case was to visualize Panera’s menu items.

The campaign ran on Facebook and Snapchat, letting users interact with Panera’s breakfast wraps through AR lenses. Activated through face movement (e.g. morning yawn), 3D models of the wraps appeared for hungry consumers to visualize and rotate in AR.

After spending $50,000 on Facebook and the same on Snapchat, the campaign had 9.3 million users, 171,000 clicks/swipes, and 47,000 shares. It also achieved a 25 percent store visit rate on Facebook, and a 2.8 percent conversion rate for digital purchases on Snapchat.

“AR is very engaging,” said M7 founder Matt Maher. “It gets people to click through; it gets people to actually play around with these models. But the second piece is what AR actually does to the brain. […] Qreal just did a study with Oxford and New South Wales University, and we now have scientific data that proves that when a human sees a dish in 3D in photogrammetry, it increases craveability. It increases them wanting to actually consume that dish rather than just seeing a 2D image.”

Amortizing AR

This campaign success partly stems from AR’s inherent advantages that Maher cites. But it’s also about execution, such as realistic 3D models and competency with this developing medium. For the latter, Maher sees the most success from brands that are committed to AR.

In other words, ongoing work with AR not only improves knowledge and execution but also amortizes early-stage costs over many campaigns. For example, this was Panera’s third AR campaign, separating it from brands that are doing AR to “check a box.”

“It shows that Panera is investing in AR as a medium, not as the shiny object that so many other brands do […] With this third campaign, we’ve honed in on how we want to show the food. We want people to crave it. And then we put this one out on Facebook and Snap. Because we went through that progression, we had this success — we have learnings, and they really take this seriously as a medium.”

Single View of the Customer

Part of that learning curve can also be accelerated in AR with real-time results for consumer engagement. And given the lower-funnel results demonstrated above, actual conversion data and revenue lifts — versus upper funnel impressions — can embolden that feedback loop.

This is amplified when operating within walled gardens like Snapchat and Facebook. Usually “walled garden” is a bad word, but in this case it enables a “single view of the customer,” versus common attribution challenges of tracking consumers across several channels.

Another advantage according to Maher is AR’s ability to integrate with physical media. Brands can utilize already-invested signage or packaging for AR calls-to-action. This can bring static and owned media to life with AR triggers that create moments of customer engagement.

It also represents a key trend we’ve been tracking: After the AR-cloud fueled excitement over the concept of “AR everywhere,” the AR industry has come back to realizing and embracing the virtues of more simplistic — but effective — marker-based AR activations, such as QR codes.

These markers are not only more practical to roll out in retail settings or product packaging, but they serve as prompts for consumer activation, which is needed at this stage of the AR adoption curve. And if we need any more convincing, there are signs that Apple is moving in this direction.

Lessons & Learnings

As for advice on campaign execution, Maher believes that there are a few success factors to add to those outlined above. For one, be thoughtful around AR calls-to-action. Give consumers an idea of what they have in store, using video previews of the AR experience.

Realistic 3D asset creation is also a big success factor. As noted, M7 works with QReal with the knowledge that investment in photogrammetry is important to achieve realistic models that evoke the “craveability” mentioned above. This is especially true in food-based AR.

Other areas of development include analytics. As we’ve examined earlier in this report and in other places, common click-based impressions don’t capture the depth of AR engagement. But they’re important in early days to compare to established benchmarks.

“With media agencies and creative agencies, it’s hard to reframe your mind in this new medium,” said Maher. “So you benchmark it based on the past medium. […] But slowly, we’re seeing the smart marketers say, ‘Okay, we’ll create new benchmarks. We’ll start to adapt what we know.’ You don’t want this to be a bolted-on innovation. If it’s measured wrong, [the client is] never going to do AR again. So you kind of need that balance of both to justify the spend.”

Originally published at https://arinsider.co on January 12, 2021.

A publication about spatial computing | Brought to you by ARtillery Intelligence.

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