Sarah Assous, Vice President of Product Marketing, Akeneo – Interview Series

Sarah Assous is the Vice President of Product Marketing at Akeneo, where she drives strategic messaging, positioning, and go-to-market strategies. A results-driven leader, she has played a key role in accelerating company growth and leveraging marketing to support revenue generation. With expertise in content strategy, customer engagement, and competitive positioning, she combines creativity and business acumen to deliver world-class product experiences.

While traditional PIM systems are effective for centralizing and managing product information, many solutions struggle to support complex omnichannel strategies, dynamic data, and integrations with other eCommerce or data platforms, meaning that the PIM just becomes another data silo.

The product cloud, on the other hand, is a composable suite of technologies that supports the entire product record for both dynamic and static data across the entire product lifecycle; our flexible, scalable PIM solution is a crucial aspect of the product cloud, however it’s only one part.

As part of Akeneo Product Cloud, we also offer an AI-powered supplier data onboarding solution, a syndication platform with the ability to activate product information across global marketplaces, a secure product portal that enables all stakeholders to access digital product catalogs on demand, and an extensive network of 150+ integrations. All of these solutions work together to ensure that product data doesn’t live in a siloed solution, but is optimized, enriched, and activated across every stage of the product lifecycle, which enables businesses to create optimal omnichannel product experiences, drive  higher conversion rates, and improve customer loyalty.

How is AI transforming product information management (PIM) beyond just centralizing data?

Beyond data centralization, AI is a powerful tool when it comes to PIM as it brings advanced technology to an industry that has previously relied on outdated and inefficient tools. Aside from centralized data, we’re seeing AI being used in a wide capacity within PIM solutions, including:

1. Cleaning and enriching product data, including de-duplication and data extraction
2. Generating ready-to-edit content using the centralized data, ensuring product page alignment with brand voice
3. Translating product content quickly and efficiently to deliver strong product experiences at scale in multiple languages
4. Optimizing product discovery and search functionality by improving natural language processing and understanding user intent

Can you walk us through how Akeneo’s AI-powered Supplier Data Manager streamlines data collection and enrichment?

Akeneo’s Supplier Data Manager (SDM) is designed to streamline the collection, management, and enrichment of supplier-provided product information and assets by offering a user-friendly portal where suppliers can upload product data and media files, which are then automatically mapped to the retailer’s and/or distributors data structure. Our system utilizes artificial intelligence to automate product classification, enrich attributes from descriptions and labels, and normalize data to ensure consistency and accuracy, all of which reduces manual effort, accelerates time-to-market, and enhances collaboration between retailers and suppliers by providing a centralized platform for efficient communication and data exchange. As a result, brands and/or manufacturers are set up for omnichannel success by having consistent supplier insights across systems.

What role does AI play in ensuring product data accuracy and consistency across multiple channels?

One of the most practical use cases of AI today is its ability to automate data standardization, enrichment, and validation processes to ensure accuracy and consistency across multiple channels. AI-powered algorithms can detect and correct inconsistencies, fill in missing attributes, and classify products based on predefined rules or learned patterns, reducing manual errors and ensuring uniformity across marketplaces, eCommerce platforms, print catalogs, and anywhere else you sell. Plus, natural language processing (NLP) and AI-driven search capabilities help businesses better understand user intent, enabling them to optimize product descriptions and attributes to match how customers actually search. By analyzing search queries, AI can suggest more relevant keywords, improve product tagging, and dynamically refine search results, ensuring customers find the most accurate and compelling product information, ultimately leading to higher engagement, conversions, and reduced returns.

What are the biggest challenges in implementing AI in product experience management, and how is Akeneo addressing them?

AI relies on high-quality, structured data to generate meaningful insights, but many businesses struggle with fragmented or incomplete product information. Scalability is another challenge, as AI models must continuously learn and adapt to new product data, customer behaviors, and market trends while maintaining accuracy and relevance. Akeneo’s Product Cloud solution has PIM, syndication, and supplier data manager capabilities, which allows retailers to have all their product data in one spot. We also leverage AI to improve data quality and consistency, ensuring that the information fed into AI solutions is complete, accurate, and reliable, which can alleviate the problem of having inconsistent data across multiple platforms and taking weight off the retailer under more manual processes.

With the rise of AI-generated content, how does Akeneo ensure brand voice and authenticity remain intact?

While AI-generated content can be incredibly useful, especially within search functionality and product descriptors, it’s important to maintain a strong sense of brand identity when using these tools. Akeneo ensures that no matter what type of content we use AI to help develop, that there’s always a human on the other side to maintain brand authenticity. When using AI-generated content, we truly rely on it as a starting point to jump off of. Being able to enhance and weave in brand messaging throughout the content allows the tone to remain consistent across channels and give the marketing team time to focus on strategic content.

What AI-driven personalization strategies can brands implement to enhance customer experiences?

While personalization is nothing new to brands, AI and ML technology allows brands to enter new levels of customer personalization to meet the high consumer expectations. Knowing the amount of data that AI tools can process, this power opens the door to enable unprecedented levels of personalization during customer interactions through data analysis. Leveraging customer data in this way allows AI algorithms to make broader connections across customer order history, preferences, etc., to create those tailored product recommendations. AI-powered search and natural language processing can also refine search results by improving user intent interpretation, improving discoverability and reducing friction in the buying journey. But it’s important to remember that without a variety of AI strategies and without a strong foundation of data to train and support the AI solutions, personalizing customer experiences with this technology is next to impossible.

How does Akeneo optimize product discovery and search functionality using AI?

A good product search and discovery experience relies on products being accurately tagged, categorized, and syndicated to the right channels. That’s why we provide native AI capabilities built within Akeneo PIM that enable enriched product data by analyzing existing information to fill in missing attributes, ensuring comprehensive and accurate product listings. Akeneo SDM also offers AI capabilities to ensure that supplier data is complete, correct, and formatted correctly. And if that wasn’t enough, we also offer 20+ AI applications within our extensive App Store that cover a wide range of AI use cases, some of which are custom built for Akeneo. These features help to ensure that the right information is provided to the right customers at the right time.

What are the most common bottlenecks in managing product data at an enterprise level, and how does Akeneo solve them?

Although technological advancements in product data are vast, many organizations are still struggling with manual product information management. Some major challenges we see enterprises facing include managing product information in multiple languages and markets, creating consistent and engaging product descriptions at scale, maintaining accuracy while reducing time-to-market, and coordinating between technical, marketing and sales teams. These challenges make them unable to keep up with the pace of today’s digital commerce expectations.

With Akeneo, these challenges are largely eliminated. With strong AI features, Akeneo is able to automatically implement rules for language content translation, as well as using intelligent content generation to allow technical specifications to be transformed into thoughtful summaries, and engaging marketing narratives. It’s key to note that intelligent content doesn’t eliminate marketing teams, but enables them to thrive with a starting point to personalize AI-generated content to fit their brand in the best way possible.

Where do you see the role of AI in product experience management evolving over the next five years, and how is Akeneo positioning itself to stay ahead of these changes?

It’s hard to predict five years from now knowing how the evolution of AI is shifting everyday. However, with the introduction of tools like Google’s Perplexity, we can expect to see the emergence of AI shopping agents come to life, where shoppers can research, browse, compare, and purchase products all in one place. As AI and NLP evolve to better understand and interpret customer intent, these personalized search experiences will start to grow in popularity and live alongside traditional search experiences.

While it can be hard to predict the future, we do know one thing: AI solutions will always fall short if they aren’t supported by a strong foundation of up-to-date, reliable, and complete product information. The outputs created are only as good as the data provided, so wherever the evolution of this technology is headed, the first step to success will always be creating that single source of truth for product data, which is where Akeneo can help.

Thank you for the great interview, readers who wish to learn more should vivit Akeneo.