Seasonal / holiday / promotional effects

Forecasting Product Demand in R

Aric LaBarr, Ph.D.

Senior Data Scientist, Elder Research

Influencers of Demand

Seasonal effects
- Examples: Winter coats, bathing suits, school supplies, etc.
Holiday effects
- Examples: Retail sales, holiday decorations, candy, etc.
Promotion effects
- Examples: Digital marketing, shelf optimization, etc.

Seasonal / Holiday / Promotion?

plot(M_hi)

plot(M_hi_p)

Linear Regression! Again...

Linear regression helps us evaluate the relationship between many factors and demand, not just price.
Add seasonal, holiday, and promotion effects to previous regression!
Any of these effects statistically significant?
- Are the effects due to random chance or not?

Creating Effects Example

v.dates <- as.Date(c("2014-02-09", "2015-02-08", "2016-02-07"))
valentine <- as.xts(rep(1, 3), order.by = v.dates)

dates_train <- seq(as.Date("2014-01-19"), length = 154, by = "weeks")
valentine <- merge(valentine, dates_train, fill = 0)

head(valentine, n = 5)

           valentine
2014-01-19         0
2014-01-26         0
2014-02-02         0
2014-02-09         1
2014-02-16         0

Adding Effects Example

M_hi_train <- data.frame(M_hi_train, as.vector(valentine))

model_M_hi_full <- lm(log_sales ~ log_price + valentine, 
                      data = M_hi_train)

summary(model_M_hi_full)

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  8.93102    0.44693  19.983  < 2e-16 ***
log_price   -0.70010    0.11103  -6.306    3e-09 ***
valentine    0.22942    0.07547   3.040  0.00279 ** 

Signif. codes:  0 *** 0.001 ** 0.01 * 0.05 . 0.1   1

Let's practice!

Forecasting Product Demand in R