Decision Sciences: Marketing

The “Decision Sciences: Marketing” blog offers an evolving exploration into how decision sciences enhance strategic decision-making #decisionscience

[Decision Sciences: Marketing @RobbMacDonald]

Solving the Last-Mile Problem in Analytics: Introducing the Decision Science Pre-Analysis Framework #DataScience #DecisionScience #bizML #Marketing https://t.co/Bc5hDYo3oI

[Decision Sciences: Marketing @RobbMacDonald]

ROAS and the Flaws of Linear Thinking in Marketing Spend Decisions #DataScience #bizML #Marketing https://t.co/yYOBd0qm4l

[Decision Sciences: Marketing @RobbMacDonald]

“Data Helps, People Deliver”: Reflecting on My Last 10 Years as a Data Scientist—and Looking Ahead to the Next 10 #DataScience #bizML #Marketing https://t.co/0RbNsHWwg0

[Decision Sciences: Marketing @RobbMacDonald]

The Economy of Insights in a GenAI-Driven World: A Decision Scientist’s Perspective #DataScience #bizML #Marketing #DecisionSciences https://t.co/oaa3bOxKeM

[Decision Sciences: Marketing @RobbMacDonald]

The Power of Decision-Driven Analysis
#DataScience #bizAI #Marketing https://t.co/A2G0aDMI9J

[Decision Sciences: Marketing @RobbMacDonald]

The Executive Decision Series (Post 4): Avoiding Risks with Monte Carlo Simulations in Marketing #DataScience #bizML #Marketing https://t.co/GJmaKodZld

[Decision Sciences: Marketing @RobbMacDonald]

From Insights to “Out-of-Sights”: How Decision Sciences and GenAI Help Drive Consistency #DataScience #bizML #Marketing https://t.co/aZ3Y74bfp3

[Decision Sciences: Marketing @RobbMacDonald]

The Executive Decision Series (Post 3): Transforming Decile Tables into ROI Powerhouses #DataScience #Marketing #bizML https://t.co/ulIZe4AkFv

[Decision Sciences: Marketing @RobbMacDonald]

The Executive Decision Series (Post 2): How to Read a Decile Table for Response Optimization
#DataScience #Marketing #bizML https://t.co/3JGzJxv7yk

[Decision Sciences: Marketing @RobbMacDonald]

Drawing on HBR’s ‘Where Data-Driven Decision-Making Can Go Wrong,’ this post connects insights from the article to the ideas of ‘impact paths,’ ‘decision black holes,’ and ‘data ‘shoehorning.’ #DataScience #bizML #Marketing https://t.co/svXPvlPTCf

[Decision Sciences: Marketing @RobbMacDonald]

“500 Cats” or one “Tiger”? The promise versus the reality of data analysis and its role in driving actionable decision-making within today’s organizations. #DataScience #bizML #Marketing https://t.co/7BclsgtbC9

[Decision Sciences: Marketing @RobbMacDonald]

“The Executive Decision” is a new series I’ve launched to bridge the gap between advanced analytics and actionable decision-making. Each post spotlights a new conceptand shows how it empowers smarter decisions #DataScience #bizML #Marketing https://t.co/7gYwVbDbq0

[Decision Sciences: Marketing @RobbMacDonald]

My latest blog post explores the concept of impact paths—structured, traceable frameworks designed to connect data-driven insights to explicit business decisions and measurable outcomes. #DataScience #bizML #MarketingStrategy https://t.co/xVljP8DxsT

[Decision Sciences: Marketing @RobbMacDonald]

In my latest blog, I explore the ‘data veneer’—how surface-level insights and confirmation bias undermine data-driven decisions #DataScience #bizML #Marketing https://t.co/kcUwjRyRSb

[Decision Sciences: Marketing @RobbMacDonald]

“From Meaningful Data Science to Impactful Decisions: The Importance of Being Causally Prescriptive.” A must-read for data scientists aiming to establish a new framework in decision sciences #DataScience #bizML #DecisionScience https://t.co/dd3ATSxjzC

[Decision Sciences: Marketing @RobbMacDonald]

… shaping data to fit preexisting storylines can be dangerous and undermine objective decision-making. We want to tell a story with data, for sure, but we can’t put the story ahead of the data and unbiased analysis #DataScience #Integrity #bizML
#Marketing

[Decision Sciences: Marketing @RobbMacDonald]

Decision-scientists must guard against confirmation bias: the tendency to draw conclusions first and then seek data to support pre-existing beliefs, ignoring contrary evidence #DataScience #DecisionMaking #bizML #DecisionScience

[Towards Data Science @TDataScience]

What's the difference between model explainability, interpretability, and observability? Jason Zhong's debut TDS article outlines the nuanced distinctions you should be aware of. https://t.co/g2aiYfXD9B

[Decision Sciences: Marketing @RobbMacDonald]

Post 7: Bridging the Intelligence Value Gap: Advancing Decision Sciences with Predictive & Prescriptive Analytics https://t.co/RbW3VSCXvr #bizML #datascience #marketing

[Decision Sciences: Marketing @RobbMacDonald]

I launched a new blog series on the (r)evolution of data science and ML for enhancing decision-making in Marketing. New content drops next week. Catch-up on current posts below… https://t.co/5EGMsVNvF7 #bizML #datascience #marketing

[Decision Sciences: Marketing @RobbMacDonald]

Post 6: Empowering Decision Science with GenAI: Enhancing Strategic Decision-Making https://t.co/vjTU3Jpuvr #bizML #datascience #marketing