Ex3 Café

Mail-in Rebate for an On-Line Purchase?

Now that's a bit of an oxymoron, don't ya think?

I encountered this scenario when I was looking at wireless PC cards on AT&T's website (see below). 

 

What struck me when looking at this rebate offer was why do I need to go through the hassle of printing a rebate form, gathering all of the required proof of purchase information, filling out the rebate form and mailing the form to AT&T's rebate center when I purchased the product directly from AT&T?  Isn't purchasing the product from AT&T (and having a record of this purchase in AT&T's sales transaction system) the ultimate proof that I legitimately purchased the product?  And once I go through all of these shenanigans, I have to wait 8 weeks to get my rebate card?  How come I can get the wireless PC card in about a week (or less) after ordering it on-line, but it takes 8 weeks to get the promo. card?  I understand that I may have to wait 30 days (to make sure I don't return the product) but once the 30 day return period is over, why make me wait almost another month to get the card?  I wonder if it's a coincidence that AT&T benefits financially from this seemingly unnecessary and inefficient process that is highly prone to errors.

The diagram below sums up (in my uncreative, business process analyst sort of way) this scenario:

Unless I'm missing something, here's what I would suggest to AT&T for a better customer experience when offering rebates for on-line purchases:

• At the on-line check out, have the customer check a box indicating that they would like to have the rebate promotion card mailed to the same address that the product is being shipped to. 
• If the customer wants to have the rebate card shipped to a different location, provide the means for the customer to enter an alternate shipping address.
• Once the 30 day return period has expired, send a fulfillment request to the rebate center (automatically) to have the rebate card shipped to the customer.

Of course it would be great if rebates were eliminated all together.  But if a company is going to offer rebates (especially for on-line orders) at least provide a more efficient and accurate method for customers to submit rebate claims.  Otherwise, in this increasingly on-line, real-time, automated, work flow driven world, to only provide this arcane method for submitting rebates becomes ever more suspicious.

Am I missing anything here?  Please feel free to post a comment with your input/thoughts.

P.S.  I don't mean to pick on AT&T, as I'm aware that most wireless carriers offer the same type of mail-in rebates.

Note to IBM: Please Make Data Mining Work for Mainstream Marketing This Time

With IBM's recent press release announcing a new consulting organization dedicated to advanced business analytics, I thought to myself, "I sure hope this new organization helps to incorporate advanced analytics/data mining into mainstream marketing this time around."  Because up to now, other than a few BIG exceptions (i.e. Amazon.com), the promise of integrating data analytics and marketing (in a scalable and repeatable manner) has yet to be realized.  It's quite frustrating, as data mining technologies have been around for a number of years and incorporating data mining into marketing seems like such a natural fit.  For example, customer exhibits pattern of behavior for product cross-sell opportunity so complementary product offering is dynamically presented to customer and add on sale is made.  Done.  End of story.  Not so fast.  Here's what's throwing a wrench into this seemingly straight forward scenario:

• The PhD's in machine learning and mathematics (in the Reporting and Analytics Division) and the MBA's (in Marketing) are wired completely different.  Here, the PhD's are concerned about accuracy (to the n'th degree), methodology, sample size...etc. and the marketers are concerned about "just getting the stuff out the door".
• For direct marketing, most marketers are still obsessed with list quantity versus list quality.  "You mean my list count is only 150,000, I thought it was going to be more like 2,000,000?"  In this case, if a list (generated via data mining) has a smaller count than expected, the marketer may request that the list be pulled using more traditional data selection/segmentation methods to increase the list count (completely missing the point).
• The raw data (to be mined) is never right.  So the data mining folks spend most of their time "getting the data ready to mine" versus actually mining the data.
• Very few companies have figured out how to integrate data mining and marketing execution efficiently (or at all).  As such, a lot of interesting discoveries are made, via data mining/analytics, but no direct action is taken to help generate additional sales from these discoveries.  For example, through mining its sales transaction data, an on-line retailer may have discovered that customers who purchase products in category A, are likely to purchase products from category B as well.  Unless there's a process/technology in place to alert the customer about products in category B (i.e. automated e-mail, website message...etc.) this discovery, while perhaps interesting, has limited or no monetary value.

So, with the above realities in mind, my advice to IBM (if the company wants to be successful at selling data analytics products and services to marketers) would be the following:

• Figure out a way to bridge the communication barrier between the data modelers/analysts and the marketers.
• Set expectations for senior management on the process of data mining.  Many senior executives believe the process involved with advanced data analysis and modeling is likened to the Ronco "Set It and Forget It" Rotisserie Oven.  Here the assumption is that a magical software tool is turned loose against a sea of data and (miraculously) revenue generating discoveries pop out the back end with limited or no human intervention.  Obviously there is a lot more to data analytics/modeling than this, so senior management's expectations need to be managed accordingly.
• Make sure the raw data that's being analyzed/mined is complete, accurate and structured correctly on an on-going basis.  Otherwise you will have highly skilled data modelers spending most of their time doing manual, mundane data "grunt work" instead of the work they are hired (and paid handsomely) to do.
• Educate marketers on the value of data quality versus data quantity.  Here various tests could be set up to compare the marketing ROI between segments derived via data analytics and segments derived using more traditional data selection methods. 
  NOTE:  I find that numbers speak much louder than words when it comes to proposing new marketing techniques and technologies to marketers.
• Don't focus solely on analytics and discovery.  Make sure you also provide the customer with a scalable and repeatable method to "take action" when key, revenue generating discoveries are made.  In other words, help the customer fill the gap between marketing discovery and marketing execution.

If IBM is mindful of the above recommendations, I believe this newly formed consulting organization will be highly successful at selling data analytics products and services to marketers.

P.S.  Here's an interesting video I found that helps answer the question "what is data mining?":