Unleashing the Power of Data: Two Recent AltHub Case Studies

Unleashing the Power of Data: Two Recent AltHub Case Studies

Piecing the Puzzle – The Power of Telco Data

One of the most striking insights derived from data was from the Asian market where different data sets from about ten telecom operators were combined to gauge the number of workers exiting factories. The task wasn’t as straightforward as it seemed.
The first challenge was to ensure that the data captured truly reflected workers and not visitors. The next part involved modeling to see if the number of workers aligned with a forecast for the next quarter’s revenue. After a rigorous exercise involving over a hundred models and constant refinement, the performance of this data set showed significant improvement.
The result was a potent predictor capable of providing a five-day advance over street estimates regarding a company’s performance. This mix of data sources, stringent quality checks, and back-and-forth modeling culminated in a product that boasted a 50% trial rate per meeting – a stellar success in the realm of location mobility data.

Uncovering Hidden Patterns – The Recycling Business Data

A seemingly unassuming project involving recycling data offered surprising insights. The project involved tracking different categories of recycling – from discarded television sets to picked-up boxes. At a first glance, one might think that there is no actionable data here, but our machine learning systems thought otherwise.
When run through our system, the data revealed interesting patterns correlating with consumer buying behaviors and market fluctuations. Despite a near-zero correlation with the Dow Jones, the recycling data proved to be an exceptional risk indicator, signaling the best times to exit the market.
This successful case illustrates the potential of machine learning in identifying and leveraging obscure patterns in data, which humans could easily overlook. With careful tracking and leveraging machine learning capabilities, even the most unassuming data sets can yield valuable insights.