Sequence of shopping carts in-depth analysis with R – Clustering

This is the second part of the in-depth sequence analysis. In the previous post, we processed data in the required format, plotted a Sankey diagram, and did some distribution, frequency, time lapse and entropy analysis with visualization. For dessert, clustering! Clustering is an exploratory data analysis method aimed at finding automatically homogeneous groups or clusters in the […]

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Sequence of shopping carts in-depth analysis with R

Although the sankey diagram from the previous post provided us with a very descriptive tool, we can consider it a rather exploratory analisys. As I mentioned, sequence mining can give us the opportunity to recommend this or that product based on previous purchases, but we should find the right moment and patterns in purchasing behavior. […]

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Sequence of shopping carts analysis with R – Sankey diagram

We studied how we can visualize the structure of a shopping cart in the previous post. Although you can find a great deal of materials on how to analyze combinations of products in the shopping cart (e.g. via association rules), there is a lack of sources on how to analyze the sequences of shopping carts. […]

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Shopping cart analysis with R – Multi-layer pie chart

This post was updated on 12/05/2015. In this post, we will review a very interesting type of visualization – the Multi-layer Pie Chart – and use it for one of the marketing analytics tasks – the shopping carts analysis. We will go from the initial data processing to the shopping carts analysis visualization. I will share the R […]

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Cohort analysis with R – Retention charts

When we spend more money for attracting new customers then they bring us by the first but, usually, by the next purchases, we appeal to customer’s life-time value (CLV). We expect that customers will spend with us for years and it means we expect to earn some profit finally. In this case, retention is vital parameter. Most of our […]

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Include promo/activity effect into the prediction (extended ARIMA model with R)

I want to consider an approach of forecasting I really like and frequently use. It allows to include the promo campaigns (or another activities and other variables as well) effect into the prediction of total amount. I will use a fictitious example and data in this post, but it works really good with my real data.  So, you can […]

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Cohort analysis with R – “layer-cake graph” (part 2)

Continue to exploit a great idea of ‘layer-cake’ graph. If you liked the approach I shared in the previous topic, perhaps, you would have one or two questions we should answer additionally. Recall “Total revenue by Cohort” chart: As total revenue depends on the number of customers we attracted and on the amount of money each of them spent with us, there […]

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Cohort analysis with R – “layer-cake graph”

Cohort Analysis is one of the most powerful and demanded techniques available to marketers for assessing long-term trends in customer retention and calculating life-time value. If you studied custora’s university, you could be interested in amazing “layer-cake graph” they propose for Cohort Analysis. Custora says: “The distinctive “layer-cake graph” produced by looking at cohorts in calendar time can […]

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Twitter sentiment analysis based on affective lexicons with R

Continue to dig tweets. After we reviewed how to count positive, negative and neutral tweets in the previous post, I discovered another great idea. Suppose positive or negative mark is not enough and we want to understand the rate of positivity or negativity. For example, if word “good” has 4 points rating, but “perfect” has 6. In […]

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Twitter sentiment analysis with R

Recently I’ve designed a relatively simple code in R for analyzing Twitter posts content via calculating the number of positive, negative and neutral words. The idea of processing tweets is based on the presentation http://www.slideshare.net/ajayohri/twitter-analysis-by-kaify-rais. The words in the tweet correspond with the words in dictionaries that you can find on the internet or create by yourself. It is […]

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