Artificial Intelligence (AI) can provide immediate and significant value to teams tasked with product experience management (PXM), an elevated form of product information management (PIM), for brands and retailers. AI can serve as a “virtual assistant” that can help with product enrichment and decision-making in related business processes. In this article, we look specifically at how artificial intelligence accelerates and improves product enrichment processes.
Consumers find products across an endless array of channels—both digital and physical. In the digital realm, it is more important than ever to ensure products are appropriately attributed and provide enough information to win the sale.
Attributes are critical not just from the perspective of rich and robust product descriptions, but more so they play a critical part in SEO (Search Engine Optimization) and product discoverability. Search optimization means not just enabling consumers to find items via the free-text search field at the top of e-commerce sites, but also to be able to drill into left-hand navigation (we call them “facets”). Within owned e-commerce sites this may be a bit easier to manage, however selling on marketplaces like Amazon, Target, Rakuten, and others requires that attributes comply with those of the 3rd party platform.
Product descriptions (a.k.a. romance copy) are another crucial factor that informs the buying decision. Inspiring descriptions paint a picture of the consumer using or experiencing the product, getting some benefits or needs met. Bland descriptions reduce the searchability and discoverability of the product and do not create excitement for purchase.
Finally, digital media is also a critical part of informing the buying decision. Consumers want to see products from every dimension possible, and video also has been proven to make a dramatic difference in winning the sale. Due to the volume of work, brands and retailers often settle for just a single image, which is not enough media to meet the consumer’s demands.
While there are many other important dimensions to enrichment, such as how products are merchandised on product listing and product detail pages online or localizing product content and media for channels, the three items listed above represent the minimum viable product (MVP) content that brands and retailers should focus on getting right first.
Digital Wave’s AI for Product Enrichment
Digital Wave’s AI-powered Product Platform is helping consumers significantly accelerate and improve the product enrichment process.
Using neural networks and computer vision, Digital Wave Product Platform examines digital media to extract and provide attributes in a dashboard for team members to review and approve. One of Digital Wave’s customers who is using this capability found that the platform helped to validate attributes applied by team members as well as suggesting attributes that may have been missed, overlooked, or not considered at all. The attributes are then used to automate the placement of products in more categories, providing a wider assortment per category, as well as feed search, navigation, and personalization / recommendation systems.
Using natural language processing, machine learning, and AI, Digital Wave Product Platform also serves as an assistant copywriter. By looking at existing product information, attributes (which are enriched by the AI prior to this step), and a “seed” provided by the user (a short 1–2-line example), ONE generates five product descriptions in milliseconds and exposes the best three descriptions for a user to select. A customer using this capability found it to be invaluable in creating variations in romance copy for a category of products that often have the same description verbatim, except for a word or two. With the Digital Wave Product Platform, the consumer has been able to generate many varied descriptions of products instead of the cookie-cutter copy-paste that was done previously.
Finally, the Digital Wave Product Platform also provides extensive, lightning-fast, actionable dashboards that easily identify bottlenecks in bringing products to market as well as gaps in product data and digital media. The AI engine surfaces issues such as how much inventory dollars are tied up in various process steps and how to remedy the issues so products can get to market faster. It can also identify items missing images or lacking videos, giving teams the reports they need.
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