BMGT7072 Business Intelligence Case Study

Case Study – The Complete Journey - Waitrose

For this exercise, we will use The Complete Journey shopping dataset, simulating that this belongs to the retailer Waitrose.

The company: Waitrose

Waitrose & Partners is a brand of British supermarkets with a presence all around the UK. With 329 stores across the UK, one of the main marketing strategies of Waitrose, is the use of coupons through their MyWaitrose club (see image below). The coupons are delivered to customers' households through the mail.

The Datasets

The Complete Journey provides access to datasets characterising household level transactions over one year from a group of 2,469 households who are frequent shoppers at a grocery store. It contains all of each household’s purchases, not just those from a limited number of categories. For certain households (~800), demographic information, as well as direct marketing contact history, are captured.

The dataset allows us to solve questions such as the following:

• How many customers are spending more over time? Less overtime? Describe these customers.
• Of those customers who are spending more over time, which categories are growing at a faster rate?
• Of those customers who are spending less over time, with which categories are they becoming less engaged?
• Which demographic factors (e.g. household size, presence of children, income) appear to affect customer spend? Engagement with certain categories?
• Is there evidence to suggest that direct marketing improves overall engagement?

You are free to take some of these questions in your report. However, you can go far beyond.

Data Schema

The data is divided into multiple datasets for better understanding and organisation. Please refer to the following data schema when working with it:

The Data Sets

The following datasets will be available in the Assessment section.

[1] Campaigns: campaigns received by each household

Contains identifying information for the marketing campaigns each household participated in.

[2] campaign_descriptions: campaign metadata (length of time active)

Contains campaign metadata, specifically the time a campaign was active

[3] coupons: coupon metadata (UPC code, campaign, etc.)

This table lists all the coupons sent to customers as part of a campaign, as well as the products for which each coupon is redeemable. Some coupons are redeemable for multiple products. One example is a coupon for any private label frozen vegetable. There are a large number of products where this coupon could be redeemed.

For campaign TypeA, this table provides the pool of possible coupons. Each customer participating in a Type A campaign received 16 coupons out of the pool. The 16 coupons were selected based on the customer’s prior purchase behaviour. Identifying the specific 16 coupons that each customer received is outside the scope of this database.

For campaigns Type B and Type C, all customers participating in a campaign receive all coupons pertaining to that campaign.

[4] coupon_redemptions: coupon redemptions (household, day, UPC code, campaign)

Contains individual coupon redemptions (household, day, UPC code, campaign) that can be used to measure campaign efficacy and coupon usage on specific products.

[5] demographics: household demographic data

This table contains demographic information for a portion of households. Due to the nature of the data, the demographic information is not available for all households.

[6] products: product metadata (brand, description, etc.)

Contains metadata regarding the products purchased (brand, description, etc.).

[7] promotions: a sampling of the product placement in mailers and in stores corresponding to advertising campaigns

Contains product placement information (e.g. mailer page placement and in-store display placement) corresponding to campaigns.

[8] transactions: a sampling of the products purchased by household

Contains transaction-level product purchases by households (what you would normally see on a receipt).

The variable sales_value in this table is the amount of pounds received by the retailer on the sale of the specific product, taking the coupon match and loyalty card discount into account. It is not the actual price paid by the customer. If a customer uses a coupon, the actual price paid will be less than the sales_value because the manufacturer issuing the coupon will reimburse the retailer for the amount of the coupon.

To calculate the actual product prices, use the formulas below:

• Loyalty card price = (sales_value – (retail_disc + coupon_match_disc)) / Quantity
• Non-loyalty card price = (sales_value – (coupon_match_disc)) / quantity

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