Thomas Friedman On Cataloging

"... our bailout of Detroit will be remembered as the equivalent of pouring billions of dollars of taxpayer money into the mail-order-catalogue business on the eve of the birth of eBay".

Thomas L. Friedman. NY Times Op-Ed Piece "While Detroit Slept", December 9, 2008.

Our government will toss Detroit billions. Yet our government hammered us in 2007 by dramatically increasing postage (the opposite of a bailout).

It's funny ... nobody cares when the Circulation Manager at Red Envelope loses a job ... no bailout for this poor sap. And our industry stands up to our responsibility ... heck, many of us partner with a business that is just plain mean and condescending to us publicly. We're taking catalogs out of the mail at a rapid rate (take that USPS), moving our businesses online. We're evolving. We don't need no stinkin' bailout!

Lost Your Job? Worried About Your Job? Co-Workers Lost Their Job?

If you've recently lost your job, had to let people go due to the economy, or survived while co-workers were let go, please leave an anonymous comment (or privately e-mail me), offering the following information:

• Job titles of the positions that were eliminated. I'm looking for the job titles and stories from individuals who follow this blog, including Executive Management, Catalog Circulation, E-Mail Marketing, Online Marketing, Web Analytics, Business Intelligence, SAS/SPSS Programmer, Statistician, Social Media.
  

• Any information you wish to share regarding the circumstances of the job eliminations.
  

• What type of job/company/geography are you looking for? Maybe there is a way that the MineThatData community can help, or I can help?
  

I'm considering a study of the job reductions caused by "The Great Implosion" (named because this seems worse than a recession and better than a depression), so any help you can offer would be appreciated.

Given that a third of recent visitors are coming from Twitter and Facebook, let's demonstrate the power of social networks by spreading the word (here's the post URL), and see if we can all learn something about job loss during The Great Implosion. If we get a good response, I will publish comments, e-mails, and findings in a separate series of posts.

An Open Letter To The Web Analytics Community

Dear Web Analytics Experts:

I have a soft spot in my heart for you, given that your skills are more technical than the average marketer, more practical than the average IT staffer, and more focused than the typical database marketer / SAS programmer.

But I need your help.

My clients are looking for a thorough, comprehensive analysis of customer behavior. And they don't always feel like web analytics provides this view of customer behavior for them. Since the vast majority of my clients don't have a SAS programmer to help integrate data like the big companies have, they heavily depend upon the web analytics expert for support. These folks need you to give them accurate answers. They don't feel like they are getting accurate answers.

Let me give you an example.

One client felt that shopping cart abandonment was a major problem. The VCBs (vendors / consultants / bloggers) suggested that their business would dramatically improve if they made key changes to the website. With a 3% conversion rate and a 40% shopping cart abandonment rate as measured by the web analytics expert, the VCBs appeared to have a case.

When the SAS programmer combined site visits over the course of a month, a very different story appeared. It turns out that the same customer visited the website multiple times per month. The monthly conversion rate was actually twenty percent (20%), not the 3% rate with 40% abandonment that the VCBs clobbered leadership about.

This doesn't mean that there isn't improvement that can be offered by the VCBs, because they certainly can help.

What this does mean is that the web analytics expert failed to provide a realistic view of customer behavior. The web analytics expert used the software given to her, and the database structure offered by the web analytics vendor, to do the best job she could do.

In order for the web analytics community to move from a valued team member to a trusted advisor, change has to happen in the industry.

• Web Analytics vendors can better integrate with offline systems, providing better data integration across channels. The big web analytics vendors are already doing this --- one major web analytics vendor called me numerous times, picked my brain for data integration ideas, then launched a product without attribution or payment. I won't make that mistake again.

• Your company may not want to pay one of the big web analytics vendors to integrate data. This puts the responsibility on your shoulders. You will have to work to integrate data, either partnering with your SAS/SPSS expert, our BI expert, or a savvy IT staffer willing to help.

• You will have to provide a vision for where this goes. This means you will transform yourself from being the person who tells a merchant that customers had a 4.7% conversion rate on her landing page to being the person who makes a business case for a $500,000 data integration project. You will have to become good at calculating profit. You will have to become good at convincing management why your vision is important --- how will the executive benefit from your vision?

• You will have to become political. Yup, this sounds hokey. Being political does not mean you're going to suck up to executives, driving their children to daycare. Being political means that you'll get to know your executives. You'll learn what they need. And then you will craft a story that blends their challenges with your vision, providing a compelling narrative that the executive takes on as her own vision.

• Part of this learning process will include understanding all channels. I repeatedly run into bright web analytics individuals who have not been given the opportunity to integrate with other staffers in the company. The web analytics expert in 2009 will actively learn about all channels, and will get to know people who are "not like us". And the web analytics expert will take this responsibility upon herself, not waiting for her boss to provide the experience for her.
  

• You will create your own data marts. The SAS/SPSS experts have been doing this for decades. If something doesn't exist, the SAS/SPSS experts "make it happen". They get no credit for this, and they get blasted by the IT people when it all has to be integrated together, but they come up with answers. You need to inherit this process. Think what you could do if you created your own data mart of social media activity across your customer base?

• You will stop doing what Google tells you to do. Many companies cannot afford tools from the big vendors, so they work with Google Analytics. An entire generation of web analytics experts are being trained by Google to analyze business exactly the way Google wants your business to be analyzed. You will migrate beyond Google in the upcoming year. You will start looking at your business the way your CEO or CMO wants to look at the business.
  

To quote a former Presidential candidate, "my friends", you have a huge opportunity in front of you in 2009. I strongly believe that ownership of customer understanding is yours for the taking. The BI folks, who aren't as good as the SAS/SPSS or Web Analytics folks at analyzing data (but are really good at organizing data), are actively working to integrate corporate data for you. Once they accomplish this, they will take ownership of your area of responsibility.

I think you are ready to take ownership of corporate analytics. Always remember that the secret to your success is not in the area of KPIs or measurement. Your success is tied into your ability to link together all data within the company, to be able to tell a compelling story, and to be able to have executives trust you enough to make key business decisions based on your recommendations.

Thanks,
Kevin
kevinh@minethatdata.com

Consulting Project Focus Is Changing

The Multichannel Forensics projects you're asking me to work on have taken a turn.

Two years ago, you asked me to explain how customers interacted with channels.

One year ago, you asked me to explain how customers interacted with both channels and merchandise divisions, with an eye toward forecasting the future.

Then you saw what the future held, and it wasn't pretty.

Today, you ask me to use Multichannel Forensics to identify customers who will keep purchasing if advertising is significantly reduced.

The framework isn't significantly different than Multichannel Forensics projects from a few year ago. I still measure how customers interact with products, brands, and channels. And I still forecast the long-term trajectory of your business by product, brand or channel.

The mechanics of the project, however, have changed. We use whatever data is available to understand how customers move along the continuum above --- organic, social, algorithm, advertising, and begging. We attempt to identify where the customer resides on this continuum.

Customers who respond to begging (discounts, promotions, free-shipping, GWPs) are at the bottom of the ladder. We'll need to market to them, and we'll need to give them a reason to purchase. These may be profitable customers, but we'll have to work hard at creating gimmicks to encourage them to purchase. This is the realm of the marketer, especially in Fall 2008. In so many ways, we ruined e-commerce with our obsession of begging customers to purchase.

Traditional direct marketing focused on customers who respond to advertising. This is a segment of the customer file that is decreasing in size. We look for attributes that suggest a customer must be advertised to, in order to purchase. Customers who order over the telephone, customers who give catalog key-codes when shopping online, customers who click-through e-mail campaigns, customers living in zip codes classified as "Catalog Crazies". These customers are unlikely to buy in the future unless they are marketed to.

Then we have customers who use algorithms to purchase. Yup, these are the customers who use tools like paid search to purchase merchandise. These customers are different. They don't always respond to future advertising, and when they do respond, they combine advertising and algorithms to make decisions. This is where your Net Google Score comes into play. Catalog brands really struggle with algorithm customers, and online marketers struggle with e-mail marketing programs for algorithm customers.

Increasingly, we find ourselves managing social customers. If you're Crutchfield, you have customers who buy merchandise, customers who write reviews, and customers who are referred from blogs to your site. The latter two groups represent "social customers". Social customers are different than are typical catalog customers, and are different than typical e-commerce customers. Catalogers are way behind the curve when it comes to managing social customers. In fact, almost everybody is behind the curve regarding social customers. Hint: Social customers don't necessarily embrace catalogs, and sometimes get really angry when they are stuffed in the mailbox.

Finally, we get to the most valuable customer on the planet, the organic customer! I receive a lot of criticism about my assertion that there are customers who do not need to be advertised to. Why? I don't know. Many of you think customers only buy something if they are advertised to. Amazon.com gets a lot of organic business. Now it is true that maybe Amazon sent an e-mail at one time, and you bought because customers like you purchased certain texts. But that doesn't explain the fact that you see "Outliers" discussed on a blog, so you go and buy the book on Amazon (that makes you a social customer!). Or maybe you read about the book in New York Magazine, then buy it on Amazon (that makes you an organic customer). Organic demand is the most important kind of demand to generate, because it comes without advertising cost. Retailers have thrived for centuries via organic demand. E-commerce is a hybrid of retailing (organic demand) and cataloging (advertising demand).

So how did project work change?

These days, I score customers across each of the five dimensions listed above. If the customer generates organic demand, the customer gets an "A", if not, the customer gets an "F". The same process happens for Social Customers, Algorithm Customers, Advertising Customers, and for Customers Who Respond To Begging.

Once customers are graded, we monitor migration. Does the "Begging" customer migrate to "Organic" status? If so, then discounts and promotions work! Does the "Algorithm" customer slide down to "Begging"? If so, then Google isn't doing us any favors. Is the "Advertising" customer married to advertising? If so, then we have to keep streaming the catalogs at this customer. We apply the migration patterns, understanding the long-term trajectory of your business. Finally, we identify the customers who we can stop marketing to, without a significant dip in business.

Online pureplays are using this methodology, too ... they want to understand who should receive e-mail marketing, and they want to understand how deep they should dive into paid search.

Retailers ask me to do this, so that they can identify retail shoppers who are unresponsive to direct marketing, customers who have a high organic percentage.

Catalog Choice should love this (especially given the slowdown in user growth in recent months), because the end result of the project is the discontinuation of catalog marketing to customers who no longer respond to advertising, while protecting the catalog relationship among highly responsive customers.

That, my dear readers, is a description of the type of project I am being asked to work on by online marketers, retailers, and catalog brands. And it is big-time fun!

Cost Per Customer: Free Worksheet

One of our loyal readers asked to have a spreadsheet created, one that calculated Cost per Customer and Profit per Customer.

Your wish has been granted. Please forward the following links to those in the marketing community who you feel would benefit from the content:

A link to the highly popular Cost Per New Customer and Profit Per New Customer post.

A link to the Cost Per Customer / Profit Per Customer Free Spreadsheet (in traditional Green Bay Packer green and gold ... change the cells with a gold background).


Profit Calculation:

Many of you have asked how to compute profit, specifically, how to identify the "profit factor" outlined in the spreadsheet.

The profit factor is the percentage of demand that flows-through to profit. Here's an example:

• You generate $100 of demand.
• Of the $100, the customer returns $20, leaving $80 of net sales.
• Of the $80 net sales, your cost of goods is $35, leaving $45 of gross margin.
• It costs you, on average, $11 to pick/pack/ship $100 of demand, leaving $34 of profit.
• The profit factor = ($100 - $20 - $35 - $11) / $100 = 34.0%.

In this case, 34% of demand flows-through to profit. If you generate $100 of demand, and you spend $30 of marketing to generate the demand, your efforts were profitable ($100 * 0.34 - $30).


Why Profit Per Customer?

Some of you want to know why you should use profit per customer, feeling like cost per customer is an appropriate metric --- especially among online marketers.

Web Analytics folks --- here's your chance to shine --- get the metrics in the worksheet above plugged into your web analytics software tool, and calculate profit per customer. The metric is important because you can compare this metric against long-term customer value. If you lose $10.00 generating the order, but generate $20.00 profit in the next twelve months, then you want to participate in marketing activities that lose $10.00 per customer. When you use cost per customer, you are not tracking average order value or profit --- you're still doing a good job, but you can add additional color to your analysis.

Salt Lake City

Compared to Medford, Salt Lake City is an internet hotbed.

Zip Code Forensics suggests that, east of town, you have a plethora of high-spending skiers who love to shop online.

Ok, marketers, tell me how your strategy for the customer in Medford compares with the strategy for the customer east of Salt Lake City?

Medford

I'd guess that most of you haven't been to Medford, or haven't taken that curvy two lane highway down to Crescent City.

Southern Oregon is catalog country, as illustrated by Zip Code Forensics. You're looking at dial-up internet access, folks. The only "tweets" you hear are from birds.

Social media pundits struggle here, don't they? --- the average person isn't carrying a 3G phone with fancy apps. The social media pundit would dismiss this person as being a technophobe ... even though the 3G network doesn't reach all people in this area ... in fact, the old-school network doesn't reach all residents in Southern Oregon.

Retailers can be snobby, too. You won't find $30,000 gifts from Neiman Marcus in any shopping center in Ashland. But they do sell a lot of t-shirts at the sprint car races in Medford.

You're a marketer, or you wouldn't be reading this. What is your strategy for the customer living in Southern Oregon? Or, do you just disregard this customer? Or do you treat this customer the same as you treat the customer living in Manhattan?

Your choice.