The Brand Basket collects data from open sources related to the company’s brand reputation and customer feedback. It utilizes its own Language Model (LLM) and small databases to annotate and prepare the data for the Generative Pre-trained Transformer (GPT) model, which generates a text document for further actions. This data can include social media trends such as the occurrence of hate speech and other observable changes. Additionally, the basket can analyze brand mentions and customer feedback.
The data collected in the Brand Basket can be combined with internal information and compared for interdependencies and impacts. The gathered information helps the company understand the factors and consequences that affect its brand reputation. It also enables the monitoring of customer experiences and market trends. This knowledge facilitates the development of brand strategies and communication efforts, empowering the company to strengthen its brand and improve customer satisfaction.
For example, the company can use the data from the Brand Basket to measure the negative impact of stock announcements on its external and internal image. Armed with this information, the company can react promptly to potential reputation crises and take necessary actions to safeguard its reputation. Furthermore, the Brand Basket allows tracking the evolution of the brand and adapting the brand strategy to market-driven changes.
The insights derived from the Brand Basket’s data can also inform communication planning and execution. This enables targeted and impactful communication that aligns with the brand’s values and enhances the customer experience. Through skill development materials, the company ensures that its employees understand the significance of the brand and can effectively communicate it across various channels.
