Dear Catalog CEOs: Cannibalization

Dear Catalog CEOs:

One of the most interesting aspects of marketing, unique largely to catalog and email marketing, is the concept of cannibalization.

Simply put, when you fail to market during one timeframe, you lose sales, but sales also shift into other timeframes.

Take a look at this:

The second test group did not receive a catalog in the second month.  When this happened, demand moved out of the second month, and moved into the third month.

Similarly, when catalogs are not mailed at all, customers still spend 50% of the demand they would have spent otherwise (this is known as the "organic percentage").

Look at the last row ... send 0 catalogs, get $0 of catalog-attributed demand.  Send 2 catalogs, and you don't get $12 (as one might expect), instead, you get $14.  This is a classic case of catalogs cannibalizing each other.

Twenty or more years ago, when I worked at Lands' End, we measured the living daylights out of cannibalization.  Twenty years later, you're hard-pressed to find a cataloger who understands cannibalization.

Execute a test and measure it for yourself.  You'll be fascinated by what you learn.

Want to implement cannibalization findings into your business?  Contact me (click here) for your Catalog/Email PhD Project.

#Omnichannel Future - Channel Pairs Part 2

Let's take a look at another channel pair.

Review the E-Commerce / Tablets row.  This is an interesting row, because these customers have spent more, historically, on e-commerce than on tablets.  The key with this row, of course, is what these customers do in the future.

Take a peek at the future.

• Retail = 29%.
• E-Commerce = 30%.
• Tablets = 36%.
• Mobile = 5%.

Ohhhhh, this result is absolutely delicious, isn't it?

The historical preference is e-commerce.  The future preference is a mix of retail, e-commerce, and tablets, with a skew to tablets.

This illustrates a customer that is in transition ... the customer is slowly switching from e-commerce to tablets.  This tells you that your tablet-based investments are appropriate.  Just as important, the customer spends nearly 30% of future volume in stores, telling you that you must have synergy between retail and tablets.

Next week, we'll analyze additional channel pairs.  It should be obvious to you, by now, that channel pairs help us visualize how our customers are evolving and changing, providing us with the information we need to determine future strategies.

Merchandise Forensics Project Cost

If you're wondering how a Merchandise Forensics project is configured (and you want to know what a project costs), please click here.  

The Merchandise Forensics project is the second most popular project of the spring season, and is, to be honest, exceptionally inexpensive.  Few vendors offer this service, so contact me (click here) for your own Merchandise Forensics project, before my calendar fills up.

#Omnichannel Future - Channel Pairs

If we want to understand what our omnichannel future holds, we should look at our own customer data for clues.

Many of us now categorize physical channels based on a Retail / E-Commerce / Tablets / Mobile Phone framework.  Using this framework, we can see how trends are playing out.

Take a look at the Retail / Mobile channel pair ... the fourth row in the table.  These customers spent more weighted dollars in retail than any other channel, with mobile phones in second place.

• 72% of future demand happens in retail stores.
• 10% of future demand happens in e-commerce.
• 5% of future demand happens in tablets.
• 13% of future demand happens in mobile.

In this case, the retail/mobile customer spends the vast majority of future demand in stores.  In this case, you'd say that mobile is largely supportive of the retail store experience.  Given this development, you'd build a mobile experience that is highly integrated with your store experience.

Tomorrow, we'll look at another channel pair.

Where Is My #Omnichannel Business Headed? Start With Channel Pairs

An awful lot of omnichannel experts seem to know what the future holds.

Fortunately, you don't have to listen to their guesses.  You have actual data, based on how your customers (not generic consumers) perform.

All you have to do is perform a weighted channel pair analysis.

Remember weighted channel pairs?

We sum weighted demand by physical channel ... for example, retail, e-commerce, tablets, and mobile.

• Transactions 0-12 Months Ago = Demand * 1.00.
• Transactions 13-24 Months Ago = Demand * 0.50.
• Transactions 25-36 Months Ago = Demand * 0.25.
• Transactions 37-48 Months Ago = Demand * 0.15.
• Transactions 49+ Months Ago = Demand * 0.10.

Then we rank order the pairs, based on the channels that generate the most weighted demand.

Here's an example:

• Retail 0-12 Months Ago = $100 (weighted = 100*1.00 = 100).
• Tablets 0-12 Months Ago = $40 (weighted = 40*1.00 = 40).
• E-Commerce 13-24 Months Ago = $180 (weighted = 180*0.50 = 90).

This customer possesses a Retail / E-Commerce channel pair.

Tomorrow, we'll analyze one specific channel pair.

The #Omnichannel Challenge - Forecasting Sales

Here's the challenge that nobody wants to talk about.

We know that mobile is growing, exponentially.  Some businesses (not retailers) generate 30% or more of volume via mobile.  Most businesses, especially those catering to a customer over the age of 45, generate a very small ratio of sales via mobile.

When newer channels "explode", we make an invalid assumption ... we assume that the new channel will result in an increase in total sales.

It is more likely, however, that the new channel will cannibalize existing channels.  Credit cards and 1-800 numbers eliminated the need for customers to mail checks.  E-commerce ended the call center.  And rest assured, mobile will end something.

The only question, then, is this ... "what channel will be cannibalized at the expense of mobile?"

• E-commerce.
• Retail.

Look at our example, above.  This is a reasonable forecast for a large retailer.  Omnichannel experts tell us that customers will use the retail channel as an "experience channel".  They tell us that retail will not be where sales are generated, in the future.

Ok, let's accept the premise (flawed though it may be).  In our example above, if retail sales begin to drop (see 2015 and then 2016), then we must get a dramatic increase in e-commerce + mobile sales to offset the retail drop --- or the retailer goes out of business due to retail debt obligations.

If the omnichannel experts are right, then mobile is going to explode, e-commerce growth is going to slow (causing e-commerce folks to add mobile to their totals to keep e-commerce relevant when, really, it is being replaced by mobile), and retail is going to shrink.

This will require mobile to really, really explode, in order to keep the total net sales line growing.  You have to project some really big mobile numbers to make this happen.  It will be fun to watch, no doubt.

Dear Catalog CEOs: Answers To Your Questions

Dear Catalog CEOs:

Last week, I asked you to submit questions that you wanted me to answer via a blog post.  You responded!  Let's address your questions.

Question:  How will Big Data impact my catalog business?

• There are several answers to this question.  First, you've been using Big Data for twenty years.  Co-ops are Big Data, always have been, always will be.  This means that the behavior of your competition dictates how your business evolves.  When your competitors do well, especially within certain product categories, your business is influenced as well.  Big Data, a generic information technology term, suggests that what we've observed in catalogs will now take over mobile and social, but much faster.  In other words, when catalogers / co-ops interact, the impact is almost glacial.  When data providers harvest social/mobile activities in real-time, your business will evolve faster.  By the way, 90% of what you hear/read about Big Data is going to be completely meaningless.  Look for depth of meaning in what you read.  Finally, look for actionable information ... just because your customer is within 1.0 miles of your retail store doesn't mean the customer wants a 10% off notification to visit your store.

Question:  Do I have to worry about Amazon?

• The answer, quite honestly, is that we had to worry about Amazon from 2000 - 2005.  We largely ignored Amazon during this timeframe.  Now, it's almost too late to "worry". I want you to think about something for a moment.  You ask me how you should calibrate free shipping offers (hurdle, no hurdle, channel-specific, with or without a percentage off).  Amazon gets customers to pay $79 (or whatever the number is) for shipping a year in advance of any possible purchase.  You are trying to figure out how to give shipping away.  Amazon has figured out how to charge the customer for shipping before purchases have ever been placed.  It's time to pick another fight.  I know, this isn't the easy, tidy answer you were looking for, but there are many ways to attack giants.

Question:  Can I sell merchandise that isn't featured in my catalog?

• You bet!  Go analyze your mail/holdout tests.  You execute mail/holdout tests, right?  Right?!  Analyze items featured in catalogs, comparing mail/holdout performance.  Then analyze items that only appeared online during that timeframe, comparing mail/holdout performance.  Many of my clients find that between 10% and 40% of incremental demand comes from items that did not appear in catalogs.  The job of the catalog, in 2013, is to stimulate purchasing, and to tell a story.  Your job is to find items that stimulate purchasing, and to find items that tell a story.

Question:  What benefits do you get when you re-purpose offline marketing on tablets?

• This is a multi-step process, and the process benefits the employee and the company.  From an employee standpoint, do you remember 1996 - 2000?  This was a time when e-commerce accounted for almost nothing.  And yet, those working in e-commerce put in 10,000 hours.  This became an insurmountable experience difference between 2001 - 2005, when the e-commerce folks took all the good jobs at catalog companies.  Employees need to test channels like tablet commerce.  If the channel ever takes off, the employee is the subject matter expert.  In our modern economy, you MUST be the subject matter expert at something.  From a company standpoint, the current iteration of tablet commerce is not going to last, regardless what your printer or vendor tells you.  Somebody is going to figure out HOW to sell on a tablet at scale (i.e 10% or more of annual sales).  The form (current website, tablet website, mobile website, app aggregators like CoffeeTable and Catalog Spree) will be decided by the customer.  You can wait until the battles have been decided, or you can jump in with low risk and use analytics to learn as much as you can about how customers interact with a hybrid of your catalogs and technology.  Go learn something!  Go learn something that might be applicable to other channels.

Question:  What is the appropriate email contact frequency?

• The individual asking this question links us to this article (click here).  Here's the thing.  Out of 100 projects, I can't think of 10 where somebody told me that they've tested email marketing frequency and know the optimal number of email messages to send to customers, on a weekly basis.  When I apply my findings, it is common to learn that a business under-mails - it sends one campaign a week when it could send three a week.  Of course, there's a law of diminishing returns here ... $0.20 for the first campaign, $0.10 for the second, $0.06 for the third ... but why not get the additional $0.16?  But make that decision after doing a few tests ... it only takes a month and you'll have the answer.  And if critics get upset, test for a year and satisfy them, why the heck not?
• Here's another way to think about this ... folks will tell you that you can't have opt-outs. Let's assume that you go from one campaign a week at $0.20 each, to three campaigns a week at $0.12 each.  You've increased demand from $0.20 a week to $0.36 a week ... or by 80%.  Eighty percent!  This means that if you lost more than half of your email file, you'd still generate more sales at 3x contacts a week.  Just do the math, folks.  Do the math!

Question:  How do I perform a square inch analysis in the age of the internet?

• You don't.  That train left the station in 2005.  Perform a quarterly profit and loss statement by item, factoring in all advertising channels and marketing spend.

Question:  How does the omnichannel movement impact catalogers?

• The omnichannel movement is going in two opposite directions.  First, retailers are going to encourage omnichannel as a way to drive customers into stores.  Long-term, retailers may have challenges (high debt + tepid sales = low profit), so they will leverage every possible channel (hint - mobile + social + big data) to push customers into stores.  That's the first half of the movement.  The second half of the movement comes from online marketers that now realize just how little customer behavior they've actually measured in the past decade.  Their omnichannel objective is to align strategy across channels (like catalogs & retailers a decade ago in the multichannel movement), and then measure every single customer breadcrumb.  They're going to learn that 95% of the breadcrumbs are stale, and useless!
• From a data standpoint, omnichannel will impact Jasmine more than anybody.
• For Judy, omnichannel is likely to have little meaning.  Judy, at age 60, isn't going to be using six digital devices before buying in-store after receiving a relevant email marketing message.
• In other words, omnichannel is the e-commerce / digital version of multichannel, and is more likely to impact Jasmine, not Judy ... and therefore, be of less importance to catalogers who already integrated operations and creative.
• That being said - ask good questions.  Did your business explode when you aligned channels?  Not many did.  Keep an eye on those who claim to be making omnichannel progress, and ask them to validate results via sales/profit data.

Barnes and Noble: #Omnichannel Struggles

Have you had a chance to read through the most recent 10-Q for Barnes & Noble?  Click here to take a peek.

Barnes and Noble continue to generate a loss - and according to the profit and loss statement, the loss is in the Nook division.

We hear an awful lot about omnichannel, especially from the retail side of the spectrum.  We're told that we have to do the following (at minimum):

• Align inventory across channels.
• Align creative strategy across channels.
• Same promotions in all channels.
• Price parity, where reasonable, across all channels.
• Be everywhere your customer is by participating in an explosion of channels.

If businesses do this, then omnichannel experts suggest that profit should be robust - because the business is meeting the needs of the customer.

Does Barnes and Noble meet the needs of the omnichannel customer?  Absolutely!

• Inventory available via Nook (digital), e-commerce, or in-store.  How do you beat that?
• Digital device (Nook), or available on iOS and Android devices via an app.  How do you beat that?
• Similar book-based merchandise assortment to the competition (Amazon).

And yet, Barnes and Noble struggles to generate a profit.  The Nook division appears to be losing hundreds of millions of dollars, and it appears that sales of the Nook device are in decline ... content was +6.8% last quarter.

If omnichannel strategies are so critical to success, then wouldn't Barnes and Noble, with retail, e-commerce, and digital (Nook) have an enormous advantage over Amazon, which doesn't have the bricks 'n mortar advantage?

You can't blame the failure on merchandise (same merchandise as Amazon).

Why does an omnichannel strategy, one that should guarantee success for Barnes and Noble, lead to the opposite outcome?

Discuss.  And discuss what this truly means for the validity of omnichannel strategies.

Facebook Likes, Size of Business, Age of Online Customer

I follow nineteen publicly traded retail / catalog / department store / online brands that sell apparel.  Via Quantcast, I can estimate the average age of a website visitor.  Via Facebook, I can quantify the number of likes.  Via the SEC, I can measure annual net sales.

This allows me to develop a relationship between Facebook likes, annual sales, and Quantcast estimates of customer age.

• Facebook Likes = Constant + (X1) * (Annual Net Sales) + (X2) * (Average Quantcast Age).

This simple relationship accounted for 52% of the variability in the dataset I track.

Here are a few tidbits from the model.

• Each incremental billion in net sales add 266,000 Facebook likes.
• Each additional year of average age of customer reduces Facebook likes by 345,000.
• Both annual sales and likes are statistically significant at a 0.07 level, on just 19 observations.

The age factor is important.  Let's pretend we're analyzing a five billion dollar business.

• Average Customer Age of 30 = 8.3 million predicted likes.
• Average Customer Age of 40 = 4.8 million predicted likes.
• Average Customer Age of 50 = 1.4 million predicted likes.

I get a lot of requests for what I'd call "social media viability".  In other words, the business owner asks if she can grow sales by 10% per year by shifting marketing focus to social media.

I have a simple answer to that question.

• If your customer is 35 or younger, social media isn't a marketing tactic, it must be part of the fabric of your brand experience.
• If your customer is 55 or older, social media is meaningless.

I know, the social media elite will reject these findings, citing research articles published in trade journals.

But if you're one of my catalog clients, the findings are relevant.  If you want to grow via social media, it is going to be terribly hard to do so when your customers are acquired via co-ops that spin you 55+ age customers.  And if you do succeed, somehow, in social, your customers will be younger, and will likely reject your catalog.

Honest #Omnichannel Assessment From Internet Retailer

Give this little ditty from Jack Love at Internet Retailer a read.

• The Flaw In Omnichannel Retailing.

Key Takeaways:

• He cites growth rates, showing that e-commerce grows faster at pure plays than at retail brands.  I see this in my work, too.
• Stock prices are tepid.
• Comp store sales have to be lousy, and are then masked by e-commerce growth rates to report overall totals that sound impressive but truly aren't.  I see this in my work, too.

I've worked on more than 100 projects in the past six years.  When you force e-commerce (and now mobile/social) to be a slave to retail, you do get an omnichannel outcome.  And that's ok.  But you don't achieve the potential of e-commerce (and now mobile).

We need more people to speak the truth.  Just analyze the numbers, the proof is in the pudding.

And I know, most of you will think I'm wrong, here.  You'll quote something from Forrester or Gartner or Shop.org, where 1,143 likely shoppers were surveyed and 43 executives were cited.  You'll show me how "everybody" is talking about omnichannel, so it has to be the right way for retailers to go.

You can help me.  Find non-survey research that shows how a business like Macy's, after subtracting the impact of merchandise strategy and marketing strategy, grew by 10% solely due to multichannel / omnichannel strategies.  Find this information, and I'll happily publish it here on this blog, and I will cite you as well.

What Are You Doing April 4?

Are you located in Eastern Ohio, Southern Pennsylvania, or Maryland?  Do you have a free hour during the afternoon of April 4?

I'll be passing through that general area on April 4 ... so I will have time for a meeting, first-come, first served, with catalogers, e-commerce brands, retailers, or other commerce organizations.

Click here to contact me via e-mail.

Thanks,
Kevin

Each Channel Has A Unique Merchandise Profile

Hopefully, your analytics team run merchandise reports that illustrate best selling items by marketing channel.

Your analytics team run these reports, don't they?  If they don't, click here and have me do it for you.  

I create an index for each marketing channel.

• Index = (Item Demand Within Channel / Total Demand Within Channel) / (Item Demand Overall / Total Demand Overall).

This merchandise index tells me the items that sell best within a channel, after standardizing for overall merchandise performance.  For example, an index of 2.0 tells me that the item sells twice as well within a channel as it sells overall.  An index of 0.5 tells me that the item sells half as well within a channel as it sells overall.

Why perform this analysis?

Simple.  Each marketing channel attracts a somewhat different mix of customers, and those customers have unique preferences that are different than the overall merchandise preference of your average customer.

In the image above, we clearly see that the items that sold best over the telephone to catalog customers performed worst among customers buying from email marketing campaigns.  In other words, the customer who buys over the telephone is looking for fundamentally different merchandise than the customer who buys from an email marketing campaign.

Now, I can already hear the critics screaming from all corners of the Twitter world ... "yeah, but you offered different merchandise in email campaigns, and that drove the result."

Ok.

Let's look at another graph ... this one compares phone/catalog demand with online/search demand, at an item level.

Notice that the outcome is similar?  For the most part, the items that sold best in search are different than the items that sold best in catalogs over the telephone.  Search is driven by catalogs and by customer questions (for many of my clients, half of search volume is catalog driven, a quarter is email driven, and a quarter is customer driven).

We simply have to measure the performance of merchandise by channel, especially now that some businesses are generating 25% to 40% of demand via mobile devices.  The merchandise customers by within channels are different - yes, go analyze your own business and you'll learn the same thing - go create the index I outlined above!

Furthermore, the customers who use different channels are in different demographic cohorts.  Judy buying from a catalog over the phone is fundamentally different than Jasmine buying from a mobile device.

This is important.

1. The merchandise purchased in each channel is fundamentally different.
2. The demographics of customers buying in each channel are fundamentally different.

Therefore, if you are a cataloger and you want to see what the future of your business looks like, analyze the merchandise purchased by Jennifer in email and search.

If you are an e-commerce brand or retailer, and you want to see what the future of your business looks like, analyze the merchandise purchased by Jasmine on mobile devices.

In fact, analyze the top 200 best selling items, creating an index by channel.  On the wall of a conference room, post the items ... on the left side of the room, post the items preferred by Judy ... on the back of the room, post the items preferred by Jennifer ... on the right side of the room, post the items preferred by Jasmine.  Bring your creative team into the room, bring your merchandising team into the room.  Ask each team what they see.

Then it's time to make a decision.  Who do you want your customer to be in the future ... Judy, Jennifer, or Jasmine?  Once you pick your customer, look at the merchandise that your customer prefers, and look at the creative presentation of the merchandise your chosen customer prefers.  You now have a merchandise/creative road map into the future.

I recently performed this analysis for a business.

• Judy = "Feel younger".
• Jennifer = "Hard to find merchandise".
• Jasmine = "Popular favorites at a low cost".

Same business, mind you ... but the themes in the creative were different.  Pick your creative, pick your merchandise, and you end up picking the customer you want.

It's an important analysis.  Go perform it - or email me and have me do it for you.

ExactTarget

Let's look at the 10-K statement of ExactTarget, a brand many of you utilize for digital marketing execution.

As you already know, this is one of many vendors that strongly encourage you to utilize digital, cross-channel (omnichannel) tactics to grow your business.  This is interesting, of course, because ExactTarget tells us on page four that the market for digital solutions is large and underserved, causing ExactTarget to attempt to attract new clients by growing their sales force.

This is a consistent theme, folks, when reading vendor statements (recall, we talked about this when reviewing Forrester Research).  Vendors tell us we must grow our digital footprint ... then the same vendors communicate to Wall St. that they will grow via an analog sales force.  Pay attention to what vendors tell you to do to grow, and pay attention to what vendors actually do to grow themselves.  There is a disconnect, and we should question the disconnect.

In fact, here's a direct quote from the 10-K:

• We believe our team is the largest sales organization devoted to selling digital marketing SaaS solutions, with more than 400 sales professionals located on four continents. Our field sales team sells into the enterprise market, while our inside sales team sells to small and medium-sized organizations primarily via telesales.

Again, vendors are telling us to grow, digitally.  And then, vendors do the opposite.  Do vendors tell us to sell via telesales?  Telesales!!

This is not meant to criticize ExactTarget.  They're growing by 40%, each of the past three years.  It's obvious analog sales techniques work!

Here's another tidbit.

• 290 research and development employees.
• 400+ sales professionals.

ExactTarget employs more sales professionals than folks who create digital marketing solutions.  Ponder that one for a moment, when vendors tell you that you must be digital or you'll be dead.

From page 16.

• If cross-channel, digital marketing SaaS solutions are not widely adopted, or the market for such SaaS solutions does not develop as we expect, our business, growth prospects and financial condition would be adversely affected.

They're telling you, flat out, that if you don't embrace what they're selling, their financial condition would be adversely affected.  Keep this in mind when you read about vendors telling you that you must become digital or die --- what they're saying is if you don't embrace digital, they may die!

You might appreciate the five year sales and profit trajectory.

• 2012 Sales = $292.3 million ... EBT = ($21.0) million.
• 2011 Sales = $207.4 million ... EBT = ($24.6) million.
• 2010 Sales = $134.3 million ... EBT = ($18.2) million.
• 2009 Sales = $95.4 million ... EBT = ($2.8) million.
• 2008 Sales = $72.3 million ... EBT = $6.5 million.

To be fair, they have plenty of cash.  And they spend considerable time showing that Adjusted EBITDA is positive.

We keep reading how we must be digital, or we're in trouble.  Carefully parse what the vendor community tells you about how they grow.  ExactTarget is growing via an analog sales force.  ExactTarget employs more sales employees than research/development staffers.  Their growth strategies, in many ways, contradict the growth strategies they sell to us.

P.S.:  The phrase "omnichannel" does not appear in their 10-K filing.

P.P.S:  This doesn't mean that you shouldn't go all-in with digital strategies.  This means, quite honestly, that you should do what is best for your business and your customers.  If that's digital, great.  If that's analog, great.  ExactTarget is doing what is best for them, using different marketing tactics than the ones they sell.  There's nothing wrong with that.

Groupon

Last month, Groupon canned Founder/CEO Andrew Mason (click here).

Of course, executive gossip gets all of the attention.

Have you had a chance to read through their 10-K statement?  Sure, there are problems, lots and lots of problems.  But there are things that should earn praise, too.

• 41 million customers purchased a Groupon in 2012.  Stop, and let that number sink in for a moment.  Does your business have 41 million twelve-month buyers?
• 500,000 merchants have been featured.  Again, stop, and let that number sink in for a moment.
• Mobile accounted for 37.5% of all purchases in December, 2012.  Again, stop, and let that number sink in for a moment.
• Groupon uses Television, Radio, and Billboards as part of their marketing mix.  Yes, I know, one of the digital elite, using Television, Radio, and Billboards.  You'll do those things when you learn to appreciate new customer acquisition.
• Marketing expense was reduced to 10% of net sales in Q4-2012.
• Sales force of 1,151 North American employees, and 3,526 International employees.  As we discussed with Forrester, companies selling a digital future sure seem to employ a lot of analog tactics, don't they?
• Gross Billings per Active (12-Month) Customer were $160 in 2010, $187 in 2011, and $144 in 2012.  Oh boy.
• With approximately 10,000 employees and $654 million in wages and benefits, the average Groupon employee is receiving a total compensation package that averages about $65,000 per year.
• Number of times the phrase "omnichannel" is used in the 10-K statement?  Zero.

Keep reading upcoming 10-Q and 10-K statements - pay particular attention to their ability to generate more business from existing customers - a stated goal of the management team.  It is very, very hard to get existing customers to spend more.

Dear Catalog CEOs: Input!

Dear Catalog CEOs:

A brief message today - your input is welcomed.  Send me an email message (click here please), and let me know about a blog post you'd like to see me write.  Any topic, a topic that you think would help your business and help other catalogers as well.  Pick the topic, and send me an email message.  Next week, we'll address at least one of your questions.

Thanks,
Kevin

Creative - The Hypothesis And Ramifications

This week, I presented numerous website home pages to you.  I associated the pages with the demographic that tends to shop those pages.

I conclude that there are three predominant creative presentations for our customer cohorts. This is the start of my hypothesis.

1. Judy = Merchandise-Centric Presentation Style.
2. Jennifer = Story-Centric Presentation Style.
3. Jasmine / Jadyn = Relationship-Centric Presentation Style.

These are my opinions, but I think my hypothesis surrounding the opinions is reasonable.  Businesses catering to Judy are, in many cases, businesses that pre-date the internet.  Back in 1995, it was costly to use print or television to speak to customers, so you have to present everything you possibly could present.  In catalogs, you had no choice but to feature as many skus as possible.  The legacy of this style of creative strategy lives today, as we saw with QVC's website.  Those who run businesses that cater to Judy are hard-wired to present everything.  Judy, of course, is hard-wired, having forty years of purchasing experience.  This is a co-dependent relationship.

Jennifer.  Remember, over the course of the past two years, I've shared with you that Jennifer likes to hunt for the best item at the best price with the best promotion.  So when every company offers the same merchandise at the same price with comparable promotions, we're left with almost nothing to differentiate between businesses - except for the stories businesses tell.  It's my hypothesis that we see cleaner presentations and stories because we have to differentiate ourselves.

Jasmine / Jadyn:  The world changes once we get to the under 35 cohorts.  With Judy, businesses tell her exactly what to buy.  With Jennifer, businesses tell her a story about why she should buy. With Jasmine / Jadyn, the story is shared.  Businesses tell Jasmine / Jadyn what to buy through stories, then ask Jasmine / Jadyn to provide feedback on the story, to help shape the story.  This is a shift in tone.  The co-creation that happens here results in a lot of data being exchanged between parties.

Data sharing is different across the generations.

• Judy = Shared via co-ops and database providers.
• Jennifer = Shared via Google and Microsoft.
• Jasmine / Jadyn = Shared via Social and Mobile.

With Jasmine / Jadyn, data becomes integrated with the creative presentation.  This is new, different, interesting, and maybe a bit frightening.  But we have to know this, if we want to have a relationship with Jasmine / Jadyn.

My hypothesis, then, is as follows.

• Judy requires a merchandise-centric presentation.
• Jennifer requires a story-centric presentation.
• Jasmine / Jadyn requires a relationship-centric presentation.
• The style of presentation attracts or repels customers across generational cohorts.
• When we repel various customers, we attract others, and as a consequence, we optimize our creative treatment among those who stick around and buy merchandise.  This is called "hyper-optimization".
• When we "hyper-optimize", we make it very difficult to shift from selling from one generation to another generation.

There are two very important ramifications to my hypothesis.

1. If we shift to tactics that are required of younger generations, we repel our core customer, causing us short-term pain.
2. If we fail to shift tactics, over time, we repel younger customers, causing us long-term pain.

Catalogers, in particular, are trapped in both ramifications.  Anytime the cataloger tries to change, the core customer rejects the change.  The cataloger is forced to hyper-optimize, then, to appeal to the core customer, and this hyper-optimization leads to catalogers repelling younger customers, trapping the catalog brand.

If you're a catalog brand, you kind of have to make a choice, don't you?

1. Maximize the value of the core customer, following the cohort into retirement.
2. Or, create a new brand that appeals to a younger demographic, using profit obtained from the core customer to fund exploration into a creative strategy that appeals to a younger demographic.

Now, could I be wrong?  Absolutely!  Could a business catering to a 57 year old customer change, and cater to a 27 year old customer?  Absolutely!  Anything is possible.  Nobody knows what the future holds.

Ok, time for your thoughts.  Is the hypothesis right or wrong?  If it is right, how would you recommend businesses deal with the ramifications of the hypothesis?  If it is wrong, how would you modify the hypothesis to more closely align with reality?

Google Reader and Channel Dependency

If you read this blog via Google Reader (hint - that's more than half of you), then you already know that Google is killing Google Reader (click here).

This means, that in my case, without interaction, I lose about 60% of my readership.  Think about a retail store losing 60% of foot traffic, or an e-commerce brand losing 60% of visitors to a website.  Yeah, it's kind of an important thing.

You have options ... click here to see what some of your options are.  A good choice is to visit my blog (click here), and enter your email address in the Feedblitz box.  You'll get my posts each day at about 10:45pm PDT.

I've been playing with Feedly today (click here) ... it offers a newspaper-style presentation that, honestly, is pretty ... I'll need to have more images in my posts to capitalize on Feedly, and that's a good thing.  FYI, I know many of you are already switching to Feedly, I see the referring URLs popping up this morning, so thank you!

So - please, choose a new RSS reader or subscribe via email.  Gosh, what would happen if you missed my updates?  Think of the ramifications, folks ... think!

Now for the business side of this development.

Never ... ever ... ever ... become overly dependent upon one marketing channel, or source of customers.  Ever.  This is similar to a cataloger depending upon an insolvent USPS to deliver catalogs, an e-commerce brand depending upon Google for SEO, or a retailer depending upon a historically strong anchor store like Sears.

Be very careful trusting free cloud-based services for anything.

Thoughts?

Creative - Part 3

We started with QVC, a Judy-centric business.  We moved to J. Jill, a Jennifer-centric business.  Now let's look at a couple of businesses that have a different style of presentation.

Here's Pacsun:

You can rotate through several stories - here's another one.

Ok, here's the demographic story from Quantcast (click here).  Who is the customer?

1. Judy, Average Age = 60.
2. Jennifer, Average Age = 44.
3. Jasmine, Average Age = 28.
4. Jadyn, Average Age = 12.

This is somewhere between Jasmine and Jadyn, right?

Notice that we're still focusing on stories, but some of the links divert us from merchandise, to content / connection.  There's a link to the blog, or you can log in to the site via Facebook (at which time, lots of data is being shared between the brand, Facebook, and friends of the person visiting the site).

Let's look at Journey's, a decidedly Jasmine / Jadyn focused business.

Sure, it's a clean presentation - but look at what's going on here - on my first visit, they want information from me, so that they can stay in touch with me (or collect information that they can mine in a Big Data environment).  This style of relationship building is not readily apparent among most Judy-centric brands, and is found infrequently among Jennifer-centric brands.

What about Aeropostale, shifting even further to Jadyn:

This is my first visit - and again, very clean presentation, very "brand centric" and not "merchandise centric" ... but the immediate request for data, so that Aeropostale can communicate with me.  Below the fold, you find opportunities to connect via text, email, Facebook, Twitter, and YouTube.

As you migrate from Judy (merchandise-centric) to Jennifer (story-centric) to Jasmine/Jadyn (relationship centric), you see themes, don't you?

Tomorrow, we'll talk about the ramifications of these themes.

Creative - Part 2

Yesterday, we talked about the style of creative used on home pages that appeal to customers like Judy, the 60 year old catalog shopping maven.

Today, let's take a look at J. Jill - here's their home page as of March 9.

And again, let's visit Quantcast to see who the audience is (click here).  Who is the audience, on average, visiting J. Jill?

1. Judy - Average Age = 60.
2. Jennifer - Average Age = 44.
3. Jasmine - Average Age = 28.
4. Jaydn - Average Age = 12.

Ok, let's compare the creative treatment to QVC, from yesterday:

The style is evolving, no doubt about it.  I'm not saying one style converts better than another, no way.  What I am saying is that as the target customer becomes younger, the presentation style changes - we offer fewer options, we begin prioritizing the telling of stories over the presentation of merchandise.

Here's Dillard's - another Jennifer-centric business.

Again, there are three stories that Dillard's is telling (see the black circles on the bottom-left of the image).  But the overall story is clarity.  We move away from featuring the breadth of assortment, we move toward the story the business wants to communicate to us.

We'll continue tomorrow with a shift from Jennifer to Jasmine.

Creative - A Home Page Study

For decades, it's been understood that creative (how we present merchandise to a customer) is worth +/- 10% to the sales potential of a business.  We identify this fact by testing different creative treatments, then by measuring response/conversion - we know there is considerable truth to this statement.  

Notice that this style of measurement is "short-term" in nature.  In other words, the impact of creative is +/- 10% in the short term.  What is the impact, long-term?  That's something few people measure.

That's something that many people should measure.

I will offer you a hypothesis, my hypothesis:

• The creative treatment you employ has a +/- 10% impact on the short-term value of your business, and has a +/- 50% (or larger) impact on the long-term health of your business.

This is a hypothesis, because I don't have the data to prove my hypothesis.

But I do have information that is compelling.  This week, I'm going to share some of the compelling differences in creative, and associate the compelling differences with our Judy / Jennifer / Jasmine framework.

Let's start with an example.  This is the home page of QVC, as of the evening of March 8.

Which audience purchases from QVC?

1. Judy - Average Age = 60.
2. Jennifer - Average Age = 44.
3. Jasmine - Average Age = 28.
4. Jadyn - Average Age = 12.

Click here to find out if your guess is right - visit Quantcast to identify their estimate of the audience buying from QVC.

Carefully study the creative treatment used on the home page.  Look at all the "stuff" presented to Judy on this page.  Yes, there's a story here "A Clean Start", but, wow, QVC doesn't want you to leave the home page.

Here's Footsmart ... another Judy-centric business, according to Quantcast (click here).

Again, there's a theme ... but from the home page, there's a desire to get you to whatever you want, without any waste of time.

If you are +/- 60 years old, go find your favorite brand, and look at the presentation of merchandise on the home page.  You're likely to find similarities to this style of presentation. And if you look at the websites preferred by younger generations, you'll see a different style of presentation.

For instance, here's Zappos (Quantcast says Zappos is preferred by 25-54 year olds, the average, of course, would be Jennifer).

We've got four stories being shared instead of three (not that that matters much), but the presentation is a bit cleaner above the fold - and there is the focus on free shipping and free returns (which, you'll find, is frequently aligned with websites that appeal to Jennifer - take a look for yourselves).

You'll find that Judy-centric websites are drill-down focused, less story-oriented, and are more likely to increase the assortment on the home page.  As you move from Judy to Jennifer, you start to see the introduction of stories - still easy to get around, but the creative presentation is more story oriented.

Tomorrow, we'll continue our discussion.

Dear Catalog CEOs: Do Multiple Channels Yield More Orders?

Dear Catalog CEOs:

One of the popular arguments of our time is the "multichannel/omnichannel customers are more valuable" argument, trotted out with increasing frequency by vendors and trade journalists who have a vested interest in convincing us that we can seemingly grow customer frequency infinitely.

This is a graph of the average number of orders per buyer per year for a "multichannel business".  The graph starts in 2001 and goes through the end of 2012.  Think how few channels existed in 2001.  Think how many channels exist at the end of 2012.

What do you observe?  The customer places the same number of orders per year, year after year after year - regardless of the explosion of channels between 2001 and 2012.

Run the analysis for your business.

You're going to learn that your customers have a natural rhythm ... they place the same number of orders per year (within a band) ... this order rate is directly correlated with the annual repurchase rate of your twelve-month buyer file.  These numbers do not change, they are fundamentally tied to the merchandise you offer (i.e. groceries are needed weekly, gifts are needed infrequently).

When you learn that this is the way the world works, a few things become painfully obvious.

1. Unless customers buy merchandise more than 4 times a year, loyalty programs are largely futile.
2. Customers who buy more than 4 times a year touch many channels - not because of the channels you offer, but because of the purchase frequency inherent in the merchandise your offer.
3. For 70% of businesses, the main driver of future success is low-cost customer acquisition programs that are maximized.

Run the analysis for your business.

Then craft strategies that align with the natural purchase rhythm of your business - and remember, the natural purchase rhythm of your business is determined by the merchandise you offer, and the frequency with which your customer needs your merchandise.

Item Profit And Loss - By Advertising Channel

You probably already run profit and loss statements for each item in your merchandise assortment, based on the ad costs of each channel that generate sales for items ... right?

The first item was featured in catalogs, and as a result, generated more total volume that the second item.  However, the second item was popular enough to generate demand without the aid of advertising - hence, the strong online demand component of this item.

You run a profit and loss statement for each item, subtracting catalog ad cost, email ad cost (which is virtually zero), and paid search ad cost.  The second item, after subtracting ad cost, is far more profitable than the first item.

You run this table for each item in your assortment, on a quarterly basis, right?  If not, click here to contact me via email to get this table run for you.

Merchandise Survival - Productivity Bands

When you're evaluating the success of your merchandising team, be sure to create what I call "productivity bands".

For instance, you might band items as follows:

1. Annual Sales of $100,000 or Greater.
2. Annual Sales of $10,000 to $99,999.
3. Annual Sales of less than $10,000.

Then, measure the survival of items within each band.

1. $100,000+ Survival Probability = 88%.
2. $10,000 - $99,999 Survival Probability = 46%.
3. $1 - $9,999 Survival Probability = 23%.

You've got interesting information, now.

Ask your merchandising team why 12% of high-selling items were discontinued.

Ask your merchandising team why 23% of low-selling items were carried forward.

Merchandise Survival

When you introduce a new item, how long can you expect the new item to survive?

A year?

Six years?

Businesses that introduce items that survive the first year at increasing rates tend to be healthy.

Businesses that consistently increase the rate that first-year items survive to a second year tend to be healthy.

In our example, 41% of first-year items are discontinued, they fail to survive to a second year.  There are three metrics to keep track of, over time.

1. Does the first-year item survival rate increase, or decrease, over time?  Hopefully, it increases.
2. Does the number of first-year items increase, or decrease, over time?  Often, I analyze businesses that struggle to produce enough productive first-year items, and this hurts the business, long-term.
3. Does the business generate enough first-year items with high levels of productivity?  The healthiest businesses tend to observe increases over time.

Give me a holler (click here) if you'd like for me to perform a Merchandise Forensics analysis for your business.

Big Data

Maybe a quarter of the questions I get these days are about what some call "Big Data".  For a brief primer, please refer to Wikipedia's definition of Big Data (click here).

There are two distinctly unique aspects to what the pundits call "Big Data".

• Technology.
• Applications.

I won't focus on Technology.  Rest assured that large vendors will develop slutions that promise to save the world.  You'll purchase the solutions, and you'll achieve varied levels of success ... just like you've been doing since we moved from mainframes to PCs in the late 80s.

I focus on Applications.

There are at least four key Application concepts to pay attention to.  They are:

1. Complex Adaptive Systems.
2. Dirty Algorithms.
3. Hyper-Optimization.
4. Brand Interaction.

Complex Adaptive Systems (click here):  This is what we fail to understand about our world.  Things connect, and they interact with each other, often yielding unpredictable outcomes.  In the catalog world, cataloger interaction with co-ops is representative of a Complex Adaptive System.  Catalogers volunteered customers to the co-ops, co-ops used algorithms to redefine the names, and then resold the names back to catalogers.  There are many participants in this system, dependent upon each other.  Their interactions yield unpredictable and unusual results (i.e. co-ops spinning 55+ customers to catalogers, accelerating the evolution of catalogers).

Dirty Algorithms:  This is my term, and it will be the bane of our existence!  Dirty algorithms seek to maximize the profitability of a portion of a Complex Adaptive System, without understanding how the Dirty Algorithm soils the entire Complex Adaptive System.  Example?  Easy!  Credit Default Swaps and their role in the meltdown of the global economy in 2008.  When a financial institution buys insurance to "spread the risk" of an investment, the financial institution is inserting a Dirty Algorithm into the Complex Adaptive System.  In the "Big Data" world, companies will routinely insert Dirty Algorithms into Complex Adaptive Systems.  9 times out of 10, this will not be done with malice, but rather, ignorance of how Complex Adaptive Systems work.  1 time in 10, this will be an act of pure evil.  We won't know the difference, we'll just be cleaning up messes all the time.

Hyper-Optimization:  We're at least a decade in to the era of Hyper-Optimization, and thus far, the results have not been pretty.  The best example of Hyper-Optimization happens in web analytics - earnest, honest, and well-intentioned analysts seek to increase conversion rates.  They take friction out of the system, spending time, resources, and money improving conversion rates, not realizing that the actual behavior exhibited by customers does not change ... that in reality, the web analyst caused a customer who visited the website 4 times before a purchase to visit 3 times before a purchase.  When the underlying behavior does not change, we are Hyper-Optimizing ... changing an outcome that does not fundamentally change the behavior.  This happens when we measure the wrong attribute.  If the web analyst measured annual frequency and annual repurchase rates, the web analyst would not Hyper-Optimize a meaningless outcome.  Email subject lines also fall under Hyper-Optimization ... here, marketers realize that conversion rates won't increase unless 20% off plus free shipping offers are provided.  The problem in this form of Hyper-Optimization is that the email marketer only attracts discount buyers, further fueling the need for future discounts.  If this behavior continues, the email marketer is no longer engaged in Hyper-Optimization, but rather, has introduced a Dirty Algorithm into the Complex Adaptive System.  Along these lines, Cyber Monday is the most disappointing version of Hyper-Optimization, whereby online brands now offer 30% off plus free shipping to yield the best final Monday of November in history, never minding that sales are depressed in the three weeks prior to Cyber Monday to wait for the discount.  Hyper-Optimization is a direct outcome of terrible measurement practices.

Brand Interaction:  Here's where most of us enter into our relationship with Big Data.  Most of us will treat Big Data as a glorified form of Campaign Management.  In Campaign Management, actions were linear and additive.  We mail 100,000 catalogs, we get $500,000 in demand ... we send 1,000,000 email messages, we get $200,000 in demand ... we buy 10,000 clicks for $0.50 each and we get 300 orders ... Cause and effect.  This is the world most of us honed our marketing skills in, in the 1980s and 1990s, a pre-Google world.  The reality is that we've always operated in a Complex Adaptive Ecosystem (called "the economy"), but we didn't have the data to help us understand the truth.  Most of the Big Data hucksters will operate in this realm, promising real-time decisions that dramatically boost profitability.  What they'll be doing, however, is a simple transfer of demand, from one party to another.  Yes, on a macro-economic level, growth can happen.  But by and large, on the level we deal with, we're trading demand among players.  Big Data solutions providers will simply push demand back and forth between those buying (or not buying) solutions ... and in some cases, will, by accident, interject a Dirty Algorithm that will cause all sorts of problems, or will Hyper-Optimize (pushing demand out of certain windows, into others).

Your Job?  Be smart, and I mean that with all honesty.  Most Big Data solutions will sound very seductive, on a Campaign Management / Brand Interaction level.  Your job is to ask solid questions, as you try to understand how a Big Data solution interacts on a Complex Adaptive System basis.  Are you being sold a Dirty Algorithm?  Who is demand being transferred from?  Are you simply Hyper-Optimizing a situation without yielding long-term growth?  As an example, remember that every time you use Dictionary.com, more than 200 cookies are placed on your computer.  Your simple level of inquisition at Dictionary.com results in hundreds of businesses harvesting information, pushing your inferences into the Complex Adaptive System called "Marketing", with Dictionary.com obtaining profit.  Those companies will attempt to influence you via Brand Interaction, in the form of Campaign Management.  You need to learn how this impacts you as a customer, and how it impacts the company you work for.

Go beyond the hype.  Study Big Data within the context of Complex Adaptive Systems, Dirty Algorithms, Hyper-Optimization, and Brand Interactions.  You'll find that Big Data is far more interesting at this level than what you read about in trade journals.