How to enrich your product data to create great AI product descriptions for Shopify
eCommerce is driven by data, so getting your product data into a state of the highest quality is imperative if you’re to create engaging and informative AI-generated product descriptions. This practice, AI data enrichment, not only improves the customer experience but also influences SEO performance, crucial if you’re operating on platforms like Shopify. You can leverage a product description generator on Shopify to streamline this process, but at the end of the day, its effectiveness hinges on the quality of the data you input. This article has a close look at how you can enrich your product data effectively and make your AI-generated product descriptions stand out from the crowd.
The Importance of AI Data Enrichment in eCommerce
Fundamentally, data enrichment involves improving the quality of your product information – accuracy, completeness, relevance, reliability, recency – so it’s usable. It usually includes addition of detailed attributes, correction of inaccuracies, and monitoring of consistency across your product catalogue. Why does it matter so much?
Combatting shopping cart abandonment: Comprehensive product descriptions help customers make informed decisions and complete their journey.
Enhancing customer loyalty: Detailed, accurate, and up-to-date product information engenders trust in your brand and encourages repeat purchases.
Boosting product discoverability: Enriched product data with tags and categories, enhances search functionality, making it far easier for customers to find what they need.
Types of Product Data Enrichment
Product data enrichment takes different forms, but they’re all aimed at providing a more comprehensive and appealing product presentation. Key enrichment types include:
- Category organisation: Structuring products into well-defined categories for easier site navigation
- Certification information: Adding information for compliance, such as eco-friendly labelling or safety certifications
- Size and dimension details: Precise measurements, especially important in sectors like clothing.
- Intelligent tagging (identifying and labelling): Using tags like “waterproof jacket” or “organic skincare” enhance searchability for users.
Steps to Enrich Your Product Data
When it comes to actual action on product data enrichment, AI has become a background tool which greatly speeds up the endeavour, as well as minimising the risk of human error. Here’s a brief rundown of common enrichment processes:
Data cleansing: Start by identifying and correcting errors in your product data. This includes fixing typos, standardizing formats, and removing duplicates.
Filling in missing values: All relevant product attributes should be filled in, which might involve adding specifications, detailed descriptions of features, and addition of digital assets like diagrams, instructions, or image galleries.
Providing further product properties: Layered on top of the basic data, these extra attributes include use scenarios (cases), benefits (based on features and attributes), and customer reviews, which are rapidly becoming an expectation of customers.
Using AI-powered PIM software tools: A Product Information Management (PIM) platform is a boon when it comes to carrying out these processes, as its array of AI-driven tools can automate many areas of data enrichment, which both guarantees consistency and saves a lot of time – a key factor in the race to minimise TTM compared to competitors.
The Role of AI Product Description Generators
If you deploy an AI product description generator, it’s straightforward to integrate it with Shopify, and such a tool is capable of transforming enriched product data into truly compelling product descriptions. BUT, the effectiveness of these AI generators depends heavily on the quality of the product data you input (Remember ‘Junk in, junk out’?). You may be able to produce great, attractive, persuasive product descriptions, but the low-quality data input leads to an inaccurate description, regardless of that text. That’s why investing time in product data enrichment is not only desirable, but obligatory.
Best practices for enriching product data for Shopify
To fully optimise how effective your AI product description generator can be on Shopify, follow these best practices:
- Focus on your main products: Prioritise the order in which you enrich data -your best-selling and most competitive products come at the front of the queue!
- Implement the 80/20 rule: It’s 20% of your efforts (time, people, money) in enriching the data that will drive 80% of your sales.
- Fill Content Gaps: Try to cover all bases in your product descriptions regarding potential answers to customer queries about information
- Leverage your customer feedback: You should be continually monitoring product data and insights from customer reviews and enquiries can significantly help you to tweak or revise the content you provide on any given product page.
- Use PIM: If you integrate your AI product description generator with a Product Information Management (PIM) system and then Shopify, you streamline data management, ensure consistency, and optimise your processes for onboarding supplier data for their products, using AI to enrich that data and then sending it out to your sales channels.
Choose Descriptionwise for your AI product descriptions
At Descriptionwise, our top-tier AI-powered product description generator is designed precisely with eCommerce optimisation in mind. Its versatility makes it ideal for both B2B and B2C eCommerce needs. What’s more, it integrates seamlessly with major PIM platforms like Akeneo, Pimberly, and Sales Layer. Our Descriptionwise tool makes the most of your high-quality, enriched data, effectively deploying it to create high-quality and customisable product descriptions. You can train Descriptionwise on your product data models so that it reflects your unique brand voice and, even better, you can generate descriptions in bulk, removing the stresses and strains of attempting to scale your business relying on manually-created product descriptions.