uam

uam combines aggregated attribution with customer journey information. It uses D_variables to map each input signal to a final channel, measure, and mandatory prior_weight. If journey paths are provided, the aggregated baseline is adjusted with path-based Markov information; otherwise, UAM returns the aggregated baseline only.

PARAMETER	TYPE	DEFAULT	DESCRIPTION
df_aggr	data.frame / table	required	Aggregated dataset containing a timestamp column, the target column, and the marketing or business signal columns used for attribution.
D_variables	data.frame / table	required	Mapping table with one row per input signal. It must contain variable, channel, measure, and prior_weight. prior_weight is the business weight assigned to each raw signal. A common way to estimate it is conversions / touchpoints or conversions / cost, but it can also be set from domain knowledge or historical benchmarks.
target	string	required	Name of the target column in df_aggr. The target must exist in df_aggr and must not be included in D_variables.
df_paths	data.frame / table	optional	Customer journey data. It can contain serialized paths or event-level journeys, depending on the columns supplied.
baseline_model	string	"linear"	Aggregated attribution engine used as UAM baseline. Allowed values are "linear", "reward", and "copula".
var_path	string	"path"	Column containing serialized journeys when aggregated path data is provided.
var_conv	string	"total_conversions"	Column containing the number of conversions associated with each path.
var_null	string	"total_null"	Column containing null-path counts when available.
channel_conv	string	"((CONV))"	Conversion marker used when df_paths is provided as event-level journey data.
max_p	integer	12	Maximum lag depth considered by the aggregated baseline.
nsim	integer	1000	Simulation parameter used by model components that require simulation, kept for API consistency.
seed	integer	1234567	Random seed used for reproducible results where random or simulation-based components are involved.
verbose	integer / bool	1	Controls runtime logging. Use 0 or False to reduce printed output.
order	integer	1	Markov model order used by the path-based component.
sep	string	">"	Path separator used inside serialized journey strings.
ncore	integer	1	Number of cores used by supported computation steps.
password	string	optional	ChannelAttributionPro license token.

Example structure for D_variables:

variable	channel	measure	prior_weight
google_clicks	google_ads	clicks	0.25
google_impressions	google_ads	impressions	0.015
facebook_impressions	facebook_ads	impressions	0.015
email_clicks	email	clicks	0.30
direct_searches	direct	searches	0.50