There are various ways how you can use our data, with different levels of complexity. In its most basic form, users simply track how various drivers (reputation, satisfaction, NPS) for multiple stakeholders (general public, customers, suppliers, investors) evolve over time. This enables them to connect these live streaming sentiments, with news media, social media, internal issues and other issues they know of themselves. We support this type of basic analyses with a live news media (Lexis Nexis) and social media (Twitter and Instagram) data.
In a way, such analysis resembles classic use of market research that provides a single datapoints for a fixed timeframe (month, year). Yet, as we provide much richer and broader data (continuous streaming for multiple stakeholders and multiple drivers) our data opens up the possibility to really explain trends, issues and crises in far greater detail. For example: if an event suddenly occurs, our data are live streaming and impact can immediately be evaluated. How do you evaluate such event with monthly data?
So when a negative trend exposes itself for customers (in real time), firms may immediately compare these data with corresponding employee data. Or compare it with news media, live firm production data, social media data…
Such (big) data also creates more complexity. Yet, the potential benefits of solving the ‘giant puzzles’ that sometimes emerge, are huge as well. Being able to identify in time which influences and sentiments affect firm performance and understand what interventions may fix these sentiments or solve a crisis, is priceless. We help firms by suggesting a structured, step by step approach to solve the many puzzles they face. We always focus on discovering the areas in the stakeholder network that are affected most, understanding how and why sentiments in these areas change and what sources affected stakeholders.