Dear Catalog CEOs: The iPad Problem

Dear Catalog CEOs:


Here's a thought that keeps coming up:

• "We really think the iPad is the future of cataloging, and yet, so few people truly use our app.  How do we get customers to use this thing?"

Here's the problem, folks.  We keep trying to encourage our "core audience" to do new and interesting things.  They don't want to do new and interesting things.

I've been talking about "Judy", "Jennifer", and "Jasmine" for weeks.  We made a choice, somewhere around 2001, to be "multichannel".  That choice sent us down a path that is difficult to reverse, now.  Our customer file, thanks to the co-ops, is disproportionately comprised of customers like Judy --- a 55+ rural shopper.  Now, be honest with yourself.  Put yourself in the head of this 59 year old customer.  What problem does your iPad app solve for this customer?  How does thumbing through the pages of a catalog on a digital device improve the experience, when this customer already has your catalog in her hand, and has enjoyed shopping that way for thirty years?

It's my opinion that Judy is not going to shop on an iPad.  If Judy represents more than half of your customer file, well, don't expect big-time iPad app success.

Let's move on to Jennifer.  She's somewhere around 43 years old, she's a part of the Google generation.  She scours the internet for the best deals, your catalog inspires her, but it inspires her to visit Google.  So, again, what problem does the iPad app solve for Jennifer?  Be honest.

This brings us to Jasmine.  Think of her as being a 27 year old mobile/social/local customer, one where the iPhone is never out of her hands.  This customer may well use your app.  Here's the problem, however ... how is she going to find out about your app?  You'll advertise your app in your catalog, you may advertise it on your website, you may even talk about it on Facebook or Twitter.  But if you are Cuddledown of Maine, for instance, you're using marketing materials tailored to a Judy/Jennifer audience to try to track down Jasmine.

The secret, of course, is to be where Jasmine is.  As catalogers, we're terrible at this, we know how to be where Judy is.

If we want iPad or app or iPhone or Android success, we're going to have to do two important things.

1. Solve a problem that a catalog and/or website can't solve.  Be honest, what problem does your app solve that isn't solved by catalogs or e-commerce?
2. We're going to have to develop a marketing plan that gets the app in front of the audience most likely to use it.  What is our marketing plan, folks?

Discuss.

Observations About Judy, Jennifer, and Jasmine

Ok, you've been hearing about Judy, Jennifer and Jasmine for close to a month.  You're going to hear about them more in the future.  My web analytics data on each persona reveals your perceptions about each individual.


In order, you prefer Jasmine first, then Judy, and Jennifer last.  If I put Jennifer in the subject line, you tune out.  This is so reflective of what we read in the trade journals and on Twitter, isn't it?  We're either told that we have to be "multichannel" ... which is ultimately a way of saying "we need to communicate with Judy", or we have mobile/social/local shoved down our throats like a garden hose hemorrhaging water.


The folks who have a passion for Jennifer have a passion for tactics, and for good reason.  Marketers speaking to Jennifer use tools like Google Analytics ... and as we all know, this tool doesn't allow us to do true customer-level research, so we never know the customer, we only know sporadic, channel-based facts about Jennifer.  Facts like the search terms she uses, the affiliates she snaps up a coupon code from, facts like her love for email marketing that results in 1 in 400 people who receive an email campaign actually buying something that generates profit.  When it comes to Jennifer, we only know tactics, we don't know the lady.  It's the great weakness of the "Jennifer Generation" of marketers/analysts.


Many of you love Judy.  I think this is because many of you can relate to her.  This is also a weakness ... many of you help run companies that cater to Judy, you are in her cohort, so you understand what motivates her.  This deep, thorough understanding limits knowledge of Jennifer, and as a result, has some catalog brands on the verge of falling off of a cliff.  Go perform a demographic analysis of your customer base.  Is your average customer 59 years old, or 64 years old?  If your customer is that old, ask yourself what you're going to do in five years when this customer is now 64-69 years old, or in ten years when your customer is 69-74 years old?


I realize that you're hoping that you'll be retired by the time your customer falls off the commerce cliff into retirement, but somebody is going to have to deal with this.  Don't put this problem off for five years, why not start trying to relate to Jennifer today?  I know, you don't have a passion for Jennifer, for this iPad-toting 43 year old professional who desperately wants to purchase with 20% off and free shipping.  You don't have a choice, folks.  Get to know Jennifer, start relating to her before it is too late.  For many catalogers, we're about to cross over into the realm where it is too late.


Your love of Jasmine is more of a curiosity than anything else.  You click on all of the links, checking out the businesses I mention ... whereas you don't click on any of Jennifer's links.  Here's where things get interesting ... the feedback stops after the links are clicked.  In other words, you want to know what Jasmine is doing, you don't necessarily want to take advantage of what Jasmine is doing.  You want to know that she likes buying a handbag for $99 on MyHabit instead of paying $399 at Nordstrom ... but you don't care about creating a business model to compete with MyHabit.  This is important, folks.  I get feedback like "but how do I get Jasmine to buy from my catalog?" or "nobody buys from social commerce" or "we can't sell something below cost" or "this audience isn't big enough to matter."  We won't get Jasmine to buy from a catalog.  And yes, almost nobody buys from social commerce today, and social commerce as defined today won't be what it will be in five years so why invest today, and I realize you can't sell below cost but maybe other companies have figured out different business models that allow them to cobble together a profit (or not), and yes, the audience isn't big enough to matter today, but it will be big enough to matter in five or ten years ... at the same time when the catalog generation retires.


So all of this is interesting, folks.  Your clicks, what you choose to look at, what you decide to focus on, dictate what you get from this series.  Your clicks suggest that you like Judy, you enjoy reading about Jasmine the most, and suggest that many of you really don't understand or have a passion for Jennifer, fueled by a focus on the tools that you use to analyze Jennifer (i.e. Google Analytics).


We end this post with an opportunity for you to share your thoughts ... what do you think of Judy, Jennifer, or Jasmine?  What resonates with you, what doesn't make sense whatsoever?  Who do you like, who don't you like?  What am I right about, what am I off base about?

The Jasmine Experience

We marketers really mess up the "Jasmine Experience", don't we?


Remember, Jasmine is a whole different shopper than we're used to.  The economy caused her to have a laser-like focus on price.  She's going to buy a handbag, but she'll pay $99 on MyHabit instead of paying $399 on Nordstrom.com.  She's going to trust what a friend says over trusting marketing messages.


So emails, flash sales, deals, Facebook, and friends comprise her preferred experience.


Let's say she buys from Cuddledown of Maine, maybe because a friend told her that the sheets are amazing.  All we see, as marketers at Cuddledown of Maine, is that this customer purchased online.  So, what do we do?

1. We send her a hotline catalog, after all, this is a "best practice" in catalog marketing, right?
2. We make sure that she receives six or seven catalogs in her first six months as a customer.
3. We push eight promotional email campaigns at her, each month, offering 20% off.

We make the mistake of treating Jasmine like Judy, don't we?

Not surprisingly, those dollars are largely wasted, causing us to say that some of these online channels "don't work".

Maybe, just maybe, we should work hard to identify this customer as "Jasmine" after the first order.  We take online data from Omniture or Coremetrics or Webtrends and append it to her customer record.  Maybe we ask her for her Twitter ID when she purchases, and then we thank her for her purchase within a day of the order.  Maybe we give her content that she can put up on her Pinterest page.

I know, you'll say that those are "dumb" ideas.  Maybe they are.  But how much dumber are they than sending a half-dozen expensive catalogs to a customer that has no interest whatsoever in purchasing via catalogs ever again?

We need to segment customers, and start treating customers differently.

• Judy is the quintessential catalog buyer.
• Jennifer is a charter member of the online marketing generation.
• Jasmine is the social commerce shopper who will make the purchasing decisions that fuel the economy from 2020 - 2029.

Calculating Jasmine

There are two things that set Jasmine apart from Jennifer.

1. Jennifer is e-commerce old-school.  She'll buy on Amazon using Amazon Prime.  Jasmine says that "if it is important, it will find me".  Her social commerce purchases are influenced by her friends.
2. Jennifer is the "multichannel attribution" shopper, using search + email + affiliates and other channels to purchase.  Jasmine loves MyHabit, and isn't going to leverage Google's empire to buy, she'll leverage Facebook.  If you see Jasmine on your site, you're likely to see an e-commerce order that doesn't appear to be attributed to any marketing activities.

Remember our weighting strategy?

• Mail Orders = Weight of 0.00.
• Telephone Orders = Weight of 0.15.
• Online Orders Matched Back to a Catalog = Weight of 0.30.
• Search Orders Matched Back to a Catalog = Weight of 0.40.
• Email Orders Matched Back to a Catalog = Weight of 0.50.
• Pure Search Orders = Weight of 0.60.
• Pure Email Orders = Weight of 0.70.
• Online Advertising Orders, No Offline Interaction = Weight of 0.75.
• Pure Online Orders = Weight of 0.80.
• Mobile, Social, Flash Sales Orders = Weight of 1.00.

Well, here's what Jasmine looks like.  She placed an order 13-24 months ago, a pure email order for $100, and then she purchased yesterday via a link from Facebook, spending $100.

Net Weighted Value = ($100 * 0.50 * 0.70 + $100 * 1.00 * 1.00) / ($100 * 0.50 + $100 * 1.00) = 0.900.

Here's our segmentation strategy:

• Judy = Value of 0.000 to 0.333.
• Jennifer = Value of 0.334 to 0.667.
• Jasmine = Value of 0.668 to 1.000.

Clearly, this is Jasmine.


If you want to make this stuff even more actionable, you link your web analytics data to this solution ... referring URL becomes very important ... skew net weighted value based on visits from Jasmine-like sites.

Tomorrow, we'll talk about what we, as marketers, do to ruin the "Jasmine Experience".

Calculating Jennifer

This Jennifer character, she's an interesting one.  Let's look at a few example of what Jennifer looks like.


Remember, I assigned the following weights by channel (your mileage may vary):

• Mail Orders = Weight of 0.00.
• Telephone Orders = Weight of 0.15.
• Online Orders Matched Back to a Catalog = Weight of 0.30.
• Search Orders Matched Back to a Catalog = Weight of 0.40.
• Email Orders Matched Back to a Catalog = Weight of 0.50.
• Pure Search Orders = Weight of 0.60.
• Pure Email Orders = Weight of 0.70.
• Online Advertising Orders, No Offline Interaction = Weight of 0.75.
• Pure Online Orders = Weight of 0.80.
• Mobile, Social, Flash Sales Orders = Weight of 1.00.

And remember, we weight historical transactions by recency ...1.00 for 0-12 month orders, 0.50 for 13-24 month orders, 0.25 for 25-36 month orders, 0.15 for 37-48 month orders, 0.10 for 49-60 month orders, and 0.05 for 61+ month orders.

So here's an example.  A customer spends $100 60 months ago via telephone, and then spends $100 today via a pure email order.

• Net Weighted Outcome = ($100 * 0.10 * 0.15 + $100 * 1.00 * 0.70) / ($100 * 0.10 + $100 *  1.00) = 0.65.

Remember, we categorize a customer based on the net weighted outcome:

• Judy = 0.000 to 0.333.
• Jennifer = 0.334 to 0.667.
• Jasmine = 0.668 to 1.000.

In this case, the customer is "Jennifer".  Her telephone purchase five years ago holds her back from being a "Jasmine", just barely.  As that transaction ages, Jennifer will become Jasmine.  Or, if she buys via email again, she'll become a Jasmine.

Here's another example:  The customer purchased online after receiving a catalog 13-24 months ago, and the customer purchased off of her iPhone yesterday.  The catalog-based transaction was $200, the iPhone purchase was $50.

• Net Weighted Outcome = (200 * 0.50 * 0.30 + 50 * 1.00 * 1.00) / (200 * 0.50 + 50 * 1.00) = 0.533.

This customer is "Jennifer" because her catalog-based transaction was four times as big as the iPhone transaction.  Again, as that catalog-based transaction ages, Jennifer is more likely to become Jasmine, especially if she purchases this way in the future.


Better yet, link your web analytics data to purchase data across channels ... account for Jennifer-like referring URLs in your weighting scheme.

I know, I know, you're going to have issues with this.  Well, you are welcome to do your own research, and come up with your own weighting scheme, I'd welcome it.  Heck, if you do it, I'll consider publishing it for all to see!

Tomorrow, we "calculate Jasmine".

Dear Catalog CEOs: Valentine's Day

Dear Catalog CEOs:


Have you bought flowers yet for your spouse/partner?


Here's the thing.  Somebody decided to create an "event", and the public complied, to the tune of billions of dollars of chocolates and flowers and jewelry and cards.


An EVP recently told me that his brand had "nothing to talk about, the customer has seen it all".


Well, if you have nothing to talk about to the customer, why should the customer even care about you?


You can build upon an existing event.


You can create an event.


Or, you can do like Fab.com does ... they have sixteen events each day.  


Sixteen events every single day!


We used to plan our lives around sixteen catalogs per year ... each email campaign indirectly supported catalog mailings.


We might have to get used to a future where we have sixteen events a day, each one targeting a different customer segment.

Calculating Judy

Recall our weighting strategy from yesterday, as it relates to channels:

• Mail Orders = Weight of 0.00.
• Telephone Orders = Weight of 0.15.
• Online Orders Matched Back to a Catalog = Weight of 0.30.
• Search Orders Matched Back to a Catalog = Weight of 0.40.
• Email Orders Matched Back to a Catalog = Weight of 0.50.
• Pure Search Orders = Weight of 0.60.
• Pure Email Orders = Weight of 0.70.
• Online Advertising Orders, No Offline Interaction = Weight of 0.75.
• Pure Online Orders = Weight of 0.80.
• Mobile, Social, Flash Sales Orders = Weight of 1.00.

We'll use this rule for categorizing customers as Judy, Jennifer, and Jasmine:

• Net Weighting of 0.000 to 0.333 = Judy.
• Net Weighting of 0.334 to 0.667 = Jennifer.
• Net Weighting of 0.667 to 1.000 = Jasmine.

Here's an example for Judy.  She placed one order in the past year, for $100, over the telephone.  Her net weighting is:

• ($100) * (1.00 for 0-12 month orders) * (0.15 for Telephone Orders) / ($100) * (1.00 for 0-12 month orders) = 0.15.  Because 0.15 is between 0.000 and 0.333, this customer is a "Judy".

Here's another example for Judy.  She spent $100 13-24 months ago via the telephone, and she spent $100 yesterday via an online order matched back to a catalog.  The order from 13-24 months ago gets a weight of 0.50, the order from 0-12 months ago gets a weight of 1.00.  The phone order gets a weight of 0.15, the online order matched back to a catalog gets a weight of 0.30.  Her net weighting is:

• ($100 * 0.50 * 0.15 + $100 * 1.00 * 0.30) / ($100 * 0.50 + $100 * 1.00) = 0.250.  Because 0.250 is between 0.000 and 0.333, this customer is a "Judy".

Get the picture?  Good!  We'll take a peek at "Calculating Jennifer" next.