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05 Sep 2017
Answered a question on OpenForum: "Focus Groups - Dead or Alive?"
Principal Consultant at Expected X
Awards Earned:
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Level: LEVEL 01 (12mo pts: 9 pts)
Lifetime points: 24 pts View details
Thought Leadership:
% performance based on average of all engagements
Selected: % of applied
0%
Recognized: Contributions valued by peers
0%
Peer Support: Percentile of active participants
0%
Profile
Summary
I’m John, Founder and Principal Consultant of Expected X.Today, a data revolution is taking place and businesses of all sizes across nearly every industry have begun to evolve their corporations into ones that use analytics to grow and thrive.
But still, a lot of businesses don’t think they are “right” for data solutions and immediately disqualify themselves: their budgets are too small, they lack the internal talent, they don't know how to put data solutions into action, and so on.
That’s where we come in. We bring sanity to businesses by making them feel secure with data solutions. We add structure to ambiguity through data engineering, modeling, and execution – and most importantly: we derive value you can use to grow.
With this knowledge in hand, we help you identify and develop opportunities you can exploit to grow both your business and its data maturity.
So, what’s your business’s data strategy? If you want to grow in today’s business environment, can you afford not to have one?
Connect with us today so together we can begin your journey towards growing your 21st century business.
Web: expectedx.com
Blog: https://www.linkedin.com/today/author/johnsukup
Twitter: @ESukupIII
Phone: 415-805-6535
Email: john@expectedx.com
Experience
Principal Consultant
Expected X
September 2015 - Present
• Inherited modeler: Department of Energy/Strategic Petroleum Reserve’s Gulf Coast hurricane predictive model for estimating refinery and pipeline shortfalls. Success: improved data inputs and model accuracy
• Modeler: Telemedicine Impact Score for assessing system implementation at the U.S. county level using aggregated public data sources. Success: model successfully scored all counties
• Modeler: Customer Lifetime Value model from manufacturer CRM system to predict high-probability repurchase clients and next product purchased. Success: reduced marketing spend 11%
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Skills
Data Analysis
Segmentation
Quantitative Research
Analytics
Competitive Intelligence
Strategy
Customer Insight
Competitive Analysis
R
Qualitative Research
Quantitative Analytics
Survey Design
Statistical Modeling
Quantitative Analysis
Sample Design
Predictive Analytics
Machine Learning
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Total Points: 24
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