AI, agentic commerce and the need for impeccable product data
While most retailers view product data quality as a basic operational requirement, this perspective is dangerously outdated.
In today's AI-driven commerce landscape, subpar product content isn't just a missed opportunity — it's actively eroding your competitive position.
What many retail leaders have yet to fully grasp is that every product detail page now functions as an AI-enabled digital salesperson, capable of either championing or sabotaging your brand.
Consider this: Industry giants like Amazon and Walmart haven't merely set high standards for product content, but have fundamentally redefined how consumers interact with digital commerce. Their rigorous approach to data quality isn't just about maintaining clean databases; it's about building an AI-ready foundation that drives market dominance.
Yet, surprisingly, many retailers continue to treat incomplete specifications, low-quality images and imprecise descriptions as minor operational hiccups rather than what they truly are: strategic vulnerabilities that directly impact revenue.
Survival is at stake, as the next great commerce shift isn't just another tech upgrade, but a fundamental shift toward high-context, conversational discovery powered by large language models.
These sophisticated AI shopping assistants won't just prefer rich, detailed product content — they'll actively filter out products with inadequate data.
The uncomfortable truth is, retailers that are clinging to traditional data practices aren't just risking customer confusion and returns, but are systematically making themselves invisible to the next generation of AI-powered consumers.
The question isn't whether to invest in impeccable product data — it's whether your business can afford not to.
The current state of product data: A digital salesperson in need of an upgrade
If your website is your digital storefront, your product details page is your digital salesperson. But what happens when that salesperson is unprepared?
Missing specifications, fuzzy images and/or inaccurate descriptions lead to shopper confusion. This confusion is not benign; it results in increased returns and higher cart abandonment rates.
While it’s been long established that 42% of customers will abandon a purchase due to insufficient information, we now know poor image quality has a similar impact, with more than a quarter of shoppers abandoning purchases due to pixelated, blurry or missing imagery.
Ultimately, missing details and a lack of quality imagery fosters distrust among consumers and diminishes brand loyalty, making it impossible in most instances to get that business back. Furthermore, it’s a chief driver of a recent spike in returns, which totaled more than $890 billion in 2024, or $1 in every $4 spent in US retail.
This is why Amazon and Walmart have invested significant time and resources in establishing the industry standard for product content.
As we’ve previously discussed, these retail giants deploy strict data requirements and powerful infrastructure to ensure every detail in a product page is clear, accurate and visually compelling, in order to build trust and make conversions nearly effortless.
This approach has cemented their dominance and created a blueprint for success that other retailers must follow.
Quality product data as the foundation for future AI discovery
Applying digital content and SEO best practices to your product details pages can help increase their visibility in search and make it more likely that visitors will convert, rather than abandon their purchase.
But in the era of LLMs, it’s setting a solid foundation for the agentic commerce future that might be the most compelling reason to invest in impeccable product data.
That’s because the future of commerce isn't just about search bars; it's about high-context, conversational searches powered by the likes of Perplexity and ChatGPT. These advanced AI agents will prioritize surfacing detail-rich results, acting as a personal shopping assistant for consumers.
What does this mean for a retailer's product catalog?
Products with low-quality or missing data will likely be ignored by these sophisticated AI-driven search mechanisms and products that can't be accurately described or verified by an AI will be left behind.
This makes investing in data quality far more than an aesthetic choice. Rather, it’s a direct lever for revenue, reduced returns and lasting consumer trust. It is the key to future-proofing your marketplace against the AI revolution.
Mirakl Catalog Platform: Empowering impeccable product data and fueling the marketplace ecosystem
So how can retailers ensure their product data is ready for this new era of agentic commerce?
Mirakl Catalog Platform is a solution designed to address the challenges of product data quality in marketplace environments head-on, and can help retailers ensure their product data is ready for the new era of agentic commerce.
The platform helps retailers enforce stringent data quality standards and streamlines the ingestion and management of product content from multiple sources, ensuring consistency and accuracy.
This kind of robust product data is foundational for the broader success of a marketplace as it enhances the overall customer experience and supports effective merchandising.
Securing your future in the AI era
Impeccable product data is critical for any retailer aiming to thrive in an AI-driven eCommerce landscape.
The threat of market share loss is real, but so is the opportunity to act. Mirakl Catalog Platform empowers businesses to overcome this vulnerability by ensuring their digital storefronts are equipped with compelling and accurate product information.
Learn how Mirakl Catalog Platform can help you improve your product assortment and set you up for success in the agentic commerce era, here.
