To put it frankly, it’s always the right time to improve your product data and optimize product content! While this is a universal truth, each retailer has a unique position and situation that impacts how easy or difficult this task is.
Retail tech stacks vary and are rarely static. You may be re-platforming, piloting, building a new solution in-house, or even eliminating aspects of your tech stack entirely. Variables like these may lead you to think that now is not the time to invest in Product Content Optimization (PCO), or frankly, you may not be sure where to even start!
Poor Quality Product Data Drives Poor Performance
Poor quality data equates to missed revenue opportunities. This is because AI-powered product content optimization enhances product discoverability, improves customer experience, and grows sales.
In fact, AI can improve productivity in ranges from 5:1 to 100:1 or more, creating a $1.7 trillion opportunity for retailers. Additionally, the revenue opportunities presented by retail AI are undeniable, as 69% of retailers who use it report an increase in annual revenue, directly attributed to their AI adoption.
Here’s your turnaround plan to supercharge advertising, marketing, and e-commerce by harnessing AI to optimize product content for every phase and stage.
Product Content Transformation Guide
Pre-Revenue or Pre-Launch?
What wonderful timing! You can get started with Lily AI quickly and easily, building clean data and better customer experiences from the ground up.
To get started, you’ll need to share product images and basic text that describes them. Lily AI uses a mix of generative AI, machine learning, deep learning, computer vision, and small language models to generate product content such as attributes and metadata from your text and images. It can also generate content based on CAD files or sketches, though photos and text generally provide more detailed outputs. The data and content Lily creates are highly detailed and inclusive of both objective product features as well as the natural language real people use when they search, shop, and speak.
Re-Platforming?
This is a critical time to kill two birds with one stone. You don’t just have to migrate your existing data to a new e-commerce, search, PIM or MDM platform. Instead, you can migrate enriched data into a new system and a new taxonomy.
It’s absolutely critical that retailers have everything ecommerce-focused in order, as we see the worlds of AI-powered search and the ways people shop are changing. Upgrading your product data and taxonomy, while simultaneously replatforming, means that you’ll start fresh with massively improved customer experiences, product discoverability, and the ability to better connect with potential customers everywhere they search and shop.
Don’t Have a Centralized Product Data Management Platform?
Do you rely on an e-commerce platform alone, like Shopify? Retailers who do are in the perfect position to bolster their product attributes by way of AI. Whether you’re integrated directly into Shopify or a simple batch file via SFTP, we can help.
Lily AI will provide you with clean, accurate, complete, and up-to-date data to import into any ecommerce platform or tool you use. For example, with our Shopify integration, brands and retailers can automatically export their product catalogs to Lily AI. The integration delivers attributes downstream, while simultaneously ingesting data directly from Shopify, without working with flat files or batch files. As a part of this process, retailers receive product attributes that describe physical product details, as well as trends, occasions, and styles.
This makes it faster and easier than ever to enrich your entire product catalog with high-converting, customer-centric product attributes. The best part, Lily is tech-agnostic and can integrate with any system you use!
Already Have Basic Product Data and Attributes?
Let’s say you already have some basic product data and attribution capabilities in place . . . or you rely on vendor-contributed attributes throughout your store. In all likelihood, these attributes reflect the old adage “you get what you pay for”. How accurate and precise are they, and how consistent are the results? Do they capture basic details, or do they go deeper to capture more nuanced natural consumer language and preferences? Do you have the ability to define and refine the parameters that describe a particular aesthetic, or are you left with “out-of-the-box” definitions that don’t allow for customization?
Lily AI: The Leader in Product Content Optimization
Only a retail-focused AI that injects customer language throughout your product data and attributes will level up your product discoverability.
Lily AI is the leader due to its robust, inclusive, and industry-leading dynamic taxonomy, which includes:
- Objective Data: Including item types, materials
- Subjective Data: Including styles, occasions
- Synonyms: Such as “glossy” vs. “high shine”
- Macro and Micro Trends: Such as Barbiecore, Modern Farmhouse, or Clean Girl
- Customer Language Enrichments: Like site search queries, SEO terms
- International Language: Including localized terms, translations
The pace of AI can’t be beat either, as it consistently keeps product attributes, titles, and descriptions clean, accurate, and updated to reflect current customer language. Learn more about our industry-leading approach to Product Content Optimization and how it can impact the future of AI-powered search and shopping.
