This article explains the different types of KPIs and data that are important to an affiliate program and how to include them in reporting.
Volume KPIs
Clicks, orders, revenue, commissions, and joined partners. Not all programs track revenue for KPIs, for example, a leads or installs based program.
Business KPIs
AOV, CPA/CPL, New Customer Rate, RoAS, ROI, Commission Rate, and Conversion Rate. These help add context, understanding and can indicate value to the program. Most often these are calculated. Finance or lead programs are more likely to use CPA/CPL. Affluent has pre-created calculated metrics.
Program Evaluation KPIs
Click-Active rate, Sale or Lead Active rate, Program Weighting ( the percentage of the program coming from the top 10 partners), Content Percentage of Sales (percentage of sales coming from content partners), Program evaluation metrics help assess the program overall and indicate program health in comparison to other programs. Affluent has pre-created metrics and metric variants to automate reporting on these metrics.
For definitions of all Affluent metrics, visit the Metric Glossary.
Program Level Data
Measures performance for the whole program over a specific period of time. Reviewing program-level data helps to identify program trends and anomalies. It is important to review this data on a regular cadence.
Dimension Level Data
Dimension level data looks at a specific dimension of the program.
- Performance by Partner
- Performance by Country
- Performance by SKU/Product
Transaction Level Data
This is the most granular level of data and involves looking at transactions line by line. This may be something that you only do to answer a specific question or to resolve a red flag. In Affluent transaction level data is available via the Overview under the Transactions tab.
Reporting Tip: it is important to first understand what 'normal' performance and KPIs look like. From there you can spot any abnormalities. When you are preparing an internal or external report you can then tell the story behind the data. To include a narrative add a text box to your dashboard.
How to identify abnormalities?
The most common way to identify an abnormality is to look at period-over-period data. Affluent supports comparing data using the 'previous period' and 'previous year' metric variants.
Trends are also another great way to spot abnormalities. Consider whether of not the program is trending in the right direction. There are often reasons why a program will see temporary decreases in revenue or other metrics e.g. buying habits, seasonal trends, the promotion of a specific product, or a host of other reasons.