syndicated data … analysis for… brand… scientists
DESCRIPTION
Syndicated Data … Analysis for… Brand… Scientists. Learning Objective Give students hands-on experience using syndicated data to generate market insights, which in turn drive actionable category and product/brand plans. Some Questions We Often Ask. Score keeping - PowerPoint PPT PresentationTRANSCRIPT
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Syndicated Data …
Analysis for…
Brand…
Scientists.
Learning Objective
Give students hands-on experience using syndicated data to generate market insights, which in turn drive actionable category and product/brand plans.
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Some Questions We Often Ask
Score keeping How are we doing vis-à-vis last year? the competition?
the status quo?
Understand “causality” What factors influence our sales and share? What is
their relative influence?
Prescription What should we do?
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What is Syndicated data?
Aggregation of structured or unstructured data from multiple people or companies for redistribution to the market.
Examples and Uses: Sales: point-of-sale, consumer panel, shopper
card Attitudes & Trends: survey data (Mintel,
Simmons, Forrester) Economic: Repackaged public or government
data Media: TV/Radio/Print measurement, social
media (facebook), mobile, internet (Buzz, ads, search), couponing
Source: Eric Schmidt
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Big Data
15 out of 17 sectors in the United States havemore data stored per companythan the US Library of Congress*McKinsey Global Institute, June 2011
Source: Eric Schmidt
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Market Research Companies by U.S. Revenue
Source: http://www.marketingpower.com/ResourceLibrary/Publications/MarketingNews/2012/6-30-12/Hono-Top-50-Chart.pdf
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Approximate Schedule
Day 1 (Wed. Feb.27)- Intro; Scanner Data; Intro to Market Response
Analysis; Experimentation Lab; Market Response Analysis Lab; Category Analysis Lab; Resource Allocation
Day 2 (Thurs. Feb.28)- Promotion Analysis; Misc. Econometrics Topics;
Vendor Perspective (guest speaker); Mktg Mix Models (guest speaker); Web Analytics (guest speaker); Social Media (guest speaker); SAS Programming Lab
Day 3 (Fri. Mar.1)- Brita Case Study; Valuing Customers; Leveraging
Customer Databases (guest speaker); Reading Published Studies