Are you looking to improve product discoverability on your ecommerce site? Want to reduce cart abandonment and boost conversions? The answer may lie in optimizing your product tagging strategy.
In this comprehensive guide, we‘ll explore what exactly product tagging is, why it‘s so critical for ecommerce businesses today, what common pitfalls to avoid, and smart solutions to implement tagging efficiently at scale.
By the end, you‘ll understand how to leverage product tagging to unlock your ecommerce growth potential in 2023 and beyond. Let‘s get started!
What is Product Tagging and Why it Matters
Product tagging refers to adding relevant keywords, categories, attributes, and metadata to products on an ecommerce site to describe them accurately and make them easy to find.
For example, a blue Nike running shoe might have tags like:
- Category: Shoes, Running Shoes, Men‘s Shoes, Athletic Shoes
- Color: Blue
- Brand: Nike
- Size: 10 M US
- Model: Air Zoom Pegasus 39
These tags allow the shoe to appear in search results and filters for terms like "blue shoes", "Nike sneakers", "running shoes for men", and so on.
As an ecommerce business, effective product tagging should be a top priority for the following reasons:
Boosts Product Discoverability
Tags connect your products to relevant search queries and buyer keywords. One study found products with comprehensive tags have 36% higher views and sales compared to untagged products.
|Search Term||% Traffic from Search|
|black leather jacket||58%|
Most product searches are navigational, not generic. Tagging allows you to catch that highly intent traffic.
Reduces Cart Abandonment
Cart abandonment across all industries averages around 70%. But detailed tags can reduce abandonment by providing customers with enough product information to make decisions.
Tags like brand, color, category enable personalized product recommendations based on browsing history and purchase patterns. One retailer saw a 26% revenue increase from personalized recommendations.
As such, product tagging is a high-reward activity for ecommerce merchants – but only if executed properly.
Common Product Tagging Challenges
While the benefits of tagging are substantial, it also comes with significant pain points, especially at larger scales:
Extremely Labor Intensive
Let‘s say you sell fitness apparel and add 100 new products each month. Manually tagging each product image and description could take at least 15 mins per product, or 25+ hours every month.
As catalogs grow, required human tagging effort grows exponentially. Ecommerce websites with 100k+ SKUs would spend thousands of hours tagging manually.
Prone to Inconsistency and Errors
Relying on a small team introduces inconsistencies. One product may get tagged thoroughly while another gets incomplete or inaccurate tags.
Even with guidelines, human taggers make mistakes like typos or applying wrong tags. This affects search performance and customer experience.
Difficult to Scale Up
Hiring more staff to manually tag more products increases costs significantly. Long term viability requires reducing reliance on pure manual effort.
Maintaining quality and consistency also gets harder as more taggers and products are added to the mix.
These pain points lead many merchants to seek out technology-driven solutions.
Leveraging AI to Automate Tagging
Recent advances in artificial intelligence and machine learning have enabled the automation of repetitive tasks like product tagging.
AI-powered solutions can programmatically analyze product data – images, titles, descriptions, SKUs, etc. – and apply relevant tags. This removes much of the human effort.
Here‘s how an automated tagging solution works:
- Product images and data are uploaded to the system
- Computer vision algorithms analyze visual attributes like color, pattern, shape
- Natural language processing extracts keywords from text
- Machine learning matches attributes to an existing taxonomy
- Tags are programmatically applied to each product
Automated solutions can tag thousands of product variants in hours with much higher throughput than human taggers.
- Speed and efficiency – AI tagging is up to 10x faster than manual efforts
- Consistency – Algorithmic tagging ensures uniformity and quality
- Scalability – Easily tag all products in catalogs of any size
- 24/7 availability – No downtime or human fatigue
According to one benchmark, the top AI product taggers achieved 85-92% accuracy in independent tests.
However, AI tagging has some limitations currently:
- Upfront setup and training costs
- Limited ability to capture hidden or subtle attributes
- Periodic human review still required
- Customization may be needed for unique products
Overall though, AI paves the path to scalable, high-quality product tagging.
Comparing AI Tagging and Outsourced Tagging
Rather than build an in-house team, another option is outsourcing product tagging to an external service provider. How does this compare to AI solutions?
|AI Tagging||Outsourced Tagging|
|Speed||Very fast, can tag 1000s of products per hour||Slower than AI, dependent on size of team|
|Accuracy||85-92% typical accuracy||Prone to more errors without AI|
|Scalability||Effortlessly scales to any product volume||Scaling requires hiring more people|
|Cost||Fixed upfront cost, low marginal cost||Ongoing variable costs|
AI tagging sees higher adoption for categories like apparel, electronics where visual cues are strong. Services are recommended for niche product types requiring specialized domain expertise.
The best solution depends on your product mix, budgets and business goals.
Key Recommendations for Ecommerce Companies
Here are my top tips for ecommerce brands looking to step up their product tagging game:
- Audit existing tags – Quantify gaps, errors, inconsistencies in current product metadata.
- Define taxonomy – Structure an optimal, standardized tagging taxonomy for your product catalog.
- Evaluate AI solutions – Consider AI tagging apps tailored to your business needs and product types.
- Compare services – Weigh AI tools vs outsourced tagging services.
- Validate automatically – Spot check AI-tagged products before publishing tags.
- Continuously refine – Use analytics to identify new search terms and optimize taxonomy.
- Prioritize hero products – Ensure your best-sellers have the most comprehensive tagging.
With a data-driven product tagging strategy, ecommerce merchants can reap huge dividends through improved discoverability, conversions, and customer experience.
Hope this guide has provided a helpful overview of maximizing the value of product tagging for your online store. Let me know if you have any other questions!