The feeling of trying a product in person, only by looking at the picture on an e-commerce store, didn’t happen in a day. It’s actually been almost 3 decades through which the history of eCommerce product photo editing has been maturing little by little.
From the very beginning, there was no such thing as image editors, where there was no scope for editing after the photoshoot before posting the photo.
How did it get from that to now, where viewers expect more even though the photo looks exactly like the real product? Carry on with us, that very walkway is about to widen before you.
The Rise of Product Photography in eCommerce
It was the very end of the 90s, when photographers slowly began to realize, at a very slow pace, the importance of editing the photos they took.
The Early Days: The Marketplace Wild West
Ecommerce pioneers like eBay and Amazon had been doing great work across the market. And in the midst of this epochal reshaping, a huge roadblock has come up like a thunderbolt- the lack of adequate lighting in product photos.
It was not possible to come up with an acceptable solution to this problem of light and darkness at that time. Instead, eCommerce marketers understood it well that product images should be kept as clean and free from unnecessary things as possible.
First-Generation Editing: The Era of the Pen Tool
In continuity of cleaning up the image came the idea of isolating the product from its background. This trend got a great boost thanks to the then-popular Photoshop Pen Tool (introduced in 1991).
Photographers used this pen tool to carefully draw lines around the object with their bare hands to separate it from the background.
Yes, you guessed it right, I’m talking about clipping paths.
This basic level of work was a breakthrough at the time. This was the late 90s, you see, when photographers were just starting to get used to the concept of photo editing.
High-Stakes Category: Apparel
Later, joining clipping paths was cropping, and the apparel industry was able to reap its full benefits. The editors couldn’t select the edges of the product very finely, but what they could do was not at all small.
The best part was that by cropping, they could keep the products in the entire catalog the same size.
Keeping up with Marketplaces
Marketplaces have taken their shortcomings against customer demand in the past decade very seriously. In line with this, they created specific image guidelines throughout the first decade of the 21st century.
The Directives That Rewrote the Pixel
By 2010, Amazon brought some conditions for uploading images which binds artistic intent within brackets. This has also led photographers to gradually rethink how they take pictures.
- Pure White Background: Amazon was the first to announce that main images must have a white background color (RGB 255, 255, 255).
- Shape of Image: Images had to be kept in a square (1:1) aspect ratio along the width and length, which was 1000×1000 in pixels.
It was at this point that the sellers realized the difficulty of editing so many photos at once. For good reason, finding a template for thousands of SKUs became inevitable, but the idea was only in its infancy at the time.
Platform-based Changes
It didn’t take long for eCommerce platforms to turn into comprehensive services. Thanks to this, the industry got-
- AWS: Amazon launched its cloud service, where users can set up their complete business online, which put the final nail in the coffin of loads of paper handling.
- Shopify and Etsy: The emergence of these two platforms gave ordinary users, who aren’t that much tech savvy, the opportunity to enjoy photo editing with ease as well as create digital stores.
Advancing Image Editing Tools up to Process Automation
The 2010s saw editing tools that have pushed photo asset preparation towards automation. At least you can feel the need for this massive boost for the following workflows:
Digital Asset Management Replaced Scripting
As time went on, catalogs grew fatter, so working in the same way that had been going on for a long time was time-consuming. Then, software began to bring new tools to make editors’ work easier that had never been seen before.
The Automation is in Pursuit
Photoshop broke out of its traditional form and brought the following features of applying continuous edits to thousands of pictures with a single click:
- Resizing
- Sharpening
- Saving
Consequently, editors got their hands on plugins that can do quick color matching and even batch clipping.
Digital asset management didn’t just stop there, rather automated the following processes to shorten the long path of a photo from the camera to the store:
- Metadata tagging
- Color profile conversions
- Web-ready formatting
The Rise of Outsourced Hubs
As the second decade of the 21st century began, there was a boom in image editing outsourcing. Because the brands around the world utmost feel the need for professional touches for their large scale photo asset.
Other most crucial factors that contributed to their badly needs for the services are:
- 24-Hour Production Cycles: Outsourced companies maintained large teams that were so efficient that they could deliver thousands of edited photos within 24 hours.
- Managed QA: Beneficiary brands found these photo editing partners as well-organized quality assurers who checked each image with their bare hands.
The First Wave of AI
The Machine Learning in Action
Computer vision became a boon for both marketers and editors as they got their hands on AI-powered photo editing as well as AI image generation tools.
Automated Boundary and Pixel Refinement
- Background Removal: No more need for clipping paths, which took a lot of time with human editing. One click is enough to isolate an object within seconds.
- Denoising and Upscaling: AI’s photos provide just the quality the displays of current devices want to show. At least AI is learning on its own to detect what is noise and what is a material defect in the product.
Generative and Context-Aware Editing
In recent times, customer expectations have been constantly rising due to frequent developments. Editing with the understanding of the context of a picture is nothing but a consequence of it.
Redefining the Canvas with Pixels on Demand
The AI self-learning trend has made everyone in the eCommerce supply chain greedy. Those who were previously content with just fixing the photos are now looking to get all their photos from scratch, ready for their campaigns.
Advanced Spatial and Asset Manipulation
- Generative Fill and View Synthesis: Editors now don’t go through the hassle of re-shooting the product when they need to create its views from more new angles. They just generate the views while keeping the product the same.
- Auto-Shadowing: AI can now understand what the shadow of an isolated object will be when placed on any surface in a lit environment.
Commercial Scaling and Conversion Optimization
The way generative AI instantly creates countless SKU variants by simply changing the color or background is taking the photography costs of businesses down to zero.
The way marketers test which images are bringing the most conversions is getting faster ever. The result? Viewers are turning into buyers in a much faster time.
Frequently Asked Questions About The History of Ecommerce Product Photo Editing
1. When did automatic background removal take the place of manual clipping paths?
This change came around 2018 when SaaS tools started to go mainstream. But manual edge selection hasn’t lost its relevance yet because it still gives results way better than AI when edges get complex.
2. What factors have led ecommerce brands to move from simple product shots to picture editing?
The variety of platforms on the internet and the mobile-first trend have added constraints like specific format, resolution, etc. These are the main reasons why brands are turning to picture editing, because mere product shots cannot meet these demands.
3. How important is the ghost mannequin effect in the history of eCommerce product image editing?
This technique of overlaying the inner lining of product images emerged in the early 2010s. With this effect, editors can bring clothing to life by blending it with an almost 3D look.
4. When did batch editing become extremely relevant for large product catalogs?
At the very beginning of the 21st century, the demand for working with large-scale catalogs for SKUs in front-row marketplaces began to rise. And it was precisely to meet this demand that batch editing began to become necessary.
5. How did digital studios handle color matching of products before AI?
Before AI, studios manually worked with calibration cards (you can recall, for example, X-Rite ColorChecker cards) that they placed inside the frame of the picture. Editors would collect samples that they were targeting to obtain RGB profiles. Here they would check whether the colors shown on the screen matched the actual product in every way.
Final Words
The history of eCommerce product photo editing is actually a flow where it has advanced along with different tools with itself depending on the needs at different stages.
Editing that once took a lot of labor and time is now a matter of seconds. Not only that, the time and money saved as a result went towards more important tasks, which brought about new editing techniques.
But the task of providing quality checks is still in the hands of humans, at least when working on a larger scale, there is no efficient alternative. Do you have to deal with the same feelings with your product catalogs?
Retouching Zone, a pioneer in platform based image editing, is here to be your partner to shoulder these burdens. Take their free trial now and see how photos edited by a team of experts with 12 years of experience turn out.
