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https://github.com/y-bar/mmetrics
Easy computation of Marketing Metrics in R
https://github.com/y-bar/mmetrics
marketing marketing-analytics marketing-tools r
Last synced: 3 months ago
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Easy computation of Marketing Metrics in R
- Host: GitHub
- URL: https://github.com/y-bar/mmetrics
- Owner: y-bar
- License: other
- Created: 2019-05-17T08:37:34.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2019-08-14T06:57:45.000Z (about 5 years ago)
- Last Synced: 2024-05-21T02:11:45.931Z (6 months ago)
- Topics: marketing, marketing-analytics, marketing-tools, r
- Language: R
- Homepage: https://y-bar.github.io/mmetrics/
- Size: 219 KB
- Stars: 27
- Watchers: 10
- Forks: 4
- Open Issues: 6
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
- jimsghstars - y-bar/mmetrics - Easy computation of Marketing Metrics in R (R)
README
---
output: github_document
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-"
)
options(knitr.table.format = 'markdown')
```
# mmetrics 
[](https://travis-ci.com/y-bar/mmetrics)
[](https://ci.appveyor.com/project/teramonagi/mmetrics/branch/master)
[](https://cran.r-project.org/package=mmetrics)
[](https://codecov.io/github/y-bar/mmetrics)
[](https://github.com/y-bar/mmetrics/blob/master/LICENSE)
[](https://www.tidyverse.org/lifecycle/#experimental)
Easy Computation of Marketing Metrics with Different Analysis Axis.
## Installation
You can install the released version of {mmetrics} from CRAN with:
```r
install.packages("mmetrics")
```
Or install the development version from github with:
```r
# install.packages("remotes")
remotes::install_github("y-bar/mmetrics")
```
## Example
### Load Dummy data
First, we load dummy data from {mmetrics} package for this example.
```{r}
df <- mmetrics::dummy_data
df
```
### Define metrics
As a next step, we define metrics to evaluate using `mmetrics::define`.
```{r}
# Example metrics
metrics <- mmetrics::define(
cost = sum(cost),
ctr = sum(click)/sum(impression) # CTR, Click Through Rate
)
```
### Just call `mmetrics::add()` !
Call `mmetrics::add()` with grouping key (here `gender`) then we will get new `data.frame` with defined metrics.
```{r}
mmetrics::add(df, gender, metrics = metrics)
```
### Remove aggregate function from metrics using `mmetrics::disaggregate()`
It is hassle for users to re-define metrics when you would like to use these for `dplyr::mutate()`.
In this case, you can use `mmetrics::disaggregate()` to remove *the first aggregation function* for the argument and return disaggregated metrics.
```{r}
# Original metrics. sum() is used for this metrics
metrics
```
```{r}
# Disaggregate metrics!
metrics_disaggregated <- mmetrics::disaggregate(metrics)
# Woo! sum() are removed!!!
metrics_disaggregated
```
You can use these metrics with `dplyr::mutate()` for row-wise metrics computation.
```{r}
dplyr::mutate(df, !!!metrics_disaggregated)
```
...or, you can do the same compucation using `mmetrics::gmutate()` defind in our package.
In this case, you do not need to write `!!!` (bang-bang-bang) operator explicitly.
```{r}
mmetrics::gmutate(df, metrics = metrics_disaggregated)
```
## More examples
- As a first step, see the vignettes [Introduction to {mmetrics} package](https://y-bar.github.io/mmetrics/articles/introduction.html)