Pricesensitivitymeter Package v1.2 Released

An updated version of the “pricesensitivitymeter” R package is now available on CRAN: This version 1.2 includes two main new features: The new function psm_plot() is a convenience function for creating the “standard” Price Sensitivity Meter plot. You can see a simple example in the Visualizing PSM Results vignette. The psm_analysis() function now also supports input in tibble format (which is common in the “tidyverse”), in addition to standard data.
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Pricesensitivitymeter Package v1.1 Released

The version 1.1 of the “pricesensitivitymeter” R package enhances interpolation: Instead of fixed steps of 0.01, it lets the user choose the size of the interpolation steps. This makes it easier to work in currencies in which a subdivision into 1/100th is not meaningful, such as Japanese Yen or Chilean Pesos. Moreover, it makes it easier to analyze data for more expensive products in which a subdivision on cent-level is not necessary.
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Pricesensitivitymeter Package v1.0 Released

v1.0 of the “pricesensitivitymeter” R package is now available on CRAN. This version adds a new function psm_analysis_weighted() which allows to properly deal with weighted data. As far as I know, this is the first implementation of the van Westendorp Price Sensitivity Meter methodology that accounts for weighting. The R package uses the infrastructure that is provided by the excellent “survey” package: To use weighted data, it must be set up as a “survey design” object via the svydesign() function from the “survey” package.
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Pricesensitivitymeter Package v0.4.1 Released

v0.4.1 of the “pricesensitivitymeter” R package has been released on CRAN. It fixes a bug in the calculation of the “point of marginal cheapness” and the “point of marginal expensiveness”, properly shows the percentage of invalid cases, fixes several typos and adds unit testing for the input to the Newton Miller Smith extension. The package is available on CRAN. Feedback via e-mail or via opening issues in the corresponding Github repository is always welcome.
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Pricesensitivitymeter Package v0.3 Released

v0.3 of the “pricesensitivitymeter” R package expands the functionality for interpolation between price points. If the sample size is small or price information in some areas of the price curve is sparse, the package now is able to use linear interpolation between price points to make the price curves appear less bumpy. The option is by default set to FALSE, but can easily be switched on: output <- psm_analysis(toocheap, cheap, expensive, tooexpensive, interpolate = TRUE) The package also contains a vignette (“Interpolation in Small Samples”) that explains how the function works.
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Pricesensitivitymeter Package Released on CRAN

Great news: The “pricesensitivitymeter” package has just been released on CRAN! Please use the following link to find it there: https://cran.r-project.org/package=pricesensitivitymeter CRAN is the standard repository for R packages, which means that the “pricesensitivitymeter” package can be installed via R’s standard routine: install.packages("pricesensitivitymeter") Compared to v0.1 of the package (which was available via Github), I have added the following features: support for running the analysis without a “too cheap” price vignette to explain charting unit testing for main function inputs and outputs smoothing of trial/revenue optimization for Newton Miller Smith extension (previous version was a bit bumpy when there were areas with sparse data) (changed the name of the main function to psm_analysis() for readability reasons) I am excited that the CRAN release makes the package available for a wider group of users.
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Pricesensitivitymeter Package v0.1 Released

Today, I have released the first version (v0.1) of the R package I have written during the last couple of months: “pricesensitivitymeter” is an implementation of the van Westendorp Price Sensitivity Meter (PSM) - a standard market research methodology for assessing consumer price preferences. The package is available via this Github repository. The original research paper which explains the methodology was published in 1976 in the Proceedings of the ESOMAR congress and is available at ESOMAR’s Research World website.
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