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Immersive shopping is proving to have experiential impact for consumers, and revenue impact for brands. Related to – but separate from – AR advertising, this is when AR is used as a tool to visualize and contextualize products to engender more informed consumer purchases.
This is a subset of AR that we call camera commerce. It comes in a few flavors, including visualizing products on spaces and faces. It also includes visual search – pointing one’s smartphone camera at a given product to get informational, identifying, or transactional overlays.
In each case, AR brings additional context and confidence to product purchases. And these factors continue to demonstrate effectiveness through higher conversion rates on average than non-immersive benchmarks. They also reduce return rates for eCommerce purchases.
But beyond this well-worn narrative about AR shopping’s benefits and brand ROI, there are other potential gains. For example, it turns out that it’s more cost-effective to produce AR assets such as 3D models, compared to traditional product photography for eCommerce.
Adoption Barriers
As background before jumping into the data, one of the key components of “try-before-you-buy” AR shopping is having 3D models of a given product library. The photorealistic quality and volume of these scans – depending on the brand or retailer – have been barriers to AR adoption.
But those barriers mostly include typical resistance to change or lack of knowledge. Cost is always a factor in any new tech adoption decisions, but it turns out that cost shouldn’t be a concern for AR adoption – at least for the part of the process that involves generating 3D models.
CG Trader – a vested interest in the 3D model creation ecosystem – recently validated this notion. The company ran a study that compared the average cost of product photo shoots in several markets with the fees it charges for 3D scanning and photorealistic model creation.
And the verdict? It can be up to 6x cheaper for 3D model creation versus analog photo shoots. Specifically, its price of $2000 stacks up against comparative photography pricing in various cities averaging $11,076, and ranging from $17,952 (New York City) and $6,178 (Montreal).
The reasons for these elevated costs range from shipping furniture, to labor costs for technically-sound photo shoots, to post-production work. CG Trader’s ARsenal platform by comparison boasts a streamlined and automated approach to 3D model creation that’s software-forward.
As for its methodology, CG Trader gathered pricing from 17 international markets to shoot a table, armchair, sofa, vase, and lamp. Each of these was priced for shoots that included 30 white-background and “lifestyle” scenes. Its 3D-scan comparisons did the same.
User Touchpoints
To be clear, 3D models aren’t only used for AR shopping. In fact, AR currently represents a small share of the endpoints for these visual assets. They’re more often used in desktop or mobile 3D shopping experiences where consumers can spin product images around for perspective.
The difference with AR is that those same 3D models can be placed in your immediate space, rather than set against a white background. The former has advantages in getting better context and confidence for product look and fit. It’s particularly valuable for bulky products like furniture.
One example of a product that currently does 3D and AR is Google Swirl. In its case, the same 3D assets are used for both modalities. This signals that e-tailers that already offer 3D models need only a short jump to raise their game to AR. They already have the base ingredients.
3D scanning prices will also fall as parts of its tech stack follow the course of Moore’s Law (while photography does not). Other adoption accelerants will include competitive pressure that ratchets up among retailers as 3D becomes expected by shoppers (just like 2D images did).
Meanwhile, companies like CG Trader are well-positioned as enablers (see AR as a Service). They’re the proverbial picks and shovels in the gold rush. And the timing of that gold rush hinges on the pace at which consumer brands internalize 3D and AR’s cost and performance advantages.
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