A Decision Support System for Maximizing Brand Equity using Social Interaction Analysis
Cluster3 Project ID : 37-2016-4391
Summary of the technology
Project ID : 37-2016-4391
Description of the technology
Research-based tools for maximizing social interactions on a brand
Social interactions among consumers, both offline and through social media, have proven to be a central driver in the success of brands. Firms and brand managers are constantly looking for ways to monitor these social interactions, enhance them, and understand how these interactions are translated into sales.
This task is far from being trivial. Social interactions are complex and dynamic. It is hard to know what makes a topic "catch" and create buzz, how this buzz can be influenced, and whether it creates an economic outcome. Currently brand managers rely on experience and intuition but lack solid, quantitative guidelines.
Over a number of years, data was compiled on the online and offline word of mouth occurrences of hundreds of leading US brands. Complex system modeling was employed together with statistical inference methods to answer the following questions:
The research identified a "DNA" backbone of 12 brand characteristics which have proven to influence social interactions on a brand. Using a set of algorithms, managers and consulting companies can be provided with a decision support tool that will enable them to develop their brand in order to maximize social interactions.
A decision support system for creating talkable brands has been developed. The system combines state-of-the-art algorithms with a compilation of big data analysis. Using this system, brand managers can fine-tune perceived characteristics to maximize social interactions on their brand (offline and through social media.)