<!-- TITLE: Understanding Data For Churn Applications --> <!-- SUBTITLE: A quick summary of Understanding Data For Churn Applications --> # Preparing and uploading data for Churn Model ## Understanding Data Requirement for Churn Model To build a highly accurate churn model for your business, you need to understand what kind of data will be used to train your models. We have categorized data points into various indicator categories for you to understand what drives churn predictions. * Profile: These are data points which define the profile of the customer * Symptom: These data points represent customer health symptoms which may contribute to churn or non-churn * Causes: These data points represent causes that may lead the customer to leave or stay. We have come up with a framework that is suitable for most of the business, You may improve it by adding more such data points based on your business context. |Type|Field Name|Indicator|Description| | ----------- | ----------- |----------- | ----------- | |String|customer_id|profile|Unique id of the customer, it can be anonymized on your end as long as it identifies customer uniquely.| |String|age|Profile|Age of the customer| |String|sex|Profile|Is customer male or female| |String|city|Profile|City of the customer| |Number|days_since_joined|Profile|How old is the relationship with the customer?| |Number|days_since_last_purchase|Symptom|When did customer make his/her last purchase?| |Number|total_no_of_purchases|Symptom|How many times has customer made the purchase?| |Number|lowest_rating|Symptom|What is the lowest rating by the customer so far?| |Number|lowest_rating_l3m|Symptom|What is the lowest rating by a customer in the last 3 months ( **l3m** )?| |Number|total_engagements|Cause|How many times have you engaged with the customer so far? Engagement can be in the form of email, newsletters, calls, etc. | |Number|engagements_l3m|Cause|How many times have you engaged with a customer in the last 3 months?| |Number|total_sales|Symptom|What is the total sale of the customer so far?| |Number|total_sales_l3m|Symptom|What is the total sale of the customer in the last 3 months| |Number|average_session_time_secs|Symptom|What is the average time spent by the customer on your app?| |Number|average_session_time_secs_l3m|Symptom|What is the average time spent by the customer on your app in the last 3 months?| |Number|total_logins|Symptom|How many times did customer log into your app so far?| |Number|total_logins_l3m|Symptom|How many times did customer log into your app in the last 3 months?| |Number|complaint_count|Cause|How many complaints have you received from the customer so far?| |Number|complaint_count_l3m|Cause|How many complaints have you received from the customer in the last 3 months? |Number|total_no_pricing_changes|Cause|How many times has price changed for your offering so far?| |Number|pricing_changes_l3m|Cause|How many times has price changed for your offering in the last 3 months?| |Number|total_no_customer_support_change|Cause|Has there been a change in your support team so far?| |Number|customer_support_change_l3m|Cause|Has there been a change in your support team in the last three months?| |Number|average_delivery_time_in_days|Cause|What was average delivery time for the customer so far?| |Number|average_delivery_time_in_days_l3m|Cause|What was average delivery time for customer in the last 3 months?| |Number|site_response_time_secs|Cause|What is the average response time of your app?| |Number|site_response_time_secs_avg_l3m|Cause|What is the average response time of your app in the last 3 months?| |Number|downtime_counts|Cause|How many downtimes did customer face so far?| |Number|downtime_counts_l3m|Cause|How many downtimes did customer face in the last 3 months?| |Number|competitor_promotions_l3m|Cause|How many competitors promotion campaigns happened in the last 3 months| |Number|promotions_l3m|Cause|How many promotion campaigns have you done in the last 3 months| ## Format : CSV Once you prepare the data, make sure it is in **CSV format** with the headers similar to the above table. You can add more fields to data set when you are ready to build your own ML model. > Download a sample data set: [Datoin Sample Churn](/uploads/churn/datoin-sample-churn.csv "Datoin Sample Churn") > For more details on Data Sets [visit here](/diy-platform/data-store#DataSets)