Simple agent-based view of customer campaign response behaviour based on months since last open. This represents a typical newsletter campaign sent to a company's subscriber base where each subscriber receives one email per week.
This weekly version models agents based on tenure & recency by using x and y agent-location axes to reflect time since open and overall tenure respectively.
This model enables you to see how, because of the inter-relationship between open rates in subsequent weeks, increasing open rates for groups of customers (e.g. increasing open rate for those that have not opened in the last week) can have a disproportionately large effect over time.