Customer-Analytics/Answers at master · t-varun/Customer-Analytics · GitHub

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######################################## WEEK-2 ##########################################

All answers are correct

When the managerial problem is ambiguous

Return on Investment is quite uncertain

For context-specific, at the moment surveys

All answers are correct

Cannot make causal claims

It is frequently used in social media data to quantify the valence of information

All answers are correct

Surveys

9,10


########################################### WEEK-3 ##########################################

Predicting when the customer will make her next purchase

MARS, CART

Customers are not truly random but appear to be “as if” random from an outsider observer’s perspective

Regression-like models are fine for a one-period-ahead prediction, but not beyond that horizon

Recency is the most predictive of the three

Share similar acquisition characteristics (e.g., time of acquisition)

Yoshinori would likely be more valuable

Bayesian Transformation of Yearly Data………..

Jane would likely be more valuable

All answers are possibilities


########################################### WEEK-4 ##########################################

Make a recommendation on an action that will optimize a goal

All answers are correct

The quantity of a product sold

A part of the model under the direct control of the firm && A choice that impacts the goal

Explain the relationship between actions and parameters to the goal

When the marginal cost is zero && When the marginal revenue equals marginal cost

We may give a different recommendation for different models

Discounts on a product brings more buyers now and makes buyers wait for discounts in the future

All of the above

Shows ads to people after they visited a specific website


########################################### WEEK-5 ##########################################

household-level scanner data from their home

Tracking customers across digital properties is difficult.

All of these answers apply.

Pop-up advertising

A lack of local distribution centers

Software that reads customer intonation

A customer who spends $100 per year, but has a 10% churn propensity per year.

None of these statements is always true.

Highest to lowest marketing effectiveness

All of these are correct