A 15 Year Old Analyst Running Circles Around The Rest Of Us

Those of us in the Database Marketing field are on the verge of losing our deathgrip on customer information.

As an example, take the blog Yuvisense, hosted by Yuvi, a fifteen year old in India. Recently, Yuvi decided to analyze information about uber-blogger Robert Scoble's blog. This link is the second of his posts about Scoble's blog.

Two topics come to mind.

First, who are you going to hire, the twenty-six year old who mails you a resume, touting the three years of experience at a great company, or Yuvi, the person who had the initiative at age fifteen to unabashedly share his analytical insights about a uber-blogger with the entire world, illustrating a clarity of presentation that most forty year olds cannot aspire to?

Second, pretend you are the Vice President of Database Marketing at a company like Talbots, J. Jill, Williams Sonoma, J.C. Penney, J. Crew, or any other company that starts with a J. In time, which option makes more sense?

Option #1 = Hire bright analytical minds, competing against companies like Google or Yahoo! on the basis of salary, benefits, stock options and prestige.

Option #2 = Farm out Database Marketing to Abacus or any number of competitors.

Option #3 = Make your analyses available to a throng of eager analytical bloggers, offering prize money to the individual who develops an acceptable answer, and a stipend to other individuals who invest time in the solution.

In time, I can see a world where folks like Yuvi access corporate datasets with anonymous information, creating brilliant insights and analyses that cannot possibly be matched by in-house talent. And what an interesting opportunity this presents for both businesses and individuals.

I subscribed to Yuvi's RSS feed. Let's see where Yuvi, and thousands of other bright, enterprising analytical minds take the field of Database Marketing.

Please Help Our Industry Measure Advertising Effectiveness!

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

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.

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
	Catalog	Online	Total
	Net Sales	Net Sales	Net Sales
Catalog Mailing	?	?	?
Postcard Mailing	?	?	?
E-Mail Campaign #1	?	?	?
E-Mail Campaign #2	?	?	?
Organic Sales	?	?	?

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.

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.

Friends of MineThatData

From time to time, I will be sharing commentary from individuals in the Database Marketing, Direct Marketing, and Analytics areas of the blogosphere. If your site falls into one of these three categories, you can become one of the "Friends of MineThatData".

Here is the inaugural "Friends of MineThatData", with associated BlogJuice rankings.

4.2 Occam's Razor
3.1 LunaMetrics
3.0 Juice Analytics
1.9 Rimm Kauffman Group Blog
1.2 Acxiom-Direct Blog
1.1 Enterprise Decision Management
0.9 Marketing Measurement Today
0.8 Marketing Geek
0.8 Chris Baggott's E-mail Marketing Best Practices
0.6 Sports Marketing 2.0
0.5 Digital Solid
0.5 Profitable Marketing
0.5 Rick Whittington
0.5 Power Points
0.5 Customer Experience Matrix
0.5 Sandeep Giri's Blog on Business Intelligence

If you enjoy reading other Database Marketing, Direct Marketing or Analytics websites, or want to be considered for inclusion, give me a holler.