Since 2017, the global revenue for e-commerce has jumped by 103%, with brands clamoring to build, through immersive visuals, online shopper experiences that replicate in-store visits. To that end, brands must manage a large volume of ever-growing visual assets, as shown by these statistics:
- From 2019 to 2020, video usage across our customer base increased by 88%; a large retail customer’s content bandwidth jumped by 129%.
- We managed and delivered an average of 2.4 million image and video assets per customer in March 2021 alone.
At eTail West, I gave a talk on a game changer in e-commerce: personalization, which boosts conversions, fosters content virality, and wins customer loyalty, let alone attracting a flywheel of repeat buyers. Below is a recap of that presentation.
Consider this gratifying experience of mine. A clothing ad on Facebook that caught my eye a while back drove me away from my newsfeed to visit the brand’s e-commerce site, where I made a purchase. Before long, I started seeing ads for similar apparel, which led to a discovery of new brands and products. All that personalized content based on my taste and shopping history was a welcome surprise, for I was able to make purchases in a fraction of the time I’d have had to spend at the mall.
Not only that, that immersive, “near-life” experience mimicked how I’d shop in person. I could zoom in for a clear look of texture, view products from different angles, and browse photos uploaded by other shoppers. Besides, instead of being on models in studio light, the apparel was worn by women of a build similar to mine, photographed in a more natural or candid setting.
Also important, because algorithmic personalization self-learns through my preferences, its recommendations improve over time, more precisely serving me on my retail journey in the times ahead.
Given all the benefits of personalized experiences, what’s stopping brands from creating them? By and large, the myriad resources and technologies required are the major barriers.
The biggest bottleneck is the supply chain of creative professionals. Not only are many people involved in the process as a rule, but they’re also manually managing multiple versions or customizations to accommodate the deluge of screen sizes and unique geographical requirements. Browsers and network bandwidths complicate things, too, especially in the absence of optimized content, particularly weighty images and videos.
An ideal solution is Cloudinary’s Media Experience Cloud, which automates with AI the management of media assets end to end: uploads, organization, version control, and generation of variations for all device types and network bandwidths. Creative teams can then focus on projects that require initiative and brain work.
Being image and video aware and integratable with your tech stack, the Media Experience Cloud performs tasks that traditionally require manual efforts, such as the following:
- Tag assets for storage, organization, and access.
- Convert raw photos to web-ready images.
- Dynamically crop and scale images based on their content so that you can generate responsive layouts, change colors, and apply other visual effects for all viewing devices and screen sizes.
- Determine images’ optimal point of focus, such as faces and moving objects, after which you can smart-crop and reframe those images to focus on the primary subjects regardless of screen orientation.
No matter the exponential growth in the volume of media assets deployed for e-commerce, AI can intelligently manage and optimize them all for use cases and user context with no human involvement. The result is the very best experience for online shoppers irrespective of device.
Building agile workflows with Cloudinary’s capabilities, which are powered by AI and machine learning, affords you flexibility for personalizing user experience in real time and at scale. Ultimately, you work smarter, not harder, assured that your shoppers will be well served.