Conversion lag distribution

How long journeys take, measured from first touch to conversion. This is how you choose a lookback window instead of reaching for thirty days because everyone else does: pick the quantile you are willing to truncate at and read the window off the table.

Usage

conversion_lag(paths, probs = c(0.5, 0.75, 0.9, 0.95, 0.99, 1))

Arguments

paths

An mm_paths object from build_paths().

probs

Quantiles to report.

Value

A data frame with columns quantile and lag, in the journey table's time units, plus an attribute units naming them. Only converting journeys contribute.

See also

build_paths(), path_diagnostics()

Examples

data(mm_events)
paths <- build_paths(mm_events, id = "customer_id", channel = "channel",
                     timestamp = "timestamp", conversion = "conversion",
                     split_on = "conversion")

# 90% of journeys complete within this many days
conversion_lag(paths)
#>   quantile        lag
#> 1     0.50   4.634553
#> 2     0.75   8.957101
#> 3     0.90  14.046532
#> 4     0.95  17.427263
#> 5     0.99  29.265186
#> 6     1.00 135.453204