Introduction to Customer Lifetime Value in Connectif


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Customer Lifetime Value (CLV) is a series of indicators that help you to understand the value of your customers and how likely they are to shop with you again. In Connectif, the machine learning model that calculates these metrics is unique to each account. Using the information you acquire from your business, you’ll obtain increasingly accurate data to help improve your performance against KPIs.

This article explains the properties of CLV in Connectif, the requirements for activating it in your account, how these predictions are made, and what the metrics in your dashboard mean.


1. Properties

CLV Model

  • Each CLV model is unique and learns from the account's data to provide the best possible forecasts and predictions. 
  • Connectif's Customer Lifetime Value machine learning model is based on the Buy Till You Die models, which describe customer behavior in two main processes:
    • The repeat purchase process indicates that, while active, a customer makes purchases at random around their average transaction rate, which varies from that of other customers.
    • The dropout process, whose premise is that each client has an unobserved propensity to churn and that this propensity varies among customers. 

Each customer will stop making purchases at a point in time that cannot be determined. The fact that a customer does not make any purchases for a period of time does not indicate that they have stopped forever.

Contacts' CLV Data

  • The CLV is updated at various different times to get the most out of the data and to make the machine learning system increasingly accurate:
    • Once a day, Connectif will verify if your account meets the requirements for CLV calculation and if so, CLV will be activated in your account.
    • Once a month, CLV will be recalculated for all contacts with at least one purchase. Therefore, the longer it is active and the more data you collect, the more accurate it will be.
    • When a purchase is made, the contact’s CLV will be recalculated.
    • When merging contacts, the system will recalculate the contact’s CLV (if enabled and the anonymous contact has made at least one purchase).
Customer Lifetime Value is based on repetition. The more repeat purchases your customers make, the more accurate the model will be.



2. How CLV works in Connectif

a. Requirements for having CLV in your account

In order to have the Customer Lifetime Value calculation and metrics in your Connectif account, you must meet some minimum requirements (so that the algorithm can calculate and extract the necessary predictions):

  • Time: your account must have at least four months of purchases.
  • Customers: you’ll need at least 500 different purchasers.
  • Repeat purchase rate: of these 500 customers, at least one must have made three or more purchases.

It is possible that the system may not be able to generate a model even when all the requirements are met.




You can easily check if you qualify to have the CLV model activated in your Connectif account. All you have to do is log into your Data Explorer and check:

— If you have at least four months of purchases (if your account does not allow you to verify data older than three months in Data Explorer, you can do so through "Catalog > Purchases").
— The number of unique purchasers.
Repeat customer metrics.


b. CLV parameters in Connectif

Once the model is adjusted, you can start obtaining insights. CLV machine learning will offer you the following predictions:

  • Customer Lifetime Value: indicates the total amount of money this contact is expected to spend with your business in the next 12 months.
  • P-Alive: This metric indicates how likely the customer is to purchase again. The higher this value, the more likely it is that the customer will make another purchase.
  • Churn rate: the opposite indicator to P-Alive, this refers to the probability that the customer has definitively stopped making purchases.
  • Expected purchases: this figure represents how many transactions you can expect from the customer in the next 12 months.
 The model aims to make the best prediction based on the data. However, when it comes to predictions, the data may not reflect reality 100%.

This series of parameters makes up the Customer Lifetime Value machine learning model in your Connectif account. With these metrics you can make an estimate about the value of your contacts and their probability of repetition.


c. Where to find CLV in Connectif

You can find and use CLV metrics in your Connectif account in various locations on the platform:

    1. In the contact sheet: you can see the value of each contact’s CLV metrics on their contact sheet.


    1. Dynamic Segments: when creating your dynamic segments, you can filter by contacts that meet certain CLV conditions.


    1. Dynamic Plus Segments: select "Value Indicators" in the search engine and choose the CLV parameters you want to filter.


    1. Workflows: you can use the "Check value" node, filtering by Customer Lifetime Value metrics and activate certain actions within your workflows for those contact segments.



CLV information is also included in the contact’s information that is exported from one node to another.

    1. In the export of contact data: when exporting your contacts from Connectif, you can also save their available CLV metrics.



Use this information to draw up automated strategies that allow you to optimize your databases and increase the value of your customers.



You’ve reached the end of the lesson.


Do you have questions? 
Don’t forget, our Connectif specialists are here to help you. To contact them, just open a Support ticket by clicking the blue “Help” button on your dashboard.


Keep learning!

To make the most of your Connectif account, we recommend reading these articles next:

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