Science Product Pipelines with A.I. Model-Assisted Selection
We are working with:
Systematizing Science with A.I.
Nucleus Learns Why Products Work:
How can I identify more promising products while testing fewer candidates?
Typical early-stage product funnels need to test a wide set of candidates--and this is expensive. We've found the root cause to be that we don't know which mechanisms will fulfill product requirements. Should a tastier strawberry produce more sugar or more flavor compounds? Nucleus drops losing candidates using in-silico simulation to reduce early stage testing.
How can I advance candidates more quickly through phases?
Typical product funnels require many successive phases of testing--and this is slow. We've found the root cause to be that mechanisms are entangled with each other and with the environment. Was this strawberry variety really tastier, or was it just a good year? Nucleus allows you to advance earlier by learning to disentangle mechanisms. It does this by combining your testing data with a simulation model built on a catalog of causal mechanisms mined from the academic literature.
Which promos and prices would drive incremental profits for Product?
The Nucleus platform automatically quantifies price elasticity from historical data. Product teams use Nucleus optimizers and what-if scenarios to confidently plan promos that hit sales targets while preserving margin.
Which half of agency spend is actually driving incremental sales from Media?
The Nucleus platform automatically quantifies how every ad dollar drives incremental sales, including the effects of saturation, awareness and interaction with promos and season. Media teams can right-size and reallocate budgets to boost profits.
clients are saying
Once we started using Nucleus for our ad spend budget planning, we saw immediate opportunities to improve ROAS. We quickly learned which tactics just weren’t driving results and relied on the Ad Spend Optimizer to continuously replan and improve.
With Well Principled, we created a supply chain “nerve center”, being able to optimize costs and resources with machine learning, while funneling in input from customers, finance and commercial which led to best-in-class results in new product forecast accuracy.
With WP Nucleus we’re more confident in who we target, what products to promote, and the investment needed to scale return. The intelligence and automation it provides has greatly improved our efficiency.