April 18, 2025
In today’s crowded commerce landscape, growth isn’t driven by more products, bigger promotions, or additional channels — it’s powered by smarter systems. Specifically, how effectively a brand manages, enriches and activates its product and customer data.
Retailers are sitting on a goldmine of data, yet much of it is fragmented, underutilized, and disconnected from the customer journey. The cost? Up to 30% of potential revenue is lost due to poor product data governance, according to McKinsey. Meanwhile, 43% of online shoppers abandon sites when they can’t quickly find what they need (Forrester).
This is where AI changes everything.
At Valtech, we help global brands harness AI to transform data into a competitive advantage — creating seamless, personalized and high-performing digital experiences.
Here’s how smarter product data and AI-powered search unlock real revenue — and what you can do to get ahead.
The untapped power of product data and search
When it comes to e-commerce performance, few things matter more than how products are described, structured and surfaced. If customers can’t find what they want or don’t trust what they see, they won’t convert.
Product data is your silent revenue driver
Every product description, attribute and tag directly impact discoverability, trust and conversion. Yet incomplete or inconsistent data remains a common bottleneck. The consequences?
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Confusing or mismatched titles.
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Duplicate SKUs.
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Inaccurate pricing or availability.
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Poor search relevance.
What’s more, 85% of online shoppers say detailed product info is critical to their decision-making (Google). Weak data equals weak experiences — and lost revenue.
Search: The GPS of retail
Search has evolved from a nice-to-have into a strategic imperative. Over 50% of e-commerce revenue now comes from shoppers using site search. And that’s no surprise, search is the primary interface between consumer intent and product discovery.
But most retail search engines still rely on outdated keyword matching or static business rules. This leads to irrelevant results, frustrating UX, and low conversion rates.
To compete today, brands need AI-powered, goal-based search that understands what the shopper wants, not just what they typed.
From scroll-based to goal-oriented: The new search paradigm
We’ve moved beyond the age of “scroll and hope” to one of intent-based discovery. This shift is transforming how customers interact with digital storefronts and how businesses structure their digital shelves.
Traditional search forces users to scroll endlessly through loosely relevant results. AI flips this experience, making search intuitive, contextual, and conversion driven.
Old way: Scroll-based search
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Relies on static filters and string matching.
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Offers overwhelming, non-personalized results.
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Leads to decision fatigue and cart abandonment.
New way: Goal-based discovery
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Uses AI to interpret intent behind queries.
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Surfaces curated, relevant, and personalized product selections.
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Responds to natural language like “flowy dresses under $50” with meaningful results.
AI transforms the experience from “searching” to “finding.”
Many brands now use AI search engines that respond to natural language queries, images, and semantic context. When shoppers input “flowy dresses under $50,” they don’t get a list — they get a curated, personalized collection.
That’s the difference between navigation and recommendation.
The four AI capabilities powering retail transformation
Artificial Intelligence isn’t just changing how we search. It’s transforming the very foundation of how retailers manage and activate their product ecosystems.
Four core AI capabilities are fueling this transformation:
1. Semantic search and predictive ranking
AI understands shopper intent, not just keywords. It uses:
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Natural language processing to interpret meaning.
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Behavioral signals from browsing and cart history.
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Dynamic ranking based on trends, demand, and stock.
Valtech’s solution for Not On The High Street — a curated online marketplace that connects shoppers with small creative businesses — addressed the challenge of product discoverability across a large, diverse catalog.
The implementation included AI-driven search capabilities using natural language processing and behavioral data to improve relevance. This resulted in faster search performance, more accurate product recommendations, and increased conversion rates.
2. AI-powered product data enrichment
AI automates data enrichment at scale by:
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Generating on-brand product descriptions.
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Classifying SKUs and tagging attributes.
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Detecting inconsistencies and duplicates.
For example, Valtech’s work with Matalan, a British clothing, homeware, and toy retailer, streamlined product data management through a scalable e-commerce platform. Automation supported the generation of consistent product descriptions, accurate SKU classification, and attribute tagging — reducing manual effort and improving data quality across thousands of items.
3. Intelligent merchandising
AI enables real-time, data-driven merchandising through:
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Demand forecasting.
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Inventory-aware product prioritization.
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Personalized sorting by customer segment.
Valtech’s work with PepsiCo LATAM is a strong example of intelligent merchandising beyond ecommerce. By creating a centralized digital hub, PepsiCo enabled real-time, data-driven decisions across campaigns and brands. This allowed for smarter content delivery based on demand signals and audience segmentation, resulting in a 600% ROI increase, 35% reduction in agency costs, and sustained market share growth.
4. Unified data ecosystems
AI is only as powerful as the data feeding it. That’s why retailers must unify data across:
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Product content management.
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Commerce platforms.
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Analytics tools and Data ecosystems.
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CRM systems.
When product data, customer behavior, and inventory data live in a single ecosystem, AI can deliver next-level personalization, smarter recommendations, and optimized pricing strategies.
We saw this firsthand with one of our Sporting Goods retailers, where Valtech developed an AI dashboard to analyze product launch performance, predict demand, and optimize pricing dynamically — fueling more informed decisions at every level.
Proving ROI: The metrics that matter
When done right, AI doesn’t just streamline workflows, it transforms outcomes. The impact is measurable:
conversion lift from personalized search
This is more than digital transformation. It’s performance optimization, made real.
Why most retailers are still playing catch-up
Despite clear gains, many brands remain stuck in manual processes, legacy tools and disconnected systems.
Why? Perceived complexity of AI, fear of disruption, existing tech debt and or change fatigue.
But waiting is no longer neutral. Every day of delay is revenue left on the table. Retailers who act now will define the next generation of customer experience. Those who hesitate may not catch up.
What’s next for AI in retail?
The next wave of innovation isn’t about more features. It’s about deeper intelligence:
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Search becomes conversational via voice, image, and natural language.
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Merchandising self-optimizes based on live data and intent signals.
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Product data becomes real-time and multi-modal, generated, validated, and deployed by AI.
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The digital shelf becomes the brand’s flagship, dynamic, personalized, and revenue driven.
The winners will treat product data and AI as core capabilities — not outsourced functions.
The time to move is now. AI is not a future feature. It’s a present requirement. Retailers that take a wait-and-see approach will miss the competitive leap that early adopters are already realizing.
The foundation is clear: unify your data, automate what slows you down, and personalize where it matters.
The result? Smarter teams, smarter experiences, smarter growth.
Start here: Retail AI optimization assessment
Valtech’s AI-Powered Retail Optimization Assessment gives you a clear picture of where you stand — and what it’ll take to lead.
We assess:
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Product data maturity.
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Search performance.
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Platform readiness.
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Team enablement.
The output? A roadmap to turn gaps into gains.
Don’t wait to catch up. Leap ahead. Contact us today to learn more.
Gabriel Laliberté leads strategic transformation for some of the world’s most iconic retail and consumer brands. With over two decades of experience in enterprise commerce, data ecosystems and experience innovation, he helps global organizations unlock growth through intelligent, future-proof strategies. At Valtech, Gabriel works at the intersection of business, technology and experience, turning complexity into competitive advantage.
