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This gist shows you how to run a retention analysis. I blogged about how to run a retention analysis here: https://keen.io/blog/47823687779/how-to-do-a-retention-analysis/
require 'rubygems'
require 'keen'
require 'json'
require 'date'
require 'active_support/all' #for datetime calculation e.g. weeks.ago.at_beginning_of_week
require 'simple_xlsx' #for outputting excel files
require 'cgi' #for URL encoding
#================================oOo===================================
# This program helps you figure out how many entities that do an activity in a given week do a different activity in subsequent weeks
# For example, for users that create an account in a given week, how many of them login in subsequent weeks since their signup date
# This is commonly used for rentention analysis aka cohort analysis. Cohorts are defined by the week they do the first step in the funnel.
# You must have event data stored in Keen IO in order to run this analysis
# The program uses the Keen IO funnel analysis API to do the calculations
# The analysis can go back any num_weeks in the past and will run analysis for each week since that time (one cohort for each week)
# The results will be outputted to Terminal and also an excel file
# The total number of funnel analyses is num_weeks^2/2 so the query can take some time, espeically for very large event collections.
#================================oOo===================================
# Step 1 - Determine how far back in the past you want to go for this analysis.
# Calculations will be run for every week since that week, up until the most recent completed week.
# num_weeks determines the number of cohorts in your analysis.
num_weeks = 52
# Step 2 - Enter your Keen Project Info
Keen.project_id = <project ID>
Keen.read_key = <key>
# Step 3 - Define your funnel steps. The first step will define your cohort groups. The last step will determine your "success" criteria.
# For example, say you are interested in login activity for customers who have paid
# step one: Create Account (counts the number of unique accounts that were created that week)
# step two: Login (counts how many unique customers in the cohort logged in that week)
# Add any number of filters to any step (e.g. exclude test accounts).
# You can optionally add filters to the steps.
$steps = [
{
:event_collection => "create_account",
:actor_property => "account.id",
# :filters => [{
# :property_name => "account.name",
# :operator => "ne",
# :property_value => "TestAccount"
# }],
},
{
:event_collection => "logins",
:actor_property => "project.account.id",
},
]
# Protip: You may have more than two steps. Middle steps will further refine the number of candidates which make it to the last step.
# Step 4 - Run this script!
# These two nested loops run through all of the weeks since num_weeks ago, building funnel queries and running them.
SimpleXlsx::Serializer.new(Time.now.to_s[0..19]+".xlsx") do |doc| # This will create an excel file to output results
doc.add_sheet("Retention") do |sheet|
first_row_labels=["Week","Cohort Size"] # These are the first two column headers in excel
# This loop cycles through each week in num_weeks so that we can assign that week to the first step of the funnel
num_weeks.times do |w|
first_row_labels << "Week "+(w+1).to_s # There is one column for every week depending on your num_weeks. Week 0, Week 1, ... Week N
end
sheet.add_row(first_row_labels)
i=0
# This loop cycles through each of the weeks starting with the week num_weeks ago
while i < num_weeks do
$row_items=[]
puts "==========================oOo============================="
puts "Retention Analysis for the Cohort from " + ((num_weeks-i).weeks.ago.at_beginning_of_week).to_s[0..10]
$row_items << ((num_weeks-i).weeks.ago.at_beginning_of_week).to_s[0..10]
applicable_weeks = num_weeks - i
n=0
# This loop cycles through each of the weeks starting with the week the cohort was created and then progressing through each week since then
applicable_weeks.times do |n|
# Insert cohort timeframe into the first funnel step
$steps.first[:timeframe] = {
:start => (num_weeks-i).weeks.ago.at_beginning_of_week,
:end => (num_weeks-i-1).weeks.ago.at_beginning_of_week
}
# Insert rentention timeframe into the final funnel step
$steps.last[:timeframe] = {
:start => (applicable_weeks-n).weeks.ago.at_beginning_of_week,
:end => (applicable_weeks-n-1).weeks.ago.at_beginning_of_week
}
query_name = "Retention_cohort_"+i.to_s+".week"+n.to_s
answer = Keen.funnel(:steps => $steps) # Run the Keen IO Query
# The Keen IO query returns a result like [X, Y]
# X is the result of the first funnel step (number of a new accounts in this example, aka Cohort Size)
# Y is the result of the second funnel step (number of logins in this example)
if n == 0
puts "Cohort Size: "+answer[0].to_s
$cohortSize = answer[0]
$row_items << $cohortSize # We jam stuff into this array so we can print it to excel later. Item 0 in the array is the Cohort Size.
puts "Week "+n.to_s+": "+answer.last.to_s
$row_items << (answer.last.to_f/$cohortSize.to_f)
else
puts "Week "+n.to_s+": "+answer.last.to_s
$row_items << (answer.last.to_f/$cohortSize.to_f) # We jam stuff into this array so we can print it to excel later. In this example, each column shows the % of accounts who did step 2 in a given week after signup.
end
n=n+1
end
i=i+1
sheet.add_row($row_items) # Put the data into the excel file
$row_items=[] # Empty the array so we can use it again for the next row.
end
end
end
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