Enhancing Product Experiences with AI: Insights from Akeneo’s CEO Romain Fouache

1. What strategies can be implemented to update and maintain product information to reflect changes in inventory or specifications?

Ensuring that you are using a centralized and automated approach is key. A strong product information management system (PIM) provides businesses with the ability to centralize all product data and make it easier to update and distribute across every channel in real-time. Also, the integration of AI tools is also essential. Not only can AI help speed up and streamline the processing and sorting of data, but it can also work to ensure all the data is as current and complete as possible. Reflecting the most accurate inventory information, sizing, availability, etc. is imperative in order to create a good CX, and at the end of the day, if the customer experience is lacking, companies will feel the impact.

2. What measures are taken to verify that product images and descriptions accurately represent the items being sold?

Ensuring that product images and descriptions accurately reflect the items being sold is crucial, as the product experience plays a vital role in the customer journey. While a strong PIM system is essential for maintaining accuracy, brands must go beyond that by focusing on consistency across all omnichannel distribution channels. Implementing data quality audits, collaborative workflows, and robust data validation and enrichment processes creates a structured approach to delivering the most precise, reliable, and engaging product information to buyers.

3. What strategies are in place to regularly update and maintain product information to reflect changes in inventory or specifications?

There are a number of different ways that companies can go about ensuring information is updated with the most accurate and relevant information. AI and machine learning are often used to detect any inconsistencies and outdated information, and API integrations with a PIM ensure that supply chain systems and e-commerce platforms changes are updated as soon as possible. AI can also monitor and sort through custom reviews to identify any themes appearing in the content such as complaints about products or sizing issues that can be flagged to the team immediately.

4. What role does technology, such as AI or machine learning, play in enhancing the precision of product data?

Technology plays a critical role when it comes to enhancing product data and ensuring that it is up-to-date. By integrating the use of technologies such as machine learning or AI, we can not only speed up the rate at which we are sorting through and updating data, but we can also ensure that the collection, consistency, accuracy, and validation are as precise and accurate as possible across every channel. By using automated technology, we also have the ability to translate into different languages and identify any duplicate information at scale.

5. What initiatives are in place to encourage customers to make informed purchases, thereby reducing the likelihood of returns?

Product information and accuracy are the crux of reducing returns. We cannot control if a customer ultimately decides to make a return, but we can ensure that we reduce the chance; 62% of consumers believe having more accurate product information upfront would reduce their likelihood of making a return. So, by providing the most updated, accurate, and real-time information on crucial decision factors such as sizing, colors, stock availability, etc., customers can feel confident that they are making a purchase and receiving what they ordered as opposed to a misrepresentation online. Doing this will reduce the chance of returns and enhance customer trust and loyalty.