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Measuring Advertising Effectiveness - Catalog Mining Challen |
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Online/Catalog marketers (frequently called Multichannel marketers) have inherent challenges in properly allocating a purchase to the advertising tactic that truly drove the order. If a customer receives a catalog, several e-mail campaigns, and maybe additional direct mail within a short period of time, a purchase may have been caused by a combination of marketing activities, not just any one marketing activity. Posts from the past few days talk about this topic.
So, I am seeking your assistance. Download this spreadsheet with ten thousand simulated customers: MTD_Advertising_Effectiveness.xls 数据挖掘研究院
The spreadsheet has one row per customer. Each column in the spreadsheet is described here:
- Customer Number = Uniquely identifies each customer.
- Recency = Months since last purchase, grouped into segments.
- Frequency = Number of lifetime purchases, grouped into segments.
- Monetary = Average Order Size, grouped into segments.
- Receive Catalog = Yes/No indicator telling whether customer received a catalog in the past month.
- Receive Postcard = Yes/No indicator telling whether customer received a direct mail postcard promotion in the past month.
- Receive E-Mail Campaign #1 = Yes/No indicator telling whether customer received the first of two e-mail campaigns in the past month.
- Receive E-Mail Campaign #2 = Yes/No indicator telling whether customer received the second of two e-mail campaigns in the past month.
- Catalog Net Sales = Amount customer spent via the telephone channel in the past month.
- Online Net Sales = Amount customer spent via the online channel in the past month.
Here is what I would like for you to do. Analyze the dataset, and properly allocate the net sales each of the four advertising activities drove to the catalog/telephone channel and to the online channel. I provided the customer segmentation information, should you wish to control for this data. Sales that cannot be attributed to one of the methods of advertising should fall into the "organic" row in the table below. 数据挖掘实验室
When you have completed your analysis, submit a document (either MS-Word or PDF format) with your findings. Your analysis must have the following table, with the following information (your need to complete this table to have your results published):
| The MineThatData Advertising Effectiveness Challenge |
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数据挖掘实验室
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Catalog |
Online |
Total |
数据挖掘论坛
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Net Sales |
Net Sales |
Net Sales |
| Catalog Mailing |
? |
? |
? |
| Postcard Mailing |
? |
? |
? |
| E-Mail Campaign #1 |
? |
? |
? |
| E-Mail Campaign #2 |
? |
? |
? |
| Organic Sales |
? |
? |
? |
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The analysis should yield about $59,000 total catalog sales, and about $72,000 total online sales.
The goal of this project is to help marketing individuals in the online/catalog multichannel world understand how they should measure advertising effectiveness. Keep that in mind when you summarize your findings. You are speaking to a marketing executive who may not be well-versed in analytics.
I will accept entries between now and January 31, 2007. I will publish all findings, so long as the table mentioned above is completed and your write-up can be understood by a marketing executive. 数据挖掘工具
This exercise provides strong analytical individuals a good opportunity to showcase their skills. Vendors, in particular, have a great opportunity to illustrate use of their tool-set for marketing individuals who make decisions about which vendor to work with. Online/Catalog marketers have an opportunity to learn how they can improve their advertising measurements.
Please forward this post to your analytically-minded friends, and vendors who may already provide solutions to problems of this nature. Let's see if we can find a way to improve advertising measurement. I will post all completed entries in early February.
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