Businesses are under increasing pressure to provide hyper-personalized experiences that resonate with each individual customer. Generative AI (GenAI) is leading this effort, allowing retailers to access unprecedented levels of creativity and insight.
We sat down with Sylvain, VP of AI at Brevo. With over 20 years of experience as an entrepreneur and digital expert, Sylvain brings invaluable insights into the practical applications and challenges of integrating GenAI into business strategies.
What is Generative AI
GenAI refers to artificial intelligence that creates new content—be it text, images, audio, or video—based on the data it’s been trained on. Unlike traditional AI models, which focus on analyzing or predicting outcomes, GenAI models can “generate” new outputs, mimicking human creativity.
Expert insights into Generative AI
Q: What misconceptions about generative AI should businesses be aware of before investing in it?
Sylvain: "GenAI may feel like magic, but you should think of it as hiring a new employee. It requires rules, processes, and safeguards. Without these, you may believe you have something that appears real and true, but it might not be. GenAI can write sentences that look authentic, but that doesn’t guarantee accuracy.
"Implementing GenAI is quick, especially if you purchase access to existing platforms. However, preparing it for daily use requires significant fine-tuning and refinement to ensure it is genuinely effective. Our expertise lies in providing the right context and tools to our GenAI agents, allowing them to deliver highly qualitative results."
When it comes to the ‘Build vs. Buy’ decision, the situation can be quite complex. Depending on the sensitivity of your subject and the nature of your business, building a solution might be beneficial but time-consuming. Conversely, a buying strategy could be quicker but comes with risks like bias or data leakage. Our approach is to be very strict with data handling and to choose the most efficient strategy based on specific needs.”
Build vs. Buy: What should businesses consider?
- Build: Greater control over customization and data security, but requires significant time, resources, and expertise.
- Buy: Faster implementation and access to cutting-edge tools, but potential risks include data leakage and model bias.
Q: What are the key challenges businesses face when implementing generative AI solutions, and how can they overcome them?
Sylvain: “The ‘Build vs. Buy’ decision remains challenging, especially given the rapidly changing market trends. New, faster, more relevant, and often cheaper models are emerging almost daily. Therefore, it's crucial to establish a solid foundation by focusing on specific use cases rather than merely attempting to implement AI for the sake of making it appear “smart.”
Retail use case inspiration
Focus on targeted applications such as:
- Personalized marketing: AI-generated product recommendations tailored to individual preferences.
- Dynamic pricing: Adjust prices in real-time based on demand and customer behavior.
- Content creation: Generate localized ads, emails, or even product descriptions automatically.
Q: How can companies balance the use of AI with human expertise?
Sylvain: “In my view, AI serves as an enabler for humans. Recently, some people have suggested that AI will not replace human workers in their daily jobs; rather, it will be the humans who utilize AI that will outpace those who do not. This statement holds true. For example, when comparing the capabilities of a web engineer who leverages AI with one who does not, the difference in performance is substantial.”
AI with a human touch
AI in retail acts as a valuable support system for human expertise. For instance, AI can manage time-consuming tasks such as demand forecasting and trend analysis, allowing retail professionals to concentrate on creative strategies and strengthen customer relationships. By merging AI-powered insights with human ingenuity, retailers can achieve a balance that improves both efficiency and customer satisfaction.
Brevo's Segment with AI Brevo's Segment with AI feature simplifies the process of targeting your audience by allowing you to generate a precise segmentation query with a simple text prompt. You can input specific business goals directly or request automatic segmentation of your contacts based on Brevo-inspired filter options.
Segment with AI
Q: How does generative AI handle data differently from traditional AI models? What implications does this have for businesses?
Sylvain “Data structure is always crucial. What sets GenAI apart is its ability to integrate different contexts and data sources quickly. The logic can be shared more efficiently; by simply explaining your data model, a large language model (LLM) can perform the necessary logic to identify connections.
However, it's important to note that just because AI can handle a wide range of tasks, it doesn’t mean it is applicable in every situation. We often equate ‘AI’ with ‘GenAI,’ but in many cases, traditional machine learning methods can be much more effective than using LLMs. Furthermore, there are situations where using LLMs is simply not appropriate—at least for now.”
AI data handing in retail
Generative AI can:
- Analyze unstructured customer feedback to uncover hidden patterns.
- Rapidly adapt to new data sources and trends.
- Enhance decision-making by connecting seemingly unrelated data points.
But it’s not always the right solution. For repetitive tasks like inventory management, traditional machine learning may still be the better fit.
Q: In what ways can generative AI be leveraged to create more personalized user experiences?
Sylvain: “Consider this: what creative ideas can your brain generate today? GenAI can take that creativity to new heights, often offering solutions you might not have considered. The more context you provide, the more relevant the results can be.
Additionally, you can specify the level of "freedom" you want the AI agents to have, ranging from strictly adhering to rules to exploring completely outside the boundaries.”
Hyper-personal AI
For retailers, this means that GenAI can create highly personalized shopping experiences. Imagine AI-generated product recommendations that take into account not only purchase history but also preferences inferred from customer behavior, location, and even seasonal trends. This level of personalization helps retailers build customer loyalty and differentiate themselves in a competitive market.
Brevo's AI-driven subject line generator creates compelling subject lines, increasing the probability of a customer opening your email.
Q: What role does generative AI play in understanding nuanced customer behavior, and how can retailers effectively leverage these insights?
Sylvain: “Since we don't need to present highly structured data to a language model, we can provide data points and explanations of the connections between these points. This approach adds context and can lead to unexpected insights. For example, while researching and asking users to perform certain actions, we can ask our agents for recommendations on enhancing the experience. This can result in numerous improvements that we can implement to make the experience even more effective.”
Customer-centric AI
In retail, GenAI can assist businesses in understanding customer preferences and behaviors more deeply. For instance, AI can detect subtle trends, such as variations in purchasing patterns during holidays or changes in demand for specific product categories. With these insights, retailers can develop marketing strategies and inventory plans that better align with customer needs.
Brevo’s send-at-best-time feature uses AI to analyze user behavior, historical email open times, and preferences to determine the optimal send-out times for each subscriber
Q: Looking to the future, how might generative AI transform traditional retail models into more experience-driven or community-oriented approaches?
Sylvain: “I believe that hyper-personalization of the experience will be crucial. This could involve having a personal assistant that helps you find the most suitable products for you, as well as generating images, videos, and text tailored to each individual customer based on their context, habits, and preferences. Additionally, we can think of many autonomous capabilities that would make everything as simple as asking for a cup of coffee.”
AI in action
- AI styling assistants: Brands like Stitch Fix use AI to curate personalized clothing recommendations.
- Interactive shopping: Virtual try-ons powered by AI, such as L'Oréal’s Modiface.
Further reading: Rules of Retail: 8 Retail Marketing Trends Transforming 2025
Conclusion
GenAI enables retail businesses to create hyper-personalized experiences, uncover valuable customer insights, and streamline operations. However, its implementation requires careful planning, collaboration, and alignment between AI tools and human expertise.
While GenAI offers tremendous potential, some tasks—like inventory management or demand forecasting—may be better suited for traditional machine learning methods A flexible, dual approach that combines all subsets of GenAI ensures business can adapt to different needs and maximize efficiency.
By adopting a strategic approach to AI integration and focusing on specific, impactful use cases, retailers can stay ahead of the competition and meet the ever-changing demands of their customers.
The future of retail is more personalized, efficient, and customer-centric—and GenAI is the catalyst driving this transformation.
