Leon
Liu

library(CausalImpact)

# Synthetic schema:
# date, market_id, visits, treatment_market, campaign_active

impact_data <- data.frame(
  y = treated_market$visits,
  control_1 = control_market_1$visits,
  control_2 = control_market_2$visits,
  control_3 = control_market_3$visits
)

pre.period <- c(1, 84)
post.period <- c(85, 112)

impact <- CausalImpact(
  impact_data,
  pre.period,
  post.period,
  model.args = list(nseasons = 7)
)

summary(impact)
summary(impact, "report")

-- Synthetic schema:
-- user_id, event_ts, channel, campaign, converted

with ordered_touches as (
  select
    user_id,
    event_ts,
    channel,
    converted,
    row_number() over (
      partition by user_id
      order by event_ts
    ) as touch_order
  from marketing_events
  where event_ts between :lookback_start and :conversion_end
),
paths as (
  select
    user_id,
    string_agg(channel, ' > ' order by touch_order) as path,
    max(converted) as converted
  from ordered_touches
  group by user_id
)
select path, converted, count(*) as users
from paths
group by path, converted;