Ceezaa aggregates users' purchase and location data to build a continuously updated taste graph that reflects real spending behavior, offering individuals clear insights into their personal preferences. The platform provides brands with anonymized, behavior‑driven audience segments via API, enabling more accurate targeting based on actual spend patterns.
Funding
Funding not disclosed
Founders
Product
Problem
Consumers lack a unified view of their personal preferences because existing social profiles and click‑based data capture only occasional expressions and are fragmented across multiple platforms. This makes it difficult for individuals to understand their true tastes and for brands to access reliable, behavior‑driven insights.
Solution
Ceezaa aggregates a user's purchase and location data to create a continuous, data‑driven profile of personal taste and identity. By analyzing spending patterns—where and how money is spent—the platform derives a “living taste graph” that reflects authentic preferences more reliably than clicks, likes, or reviews. The system then presents this curated insight back to the user in an easy‑to‑understand format, helping them recognize and act on their genuine interests. Brands and marketers can leverage the anonymized taste graphs to target audiences based on real spending behavior rather than superficial signals.
Target Audience
Primary users are consumers who want a clearer understanding of their personal preferences, and brands or marketers seeking behavior‑based audience segmentation for more effective targeting.
Features
- Continuous aggregation of purchase data from multiple channels to build a dynamic taste profile
- Behavioral analysis that prioritizes repeat spending over one‑off interactions to identify true preferences
- Visualization of the taste graph that translates raw spend data into understandable identity insights for users
- API access for brands to query anonymized taste segments for more accurate audience targeting
- Privacy‑first design that stores data securely and reflects insights without exposing raw transaction details