A leading retail company’s e-commerce site showed every customer the same static homepage and search results, regardless of who they were. Search results were driven purely by product availability and sales data with no personalization based on demographics or individual buying behaviour.
Aiwozo built a machine learning driven system to build and continuously refine a persona for each customer, turning generic browsing into a personalized experience.
Persona building agents established an initial profile for each customer based on their historical buying trends.
Learning agents, powered by Aiwozo’s ML capability, continuously updated that persona as the customer kept shopping refining recommendations with every purchase rather than relying on a static snapshot.
Personalization agents used the evolving persona to shape what each customer saw product displays, search results, and recommendations aligned to their individual patterns and current trends, rather than a generic storefront.
Key business and operational challenges that limited performance, scalability, and governance before automation was introduced.
