As new data grows by the minute, organizations continue to invest in talent and platforms to extract value from it. As the inputs compound and become increasingly disparate, so too do the opportunities to learn from this ever-evolving gold mine. But simply having data scientists isn’t always enough to make sense of and harness its power. Our team of statisticians, data scientists, and analytics translators tackle the data with a business-challenge-first ethos to analyze, interpret, and translate data into meaningful insights. With a system-agnostic approach, we find the perfect balance of melding the art and science of data analytics.

Data Integration & Structuring

With data dispersed across the organization, often existing in silos, potential to bring data streams together can be overlooked or deemed too challenging to accomplish. Our team partners to clean, structure, organize, and centralize data within a single data lake, building connections to ensure it’s more than just a point-in-time benefit, but long-term strategy. Ultimately, this enables cross-source analysis and activation.

Behavioral Segmentation

In a technology-dominant society, an increasing number of behavioral data sources are available within and beyond the walls of organizations. Rather than needing to rely on recall from customers or prospects, behavioral data can share more about past behavior than any other resource. Our team harnesses the power of this data to create behavioral-based segmentations that enable personalization at scale, and reveal opportunities to re-engage, increase lifetime value, and identify new prospects to target.

Predictive Modeling

Identifying strategies to prioritize time, resources, and investment is often a top concern of executives. And while no crystal balls exist, leveraging existing data resources to build predictive models can improve the quality and impact of customer and acquisition initiatives. Our custom approach towards building models means black-box solutions are kept at bay, allowing the organization to adopt, iterate, and inform future efforts in a data-centered way.