This article was originally published in Navigating Commerce.
Gone are the days when armies of salespeople had to pull strings to close deals. As buyers and customers become increasingly tech-savvy, online marketplaces take center stage, pushing businesses to prioritize seamless interactions to support buyer journeys. Today, given the vast array of products available, efficient search functionality is the cornerstone of user experience. In fact, a staggering 92% of B2B purchases start with a search, where availability and convenience are critical drivers for brand choice.
To create positive search experiences, two crucial aspects come into play: product data quality and leveraging this data for enhanced discoverability.
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Poor data quality on online marketplaces presents significant challenges for buyers and sellers. Imagine a scenario where a business is seeking precise industrial machinery parts. Accurate and comprehensive product details are paramount for informed decision-making. However, inconsistent labeling practices among sellers make comparing similar products challenging, and missing or incomplete information further hampers the buying process, leading to search abandonment.
Issues with product data quality include:
Multiply just one of these issues across thousands of SKUs and its detrimental impact on the business becomes evident.
Generative AI, powered by large language models (LLM), is a transformative solution for data quality challenges in marketplace search. Its adoption is not just an incremental change but a seismic shift in how businesses operate, interact, and grow — initiated by forward-thinking leaders. Unlike other AI forms, generative AI goes beyond data categorization, and creates new content, including text and images, making it a cutting-edge technology with immense potential.
In marketplaces, much of the data is provided by third parties—creating challenges around managing product data quality. Generative AI also helps in this context. Below are some examples.
In B2C marketplaces like Walmart and Amazon, which allow numerous approved vendors to sell identical items with varying descriptions, AI generates accurate and comprehensive product descriptions by amalgamating data from various vendors. This helps eliminate product confusion and enhances the customer experience. AI also streamlines these marketplaces by detecting and resolving duplicate content and automating the review and ranking of product descriptions, offering both vendors and customers valuable insights.
In the B2B realm, which involves curated manufacturer marketplaces and platforms like Staples with a more liberal selling approach, generative AI ensures adherence to marketplace guidelines by curating and approving product listings, suggesting complementary products for enhanced cross-selling, and evaluating seller data to establish a ranking system that highlights high-quality vendors while maintaining consistent customer information.
This multifaceted application of generative AI ties together data accuracy, customer experience, and vendor quality across diverse marketplace scenarios.
Leveraging product data, generative AI employs advanced techniques such as data enrichment, attribute completion, semantic search, sentiment analysis, image generation, and more. These powerful capabilities help improve search experiences, increase conversions, and heighten brand loyalty for buyers.
Helpful, informative, and consistent product information captures buyers' attention. Attributes like price, size, and color, serve as the building blocks of the marketplace catalog. They are used as faceting and filtering parameters for navigation, product comparison reports, and promotions. A lack of proper product attribution can make it harder for shoppers to find a product among similar offerings. Intelligent product attribution, powered by generative AI and LLMs, revolutionizes marketplace search by analyzing visuals and text for accurate listings.
Dominant colors, designs, and materials are identified through attribute extraction, boosting discoverability. From manufacturing to construction, and even in the automotive industry, the application of AI has become palpable. AI swiftly handles electronic components like resistors, capacitors, and circuits and construction materials like bricks, cement, and steel beams. Marketplaces can further improve search rankings using product freshness, reputation, popularity, and location awareness for personalized results.
Beyond standard attributes like price, size, and color, AI-generated product titles, descriptions, FAQs, and comprehensive SEO metadata now capture intangible qualities like reliability, safety, and aesthetics from complex product data. The result? Enhanced search relevance that resonates with buyers. Shoppers find products that precisely meet their needs, leading to increased engagement and higher conversions. Moreover, captivating product titles showcase a brand's unique voice and enable teams to create appealing marketing messages.
To continuously improve product data to enhance search, AI models can unlock valuable information from customer reviews and search logs. LLMs extract attributes, sentiments, and preferences from reviews, creating compelling product stories. With AI-driven analysis of search queries and attributes, a self-learning system predicts top search terms, even for the latest products. This creates an unparalleled search experience, serving users with relevant content and propelling them toward the next phase of the purchase cycle.
Generative AI holds the key to solving many marketplace challenges. If you're new to the technology, it may seem daunting. Start by evaluating your goals and strategizing practical solutions that deliver real value. And remember innovation requires both the courage to start and the perseverance to follow through. It’s time to embrace the power of AI for marketplace success.
Author bio: Jayme Reynolds is the Principal Director of Commerce and Data Partnerships at Grid Dynamics, a leading provider of technology consulting, and implementation services for Fortune 1000 corporations undergoing digital transformation.