High Level Overview

The Lifetime Value Dashboard helps you understand the overall value of your paid customers by providing an analytical view of their growth and monetization over time.

The report provides a running monetary value of first time paid customers to your Affiliate (called New to Affiliates or NTAs). It also breaks down these customers by various dimensions, all related to their first paid purchase with you Affiliate, and then shows how they were monetized throughout their lifetime as a customer. 

Using this dashboard, you can easily determine:

• The revenue per NTA for a cohort of customers
• The source of NTA customers
• The month over month monetization of NTA cohorts

About the Data Source

This dashboard uses BI’s Master Data Set as its main source of data.  This data is built using customer data from Advantage as well as the transactional data from CircBase.  The super customer number (SCN) process is used to identify individual customers.  The dashboard will show data for the current year and the 7 previous years.

Lifetime Value Business Concepts

Definition of an NTA

A customer is considered an NTA (New to Affiliate) when they do not have a current active lifecycle within your business and they make a paid purchase.  This transaction is considered the NTA transaction and all of their subsequent spending gets counted as part of the customer’s lifecycle.

Lifecycling

LTV looks at customer lifecycles within a given Affiliate, not individual human beings

• If you purchase and become an NTA and then don’t transact for a long time (length of term plus 6 months for subscriptions or purchase date plus 18 months for products) within that given Affiliate, when you do purchase again, you will qualify as an NTA anew. Thus, you would then have two lifecycles with that Affiliate. The net spending associated with lifecycle one stays with lifecycle one, but the net spending associated with lifecycle two stays with lifecycle two.

Values

Values are averaged out for the various timeframes.  Initial value/NTA shows the average initial value/NTA for that cohort.  Each subsequent timeframe shows the net average value/NTA for that timeframe for that cohort.

• Values are net of refunds and include all online and offline spending that is in CircBase
• Values are post-split, meaning that revenue sharing among Affiliates is taken into account
• Third party royalties can also be accounted for and taken out if properly defined in advantage
• Marketing and fulfillment costs are not accounted for LTV

Shading Scale

To prevent looking at Rev/NTA prematurely, a shading system is in place.  If the box is black, it means less than 50% of names for that cohort qualify for the spending timeframe you’re trying to analyze.  As more NTAs qualify for that timeframe, the boxes lighten.  Dark gray means less than 75% qualify, light gray means less than 90% qualify and white indicates that more than 90% of your NTAs qualified.

Calculating Values in LTV Buckets

The total net revenue that was generated by the cohort for that timeframe (Q1, Month 1, Year 2, etc.) is divided by the number of NTAs that have reached the end of that milestone.  So if you have a cohort of 100 NTAs and only 55 of them have reached 91 days (end of Q1), the total net revenue in the Q1 bucket will be divided by 55 NTAs instead of the total 100 NTAs. 

Lead Gen/Two-Step

LTV uses the same conversion logic that is used for EAD to determine if the customer acquisition is a Lead Gen/Two-Step.  If a customer purchase is considered a conversion in EAD (i.e. the first purchase on a list for a product owned by the same Affiliate who owns that list) then in LTV we will consider them a Lead Gen/Two-Step acquisition.  Everyone else will be considered a Direct/One-Step.  For Lead Gen/Two-Step customers, we will go back to the original source (X) code that added the customer to the list and attribute the customers LTV to that source code.

Active NTA Lifecycle

This filter allows users to drill down to look at customers whose lifecycles are active or not.  This is determined by identifying if the next purchase that is made by a customer will continue the current lifecycle or start a new lifecycle.