Perception vs. Reality

Let's pretend that you are a $50,000,000 business.

Here's what the trade journals, bloggers, and the Twitterati tell us is happening:

• Catalogs are dead, generating $10,000,000.
• E-Mail has the best ROI, and is generating $20,000,000.
• All other online and offline channels are generating $10,000,000.
• Social Media and Mobile are burgeoning, generating $10,000,000.
• Total business = $50,000,000.

We, of course, get to see how the sausage is actually made.

• Catalogs generate $20,000,000 after matchback and incremental A/B testing.
• E-Mail generates $5,000,000 after incremental A/B testing.
• All other online and offline channels generate $24,500,000 after incremental A/B tests.
• Social Media and Mobile generate $500,000, if that.
• Total business = $50,000,000.

We frequently read comments about the power of e-mail marketing.  We're constantly bombarded by folks pummeling us with messages about the power of social media and mobile.  And yet, sales fail to validate the perception offered by the punditocracy.

When we read that somebody believes that social media drives just 12% of the volume of e-mail marketing, we might conclude that the metric sounds reasonable.  And I hate surveys and studies ... but the percentage aligns with what I see on a daily basis.

When we consider that e-mail drives so much less volume than the pundits tell us it drives, well, that tells us something about both e-mail and social, doesn't it?

Reality offers a different view of online channels, and burgeoning channels.  For some, yes, social media and mobile mean everything.  70% of my consulting revenue comes from this blog.  But in no way should an established business expect 70% of their volume to come from social media ... or 7%, or even 0.7% for that matter.  And eBay may generate a billion dollars of mobile volume (fully cannibalized from e-commerce, mind you).  But that doesn't mean you will generate half of your online volume via mobile.

We have to filter through a lot of psuedo-metrics and strongly worded opinions to get to reality.  The reality is that we have added a lot of channels in the past fifteen years, and yet, our sales are increasing at about the rate of inflation.  What does that say about all of these new channels?

Dear Catalog CEOs: The Demographic Shift

Dear Catalog CEOs:

I'll be you have already reviewed this chart from ATG, published on the Greenlane SEO blog.

Look at the "catalog" set of bars.

Now, normally, I'm not a big fan of this type of research.  I prefer actual customer purchase transactions over survey data.  But when survey/research data aligns with the purchase data I typically analyze, well, then I feel the need to share it.

So, again, look at the "catalog" set of bars.

Catalogs are an important way that the 55+ crowd learns about new products.

In my projects, the customers most likely to respond to catalogs are 55+ customers.

The average age of the baby boomer generation is 55 years old.

Specialty catalogs exploded in the 1980s, when the baby boomer generation entered a prime consumption demographic.  This generation rode the catalog wave, all the way to 2011.

I keep hearing from folks that "social media doesn't work".  Well, look at the graph.  Should social media work if your customer is 55+?

Recently, I followed two conference hashtags ... both conferences were being held at the same time.  One conference was a Web Analytics conference, hosted by Webtrends.  The other conference was the NEMOA conference, the signature conference for the catalog industry.  Each conference has roughly the same number of attendees.  You wouldn't know this from following each conference on Twitter.

• #wtengage = 2,000+ tweets.
• #nemoa = 50+ tweets.

One audience embraces social media, the other does not --- not because of a social media failure, but because of a demographic/lifestyle preference.

The multichannel experts were, unintentionally, wrong.  Really, really wrong.  There are significant generational differences in customer behavior.  Generational differences drive channel usage.  A 26 year old thinks you are destroying the planet with catalogs.  A 62 year old thinks you are destroying the planet with plastic computers and plastic cell phones that consume coal-based electricity.  The average customer doesn't use all channels ... in fact, my studies show that, outside of the top 20% of the customer file, customers readily sort themselves into the channels that fit their lifestyle.


Use the channels that are appropriate for your customer.  Be aware, however, that you cannot ride the wave of a generation forever ... every generation enters a post-spending lifestage, one that is devastating to a brand (i.e. Montgomery Wards).

Purchase the book at Amazon.com (print or Kindle), or contact me now for your own customized project (these are the most popular projects I work on).

Analytics Sunday: Forecasting

I get a lot of questions about this one.

• "What the heck is the Foreasting system?"
• "How is it different than other systems?"
• "Why is this the system you, Kevin, gravitate to?"

Every individual, knowingly or unknowingly, runs an Analytics system.  Your system, of course, represents the basis for how you approach obtaining answers to questions.

Segmentation, Optimization, and Prediction systems are predicated on finding answers to marketing questions.

The Forecasting system is predicated on finding answers to customer questions.

Do you understand the distinction?

Here's the reason I like to run a Forecasting system.  I'm working with a client last year.  The client is frustrated ... a marketing campaign in August worked great, a marketing campaign in September worked terribly.  The question from the client ... "how do we get both campaigns to work perfectly?"


In a Segmentation system, and Optimization system, and a Prediction system, you go to work, analyzing the differences between each marketing campaign.  You compare and contrast, you do a ton of work, you highlight the differences, and you work on making sure that next year, things work out better.


In a Forecasting system, you ignore the campaigns.  I know, that goes against every single thing you've been trained to do.


Here's what I did.  I froze the customer file as of 8/1.  I then measured repurchase rates from 8/1 to 9/30.  I analyzed reactivation rates among 13+ month customers.  I analyzed new customer acquisition in this sixty day period.  I compared these metrics across the past three years.


Guess what?  Repurchase rates were the same as last year.  Reactivation rates were the same as last year.  New customer acquisition counts were the same as last year.  All three metrics were better than two years ago, and better than three years ago.


In other words, the overall health of the business was fine.  Marketing campaign performance was variable.


This is a distinction that wastes a tremendous amount of time withing companies.  Under the Segmentation, Prediction, or Optimization systems, companies analyze campaigns that are inherently unstable, unpredictable, unreliable, and variable.  Significant effort is made to improve campaigns that, on average, have a +/- 30% variability rate without or without improvement.  In other words, you could have a campaign that performed 50% above plan last year, you improve the campaign by 10%, and the campaign performs at -15% to the prior year ... this isn't because the campaign performed bad, it is because of random variability.


When you measure performance over time, independent of campaign performance, you often see a different story.  You often observe consistent trends, a stable file, a file that is driven not by marketing campaigns, but by organic purchases and new customer increases.


This is the magic of the Forecasting system.  You focus efforts on pre/post periods, you ignore marketing campaigns, you extrapolate current trends into the future to see where your business is heading.


Now, I can hear the complaints, from near and from far.

• "If you figure out how to make both marketing campaigns work, your business will be twice as good, so you're better off fixing the one that doesn't work!"

I wish the world worked like this.  When viewed through the eyes of the Segmentation, Optimization, or Prediction systems, this is possible.


When viewed through the Forecast system, you realize that your customers are going to repurchase at 45% rates, purchase two times per year, and buy three items per order.  These rates, on an annual basis, seldom vary by more than +/- 10%.  

You miss the reality of your business when you focus on marketing campaigns.


That's why I have shifted, over time, from a Optimization/Prediction system, to a Forecasting system that skews a bit toward Segmentation.  I can more quickly focus an Executive team on the real reasons why a business is succeeding or failing.

Forecast Forensics + Digital Profiles: Growth And Decline

Before we get to spreadsheet-intensive simulations, let's take a quick look at how counts within each Digital Profile evolved over the past three years (click here to contact me for your customized Forecast Forensics + Digital Profile project).

The red lines represent the most valuable Digital Profiles.  The biggest growth profile is "The Future of Multi-Channel", a profile that includes significant Mobile and Social purchases.  Declines are in the older-school e-commerce and multi-channel segments.  It may well be that cannibalization is underway, given that these profiles possess comparable value.


The biggest level of growth happened in "Mobile Mavens", a mid-value Digital Profile inhabited by mobile shoppers.


Catalogs Are Dead is growing at a significant rate, recall that this is a pure e-commerce Digital Profile.  Couple this with declines in Cheap Catalog Items and Pricey Catalog Items, and we may be seeing the continued evolution of the customer base.  Also notice that Web Masters and Pricey Website Performance are in decline.  This is a customer file that is evolving in stages, away from catalog to e-commerce, then away from e-commerce to emerging channels.


This is stuff you probably want to know about your business, right?

Forecast Forensics + Digital Profiles: How Channels Fit Together

Each of our Digital Profiles are defined.  Now let's see how channels fit together (contact me if you'd like to have your own custom Forecast Forensics + Digital Profiles project).

I run a query, identifying the top three Digital Profiles that customers in each Digital Profile migrate to in the subsequent year.  This relationship yields the following relationship (click to enlarge):

Oh boy.  OH BOY!

The secrets of your business are unlocked, they are visually apparent in this image.

New customers migrate in from the upper left hand corner of the image.  Loyal customers are in the bottom right hand corner of the image.

Newbies filter into lower-value segments, like Adores Email, Pricey Website Preference, Web Masters, and Gaga For Google.  In other words, the online channel is the primary source of acquisition for this brand, with e-mail and search playing a role in acquiring new customers.

Take a look at the upper right hand corner of the image.  Here's where the "catalog" portion of this business exists ... it is almost separate from the rest of the business, isn't it?  Customers can get to this part of the business through The Future Of Multichannel profile, and customers in this quadrant can become loyal customers (Classic Multichannel).  By and large, however, the catalog portion of this business is separated a bit from the rest of the ecosystem.  Pay attention to your own business ... if you notice this within your business ecosystem, well, that says something about the future of your business, and your downstream marketing strategy, doesn't it?

There are five Digital Profiles that yield loyal customers.

• Classic Multichannel (from the catalog ecosystem).
• Search and Shopping.
• The Future of Multichannel (including mobile & social buyers).
• Email Loyalists.
• Crazy for E-commerce. 

Notice that one profile includes the catalog ecosystem, one includes the e-commerce ecosystem, one includes the e-mail ecosystem, one included just about everything, and one includes search, too.  This business can yield high-value customers from a single channel, or from multiple channels.

The Digital Profile process yields several strategic questions.

• Is the catalog ecosystem separate from the rest of the customer ecosystem because the channel is dying, because it is unique and interesting to a subset of customers, or because the brand failed to integrate it properly?
• Social customers are surprisingly mainstream, among the better portion of the customer file?  It does not look like this is a big customer acquisition channel.  What value does a social channel deliver to a brand if it is skewed to best customers?
• Mobile customers are also surprisingly mainstream.  Does this mean that e-commerce will be cannibalized or enhanced, going forward?
• Search customers seem to be linked to e-mail customers.  Does e-mail marketing cause a customer to conduct a search, and if so, does e-mail marketing actually encourage customers to shop the competition? 

Forecast Forensics + Digital Profiles: The 16 Profiles

Last week, we introduced the concept of marrying Forecast Forensics and Digital Profiles (contact me for your own customized project).  This week, we get to see what the geeky math created for us!


Let's review the attributes of each of the sixteen Digital Profiles we generated.


Digital Profile #1 = The Future Of Multi-Channel

• 2,278 households.
• $642.25 spend last year.
• $40.10 price per item.
• 39% shop via Telephone.
• 13% shop Online.
• 74% shop E-Mail.
• 27% shop via Search.
• 15% shop via Social.
• 41% shop via Mobile.
• This customer has a propensity for shopping via any channel, including Social and Mobile, representing the future of multi-channel e-commerce.

Digital Profile #2 = Classic Multi-Channel

• 4,483 households.
• $735.11 spend last year.
• $43.24 price per item.
• 87% shop via Telephone.
• 60% shop Online.
• 20% shop E-Mail.
• 1% shop via Search.
• 15% shop via Social.
• 13% shop via Mobile.
• This is the classic situation, with the customer shopping via the phone and online.

Digital Profile #3 = Mobile Mavens

• 3,344 households.
• $249.55 spend last year.
• $64.62 price per item.
• 16% shop via Telephone.
• 8% shop Online.
• 13% shop E-Mail.
• 25% shop via Search.
• 21% shop via Social.
• 67% shop via Mobile.
• This Digital Profile is most likely to shop via the Mobile channel.

Digital Profile #4 = Social Mom & Dad

• 3,309 households.
• $374.61 spend last year.
• $80.44 price per item.
• 72% shop via Telephone.
• 41% shop Online.
• 2% shop E-Mail.
• 0% shop via Search.
• 36% shop via Social.
• 10% shop via Mobile.
• This customer is most likely to shop via Social, and it turns out that nearly 3/4th of this audience also shop via Telephone, suggesting this is an older audience.

Digital Profile #5 = E-Mail Loyalists

• 5,938 households.
• $692.09 spend last year.
• $41.58 price per item.
• 0% shop via Telephone.
• 85% shop Online.
• 95% shop E-Mail.
• 18% shop via Search.
• 9% shop via Social.
• 11% shop via Mobile.
• Notice that the customer also shops online ... with none of the customers shopping via the telephone.

Digital Profile #6 = Crazy For E-Commerce

• 2,026 households.
• $719.99 spend last year.
• $39.99 price per item.
• 0% shop via Telephone.
• 100% shop Online.
• 1% shop E-Mail.
• 0% shop via Search.
• 21% shop via Social.
• 26% shop via Mobile.
• An e-commerce customer with a propensity for shopping via emerging channels.

Digital Profile #7 = Searching And Shopping

• 2,078 households.
• $582.75 spend last year.
• $70.89 price per item.
• 0% shop via Telephone.
• 93% shop Online.
• 48% shop E-Mail.
• 72% shop via Search.
• 14% shop via Social.
• 16% shop via Mobile.
• Anytime you see this distribution, you worry a little bit ... the customer is brand loyal, but may not be achieving her potential due to a propensity to shop via Search.

Digital Profile #8 = Catalogs Are Dead

• 2,629 households.
• $438.68 spend last year.
• $72.46 price per item.
• 0% shop via Telephone.
• 100% shop Online.
• 0% shop E-Mail.
• 0% shop via Search.
• 35% shop via Social.
• 39% shop via Mobile.
• This customer does not fit the catalog profile (0% via phone).  Granted, the customer could shop online via catalogs, but given the high percentages associated with Social and Mobile, it's more likely this customer is aligned with emerging channels.

Digital Profile #9 = E-Mail Plus Search

• 4,214 households.
• $272.63 spend last year.
• $34.99 price per item.
• 6% shop via Telephone.
• 0% shop Online.
• 70% shop E-Mail.
• 36% shop via Search.
• 0% shop via Social.
• 0% shop via Mobile.
• This is obviously a discount-type shopper, with a low price per item, shopping online.

Digital Profile #10 = Cheap Catalog Items

• 7,380 households.
• $243.21 spend last year.
• $37.74 price per item.
• 100% shop via Telephone.
• 10% shop Online.
• 0% shop E-Mail.
• 0% shop via Search.
• 0% shop via Social.
• 0% shop via Mobile.
• Another budget customer buying low price-point items.

Digital Profile #11 = GaGa For Google

• 6,652 households.
• $146.07 spend last year.
• $71.59 price per item.
• 3% shop via Telephone.
• 0% shop Online.
• 7% shop E-Mail.
• 94% shop via Search.
• 0% shop via Social.
• 0% shop via Mobile.
• A one-time or two-time per year buyer using Google to place the order.

Digital Profile #12 = Pricey Catalog Items

• 7,168 households.
• $142.02 spend last year.
• $74.92 price per item.
• 100% shop via Telephone.
• 2% shop Online.
• 0% shop E-Mail.
• 0% shop via Search.
• 0% shop via Social.
• 0% shop via Mobile.
• Pure catalog shopper buying expensive items.

Digital Profile #13 = Adores E-Mail

• 9,832 households.
• $152.68 spend last year.
• $37.34 price per item.
• 0% shop via Telephone.
• 28% shop Online.
• 97% shop E-Mail.
• 5% shop via Search.
• 0% shop via Social.
• 0% shop via Mobile.
• E-mail shopper who enjoys buying inexpensive items.

Digital Profile #14 = Web Masters

• 12,014 households.
• $195.17 spend last year.
• $33.66 price per item.
• 0% shop via Telephone.
• 100% shop Online.
• 0% shop E-Mail.
• 0% shop via Search.
• 0% shop via Social.
• 0% shop via Mobile.
• Online buyer who purchases inexpensive items.

Digital Profile #15 = Pricey Digital Preference

• 3,040 households.
• $184.88 spend last year.
• $71.40 price per item.
• 0% shop via Telephone.
• 44% shop Online.
• 63% shop E-Mail.
• 43% shop via Search.
• 0% shop via Social.
• 0% shop via Mobile.
• E-mail shopper who buys online and buys pricey items.

Digital Profile #16 = Pricey Website Preference

• 17,345 households.
• $130.79 spend last year.
• $74.29 price per item.
• 0% shop via Telephone.
• 100% shop Online.
• 0% shop E-Mail.
• 0% shop via Search.
• 0% shop via Social.
• 0% shop via Mobile.
• Expensive items, only purchased online.

Vera Bradley Outlet Event

The image might be hard to see, so click here to visit a web-based image of this e-mail campaign.

One way to measure the strength of your brand is to charge customers money to attend an event.

In this case, for $5.00, you get to be one of up to 24,000 individuals who are allowed to attend a Vera Bradley Outlet Sale.  Sure, you get to go for free the final three days, but as anybody knows, the good stuff is snatched up quickly, so for $5.00, you get access to the good stuff.


I'm not saying this works, or doesn't work, or that I do/don't support this.


I'm simply asking you, the marketing leader, how you might think about creating urgency in your business ... how might you foster an environment that causes somebody to feel that they have to spend $5 just to have the opportunity to participate in an event?


It's certainly the opposite of 20% off plus free shipping for Cyber Monday, isn't it?