SYNOPSIS

In this report, we delve into the impact of discounts on sales during the holiday season, focusing on Easter, Christmas, and Valentine’s Day. Our objective is to explore growth opportunities by conducting customer segmentation and assessing purchase power to inform a potential early discount strategy before the official holiday period. We also look into the potential growth in offering good deals by learning customer behavior pattern.

Our approach involves identifying key products, determining peak purchase times, exploring associated items, quantifying total sales revenue and monthly margin. This strategic analysis aims to create a plan for effectively managing seasonal sales, translating insights into a marketing strategy that boost sales.

PACKAGE REQUIRED

The following R packages are required in order to run the code in this R project:

library(plotly)  # makes interactive, publication-quality graphs.
library(lubridate)  # functions used for working with dates and times
library(tidyverse)  # tidying data and working with other R packages
library(completejourney)  # grocery store shopping transactions data from group of 2,469 households
library(ggplot2)  # data visualization plotting system 
library(gganimate)  # Extends ggplot2 to create animated plots.
library(dplyr)  # manipulating and transforming data (i.e., filtering, joining, etc.)
library(hrbrthemes)  # Offers additional themes for ggplot2.
library(viridis)  # Provides perceptually uniform color maps for data visualization.
library(ggthemes)  # additional plotting themes, scales, and geoms for "ggplot2"

DATA PREPARATION & EXLORATORY DATA

# complete journey data
df_transactions <- completejourney::get_transactions()
df_products <- completejourney::products
df_demographics <- demographics

SUMMARY

Our objective was to intricately analyze ways in which Regork could significantly enhance sales for key holiday items. Employing a comprehensive approach that involved delving into Regork’s customer behavior and product data, along with an investigation into the impact of discounts on sales values, we sought to find relationships surrounding these pivotal holiday items. This strategic analysis is aimed at not only understanding customer interactions but also at formulating effective strategies to captivate and engage our customer base.

Through analyzing with various facets such as monthly sales and margin dynamics during three distinct holidays, targeted consumer segments, and key product categories, we have successfully discerned critical trends and customer purchasing patterns. These insights ranging from optimizing product ordering and stocking procedures before holidays to informing strategic decisions in promotion and managing coupon campaigns.

Our initial observation revolves around the monthly sales performance within the Valentine category. Notably, the peak sales occur in February, together with a discount effect introduced during that month. It’s worth noting that January, while generating sales, exhibits a negative monthly margin. This underscores the potential efficacy of implementing discounts to bolster profitability during this period.

Furthermore, we found February and March exhibit an uptick in sales for Easter, yet the application of discounts only commences in April. To optimize sales, aligning discount strategies with the increased consumer interest in February and March could prove advantageous.

However, discount strategies did not cover the full sales peak periods. Noticeably in veil of Christmas, weak triggering effect of discounts result in large volume of unsold seasonal products in Christmas month (December 2016), which were discounted 100% in January - Our observation indicates that a bundled approach, strategically aligning complementary products, could not only enhance customer engagement but also increases the sale values. By cross-referencing the top-selling items, such as candles and decor, with frequently associated products like pizza, dinner items, burritos, and lemons, we identified a significant opportunity for bundled promotions.

The overall takeaway from our analysis is to highlight the importance of strategizing early discount holiday sales and bundle strategy. We highly recommend discounting top 3 performers of Valentine category in January, starting Discount campaign for Easter holiday beginning March, focusing on top spending products, and implementing a bundle strategy focused on the popular items for Christmas.

Discuss the limitations of your analysis and how you, or someone else, could improve or build on it.

The analysis is constrained by the limited timeframe, relying solely on data from the year 2017. This temporal constraint impedes our ability to discern long-term trends or cyclical patterns that may exist over multiple years. A more comprehensive dataset spanning multiple years would provide a broader context for more robust trend analysis.

Moreover, the presence of numerous missing values within the dataset poses a significant challenge. These gaps in the data limit the accuracy and completeness of our insights.

VALENTINE

The initial insight revolves around evaluating the sales dynamics of the Valentine seasonal across all 12 months, examining the marginal fluctuations in each month relative to the average monthly level.

The second observation focuses on identifying the top 3 best sellers (Valentine Giftware/Decor, Valentine Plush, and Valentine Tray Pack Cards) that experience the highest acceleration during the peak season, with variations observed from month to month.

The third observation illustrates the impact of discounts on sales within the Valentine category.

Examining the data reveals a spike in sales starting from January but there is no discount effect.

The fourth insight is triggered by the question whether discount should be applied starting from January until February to stimulate more sales of seasonal products.

To answer the question, we are going to explore the behaviours of target customers for Valentine products. Taking a look at their demographic data, the common traits of the group is that they are married and have kids. Their age mainly fall between 35-54 and their income level are varied.

The group proves a strong purchase power accross food and beverage category and receives a large portion of discount over the total shopping cart value

EASTER

Taking a top-down approach to peak seasonal sales accross all product categories, Easter category observed a noticeably jump in sales value and volume during Easter period starting from Feb to Apr.

The second insight delves into the specific products accelerating the most during the peak season, which vary by month

The third insight concerns about the discount effect on sales for products within Easter category.

Based on the data, even though sales start to spike in Feb and Mar, discount regimes only happen in Apr. Furthermore, all the discounts are marked up by retailers, not by suppliers or coupon redemption.

The fourth insight is triggered by the question whether discount should be applied starting from February until April to stimulate more sales of seasonal products.

To answer the question, we are going to explore the behaviours of target customers for Easter products. Taking a look at their demographic data, the common traits of the group is that they are married and have kids. Their age mainly fall between 35-54 and their income level is in the lower-end of the range.

The fifth insight is backed by the rationale that lower-income households are more tempted by discount than others. We are going to track their buying pattern across other categories to see how discount affect their buying incentives. Based on our data analysis, the group also has huge purchase power accross food and beverage category and receives a large portion of discount over the total shopping cart value.

CHRISTMAS

The initial observation relates to the sales performance of the Christmas seasonal throughout the 12 months of the year, considering the marginal increase or decrease in each month compared to the monthly average level.

As we delve into the data, an intriguing insight emerges—January showcases a unique pattern where the discount effect on sales stands at an impressive 100%. This anomaly prompts us to embark on a journey to unravel the underlying dynamics of this phenomenon.

We aim to identify the top-performing products during this month and discern whether a strategic bundle products approach could enhance our sales strategy.

To capitalize on this insight and boost overall sales value, we are considering implementing a bundle strategy focused on these popular items.

Taking a step further, we delved into the products frequently bought in conjunction with candles and decor. Surprisingly, pizza, frozen dinners, burritos, and lemons emerged as the top 5 products frequently purchased together. This intriguing finding suggests an interesting customer behavior pattern.

The potential meaning behind this pattern could be that customers who purchase candles and decor are likely looking for convenience and quick meal solutions, as evidenced by the preference for items like pizza and frozen dinners. The inclusion of lemons also hints at a preference for fresh and flavorful additions to their meals.