Getting shoppers to your website is one thing. Getting them to have a great experience, discover products they’re looking for, complete a purchase, and even find new items they didn’t know they wanted, is another. And frankly, the latter is a steeper hill to climb. But if you have robust product tags and an overall efficient and strategic process for product tagging for eCommerce, you’ll be set up for success.
Why Does Product Data Matter in eCommerce?
As early as 2017, The Economist declared that data is “the new oil,” A.K.A. the most valuable resource. Achieving your eCommerce goals depends on multiple variables, but product data is the foundation that sets you up to win.
The retail industry and eCommerce, in particular, are accelerating at a rapid pace, largely due to the impact of the pandemic. This year, the number of digital buyers will reach 2.14 billion. According to Statista, eCommerce sales are projected to climb to $6.5 trillion by 2023, comprising 22% of retail sales worldwide.
With more consumers shopping online, brands and retailers must create convenient and accessible shopping journeys that fulfill shoppers’ wants and needs.
However, this is easier said than done, especially if you have thousands of SKUs. A large inventory means numerous website pages and just as many opportunities for shoppers to get lost, grow frustrated, and drop off.
This is where data comes into play. Your product metadata contains information about all the items you have in your inventory. It usually includes images, titles, brand names, attributes (style, color, cut, etc.), prices, descriptions, variants, availability, and more. By adding all this information to your catalogue, you can manage your products and display them in a way that is intuitive for your customers, even when you have tons of items in stock.
What Are the Consequences of Lacking Product Data and Catalogue Management?
With consistent, detailed, and accurate product data, catalogue management becomes simple and efficient. You can organize your products and structure them into a hierarchy as well as easily create relevant product groupings for your shoppers and business goals.
However, when product data is incomplete, inconsistent, or inaccurate, your customer experience suffers alongside your backend inventory management capabilities.
1) Poor product search and discovery experience
One of the first things that shoppers do when they visit a website is use the search engine, whether it’s text- or image-based search. Getting irrelevant or insufficient search results because of inconsistent product data leads to a negative customer experience. For example, if a shopper searches for “blue jeans” and receives only a few results because most of the jeans in your inventory are tagged as “navy denim” or “indigo denim flares,” they’re likely to leave in favor of another site.
2) Broken supply chain
Product and catalogue data are crucial for informing demand-forecasting and inventory management. For brands and retailers that have a huge number of SKUs coming in and out of their stock daily, a precise view of what’s happening behind the scenes — down to the finest product details — is a must. Otherwise, erroneous data leads to a waste of resources and unsold items in warehouses. For example, if a popular top is missing product data, it’s difficult to understand what’s so popular about it: The neckline? The print? Understanding the data behind the sales helps to create a better-informed inventory strategy.
3) Fragile foundation for further digital transformation
Rapidly changing consumer demands, increasing competition, and advancing technologies are drivers for brands and retailers to continuously innovate. With a fragile base of unorganized product data, implementing new digital solutions becomes a tedious and complicated process because you’re creating new data on top of a broken foundation.
Product Tagging for eCommerce: The Basics
Product tagging is the process of adding data to your products, including creating, assigning, and managing labels (or “tags”) for each product to describe, categorize, and structure its position within your inventory. As we touched on earlier, these tags, or product metadata, include everything from the brand, color, size, type, style, use-case, and more. This process is typically carried out by a merchandising team, usually responsible for the assortment, categorization, and display of all items in a brand’s inventory.
Why is product tagging important?
In eCommerce, product tagging must be consistent, updated, and accurate to enable relevant product search and discovery, and a flawless customer experience. Descriptive tags push your products and website to show up on external search engines and they make it easy for shoppers to find what they’re looking for through on-site search, menu navigation, and filters.
By offering an understanding of the product attributes that shoppers gravitate towards, detailed product tagging also opens the door for more precise personalized product recommendations, boosting the customer experience.
Finally, when it comes to the operations side, product tagging done right ensures accurate reports of sales, costs, and product demand and supply for optimized inventory management.
What are the common pitfalls of product tagging for eCommerce?
While the process of product tagging for eCommerce can yield many benefits, it also comes at a cost, and the following issues are commonly faced by brands and retailers:
- Time-consuming and hard to scale: For retailers and marketplaces with hundreds of thousands of items, including from third-party partners, manual product tagging takes so much time and effort that could easily be directed to other parts of the business. Not only that but with rapidly changing inventory, the job is never done.
- Costly: As SKUs pile up, retailers often have to hire additional staff to complete the product tagging process. Otherwise, you run the risk of being slow to bring products to market, which can impact sales, particularly for trendy or seasonal items.
- Inconsistent and incomplete: Synchronizing a growing number of product categories, models, styles, and attributes from multiple sources, on time and consistently, is a huge, labor-intensive task. When products are incorrectly or inconsistently tagged, you miss synonyms or thematic terms commonly used in searches along with the potential sales.
How to Overcome Product Tagging Challenges With AI
Manual product tagging is one of the major hurdles that retailers have to overcome to unlock opportunities for improving customer experience. Fortunately, advancements in AI, particularly visual AI, provide a solution to the most common product tagging pitfalls.
Each product within a catalogue contains at least one image, showcasing the numerous attributes that make a single item unique. Visual AI is able to scan these images and identify the details within them, creating a new path for detailed and efficient product tagging.
How does automatic product tagging for eCommerce work?
Because visual AI understands images with human-like accuracy, an automatic product tagging solution using this technology can break down each element within a given product image, categorize them, and tag them with additional metadata. For example, if a leather jacket was manually tagged as being a cropped, black biker jacket, visual AI would be able to add new tags such as silver hardware, red lining, and casual in style, creating a more detailed description of the item.
What’s more, because it doesn’t rely on manual tagging, visual-AI-enabled product tagging can be done near-instantly for massive inventories, ensuring consistency across the catalogue and tagging new items in real-time.
What Are the Key Benefits of AI-Powered Automatic Product Tagging?
As the backbone of your eCommerce site, getting product data and tagging right sets you up for success:
- More accurate search results: Connecting shoppers with the exact products they’re looking for is tough when they don’t use the same terminology you do to describe items. AI-powered product tagging ensures that they consistently find what they’re looking for even when they enter synonyms or thematic queries (i.e. “party dress” or “summery top”) since each product has so many additional attributes and synonyms. By serving up the most relevant results to your highest-intent shoppers, you not only improve customer experience but also drive significantly more search-generated revenue.
- Better personalized experiences: Traditional eCommerce personalization relies on basic product data, demographic data, and behavioral data in order to make recommendations. With the additional product data provided by visual AI, retailers have the potential to create even more accurate recommendations, because they will have a deep understanding of the details that draw shoppers to particular items.
- Improved efficiency: Automating the tagging process frees up time and resources while reducing human error.
- Optimized catalogue and inventory management. AI-powered product tags give you insight into the performance of both your products and their attributes. You can know which products are selling fast, which styles and details are gaining steam, and which to pass on. With improved predictive capacity, you can make better-informed decisions that minimize waste and prevent overproduction.
Product Tagging and the Customer Experience
Without a seamless product discovery experience, it won’t matter if you have the best products, messaging, or service. Because at the end of the day, if customers don’t find what they’re looking for, they develop a negative impression of your brand.
With AI-based product tagging for eCommerce, you can improve the chances of shoppers having a positive and engaging customer experience right off the bat as they search and discover your products without any friction. By cementing your brand in their minds as the destination that understands and serves their needs, you’ll drive long-term loyalty and word-of-mouth marketing to like-minded shoppers.