Data Analysis

In our article, The Decisiveness of Statistical Inference, we exhibit methods of measuring the accuracy of survey research to gauge brand equity, consumer sentiment, political polls, etc. In these cases we use probability samples to get our most accurate picture.

In our Greenbook blog post The Misrepresentation of Statistical Accuracy – Unethical, but Fraud?, we touch upon one of the most common areas of statistical misrepresentation, the reclassification rates of segmentation typing tools and discuss at what point do unethical practices turn into fraud?

In Advancing the Data Product, we navigate how a data company can take their inventory, collected
survey data, shopping history, or large consumer sentiment studies, and create a subscription
service. This is especially relevant as data companies seek to re-engage their vast amounts of historical data that has now become stale

Principles of sampling are analyzed in this guest blog post article.

A cruise line example illustrates how to use discrete choice to determine marginal value in this piece published in Quirk’s Marketing Research Review, How to Price an Island.

Twitter Network Analysis: Nordstrom at the Center of Resistance?, published in Greenbook, examines how visualization of social networks is now coming online to make sense of Big Data and convey the results of analyses through emerging, open-source programs.
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Using open-source software to make sense of small big data, published in Quirk’s Media, describes how to use new capabilities with traditional marketing research deliverables.
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Michael Lieberman’s Quirk’s Marketing Research Review article, Using NodeXL to Visualize Social Media, demonstrates how to leverage social networks for promotion using the NodeXL open-source Excel add-on tool.

Regression Analysis – Predicting Key Drivers analyzes a studies in which the client sought to uncover the attribute or attributes among those you measured that best define your client’s customer satisfaction, usage drivers, or leading cause of switching to a competitor’s brand.

A Look Inside the Choice Toolbox examines how to select the most appropriate choice model from these five most commonly used ones: Paid-comparison Analysis, Conjoint Analysis, Discrete Choice Modeling, Max-Diff, and Adaptive Choice Analysis.

Small Data Visualization by Michael Lieberman presents two examples for examining primary research – a two-step cluster analysis and a data-mining example that takes existing consumer purchase data and reports the items in which the client should specialize to connect to the greatest number of other products.

Design Performance – The Kano Model, published in Quirk’s Marketing Research Review, offers insight into product attributes perceived to be important to customers. The purpose of the tool is to support product specification and discussion through better development team understanding on differentiating product features, as opposed to focusing initially on customer needs, then forming strategic communications to meet those needs.

Tacos in Tel Aviv, published in Quirk’s Marketing Research Review, demonstrates how a Monte Carlo simulation analyzed the primary survey research in a market forecast feasibility study about bringing a chain of upscale Mexican restaurants to Israel’s Silicon Valley.