A data lake purpose built for analytics

Organic food CPG company

Consumer preferences and behaviors are changing rapidly during the various phases of the pandemic. Understanding these preferences, predicting where they are headed, and most importantly, what to do about them is core to survival and thriving of a CPG. ...And the key to being able to do this is having efficient access to the right external data.

An organic CPG company works to understand the factors that effect the sale of organic foods so they can identify new offerings and optimize targeting and messaging.

Their analytics team needs better access to and ability to identify relevant features that will enable a complete view of the customer and the competitive landscape. The N.ai platform automatic feature selection capability makes finding surprising predictive nuggets efficient and easy.

The CPG’s Nitrogen.ai data feature lake manages their category sales and shipments data… and manages retailer data and contributes data from commercial data providers and data. Consumer sentiment data particularly from Social media and online browsing, combined with foot traffic data and several panel data providers allowed the CPG data modelers to find features that signified actionable consumer behaviors that were predictive and potentially proscriptive

And it puts it all in one place as highly actionable features that can be easily found, evaluated and pushed into analytic modeling tools to allow rapid model discovery and deployment.

Data scientists were able to identify features that signaled preferences for organic food and which categories correlated with increasing sales and develop product versions that appeal to the changing tastes and preference to more affluent home bound consumers

Strategic Consulting company

Strategic consulting today is becoming more and more data and data science oriented. The Pandemic has made data rich data science an essential element of good strategic consulting. The pandemic has also made remote work a reality eliminated the most important element of modern... strategic consulting business development … walking the hall and being pulled into strategic discussions onsite.

The nitrogen.ai data feature lake makes data sharing a reality. The consulting form can stay engaged with the customer via data sharing and even use our automated feature selection capability a vehicle to identify customer threats and opportunities a high value way to continue the land and expand approach by delivering high value.

The N.ai platform allows the consultancy to share data features with the customer, to create proprietary features, and to access the n.ai data exchange to find and solve opportunities and issues efficiently. And the consultancy can monetize their proprietary modeled features across a larger audience, using this as a way to generate incremental revenue and to engage new potential customers.

And by sharing data with their customers during and beyond engagements it becomes much easier to maintain a consultative relationship after the initial engagement ends.

Reinsurance insurance company

Considerable information asymmetries exist in the reinsurance marketplace making it very different from capital markets. Significant value can be created by reducing these asymmetries which requires... reinsurance markets to make a significant investment in people and tools to capture and quantify all the sources of exposure to any particular risk.

Catastrophic risk, in particular, is difficult for the market to efficiently manage, in part because it is characterized by a small number of very large losses, the occurrence of which are both unpredictable and infrequent. These events drive the long tail of frequency distributions, and as such are heavily capital consumptive. It takes great underwriting skill and sufficient market scale to effectively diversify this considerable risk.

The Nitrogen.ai data feature lake makes relevant data available to assist in mitigating these asymmetries through data sharing. We manage data as features more effectively than any company can do on its own and we do this with wide ranging external data. By providing trustworthy governance and making it safe and efficient to share data among collaborators and to monetize data among non-competitive “strangers” the platform can be used to define and understand this asymmetry to achieve competitive advantage.

Our automated feature selection capability uses ML to find the needles buried in multiple haystacks helping make predictive models more comprehensive and accurate. The modern reinsurance is largely a relevant data game and the N.ai data feature lake goes a long way to arming your troops with the relevant data they need to compete.