eBrandValue, Co-Founded by Özyeğin University Faculty Member Prof. Tolga Akçura, Earns Third Place in a Prestigious Global Analytics Award

eBrandValue, co-founded by Prof. Tolga Akçura from the Faculty of Business at Özyeğin University, has been awarded third place in the Innovative Applications in Analytics Award (IAAA) 2026, one of the most prestigious honors in the field of analytics. The award is presented by INFORMS, the world’s leading professional association for operations research and management sciences.

The company is backed by Y Combinator, widely regarded as the world’s most prestigious startup accelerator, known for supporting early-stage technology companies such as Airbnb, Dropbox, Stripe, Reddit, DoorDash, and OpenAI, whose combined portfolio value exceeds $600 billion. Being part of the prestigious Y Combinator network, closely associated with influential figures such as Paul Graham, MIT professor Robert Morris, and OpenAI CEO Sam Altman, is a strong testament to eBrandValue’s global scientific and commercial potential.

eBrandValue stands out for its pioneering model, which quantifies brand value as a measurable financial metric and directly links it to stock market performance, marking a global first. By integrating social media data with key financial indicators such as sales, brand value, and stock prices, the company offers a distinctive analytical framework capable of accurately forecasting the impact of brand investments on firm valuation and sales performance.

The award-winning study, titled “AI & Big-Data Brand Intelligence: Sales-Correlated Social Metrics and Market-Valuation Signals,” presents an end-to-end analytical framework that transforms large-scale public social media data into sales-linked metrics, forecasts, and capital market signals. The system integrates multi-platform social data with corporate data such as sales, pricing, and distribution while employing a dynamic ensemble of advanced methodologies, including natural language processing, large language models (LLMs), graph modeling, machine learning, and causality-based econometric techniques (Granger, LASSO, SARIMAX, SCINet). The model achieves correlations approaching 0.9 in rolling forecasts over 12–24 months, significantly improving sales prediction accuracy compared to traditional brand metrics.

Another distinguishing contribution of the study is its demonstration that changes in brand value—calculated based on consumer learning theory—serve as statistically significant precursors to abnormal stock price movements around financial disclosure periods. These findings reveal that brand intelligence derived from social data is partially priced by capital markets beyond conventional accounting measures, reinforcing the model’s academic originality. The system has been successfully deployed across multiple sectors, including fast-moving consumer goods (FMCG), financial services, and quick-service restaurants (QSR).

Following a comprehensive assessment by an international jury comprising leading figures from both industry and academia, including Jiaxi Zhu, Head of Analytics at Google, as well as representatives from Georgia Institute of Technology and Boston Consulting Group (BCG), eBrandValue was selected for third place among submissions from around the world.

Built on Prof. Tolga Akçura’s extensive academic work in marketing science and data analytics, the model redefines the role of social data, transforming it from a descriptive metric into a predictive engine for business insight. In doing so, it not only introduces a new perspective on data-driven decision-making but also demonstrates the tangible impact of academic research on real-world business practice.