June 30, 2014

Homework Assignment: Restoration Hardware

You've probably heard all about the stink that Restoration Hardware generated by sending out a 3,300 page catalog that weighs a full twelve pounds. You can't avoid the criticism on Twitter, that's for sure! And the mainstream media love to cover a story that generates page views and/or ratings.

Here's your homework assignment for today.

Question: The Restoration Catalog marketing effort is allegedly carbon neutral. When you tweet your displeasure about the catalog on Twitter, you are consuming electricity. Is the electricity you use to voice your displeasure carbon neutral? If not (i.e. you are burning coal to tweet your displeasure), how do you feel about that?

Question: If this lone catalog generates more sales and more profit for Restoration Hardware than their previous catalog strategy, did the marketing strategy perform well?

Question: Would you rather receive one 3,300 page catalog per year from a company, or 33 100 page catalogs per year from a company?

Question: For those who think catalog marketing is irresponsible and a waste of ecological resources, please describe the energy source used to shop via e-commerce (or Amazon) and/or mobile? Or describe the energy source you use to drive to a retail store to purchase something? Can you demonstrate that your shopping habits are carbon neutral?

Question: If you do not like this marketing strategy, please describe a substitute tactic that Restoration Hardware could use to illustrate tens of thousands of skus available to the customer? In other words, develop an alternate marketing plan, and, demonstrate that your alternate marketing plan will cause Restoration Hardware to sell more than they sell via this catalog.

Question: Describe how you would measure the success or failure of this marketing effort? Make sure you use the phrase "holdout test" in your response.

June 29, 2014

Incremental Value

The experts are telling you that if you are not omnichannel, if you are not diving head-first into mobile, your business is "dead".

It's a bold prediction, of course, and it is not based on data.

Well, let me take that back, it's based on faulty data.

The popular line of thought suggests that when a customer purchases from an additional channel (mobile, e-commerce, retail stores, or any e-commerce-centric advertising channel like email or search), the customer instantly becomes more valuable.

The query is terribly flawed. Thought leaders analyze customers who bought from two channels, sum spend, and then compare spend to customers who bought from one channel. Of course, anytime you run a query as pathetic as that query, you're going to "prove" that customers who buy more often are more valuable than customers who purchase less often. Woo-hoo!!

Where possible, try to focus on incremental value. Let's pretend that you are an e-commerce-only brand. You probably have a segment of customers who purchased two times in the year ending December 31, 2013. Split that audience by those who purchased using a tablet/phone and purchased via desktop/laptop, and compare it to those who only purchased via desktop/laptop, and compare it to those who only purchased via tablet/phone. Then, measure average spend per customer through the first six months of 2014.
  • Desktop/Laptop Only = 30,000 customers, average future spend = $30.
  • Tablet/Phone Only = 6,000 customers, average future spend = $28.
  • Desktop/Laptop + Tablet/Phone = 3,000 customers, average future spend = $30.50.
In this query, we learn that:
  • Single Channel Buyers = (30+28)/2 = $29 future spend.
  • Multi-Channel Buyers = $30.50 future spend.
  • Incremental Value = $30.50 / $29.00 = +5.2%.
Your omnichannel initiatives, in this instance, yield a 5.2% increase among those possessing the behavior.

Since only 3,000 of 39,000 customers possessed this behavior, we can calculate the incremental benefit to the business:  5.2% * (3,000 / 39,000) = 0.4%.

Have you ever wondered why businesses that are the "best" at omnichannel don't grow much faster than businesses that are "terrible" at being omnichannel? This is why. The incremental benefit is rather tiny.

Now, would you rather work terribly hard to align all channels around an omnichannel initiative in order to get a 0.4% sales increase, or would you rather work on finding merchandise that customers love, a strategy likely to gain you 10% or 15% in annual sales?


June 27, 2014

Weekend Homework Assignment

Read this article (click here).

One of the key metrics cited in the article suggests that 41% of customers prefer to shop in stores.

If that is the case, then your homework assignment is to answer this question ... why do 80%+ of sales still happen in stores when only 41% of customers prefer to shop in stores and everything is available online 24/7/365, allowing the customer to not have to get in a car and drive to a store?

June 26, 2014

Oh Boy!

Click here to see an email that I received from Twitter two days ago.

Twitter tells us that they conducted a survey (they have more "digital" information than almost any brand that ever existed - they could have used that information, right?) and found that 40% of Twitter users have never been influenced once by Twitter to buy something from a small/medium sized business.

Give this thread a read ... especially the comments (click here).

Or this one from Gallup, flawed though it may be (click here).

Or this essay combining several articles from the mainstream media (click here).

Social (and omnichannel) are finally being evaluated, challenged, questioned.

I know, you're going to tell me that Yelp is inherently social, and Yelp strongly influences where sales happen. Come on!! If a restaurant has great merchandise (food), customers want to talk about it. If a restaurant has poor service, customers want to talk about it. That's not social, that's rooted in merchandise + service + story. So yes, Yelp is inherently social and is "proof" that "social works", but Yelp doesn't exist if customers don't want to talk about great food or poor food/service. Without the merchandise, Yelp doesn't exist.

I know, you're going to hop on in the comments and yell at me and label me stupid. You'll ignore the thousands of cases where social doesn't work, and focus on three cases where it did work - you'll say that the thousands of cases are proof that people "don't get social" and "don't do it right". Ok. But why is it, then, that almost anybody can easily generate sales through email marketing or paid search? Why is it that catalogers, catalogers for crying out loud, can easily make money on what you consider a "dead" concept, but social fails repeatedly and you blame the victim for using it wrong?

And omnichannel isn't much different, folks. You're told omnichannel creates riches - and yet, companies like Macy's, the alleged best at the practice, can barely boost comp store sales above the rate of inflation. Then you have H&M, who generated billions in the United States without even having e-commerce until a year ago. If omnichannel is so powerful, wouldn't H&M have died on the vine?

I've analyzed more than 120 businesses since founding MineThatData. There are several metrics that routinely illustrate success. They are:
  1. Merchandise Productivity. Are you generating more sales per comparable item, year-over-year?
  2. Number of New, Productive Items. Are you generating more new, winning items, year-over-year?
  3. New Customers. Are you increasing the number of new customers, year-over-year?
  4. Ad-To-Sales Ratio: Are you able to generate more sales on the same level of ad spend, year-over-year?
We've gotten so far away from focusing on what matters that we don't even know what matters anymore. Get back to analyzing merchandise productivity. Get back to understanding customer behavior, longitudinally ... if the customer purchased 2 times per year in 2004 and buys 2 times per year in 2014, then what good did all of those marketing concepts (social & omnichannel in particular) do for your business?

June 25, 2014

Online / Retail Dynamics: Creating Nine Segments

Ok, you've made it this far, congrats!

Now, if you don't like geeky math, here's the place where you move on - there's nothing for you to see here. I'll catch up with you another day.

Once I have my variables defined for the past year (or weighted based on the past "x" years), I plug the variables into a Factor Analysis. Here's the SPSS code I used for a recent factor analysis.

  d r visits03 visits10 visits30 visits99
  m00 m01 m02 m03 m04 m05 m06 m07 m08 m09
  m10 m11 m12 m13 m14 m15 m16 m17 m18 m19
  m20 m21 m22 m23 m24 m25
  cat aff ema nat pai ref soc
  d r visits03 visits10 visits30 visits99
  m00 m01 m02 m03 m04 m05 m06 m07 m08 m09
  m10 m11 m12 m13 m14 m15 m16 m17 m18 m19
  m20 m21 m22 m23 m24 m25
  cat aff ema nat pai ref soc 


There are several variables ... "d" and "r" represent percentage of demand in the direct and retail channels ... visits are categorized (visits03 to visits99), each merchandise category is given a weight that sums to one (listed via the m00 to m25 variables). Average price point is included, and I have weighted variables for catalogs, affiliates, email purchases, natural search, paid search, referrals, and social media.

This analysis yields two factors ... essentially, I am reducing the variability in the dataset down from 30-40 variables to just 2 dimensions.

Next, I create a segmentation variable ... I categorize the 2 dimensions based on the values of the 2 dimensions.

compute seg = 0.
if (fac1_1 lt -0.40) seg = 10.
if (fac1_1 ge -0.40) seg = 20.
if (fac1_1 ge  0.40) seg = 30.
if (fac2_1 lt -0.40) seg = seg + 1.
if (fac2_1 ge -0.40) seg = seg + 2.

if (fac2_1 ge  0.40) seg = seg + 1.

This little bit of code gives me nine segments ... the customer can be low/medium/high for the first factor, and low/medium/high for the second factor.

At this point, each customer belongs to one of nine segments. Now is the time where you drill down into each segment, analyzing the characteristics that yield each segment.

We've got it! We're there! We now have a map that tells us how customer behavior changes across segments. Each segment should be targeted differently. Go make something happen!

This is the process I go through. The variables, of course, are different in each analysis, and quite honestly, there is an art involved in creating actionable variables that yield actionable segments.

Ready for your own, customized Online / Retail Dynamics analysis? Good! Contact me (kevinh@minethatdata.com) and let's get started!!

June 24, 2014

Online / Retail Dynamics: Weighted Attributes

There are many variables that I like to analyze, on an annual basis, in an Online / Retail Dynamics project.

Merchandise Categories: I sum annual demand by merchandise category, then divide the total by how much the customer spent in the past twelve months. This gives me a fraction (0.00 to 1.00) of amount spent in each category. Some clients want two years or five years or all history included. I find this is not an optimal way to analyze what customers purchase - who cares that you purchased a love seat in 2004? In these cases, I weight historical spend ... maybe 100% for 12-month purchases, 50% for 13-24 month, 30% for 25-36 month, 20% for 37-48 month, 14% for 49-60 month, and 10% for 61+ month purchases. This greatly minimizes the influence of old purchases, especially older high-dollar purchases.

Website Visits: Here's a little secret not many folks want you to know - in most of my projects, I'm asked to analyze twelve-month website visitation behavior. Having said that, on average, only website visits in the past 15 - 30 days have any influence on future behavior. Often, I'll create three variables ... website / mobile app interactions in past 30 days, then from 31-90 days ago, and finally, 91-365 days ago. But again, only the most recent website / mobile app interaction matters. Recency is critically important online, folks. Heck, sometimes I'm asked to group website visits into buckets ... 1 visit last year, 2 visits last year, 3-5 visits last year, 6-10 visits last year, 11-50 visits last year, 51-100 visits last year, 100+, that kind of thing. Whatever works for you is fine, just make sure you have a defensible point of view.

Purchases: I like to sum twelve-month (or historical weighted) dollars by channel ... retail, smartphone, tablet, desktop/laptop, call center, that kind of thing. Then I'll divide the totals within channel by total annual (or historical weighted) dollars.

Website Characteristics: Here, I like to categorize activity on a weighted basis ... 100% for 0-30 day activity, 20% for 31-90 day activity, 5% for 91-365 day activity. I'll create 1/0 indicators for all key characteristics (cart, email click-through, referral from Bing, that kind of thing), then I will weight each characteristic by time (100%, 20%, 5% as mentioned above), and create a percentage. The weighting becomes important ... if a customer visited via Bing 100 days ago and Google yesterday, the Google visit is weighted at 100%, the Bing visit at 20%, meaning that the customer has a Google preference at a rate of 100/120 = 83%, while the customer prefers Bing at 20/120 = 17%. On an annual basis, the weightings really help us understand how the customer behaves.

Store Distance: I'll plug 1/0 indicators into my analysis for 0-5 mile bands, 6-10 mile, 11-25 mile, 26-50 mile, and 51+ mile bands. You will learn that visitation behavior changes as customers get further and further away from a store.

Zip Codes: I categorize zip codes by Catalog-Centric, Online-Centric, and Retail-Centric. Behavior in each classification is simply different, and quite interesting! You probably have your own algorithm for categorizing each zip code, so use that.

Tomorrow, I'll show you how I cook this information up - the discussion might get a bit geeky, but that's the nature of the work I'm doing when analyzing Online / Retail Dynamics.

June 23, 2014

Online / Retail Dynamics: Data Structure

There are two ways that I typically analyze Online / Retail Dynamic data.

If the client is looking for purchase-specific information, then I create a table similar to the one outlined here. Each order is "tagged", if you will, by the channels that were attached to the order. Look at the first purchase. This customer bought in a store. Each column that follows outlines a yes/no indicator for what that customer did in the 30 days leading up to that purchase. In this case, the customer clicked through an email campaign, visited the site via natural search, visited the site via social media, visited the core website, and engaged with the retail app. You can imagine the columns that would be valuable to your business - just tag each order with the channels that impacted that order in the thirty days prior to a purchase, and start analyzing!

I tend to use a different approach in most projects. Specifically, I analyze customer behavior across a full year. The information, across a year, is so much richer and more revealing than the information tied to a specific visit and/or purchase. We learn that customers have interesting, consistent, reliable behavior that is masked by noise in individual visits ... but becomes easy to see on an annual basis.

Tomorrow, I'll talk about the variables I use, on an annual basis.

June 22, 2014

Online / Retail Dynamics: Competition

When I worked at Nordstrom, we used to read all sorts of interesting content about Neiman Marcus, one of our primary competitors. Most interesting, of course, was the difference in tone.
  • Typical Neiman Marcus Comment: "We are out to crush the competition."
  • Typical Nordstrom Comment: "We welcome Neiman Marcus into our markets, because when they open stores, we find that our comp store sales tend to increase."
Catalogers know this as well - they've been sharing their most coveted asset - customers - with each other for thirty or more years.

Yes, I get it, your competition is "just one click away". Fine. At Nordstrom, we analyzed all online and retail behavior within the context of the amount of competition a customer faced within a zip code. Online, we couldn't control for this dynamic (though referring URLs taught us that our customers shopped everybody - and credit card data showed us that customers shopped Wal-Mart as much as they shopped Nordstrom). But the zip code data was invaluable for understanding the competitive landscape, and the impact the competitive landscape had on in-store purchases.

Turns out that competition isn't always a bad thing!

Contact me (kevinh@minethatdata.com) for your own, customized project.

June 19, 2014


Indulge me for a moment, while I share a story with you.

It's early 2003. I'm the Vice President of Database Marketing at Nordstrom. About three months prior, I moved from the website/catalog side of the business, and was now supporting those channels along with all retail direct marketing activities. A marketing director enters my office, unannounced. We have a conversation that goes something like this:

Marketing Director: Hi Kevin, my name is Barry (not the real name).

Kevin: Hi Barry, nice to meet you.

Barry: Why are you ruining our brand?

Kevin: Excuse me?

Barry: Look at this (Barry sets down a catalog from the website division). Just look at this piece of crap.

Kevin: You don't like it?

Barry: It's not aspirational. It is a bunch of old women wearing merchandise that old women buy. It is not reflective of the aspirational store experience we're trying to create.

Kevin: I'm not responsible for the merchandise in the catalog.

Barry: But you're ruining the brand!

Kevin: I'm not responsible for the creative in the catalog.

Barry: Just look at it! It's hideous. This is embarrassing to the Nordstrom family.

Kevin: Nobody from the Nordstrom family told me it is embarrassing.

Barry: I'm telling you it is!

Kevin: Why are you telling me it is embarrassing?

Barry: Because you determine who receives the catalog. Stop poisoning my customers with your crap.

Kevin: Your customers?

Barry: Exactly. How can I inspire a professional woman to be all she can be when you mail her this crap?

Kevin: But your customer segment is one of the most profitable catalog segments on the entire customer file of 8,000,000 twelve-month buyers.

Barry: So?

Kevin: So I can demonstrate that we generate profit by mailing 10,000 customers just like you. I can actually make an argument that I am helping the brand, and by generating profit, I am able to make sure that you receive a large bonus at the end of the year.

Barry: But at what cost?

Kevin: By mailing customers like you, I generate profit.

Barry: But you only get 3 out of 100 customers to buy something. Stop mailing the other 97 people. I'm one of the 97 you should not mail.

Kevin: I can't predict the 97 people who will buy out of 100 people.

Barry: That's you job, isn't it? You're failing at your job.

Kevin: That's not how it works, Barry. I can predict how 100 or 1,000 or 10,000 folks will respond. Nobody can predict how one person will respond. Heck, you don't even know what you're going to have to eat for dinner tonight, but I should be able to predict the day you will buy something eight weeks in advance?

Barry: I'm just giving you some friendly advice. You are ruining the brand.

Kevin: Last year, my team was responsible for generating $20,000,000 of incremental sales and $6,000,000 of incremental profit by using the techniques we use to determine who receives catalogs and email campaigns.

Barry: But you ruin the brand in the process. What good is all that profit if you ruin the brand?

Kevin: Show me the metrics that prove that I ruin the brand? Company sales? Company profit? Cash flow? Stock price? Are any of those metrics looking particularly sour?

Barry: I don't need metrics, I have this hideous catalog in my hand. That's the metric that counts. Stop mailing it.

Have you ever had a conversation like this?

We keep reading about being "data driven". There is no amount of data-driven goodness that convinces a person like Barry to move from his position. None. Barry has a belief, and Barry is going to stand behind his belief, no matter what metrics you share with Barry.

It doesn't matter how much data you have, or how much proof you have. There is a third of the audience you are never going to convert to your side, no matter how much data you have in your favor. Ignore them. Stop wasting time on them.

A third of your audience trusts you.

A third of your audience can be convinced.

A third of your audience will never be on your side.

Focus on the folks who trust you.

June 18, 2014

Online / Retail Dynamics: Store Distance

A quick note for you today ...

Store Distance plays a major role in how customers "convert", and in how customers use your online channel.

In most of my projects, there are three key store-distance bands.

  1. 0-5 Miles:  Here, customers frequently use the website to plan an in-store purchase. Conversions are hard to come by, via traditional metrics, and yet, the website has never been more important. Email, by the way, becomes a major in-store driver in this case.
  2. 6-25 Miles:  This band is driven by online research that yields a 50/50 mix of online purchases and in-store purchases. This is the classic "omnichannel" customer that you read about. These customers frequently "do everything". Email is a tool that often drives the customer online, in this mileage band.
  3. 26+ Miles:  Even more interesting is the 100+ mile band from a store. Here, the catalog plays a major role in relationship building. These customers tend to buy online after receiving catalogs, at rates higher than for any other segment.
Plug store distance into your segmentation strategy, and then carefully analyze the merchandise customers purchase, the advertising channels the customers purchase from, and the in-store / online mix by mileage band. You're going to find many unique segments that can be actively mined for increased profit.

Contact me (kevinh@minethatdata.com) for your own, customized project.

June 17, 2014

Online / Retail Dynamics: Merchandise

Yesterday, I talked about how email marketing dynamics are poorly understood in the typical online/retail setting. Similarly, merchandise preference is highly misunderstood. This, too, happens for a good reason - our web analytics platforms are calibrated to explain the impact of advertising on conversion - they are not calibrated to understand the impact of merchandise assortment on customer relationships.

Here's our map, once again.

Look at the three segments on the right-hand side of the image.

The merchandise categories are largely the same.

The customer, by and large, prefers the in-store experience.

Catalogs are a common customer conversion channel among these customers.

What we present to a customer plays a major role in determining what the customer purchases. Catalogers know this best - they've painted themselves into a corner by featuring merchandise that customers age 60+ tend to love.

I once had a client who sent a million catalogs a month, and had a million unique website visitors each month. This client obsessed about the merchandise they put in the catalog - then gave nearly no attention to the merchandise offered on the home page, and on key landing pages. Considering that many catalog recipients never bother to open the catalog, you'd think that an actual visitor on the website, looking at actual merchandise, would be considered a top priority. Not so.

Our segmentation map shows us that different customers have different merchandise preferences. Online, we should feature the merchandise that customers want to see - this isn't a difficult proposition in 2014. And we should realize that what we show the customer dictates what the customer purchases. We unknowingly influence how the customer will behave, often without much thought to the process. In this instance, the catalog aligns with a series of merchandise categories that this brand decides to actively feature - causing the customer to buy those items.

Contact me (kevinh@minethatdata.com) for your own, customized Online / Retail Dynamics project.

June 16, 2014

Online / Retail Dynamics: Email Marketing

The three most valuable segments are the upper-middle segment, the upper-right segment, and the middle-right segment.

What is the advertising channel that is common across each segment?


Email marketing is, in my opinion, the least understood of the advertising channels I work with. This happens, quite honestly, because the metrics associated with email marketing success (opens / clicks / conversions) are not aligned with the metrics that really matter (demand, profit).

For this business, there are common characteristics for email buyers.

  • More likely to browse than to buy (9.6 to 1, 6.5 to 1, and 5.3 to 1 visit/purchase odds).
  • Way more likely to visit the website than the average customer (54.45 visits, 73.57 visits, 30.59 visits, on an annual basis).
  • Likely to combine email marketing with another advertising channel.
This analysis brings two thoughts to mind.

  1. More than half of the purchases, among the email centric customer segments, happen in-store. This means that the standard open/click/conversion framework completely misses these purchases, and as a result, seriously miscalculates the effectiveness of email marketing.
  2. Email buyers tend to be browsers - they visit the site all the time - and therefore, do not need to be given "hard-sell" tactics. These customers, on average, are visiting the website once a week.
I see this outcome, often, among customers who buy from email campaigns. They visit frequently without buying. Conversion isn't the problem here - no - the problem is often a lack of a new message.

Your best customers visit the website all the time. Why bore them with website updates that happen monthly? Or every-other-week?

Some customer segments require a constant supply of new content. Segment your customers, and then give the customers who require new content a steady diet of new content! Stop boring customers!

Contact me (kevinh@minethatdata.com) for your own, customized Online / Retail Dynamics analysis.

June 15, 2014

Online / Retail Dynamics: High Price Points

Take a look at the upper-left segment in the image below.

Here are some of the purchase dynamics.

  • 1.67 Online Orders Last Year.
  • 0.18 Retail Purchases Last Year.
  • 1.85 Purchases, Total.
  • 15.59 Visits Last Year.
  • 8.3 to 1 Visit-To-Purchase Ratio.
  • Average Price Point Of Items Purchased Last Year = $93.
Now look at the advertising channels this customer uses.

  • Affiliates, Natural Search, Paid Search, Referrals.
We have a customer who primarily shops online, who visits 8 times for every purchase s/he makes, who uses all sorts of shopping comparison advertising channels, who uses affiliates to get deals, and then purchases the most expensive items of any customer segment in the analysis.

This may be a segment where the omnichannel playbook is valid. In fact, when you look across the top row of the table, these are all customers who fully utilize the omnichannel playbook. In this case, we have a segment of customers who are clearly looking to save money on the most expensive items the brand has to offer.

Also notice that the merchandise categories purchased by the customer are different than are the merchandise categories purchased by other segments.

This is a customer segment that, in many ways, is different from the rest of the business. This is a marketing-driven customer segment, not an organic brand-centric segment who loves the general merchandise assortment.

Recognize this customer. Realize that this customer is going to visit the website, often (8 visits to 1 purchase). Find ways to communicate to this customer that your pricing is fair.

Contact me (kevinh@minethatdata.com) for your own, customized Online / Retail Dynamics project.

June 12, 2014

Decentralized Commerce

We're seeing change in two different directions.
  1. Omnichannel - The idea that every single thing in a business is fully integrated, from merchandise to marketing to creative, all along channels that allow Google / Facebook / Verizon / Westfield Group / Epsilon / Trade Journalists / Apple to get paid.
  2. Decentralization - The idea that you are there when the customer needs you. Pinterest would be a good example of decentralization - the customer is inspired by an image pinned by somebody the customer admires - then the customer has an opportunity to interact with a retailer - maybe the retailer makes it easy to interact, maybe the retailer is oblivious and the customer has to do a lot of work - regardless, the experience is fully decentralized (and Verizon / Google / Facebook still get paid - think about that one for a moment).
Now, you can have a decentralized experience within an omnichannel framework. If somebody wanted to watch The Belmont Stakes last weekend at a party, they can ask me to punch it up on my phone, I can download the app from NBC, and we're doing it (with Verizon getting paid - hint hint) - that's a decentralized experience within NBC's omnichannel framework.

But here is what is important, folks.
  1. Old-school channels are inherently "omnichannel".
  2. Mobile is inherently "decentralized".
As such, it is terribly hard to integrate mobile into an omnichannel (structured) framework. In a structured, omnichannel framework, you work terribly hard to create time-based campaigns that align across channels ... the catalog is sent on Monday, emails are sent on Tuesday and Thursday, the app reflects the campaign, the creative in-store aligns, and you demand that the customer walks through the Monday - Friday experience in order to buy something on Saturday in a store (or catalog or website). 

In a decentralized, mobile world, the customer has a need at a point in time (Wednesday, 3:47pm, 88 miles from home). The marketing strategy to capture and satisfy the customer need at 3:47pm, 88 miles from home, is at direct odds with the structured omnichannel framework of campaign - reinforcement - response - repeat.

Customers naturally align with an omnichannel (structured) framework, or a decentralized (mobile) framework. Some do both. Until we acknowledge that there is this fundamental difference in marketing strategy, we're going to continue to waste resources and make mistakes. Have different approaches for different customers. Segment them - it's not hard (contact me at kevinh@minethatdata for help).

June 11, 2014

Online / Retail Dynamics: The Catalog Customer

Even in a retail environment, there are catalog customers who behave differently than other customers.

Look at the bottom right segment.
  • 0.55 Direct (online) Orders.
  • 4.11 Retail Orders.
  • 4.66 Total Orders.
  • 9.80 Website Visits.
  • 2 to 1 Visit-To-Purchase Ratio.
The ad channel this customer uses is catalogs.

Notice that this customer has an 8-to-1 retail purchase skew.

Notice that this customer does not visit the website, less than once a month, to be honest.

In other words, this customer is very different than the average customer ... this customer actively uses the catalog (not the website) as the primary shopping tool, and uses the catalog to buy in stores, not online.

In an omnichannel world, you're told you have to do everything. Wrong. You have to do what is right for specific customer segments. For this customer segment, the catalog is an important component of the purchase process - more important than the website.

Segment your customers, understand their Online / Retail Dynamics, then act appropriately!

Contact me (kevinh@minethatdata.com) for your own, customized Online / Retail Dynamics project.

June 10, 2014

Online / Retail Dynamics: The Best Customers

Let's look at the upper-right cell in this image.

Wow, what a customer segment. Look at last year's purchase/visit activity.
  • 4.71 Direct Orders (Online) Last Year.
  • 6.67 Retail Orders Last Year.
  • 11.38 Total Orders Last Year.
  • 73.57 Website Visits Last Year.
  • 6.5 to 1 Visit-To-Purchase Ratio.
This is the most valuable of the nine customer segments in my analysis - these customers spent $1,963 last year. This customer is truly "omnichannel", even as the pundits describe omnichannel behavior. Look at the characteristics ... the customer buys via catalogs, affiliates, email, and social media. My goodness! And the customer splits orders between online and stores, wow!

This is what omnichannel customer behavior actually looks like. The customer essentially "does everything". In fact, if you look at "best customers", you will almost always observe that the customer "does everything", because that's what best customers do!

But most important, this customer visits the website 6.5 times for every purchase.

In other words, stop demanding that this customer buys RIGHT NOW. Stop! This customer visits the website once every six days. That's nuts!! Heck, this customer segment is responsible for 35% of the website visits in the past year from customers who purchased last year.

We need to make a clear distinction among customers - "segmenting them", if you will. Some customers must be converted, now, or you won't see the customer ever again. And then we have loyal customers - why hawk these customers with promotional nonsense when the customer visits the website once every six days?

Contact me for your own, customized Online / Retail Dynamics project (kevinh@minethatdata.com).

June 09, 2014

Online / Retail Dynamics - Nordstrom

When I worked at Nordstrom, circa 2006, we knew that our "multi-channel" customers exhibited a consistent behavior:

  • 3 Website Visits Per Month.
  • 2 In-Store Visits Per Month.
  • 1 Purchase Per Month, 85% In-Store.
We also knew that online customers, after a first purchase, were more likely to migrate to retail than to stay within the online channel.

We also knew that retail customers, after a first purchase, were going to stay within the retail channel, using the website to research an upcoming in-store experience.

Tactically, you change your thinking when you understand the role that your website and mobile experience play in the customer relationship.

Specifically, there is no reason to demand a "conversion" on a website when the customer uses the website to research an in-store purchase. I know, I know, this runs counter to everything you've been taught. But come on!

In a retail environment (same thing with a catalog environment), the website is far more likely to play a research role than a commerce role. This means you want to recognize the customer upon a visit. If that customer is a "retail researcher", then give the customer what s/he wants - don't demand a purchase today.

Tomorrow, we'll look at one of the segments from yesterday's image (shown below).

June 08, 2014

Online / Retail Dynamics

During the next two weeks, we're going to talk a lot about what I call "Online / Retail Dynamics" (contact me via email ... kevinh@minethatdata.com ... for your own, customized project).

During the past two years, I've learned that we have a good understanding of online behavior within the context of a visit. Yup, we can clearly see what drove the customer to the website, and we can clearly see what caused the customer to "abandon" the visit. All good, no doubt.

But we're missing the context of a customer relationship, aren't we?

Study the image in this post. There are nine customer segments here, a common outcome in the Online / Retail Dynamics projects I've worked on during the past two years. In the upcoming days, we're going to dig into the nine segments, and in the process, we're going to learn how customers behave in an Online / Retail environment.

June 05, 2014

Commerce Nightmares: Wrap-Up

You're probably wondering why I spent a week-and-a-half talking about Commerce Nightmares?

Well, something changed in the past two years. Or maybe I just got older. Regardless, the challenges I see in 2014 are different than when I founded my consulting practice in 2007. The first four years of my practice were all about responding to an economic collapse. By 2011, it was clear that there were generational issues that were going to fundamentally re-shape our businesses - I created personas (Judy, Jennifer, Jasmine) to address the changes - the marketing community focused similarly on Millenials / Social / Mobile (the latter two are the tactical outcomes of the shift in generational focus).

What I observed in marketing in 2011 is spilling over into workplace dynamics, as we march toward 2015. Jasmine is about to turn 30. This means that Jasmine is moving into Manager/Director positions.

There were two comments that changed my thinking, both uttered to me earlier this year, both uttered on numerous occasions by numerous individuals.
  • Jasmine = "Why won't my Executive Team listen to me? They are so old-school. All they want to do is the same thing they've always done. I can help them. I don't think they want help."
  • Judy = "I only have six years to go before I retire. I just need to keep the wheels on this thing, then I don't care what happens."
It's the comment from Judy that has changed over the past three years.

See, I thought that the Judy / Jennifer / Jasmine issue was a business / marketing issue. Maybe I was right. But the Judy / Jennifer / Jasmine issue is becoming much more of a Management issue than a Marketing issue. The marketing issue is going to resolve itself in Darwinian fashion.

The Management issue will resolve itself as well. We, however, get to choose whether it resolves itself in a painful manner or not.

When you watch Kitchen Nightmares, you see what a difference an Owner can make when the Owner is open to change. When the Owner is willing to change the menu, change the decor, and change work processes, employees are happier, and team chemistry improves dramatically.

A few weeks ago, a young analyst asked me on Twitter, "Where has leadership gone to?" Just think about the tone of that question for a moment ...

Too often, leadership is just trying to hang on. Imagine being a 55 year old Director-level person at a retail brand, e-commerce organization, or cataloger. What do you do when you get fired? Who is going to hire you? Certainly not a startup that only respects knowledge from folks under the age of 32. Certainly not a peer company, because the peer company has to look to the future, and the future is Jasmine - the peer company is going to develop Jasmine at a salary of $70,000 a year before they take a chance on a 55 year old requiring a salary of $150,000 a year.

This reality explains, to some extent, where leadership has gone. Sure, leadership should be consistent regardless of reality - but this is what I'm observing - and it is troubling.

If I'm Jasmine, I'm going to fill the leadership void myself. Is it hard work? Yes. Is it thankless work? Yes. But in ten years, demographics will take care of the leadership void - in 2014, you'll want to have ten years of practicing leadership principles in a difficult environment.

And if I'm Judy? Well, it is time to do what Mr. Ramsey would want you to do on an episode of Kitchen Nightmares. He'd demand that you change. Or don't change, and just realize that there will be more friction than is necessary.

This brings me to a thought. Somebody made an interesting comment at a conference I spoke at ... this guy, clearly in Judy's generation, said to me ... "I just don't understand why Jasmine won't embrace our traditions. How do we train Jasmine to embrace what we love?"

Now we're getting somewhere.

We have Judy's generation pushing in two directions ... trying to remain gainfully employed through to retirement ... and trying to get Jasmine to maintain Judy's traditions. Meanwhile, we have Jasmine, using technology and communication techniques that Judy understands but didn't grow up with, pushing for change. This causes a Commerce Nightmare.

I know, I know. You are Judy, and you are wondering why I let Jennifer off the hook? You think I am picking on you.

Jennifer's case is an interesting one. She's currently 45 - in other words, she's a Gen-X person who is caught in the middle. She's mid-career, she's been bossed around by Judy in the workplace for two decades, and she's being swamped by a generation of Jasmine-esque individuals with very different habits and values. Yup, Jennifer is caught in the middle. And worse, Jennifer is not part of the catalog generation, and is not part of the social/mobile generation. Jennifer is the Amazon-centric shopper that only Amazon seems to appreciate.

But in the workplace, Jennifer is the bridge between generations.

In other words, Jennifer, leadership opportunities have been thrust upon you. It's time for you to, as Judy likes to say, "step up".

The thing that has changed since 2011 is the emergence of Jasmine in the workplace. Jasmine is in her late 20s to early 30s, and her world is fundamentally different than Judy's world. Jasmine is moving into Manager/Director positions, while Judy is now closing in on retirement. This conflict seems, in my opinion only, to be causing Commerce Nightmares - it is causing conflict.

We may need three things to happen.
  1. Judy may need to embrace change.
  2. Jennifer may need to be a leader who bridges generations, embracing Jasmine's ideas while protecting Judy.
  3. Jasmine may need to become a leader faster, and may need to become really good at teaching.
What do you think?

June 04, 2014

Commerce Nightmares: Chemistry

Notice that I do not have an "8 Steps To Social Media Success" square in The Direct Marketing Success Pyramid.

Too few people want to talk about the role that chemistry plays in a successful business. If you watch Kitchen Nightmares, you seldom see good team chemistry.

In fact, you'll frequently see chemistry fall apart when the owner chooses to not listen to line staff. Maybe the chef wants to add specials to the menu, but the owner has a rigid perspective "this is the menu, just cook it". Maybe the staff have a process for taking care of orders, but the owner has to be in the kitchen dictating work flow. Regardless, somebody messes up what could be a smooth, well-run process, and in the process, destroys any possibility of team chemistry.

This same dynamic happens in retail brands, e-commerce businesses, and catalogers. These days, the dynamic seems to happen less along VP / Director / Manager / Analyst lines ... happening instead across generations. In other words, you have a Manager who has many ideas for improving business performance, but the ideas generally speak to "Jasmine" ... and therefore, are not embraced by others. I can't tell you how often I hear the phrase "why won't Executives listen to me?" on Twitter.

When good team chemistry exists, folks are allowed to test their ideas ... not roll their ideas out untested, but they do get to test ideas. In this way, we make progress.

When you see an environment where employees are not allowed to test their ideas, and as a result, employees lose trust in each other, you are seeing a potential Commerce Nightmare.

June 03, 2014

Commerce Nightmares: It's Their Fault!

Ever watch a sporting event? Have you noticed how teammates support each other, congratulate each other, support each other?

I suppose it is easier to support each other when you are winning. Who knows, maybe the support leads to more winning?

Now, I'm not hired to verify that a 10% pre-tax profit business is doing things right. No, not even close. I'm hired to solve a problem for a company that, quite often, is struggling.

In 22 of the last 27 Merchandise Forensics projects I've worked on, I was able to find a merchandise-centric problem. The fun begins after you share what you've learned. I get it, I get it, it's hard to be a merchant. But the first sentence I hear from the merchandising leader tells me whether there is the potential for a Commerce Nightmare.

Here's the comment that suggests a Commerce Nightmare is about to erupt.
  • "I understand what you're saying, but it's not my fault. Take a hard look at marketing. They keep screwing up, making it hard for me to sell my merchandise."
When I hear variants of that statement, a Commerce Nightmare is in the offing.

Then you talk to the marketing folks, and you hear something like this:
  • "The merchants are idiots. And they're egotistical."
Now you know that a Commerce Nightmare is coming.

When I worked at Nordstrom, before the economy collapsed, business was good. And the relationship between merchants and marketers was, predictably ... good! Yes, of course, there were issues, there always will be. But good business fosters good relationships.

When I worked at Lands' End, before the internet, business was ok. And the relationship between merchants and marketers was, well, ok. If anything, the merchandising team might have felt like marketing was stepping all over them.

When I worked at Eddie Bauer, in the late 1990s, there were two years when the sky was falling. And the relationship between merchants and marketers was, well, not good. Bad business fosters bad relationships.

When business is bad, somebody needs to be a leader. Somebody needs to stop feeling defensive, and just focus people on improving business performance. That's really, really hard to do when folks are trying to remain gainfully employed.

If you work at a company that is struggling, look for somebody who is optimistic, who tries to rally folks a common goal. When you see that, your business has a chance - rally around the person. If you don't see that, maybe it is time for you to become that person? And if neither happens (not somebody else, not you), your business might be headed toward a Commerce Nightmare.

June 02, 2014

Commerce Nightmares: We're "Unique"

When you watch "Kitchen Nightmares", you'll frequently hear that the owner thinks a restaurant is "unique". They're different than everybody else - because of pumpkin hummus or some other reason.

When Mr. Ramsey goes back into the kitchen, we learn that the restaurant is not unique. It may not be clean, but it certainly isn't unique.

Do you know how often you, dear readers, tell me that your business is "unique"?
  • "We're unique because our customers do not repurchase."
  • "We're unique because our customers repurchase so often."
  • "We're unique because of dynamic pricing."
  • "We're unique because our prices haven't changed since 1982".
  • "We're unique because we offer great value and free shipping".
  • "We're unique because we sell proprietary products."
  • "We're unique because we sell branded products".
  • "We're unique because we appeal to customers age 8 to 80."
  • "We're unique because we sell in so many channels, we're #omnichannel!"
Blah blah blah ... blah.

Hint - if you can name just one company you compete with, then you are not unique, because you have a competitor doing essentially the same thing you are doing.

Too often, you, the loyal reader, tell me that your problems cannot be solved because you are unique. This is usually code for "we don't know how to solve our problems" or "we don't want to solve our problems". It's a story we tell ourselves.

Hint - the most successful companies seldom talk about being unique. They talk about selling stuff.

When you hear "we are unique", you might just be looking at a looming Commerce Nightmare.

June 01, 2014

Lands' End and Omnichannel: 2001 to 2013

One of the best things about publicly traded companies is that they have to tell you how much merchandise they sell, and they have to tell you how much profit they generate.

Lands' End was a publicly traded brand in 2001, before selling to Sears. Now that Lands' End has been spun off as a publicly traded company, we can compare the business pre-Sears and post-Sears.

The era between 2001 and 2013 coincides with the start of what was called "multi-channel", and the evolution into what it is now known as "omni-channel". Both concepts are essentially the same ... a frictionless customer experience via online, mobile, stores, and catalogs, coupled with a full digitization of the in-store retail experience. The promise of both is the same ... customers will spend a fortune if you digitize the business.

How did migration from cataloger to multi-channel brand to omnichannel apparel favorite play out for Lands' End? Let's take a look (click here for the 2001 annual report and click here for the 2013 annual report). 
  • Direct-Channel Annual Net Sales, 2001 = $1,462,000,000.
  • Direct-Channel Annual Net Sales, 2013 = $1,303,862,000 (sales are less than 12 years ago).
  • Retail-Channel Net Sales, 2013 = $258,922,000.
  • Total Net Sales, 2013 = $1,562,876,000.
  • Approximate Market Value, Pre-Sale = $2,000,000,000.
  • Approximate Market Value, Today = less than $1,000,000,000.
In twelve years, Lands' End (in total, retail + direct) grew by 0.6%, on an annual basis, with half the value of the company destroyed during a time when inflation grew by about 30%.


You know what? You can make a strong case that omnichannel tactics ruin businesses.

A series of questions for you to consider on a Monday morning:
  1. If online marketing is so powerful, then why didn't Lands' End grow?
  2. If retargeting is so powerful, then why didn't Lands' End grow?
  3. If email marketing is so powerful, then why didn't Lands' End grow?
  4. If social media is so powerful, then why didn't Lands' End grow?
  5. If mobile is so powerful, then why didn't Lands' End grow?
  6. If cart abandonment programs are so powerful, then why didn't Lands' End grow?
  7. If catalog/online integration is so critically important, and Lands' End integrated the catalog with their online business, then why didn't Lands' End grow?
  8. If the co-ops are the key to customer acquisition success, and customer acquisition excellence leads to a loyal and productive database, then why didn't Lands' End grow?
  9. Discounts and promotions are a "must", and are so powerful as we're told daily, and Lands' End never participated in them prior to the acquisition but has re-defined the brand around them in recent years. Given that thesis, why didn't Lands' End grow?
  10. Retail, what the management consultants call "bricks 'n clicks" is considered to be so very powerful, but Lands' End moved into retail and didn't grow. Why didn't Lands' End grow?
  11. If catalogs were so critical to success, then why didn't Lands' End grow but Amazon exploded (without catalogs)?
  12. If you think Sears is to blame, then why did Coldwater Creek fold, why did Gap post a -30% comp in-stores over the past decade, why did JCP crumble for years before imploding, and why did Eddie Bauer go through bankruptcy twice? Did Sears cause those problems as well?
  13. If you can buy Lands' End merchandise online and pick it up and/or return it in-store, which is what today's highly sophisticated omnichannel customer demands (as we're told), then why didn't Lands' End grow after employing the very strategies that we're told we have to employ in order to grow?
  14. If only 44% of Lands' End customers are age 35-54, then roughly half of Lands' End customers must be age 55+. Why didn't Lands' End grow during a timeframe when it continued to use a catalog to follow customers age 55+ toward retirement?
Write down your answer to each question.

Now, take a look at the answers to your questions, all of them. 

What do the answers tell you about what might be important to Lands' End? What do your answers tell you about what might be important to your business?

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