You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Create some fake dataset with continuous non-contractual process and build a story around:
Using MMM to infer cost of acquisition across different channels
Using CLV to infer differential lifetime value of customers coming from different channels
Making business decision that takes the two sources of information into account
a. Preferring to invest in a channel with higher CAC because of higher CLV
b. Binary decision to not further invest in channel if CLV is lower than CAC
I could also see RFM Segmentation being valuable for this, because customers in different segments would benefit from different strategies, which can be tied back directly to marketing budgets and channel contributions.
Create some fake dataset with continuous non-contractual process and build a story around:
a. Preferring to invest in a channel with higher CAC because of higher CLV
b. Binary decision to not further invest in channel if CLV is lower than CAC
Requires: #24, #19, #39
We might use this case-study for the initial announcement of the package
The text was updated successfully, but these errors were encountered: