Accelerate
Science Product Pipelines with A.I. Model-Assisted Selection
We are working with:
Systematizing Science with A.I.
Nucleus Learns Why Products Work:
Hard Science
How can I identify more promising products while testing fewer candidates?
Reduce early stage testing
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.
Hard Science
How can I advance candidates more quickly through phases?
Accelerate pipeline advancements
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.
Consumer Science
Which promos and prices would drive incremental profits for Product?
Increase gross margin up to 16%
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.
Consumer Science
Which half of agency spend is actually driving incremental sales from Media?
Increase ROAS up to 411%
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.
What Nucleus
clients are saying
Solving these Problems Requires More than just Analytics
Data
Curation
You can't curate data you don't know is bad. Know how to spot it.
Fit For Purpose
A.I.
You don't trust you have the best plan. Use causal models.
Scenario-
Based Execution
"Actionable insights" never are. Drive process change.
Principled Thinking Blog
Crawl, Walk, Run is Antithetical to Transformation
Is "Crawl, Walk, Run" really the best approach to digital transformation?
Exploring the limitations of common A.I. modeling approaches as applied to decision making
Untangling correlation, causation and concurrency in order to build an effective strategy.
What’s Wrong With “Data-Driven Decisions”
Well Principled removes the ??? from data driven decision making with causal models