Data Analytics & Modeling
Modern data analysis and modeling capabilities are advancing at a rapid pace, and leveraging these capabilities to guide decision-making processes has become critical for many organizational functions. To support these efforts, HCCG offers a variety of techniques for big data analysis, customized predictive modeling, machine learning, data visualization, and more. We then synthesize these findings with qualitative research to produce strategic recommendations that can help your company take advantage of the newest digital trends and innovations.
Related Modules
Statistical Analysis
HCCG can provide probabilistic models that quantify the risk and uncertainty inherent in real world data sets.
Machine Learning
HCCG can employ the latest artificial intelligence algorithms to perform supervised and unsupervised machine learning tasks.
Data Collection & Engineering
HCCG can manipulate internal data sets into forms more cohesive for future use, add additional features and provide data imputation to resolve missing data.
Predictive Modeling
HCCG utilizes machine learning algorithms to create and statistically bound predictions given internal and external data sets.
“The HCCG team performed an impressive data analysis for us that was very thorough and sophisticated. Their multi-method research design was world class, producing recommendations that our organizations will be using for years to come. The team was very professional and versatile, responding adroitly to every challenge that our organization’s data presented.”
— Rotary International
Prior Scopes of Work
Data Imputation
The Client had an incomplete picture of self-reported data the Client’s locations provided on their contributions to individual projects. In an effort to “fill in the gaps” of the unreported data, the Client enlisted HCCG to estimate global contributions of all the Client’s locations to their projects using available and exploratory missing-data imputation techniques. Separately, HCCG was tasked with further investigating why the majority of the Client’s locations failed to self-report data and recommending strategies to improve the percentage of locations reporting in each global region.
Natural Language Processing
The Client tasked HCCG with developing a roadmap of player touchpoints across various support channels. HCCG developed a tagging algorithm to identify various player personas using core player metrics as well as support interactions. Furthermore, HCCG defined various levels of support to help the Client map the state of player support across the Client's range of products. HCCG documented the steps of each interaction type and modeled how it affects player experience. HCCG identified the improvements to the customer engagement interactions at various stages through visualizations and delivered recommendations to implement them into the Client's support strategy.
Revenue Modeling
Originally tasked with producing tax revenue estimates under various economic development scenarios for a major transit corridor, HCCG created a generalizable model that predicted net tax revenue for the entire municipality under modifiable development proposals. HCCG’s model produced results on a granular individual plot basis. To design the model, HCCG conducted interviews with Harvard urban design professors, local development experts, and government officials. HCCG also conducted research on several case studies and to generate parameter values to custom tailor the model to the original transit corridor.