Published on
June 11, 2021
AI (Artificial Intelligence) is entering every part of our lives.
This smart technology can be seen almost everywhere, from self-checkout counters and automated security checks at airports.
Consequentially, according to a PwC report, Artificial Intelligence is expected to boost global GDP by 14%, or $15.7 billion, by 2030.
It's pretty much assumed that AI will expand rapidly in the coming years, with companies like Google and Microsoft already investing extensively in new AI projects.
For example, Google's £400 million takeover of DeepMind, a start-up that focuses on software and machine learning with positive effects, is only one of the planned investments as the technology's promise becomes a fact.
Other companies like Apple, Facebook, and IBM aren’t staying behind this significant trend.
The e-commerce industry is no exception. By the end of 2021, global e-commerce transactions are expected to hit $4.88 trillion.
Furthermore, the global pandemic has altered people's buying habits, increasing their appetite for internet shopping more than ever as it satisfies user desires without imposing any physical constraints.
That’s why many e-commerce companies are now using AI to understand their clients better, discover new leads, and improve customer service.
Catalog management is one of the e-commerce areas that AI widely transforms. It's not always easy to keep track of your catalog.
The level of catalog organization affects the ability of the company to sell its products across markets and increase product acquisition, which leads to more conversions.
Intelligent product tagging based on Artificial Intelligence is the answer to challenges related to catalog management.
In this article, we’ll talk about tags, intelligent product tagging , and how this technology can help e-commerce managers streamline their operations and increase their revenue.
Products must have tags for the catalog management system to be effective. Product tags are a set of additional attributes that apply detailed definitions and metadata to base-level product specifics.
Your product title and introduction will be essential information, while tags will provide more in-depth information.
A range of tags is assigned to each product in an e-commerce store to define its characteristics, features, and category.
Each tag would contain facts about the product, and anything from color and size to type and brands can be included.
A skirt, for example, may have tags like white, maxi, midi, silk, summer, and soon, containing all the necessary information to affect a shopper's buying decision and sort products based on their specific needs.
You can improve search features, product ranking, and product ratings while also simplifying the inventory management process by adding attribute metadata to your products.
The method of retail product tagging allows retailers to apply logos to their merchandise.
Suggested read: The Complete Guide for Automatic Product Tagging in E-Commerce
Conventional product tagging tactics take along time and a lot of effort.
Based on the number of products in a store, a traditional manual tagging method can take anywhere between 30–40 hours per week, identifying from 200–300 items a day.
Even then, it's possible that the employee misidentifies a summer dress like a red evening gown, resulting in a slew of other discrepancies.
Consider the impact if 500 items were misclassified.
Because of the way these items were tagged, there's a chance they won't show up in search results, which will be a colossal mistake for retailers.
Human fatigue often disrupts accuracy.
Manual tagging can have an effect on employees' energy and morale due to the extensive details and time-consuming nature of the job.
Furthermore, manual product tagging can lead to poor catalog management, which can result in a number of issues:
- Supply chains that are too complicated to satisfy consumer demand in real-time.
- For new products, this will mean a time-consuming digitization process.
- Search results that are incorrect and contribute to a poor shopping experience.
To avoid these issues, catalog data must be well-organized and provide correct product details.
It would be almost impossible to do this if you run the retail tagging process manually.
There is, however, another choice. With the emergence of AI (Artificial Intelligence), new methods of automating retail operations, such as product tagging, have emerged.
To effectively organize the product list, AI-based intelligent tagging, also known as automated tagging, is replacing manual tagging, saving a lot of time and resources.
Let's take a closer look.
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Intelligent product tagging takes care of retail tagging for you through a completely automated process that requires no human intervention.
This improves operational stability and catalog loading times while also enhancing tag accuracy.
This is a win-win opportunity with any shop trying to strengthen its brand marketing strategy.
Auto tagging organizes and marks images in the product catalog based on their characteristics using advanced Artificial Intelligence algorithms.
Deep Learning is the core of these algorithms to make the fashion tagging process more accessible and eliminate the need for human interference.
Automatic tagging works through analyzing an image and identifying attributes that are related to specific keywords, resulting in accurate metadata for catalog properties.
Intelligent product tagging is a trained Artificial Intelligence technology that can recognize elements in photos in the same way humans can.
A brief look at a snapshot is all it takes for us to find out if it's a skirt, a blouse, or a pair of sneakers.
Since this is a daunting task for algorithms, people have handled the majority of product tagging.
Computer Vision and Neural Networks, on the other hand, now replicate the workings of the human brain, allowing robots to perform the same activities as humans.
Computers can now process an image and remember its features, returning semantic information in textual form, thanks to these technological advances.
Improved product discoverability and search engine click-through volume are some of the benefits of automated image tagging.
Furthermore, it enables customers to easily browse the whole catalog and find products that meet their needs.
Layering several tags per product helps users to have a smoother onsite experience for a number of reasons, including improved friction.
It's important to coordinate and manage the entire inventory based on different customer groups, ranks, and locations using geographic and segment-specific identifiers.
Instead of targeting all, modular and adaptive tags would enable you to more effectively hit a certain audience, resulting in better conversion rates.
In general, a concrete program for automated product tagging in your e-commerce store would aid you in lowering price declines, avoiding overproduction, and reducing development loss, resulting in a more sustainable and financially efficient online strategy.
You shouldn't look at product tagging as some nice addition to your online marketing plan.
Instead, think of it as an essential part of your e-commerce shop.
A structured collection of relevant tags improves the overall online branding by giving your clients just what they want without having to search for it.
Pixyle.ai's automated product tagging engine will help you get a clean catalog, refine your store's search results, and skyrocket your sales by reviewing the whole product catalog in just a few seconds.
To see how it works, try our demo.
Pixyle AI generates e-commerce product data that enables brands, retailers and marketplaces to deliver exceptional product discovery experiences.
