Visual search continues to signal applicability and opportunity in local commerce. For those unfamiliar, the technology uses computer vision and machine learning to let users point their phones at physical world objects to identify and contextualize them. We’re talking anything from storefronts to statues.
Google leads the field with its Lens feature. As it continues to place Lens in high-traffic places like the search bar on Google’s mobile app (right next to the voice search button), Google sees this as a way to boost query volume through multiple inputs. It also future-proofs search given the camera-native gen-Z.
But Google isn’t alone. Others have visual search features such as Snap (Snap Scan), Pinterest (Pinterest Lens), and even Etsy. The thought is that each of these players see an intersection between visual search and their core products. For Snap, it’s augmented reality… for Pinterest it’s product discovery.
All of this reemerged last week when we saw that Klarna launched a visual search feature. The BNPL player is now part of the gradually thickening visual search competitive field. This has implications for Klarna and its business evolution, as well as the visual search subsector. Let’s tackle those one at a time.
eCommerce Stack
First, regarding Klarna, its new visual search play is called Shopping Lens. It lets users take pictures of physical-world objects to identify them and find where to buy them (or similar items). This is essentially a reverse image search – a longstanding technology in web search – purpose-built for mobile commerce.
Klarna says that the new tool can visually identify more than 10 million items across a range of popular eCommerce categories like clothing and electronics. It can also match those items with more than 50 million eCommerce players, including the ability to compare prices and reviews within the app.
Klarna is well positioned to pull this off due to its position in the eCommerce stack. Given that it’s already integrated with several eCommerce players that offer Klarna for payment checkout, it has essentially created its own shopping front end. And all that product metadata can train its visual-search AI.
As for the “why,” Klarna and many of its buy-now-pay-later counterparts continue to expand into new revenue streams. As my colleague and This Week in Local co-host Charles Laughlin examined on a recent episode, they’re driven to diversify revenue given some attrition to their core businesses.
Competitive Mix
As for what Klarna’s expansion into visual search means for the broader category, there are a few implications. First, the field is gradually expanding in its competitive mix, as noted. Each of these players is getting into visual search for different reasons but the result is the same: competition for users.
Second, it raises a question for the field as it grows: how will new players enter, given visual search’s technical complexity? Indeed, ample machine learning and AI training are required for visual search’s core object recognition functions. All the players mentioned above are more or less positioned for that.
One answer could be APIs. And that’s where Google comes back into the picture. Just like it powers site search for websites – and creates ad inventory in the process – it could be the API of choice for any app looking to integrate visual search. To that end, we predict it will roll out a Google Lens API at some point.
This would lower visual-search barriers to entry for consumer-facing apps, while giving Google what it wants: more surface area for monetizable search. Beyond these vested interests, another factor benefits: visual search itself. If it expands in these ways, it could accelerate consumer acclimation and adoption.
