AnalyzeCore by Sergii Bryl' – data is beautiful, data is a story: Recent Episodes
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COVID-19 or Coronavirus pandemic is having an unpredictable and huge impact on our lives, so I wanted to see the speed with which it spreads across countries. The following is how I’ve seen it: COVID-19 or Coronavirus pandemic is having an unpredictable and huge impact on our lives, so I wanted to see the speed […]
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There are some very important differences between a Kaggle competition and real-life project which beginner Data Scientists should know about. Kaggle creates a fantastic competition spirit. This is a guest blog post of my good friend Sergii Makarevych who has vast experience in Kaggle competitions and real-life data science projects implementation. There are some very important […]
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Customers lifetime value (LTV or CLV) is one of the cornerstones of product analytics because we need to make a lot of decisions for which the LTV is a necessary or at least very significant factor. In this article, we will focus on products/services/applications with recurring subscription payments.Customers lifetime value (LTV or CLV) is one […]
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The larger and more complex the business the more metrics and dimensions. One day you understand that it is impossible to track them with only your eyes.The larger and more complex the business the more metrics and dimensions. One day you understand that it is impossible to track them with only your eyes. Reducing the […]
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We will review another fascinating approach that marries heuristic and probabilistic methods. We will link marketing channels with a probability of a customer passing through each step of a Sales FunnelThis is the last post in the series of articles about using Multi-Channel Attribution in marketing. In previous two articles (part 1 and part 2), we’ve […]
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Even though the concept of the first-order Markov chains is pretty simple, you can face other issues and challenges when implementing the approach in practice. We will review some of them This is the second post about the Marketing Multi-channel Attribution Model with Markov chains (here is the first one). Even though the concept of the first-order Markov […]
The post Marketing Multi-Channel Attribution model with R (part 2: practical issues) appeared first on AnalyzeCore by Sergey Bryl' - data is beautiful, data is a story.
We will use Document-Term Matrix that is the result of Vocabulary-based vectorization for training the model for Twitter sentiment analysisRecently I’ve worked with word2vec and doc2vec algorithms that I found interesting from many perspectives. Even though I used them for another purpose, the main thing they were developed for is Text analysis. As I noticed, my […]
The post Twitter sentiment analysis with Machine Learning in R using doc2vec approach (part 1) appeared first on AnalyzeCore by Sergey Bryl' - data is beautiful, data is a story.
Using Markov chains allow us to switch from Google Analytics heuristic models to probabilistic ones. By computing the model and estimating transition probabilities we can attribute every channel/touchpoint As we know, a customer usually goes through a path/sequence of different channels/touchpoints before a purchase in e-commerce or conversion in other areas. In Google Analytics we […]
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When conducting Cohort Analysis, one of the most important measures is Customer Retention Rate. I will share a few ideas for visualizing this parameter When conducting Cohort Analysis, one of the most important measures is Customer Retention Rate. I will share a few ideas for visualizing this parameter in this post. Last year I shared […]
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We will study how to use LifeCycle Grids concept for measuring a health of the business via Delta Analysis technicThere are several posts connected with LifeCycle Grids on this blog. If you are not familiar with the concept I highly recommend you to start with Jim Novo’s book, his blog or, at least, from the first post […]
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Sales (purchasing or conversion) Funnel is a consumer-focused marketing model which illustrates the theoretical customer journey towards the purchase of a product or service. We will study a very simple example of creating a Sales Funnel by focusing on visualizationSales (purchasing or conversion) Funnel is a consumer-focused marketing model which illustrates the theoretical customer journey towards the […]
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We will study a Heatmap visualization that not only can be used for descriptive analysis as well but would be more helpful for analyzing a large number of cohorts. For instance, if you need to form and analyze weekly cohorts within a year Previously I shared the data visualization approach for the descriptive analysis of progress […]
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We will combine Cohort Analysis and LifeCycle Grids approach for obtaining more detailed analysis This is the third post about LifeCycle Grids. You can find the first post about the sense of LifeCycle Grids and A-Z process for creating and visualizing with R programming language here. Lastly, here is the second post about adding monetary […]
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We will study how we can analyze and visualize other valuable metrics like customer acquisition cost and customer lifetime value using LifeCycle Grids approachWe studied a very powerful approach for customer segmentation in the previous post, which is based on the customer’s lifecycle. We used two metrics: frequency and recency. It is also possible and […]
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We will study a very powerful approach for customer segmentation that is based on customer’s lifecycle, specifically on frequency and recency of purchasesI want to share a very powerful approach for customer segmentation in this post. It is based on customer’s lifecycle, specifically on frequency and recency of purchases. The idea of using these metrics […]
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We will cover how to find patterns of events. We will find events that occur systematically together and in the same order, relationships with customers’ characteristics and association rules between event subsequences This is the third part of the sequence of shopping carts in-depth analysis. We processed initial data in the required format, did the exploratory […]
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This is the second part of the in-depth sequence analysis and we will use clusterization for simplifying a large number of distinct sequences in a few types of trajectoriesThis 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, […]
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Although the sankey diagram from the previous post provided us with a very descriptive tool, we can consider it a rather exploratory analisys.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 […]
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We will study how to apply a Sankey diagram visualization when doing a sequential analysis of shopping carts that can bring you a helpful knowledge of patterns of customer’s behaviorWe studied how we can visualize the structure of a shopping cart in the previous post. Although you can find plenty of materials on how to […]
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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 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 […]
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When conducting Cohort Analysis, one of the most important measures is Customer Retention Rate. I will share a few ideas for visualizing this parameter in this postWhen we spend more money on 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). […]
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We will continue to exploit a great idea of ‘layer-cake’ graph for Cohort analysis 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 […]
The post Cohort analysis with R – “layer-cake graph” (part 2) appeared first on AnalyzeCore by Sergey Bryl' - data is beautiful, data is a story.
We will study a pretty helpful visualization for Cohort Analysis that 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 Cohort Analysis is one of the most powerful and demanded techniques available to marketers for assessing long-term trends in customer retention and calculating […]
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We will study another dictionary-based approach that is based on affective lexicons for Twitter sentiment analysis 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 […]
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We will study a dictionary-based approach for Twitter sentiment analysisRecently 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 […]
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