ATT is a large telecommunications company and they have really good data about phone calls globally.

DSO 510 Assignment 5

Problem Statement

The goal of this analytics approach is to optimize Home Depot’s sales through their coupon system. After a purchase is made at Home Depot, the receipt can contain up to 3 coupons. Given that each basket purchase cannot be tied to a customer, there is no way for Home Depot to track customer identities or purchase history. For every purchase made at Home Depot, they collect the following data:

· What products were bought in that basket

· Time of purchase

· Price of items in the basket

They are looking to leverage an analytics framework that allows them to choose the coupon combination for each basket purchase receipt that is most likely to result in recurring purchases (and subsequently, an increase in sales). I will therefore propose a strategy to accomplish this goal.

Offering the Right Coupon

I must consider the following when designing a strategy that offers a coupon that looks to optimize sales:

· The right product category

· Am I offering this person a coupon for a product or product category that they will likely purchase from the next time they visit Home Depot?

· Understanding this most promising product category is important to designing an effective solution.

· The right discount and stretch

· Based on the characterization of this basket, am I offering the right discount to this customer?

· In order to maximize sales, it is important that Home Depot offers a coupon that maximizes their revenue and offers a coupon at the higher price end of a basket’s item assortment.

· The right contextual timing

· Considering that Home Depot is mainly a hardware and tool retailer, weather and regional conditions must also be taken into consideration when offering an appropriate coupon.

· For example, it would not likely be appropriate to offer a coupon for snow chains in the summer, even though chains of another sort were included in a basket purchase.

Proposed Analytics Framework

In order to take into account that my solution offers up to 3 coupons in the right product category, the right discount, and the right timing, I propose the following analytics approach. It is comprehensive, efficient, and has a high likelihood of offering the right coupon to the right customer that they are most likely to redeem in the future.

I believe that an effective way to address this is through the use of association analysis. Association analysis (most commonly performed with the apriori algorithm) is commonly used to determine, for each item in a store, which items are most likely to be bought with that item. This would be a useful way to determine what coupons to provide a customer depending on what's in their basket: offer them coupons for products that are most commonly bought with their items. I could apply this to Home Depot Coupon Optimization as follows: 

· Step 1: Assign each item sold in Home Depot a product category

· This provides a baseline that categorizes each item but also relates items to one another through their shared product category family.

· Step 2: Build a database of items most commonly bought with each item at Home Depot from historical transaction data using association analysis (that crosses a certain lift threshold).

· For example, we have Huggies diapers as a sample item. When we run the association analysis for this item, we identify the items to be bought with these diapers that score above a lift of 2 (2 times more likely to buy the combination of items rather than just Huggies diapers alone)

· As an example, it is found that Coors Light is most commonly purchased with Huggies Diapers from the association analysis

· Do this for every item in the store and build a database that contains this information for every item. Build one such database each month to account for seasonality.

· Step 3: Now we look at how this system runs in real time during a basket purchase. After all items in a basket are scanned, sort them by descending price and look to the most expensive item in the basket to see what items are commonly bought with that item from the database.

· For example, from a sample basket purchase, the most expensive item is Huggies diapers, and Coors Light is most commonly bought with that

· (I start with the most expensive item in order to maximize sales and offer coupons for items in the higher end of the basket's price range, with the assumption that commonly bought items with more expensive could be higher in cost)

· Step 4: If an item on that list is not already in the basket, offer a coupon for that item (or a coupon most closely related to that item in the case there is no coupon for that specific item) and continue until all items in the list have been exhausted for that item

· If a customer didn't already purchase Coors Light, offer a coupon out of all of Home Depot’s available coupons that most closely matches to Coors Light

· Step 5: Keep iterating to the next item by descending price and perform the same analysis until up to 3 coupons have been printed on the receipt

· Step 6: In the case that all suggested items from the database have been bought, offer coupons from the most likely to purchase product category

Summary

I argue that the proposed solution will be both feasible and effective in helping Home Depot to increase their sales, but it will result in the right coupons being printed to increase sales for the following reasons:

· The right product category: It is comprehensive in determining the correct product category from which to offer coupons (covers all product categories and discovers trends in commonly bought items that may not be obvious). In addition, association analysis has the potential to offer coupons for items bought both frequently and unexpectedly.

· The right discount and stretch: It also uses price range order as a priority to offer coupons with just the right discount and stretch for that basket to increase sales.

· The right contextual timing: It accounts for seasonality by building separate association databases for different seasons of the year; this way, seasonal items and purchase combinations will also be accounted for in each month’s association analysis

Therefore, this strategy would be effective for Home Depot to be able to optimize their coupon system with the ultimate goal of increasing future sales.