October 12, 2015

But What About The 25% Of Catalogers Who Have Young Customer Bases?

Young (in catalog terms) meaning age 35-54, of course.

There are things that these businesses do that are fundamentally different than what most catalogers do. Some of this is "chicken 'n egg" logic, and cannot be unraveled, of course.

*** Their dependence upon the co-ops has always been less than the typical cataloger, thereby seeding their business with younger names who like merchandise tailored to younger customers.

*** They sell more "fashion oriented" items.

*** Their merchandise aligns with stuff needed in a new home, or aligns with stuff needed by families with children. In this way, they draw the younger portion of the co-op algorithm (where there is less competition, interestingly), and they are far more appealing to the typical individual prowling out there for the best deal on Google.

*** They offer free shipping more often than discounts/promotions.

*** Their online marketing departments are fully staffed, and are excellent.

*** They work at a pace/urgency that most catalogers cannot match.

*** Their attribution programs equalize between online marketing and catalog marketing. Traditional catalog marketers with older customer bases assign online orders back to the catalog without questioning the results.

*** They test, often.

*** They have smaller page counts.

*** They seldom mail remails, and in the process, they do not bore their customers as much.

*** They shift their customers from online to the mobile web, and then into apps. The most loyal customers end up in apps, not in catalogs. The opposite is true for traditional catalogers.

*** In "digital" and "social", they are far more likely to tell a story, without worrying about return on investment. Traditional catalogers tell stories in print, then align digital with print, causing digital to always lag far behind the customer, and then demand that everything is measured and attributed back to the catalog.

*** Email marketing supports merchandise, is merchandised dynamically and/or customers are targeted via one of the five best creative/merchandise treatment combinations several times per week. Traditional catalogers use email to support the catalog, and have only one version of an email campaign that is sent to everybody.

*** The online marketing team has minimal catalog experience, and that is not viewed as a negative.

*** Decisions are made in a nimble manner (as vendors like to say, these folks are "agile"). They will change things online without catalog alignment, capitalizing on sales opportunities. Traditional catalogers wait to change until the catalog can "catch up", thereby fully integrating channels.

*** Planning is centralized around merchandise and events. Traditional catalogers centralize planning around catalogs.

*** They often have a retail channel, where younger customers by default are likely to shop. This drives the merchandise assortment much younger, spilling over into e-commerce and cataloging.

Obviously, these are generalizations of things that I observe. I've witnessed catalogers with 40 year old customers and the oldest-school techniques you'll ever see. I've also seen catalogers with 70 year old customers who execute programs that mobile-savvy brands would envy. 

But you get the picture. I share this with you, in hopes that you'll think about what it all means.

October 11, 2015

Urban Outfitters

You've heard about this one, undoubtedly (click here).

Twenty five years ago at Lands' End, we were asked to pick/pack/ship orders in early December ... no, not on the weekend ... but on a non-descript Tuesday. I distinctly recall picking the order, setting the order aside, packing the order form, zipping the envelope, and sending the sewn package down the line. Then I looked in front of me ... three items sat there, lonely. Somewhere in Minnesota, a perfectly humble Protestant family received a package containing only an order form / receipt. Merry Christmas from Lands' End!! Moments later, I was relieved of my duties ... not as a statistical analyst ... but as a distribution center employee.

During a seventeen inch snowstorm, I committed myself to shoveling a whole road so that I could get to work. I got to work, and was promptly re-directed to one of our call centers. I took two orders ... TWO ... and messed them up so bad that I was relieved of my duties ... not as a statistical analyst ... but as a call center employee. I was reassigned to the switchboard, where my skills were more than adequate to handle the complete lack of incoming corporate call traffic on a snow day.

At Nordstrom, we were required to work sale events. Yup, there's Kevin, working in a women's apparel department at Northgate Mall, stocking shelves, taking abandoned merchandise out of dressing rooms, and answering questions I was completely unqualified to address ("why does this fit different in a size eight from this item that is a size six, when it's the same brand?"). I hated every minute of this work, work that happened three times a year for six consecutive years.

At Avenue A, it was expected that employees worked eighty hour workweeks. I recall the twenty-three year olds showing up at 9:30am, going home at 9:30pm, playing ping pong for three hours at a time. I worked 6:30am - 5:00pm. I recall being asked why I wasn't "committed to the mission?" I recall asking how a twelve hour workday that included three hours of ping pong helped increase shareholder value when I was working straight through a shorter day? No answer to that response, of course.

At the Garst Seed Company, we were required to work additional hours on weekends in October to handle "harvest season". We'd receive a bumper crop of data that could not be analyzed in the requisite fifty-five hour work week, so Saturday and Sunday were required work days in October. I recall having a weekend trip planned - I did not show up for required weekend work, and it didn't help my career one bit ... "what is wrong with you, don't you know that this is 'harvest' and you have to work weekends?"

Salaried employee are required to donate time for free. Show of hands - how many of you worked just forty hours last week? I get emails from east coast folks time-stamped at 10:30pm. I get emails from west coast folks at 5:30am. My team at Nordstrom FTP'd files at 2am on a Sunday Morning - a day of rest, no less. 

There is no rest for a salaried marketing employee.

There is nothing uncommon about what Urban Outfitters asked salaried employees to do. Sure, it appears distasteful. Sure, it might be a way for the finance team to celebrate yet another cost-cutting measure. But most salaried employees are already being abused through the magic of a sixty-hour workweek and non-stop on-call availability. 

The question isn't whether what Urban Outfitters is doing is right/wrong. The question is how did we get to a point where salaried employees are expected to work sixty or more hours a week, seven days a week no less - essentially not being paid for a third of the work they already do? It's harder to answer that question. It's easier to point to Urban Outfitters instead.

Look at your own career. How many hours north of forty do you feel compelled to volunteer, for free?

October 08, 2015

How Do I Know If I Have A Merchandise/Age Interaction Problem?

This one is simple, folks.

Go run your comp segment analysis, segmented by age of customer. Look at 2x buyers, and if you are a cataloger, segment by customers age 18-49, customers age 50-64, and customers age 65+. If you don't have enough customers age 18-49 to run the analysis, you already know your answer.

But if you do, and you see this (on an annual basis), then you have a merchandise/age interaction problem.
  • 18-49 Customers:  This Year Comp = -10%. Last Year Comp = -9%.
  • 50-64 Customers:  This Year Comp = -3%. Last Year Comp = -4.
  • 65+ Customers: This Year Comp = +7%. Last Year Comp = +4%.
  • Overall 2x File: This Year Comp = +1%. Last Year Comp = -1%.
This is the signature. Older customers love your merchandise. Customers under the age of fifty are running (not walking) away from the business.

On the surface, the business is fine ... flat comps over two years.

But under the covers, younger customers do not like the assortment, while older customers crave the assortment.

Run the analysis. It isn't hard to run a comp segment analysis. Seriously. Go do it!

And if you don't have the resources to run the analysis, contact me (kevinh@minethatdata.com). Contact me soon, too. You want the results before you get too far into 2016 to do anything about it, right?

October 07, 2015

How Algorithms Are Evolving Our Businesses

For so many catalogers, the issue in 2015 is new customer acquisition. It's become terribly hard to acquire new customers.

There's a good reason for this. 


Algorithms need data.

The smartest companies get you to pay them to collect data. Think Google - you pay them $0.60 a click, and in the process, they get to collect data about the person who clicked. Oh, and they get to collect data about every non-click as well. You fund the non-clicks. So you pay Google money, Google sends you clicks, and then Google asks you to use their software to analyze whether the clicks you paid for purchased or not. When you use Google Analytics, you give Google more data about how your customers behave, data they would not normally receive. All of this data is algorithmically used by Google to benefit Google.

As a result, Google knows that the catalog customer is 62 years old.

You pay Facebook, too. You were told to build your audience on Facebook, organically, for free. Then, when your audience peaked, Facebook figured out how to get you to pay to speak to the audience you helped Facebook create. Nicely done. Facebook takes your money, and slices and dices your customer based on behavior within Facebook and the sliced/diced data you indirectly pay some of the co-ops for ... yes, you give your data to some of the co-ops for free, they make you pay for sliced/diced names, then they partner with Facebook to create even more thorough profiles of customer behavior ... offline, online, and within Facebook. All of this data is algorithmically used by Facebook & some of your co-ops to benefit Facebook and some of your co-ops.

You pay Amazon, too. You sell your products there, allowing Amazon to collect a fee on each purchase, and more importantly, collect data on how your customers behave when shopping for your products on Amazon. This allows Amazon to craft algorithms to target your customers.

You pay the retargeting folks ... those folks track your customers all over the web, algorithmically determining what your customer should see as your customer travels the wide expanses of the online ecosystem.

Each of the 000s of companies you are paying are building algorithms, using algorithms, or are letting machines learn how to build their own algorithms.

The algorithms interact with each other, creating unexpected outcomes.

Catalogers know this all too well.

In the past five years, the average age of the catalog shopper has gotten old, quickly. The algorithms are interacting with each other. They know that the catalog shopper averages 62 years old, often older. The traffic Google and Facebook and the co-ops and the retargeters and affiliates and countless others send you represent traffic that peculated to the top of the algorithm flow chart. Those customers are older. Older customers have specific merchandise preferences.

Now your own algorithms take over, and further impact you. Sure, you call it "reporting", but be honest, it's just a simple algorithm. The co-ops and Google and Facebook and the retargeters and affiliates and countless others send you older traffic, and the older traffic has specific merchandise preferences. In 2000, those were the preferences of a 47 year old. That customer cared about mainstream, middle-aged merchandise. Your merchants responded, offering additional mainstream, middle-aged items that mainstream, middle-aged customers wanted. But today, your merchants offer stuff that older customers like, and your merchants offer stuff that younger customers like. The 62 year old sent to you by the vendor community sees each assortment, and buys the stuff that older customers like. Your algorithm (reporting analyzed by your merchants) clearly shows that stuff that 62 year olds like is the stuff that is selling best. Your merchants respond by getting more of that stuff - the opposite of the "fast fashion" movement that is fueled by a mobile vendor ecosystem that interacts with retailers catering to a younger customer.

If you are a catalog that has been around for at least twenty years, do me a favor. Go pull out a catalog from 1995, and compare it to a catalog from 2015. Objectively look at the styles featured in the first twenty pages of each catalog. Tell me that you are still marketing to a 47 year old customer, after you look at the styles offered and the models wearing them.

The algorithms ... complex machine learning algorithms at Google all the way down to merchandising reporting ... are interacting with each other, driving the age of your customer base north, driving the merchandise assortment to something that an AARP member would crave. Your merchandising team buys more of the stuff that an AARP member would like, and as a result, Google and Facebook and the co-ops all respond in kind, sending names that would like this product, driving your merchandise assortment even further from the mainstream.

You won't find many catalog vendors or catalog consultants or catalog gurus who talk about this. They don't want you to know this, because if you knew this, you'd question your long-term viability, and you'll question your circulation plan going forward. When you question your long-term circulation plan, you put vendor livelihoods at risk. They don't want that. So nobody talks about this topic. Everybody keeps quiet. 

And that does a real disservice to our businesses, don't you think?

Talk about this topic. Think. Have an honest discussion. Or not. Either way, the algorithms are sending your business down a path you didn't anticipate five years ago. Take control back from the algorithms. Please!

October 06, 2015

Hiding The Numbers

Then Bed Bath & Beyond honestly tells what is happening (most retailers don't).
  • E-Commerce = +25%.
  • Store Comps = -1%.
If you remember your high school algebra, then you know that the ratio above suggests that e-commerce sales are +/- 6% of total (remember, new stores are not counted in store comps, so the actual answer of 6.5% is overstated).

Why do retailers hide poor store comps in a blended average of store comps and e-commerce growth?

Well, as your e-commerce channel grows, your blended comp grows, as long as e-commerce keeps growing.

When e-commerce is 6.5% of the total, the blended average of +25% and -1% is +0.7%.

When e-commerce is 12% of the total, the blended average is +2.1%.

When e-commerce is 20% of the total, the blended average is +4.2%.

As retailers figure out how to grow e-commerce, store sales decrease ... and as store sales decrease, the reporting changes, skewing to e-commerce, enabling the perception that growth is fantastic.

Regardless, in every situation, store sales are in decline - and eventually, stores are closed - they have to be closed. When a store is closed, it is not included in the comp measurement.

In other words, as e-commerce gobbles up commodity-based items that used to sell in stores, e-commerce drives retail comps further negative while growing e-commerce, causing the business to report positive comps as it closes stores, accelerating the mix to e-commerce further, causing the business to continue to report positive comps as the business contracts.

That's the future. That's what is coming ... e-commerce growth and store closures and business contraction, all hidden with an overall and ever-growing positive comp store sales measure. #Omnichannel!!

October 05, 2015

The End of the Baseball Season

I grew up in Wisconsin, and I live in the Pacific Northwest. This means that I follow two teams.
  • The Milwaukee Brewers.
  • The Seattle Mariners.
By the time we got to May 1, there was little reason to watch either team.

Now think about how each team dealt with their challenges:
  • Milwaukee fired their Manager before April ended. They traded their best player away before the July trading deadline. They restocked their farm system in July and August. They announced that their General Manager was retiring, and hired a new General Manager (30 years old) in September, an individual with an analytics background. They gave extensive playing time to minor league players in September.
  • Seattle waited and waited and waited for something good to happen until late August. They then fired their General Manager a month past the trading deadline, and hired a new General Manager in late September.
Which team got a head-start on the future?

Ok, how about you? It's October. You pretty much know how your year is going to turn out, barring a miracle. If your business is below plan, are you taking the approach Milwaukee took, looking toward the future, or are you being like Seattle ... hanging on, not making changes, hoping for things to change ... not making changes until it is very late in the season?


October 04, 2015

The Data Is Wrong!!

Did you see this article from Friday (click here)?

First, look at the ad next to an article about bad weather data:

Alanis Morissette would agree it is ironic that an article talking about how terrible initial data conditions lead to terrible forecasts is supported by an ad about a conference featuring technology that uses incomplete data to put ads in front of customers that are never clicked on - a technology that you use to bid to pay higher-than-necessary rates to put an ad in front of a customer that seven in ten thousand (i.e. nobody) will respond to.

When your co-op sales rep tells you that they have a new "coherence model" (or whatever name they call the next version of models that are cousins to the models used in 1995) and that they're seeing breakthrough results, you have to question the statement.
  • Is the data being used to create the model "right" in the first place? Ask your co-op sales rep to see the data being used as an initial starting point.
  • Are the models that sit on top of the data "right" in their assumptions?
  • Ask the co-op rep to share the model coefficients with you - it's your model, you are paying for it, so you should get to see what you are paying for, right?
Ask your co-op sales rep to answer each question. If you don't get a valid answer to any of the three questions (and you probably won't), then ask yourself why these folks are still trusted partners? Why would your trusted partner hide the truth from you? (and co-op folks, this works in reverse - if your clients won't share profit/loss data on the names you give them, are these your trusted partners?).

Let me tell you a story. I was asked to visit a company and referee a discussion between vendor statisticians and in-house statisticians. What a mess! The vendor used the same data that the in-house statisticians used. But each party transformed the data in different ways, so their starting points were fundamentally different. Different starting points mean different outcomes (like in the example with hurricane forecasts). And different starting points mean different modeling approaches. Each party utilized fundamentally opposite tactics. The vendor had hundreds of variables in the model, optimizing profit. The in-house statistical team had a half-dozen variables optimizing sales. Again, both tactics are wrong (never use 100s of variables in a model, the last several hundred have no impact - the concept is called 'parsimony' ... and modeling sales instead of profit means that you reward customers who return a lot of merchandise and/or purchase via discounts/promotions), and because both tactics are wrong, both tactics yield bad outcomes. Of course, both tactics are doomed because they start with bad data (i.e. bad variables).

But man, what an argument, where two parties who are wrong yell at each other about how wrong the other side was! It almost sounded like our political process.

If your in-house statistician won't share the details of the model building process with you, find a new in-house statistician.

If your vendor co-op or retargeter won't share the details of the model building process with you, find a new vendor co-op or retargeter.

If your attribution vendor won't share the intimate details of the modeling process used to dictate your advertising investment algorithm, then fire the attribution vendor and find a new one who is honest and transparent.

In weather, we can clearly see when one modeling process, #datadriven and all that, is still woefully wrong.

In marketing, do we know if our trusted analytics partners are right or wrong?

October 01, 2015

Highly Targeted Digital Ads That, Well, Just Read The Article.

Look at the ad that Google decided to interrupt my viewing experience (of the VW scandal) with:

It's a local Lexus Dealership ad featuring a used 2013 Volkswagen!!! That's exactly the car I want to buy when I'm viewing a video about how VW cheated their customers and the rest of us who have to breathe the post-processed air exhausted out of VW cars.

Remember stuff like this the next time the sales person arrives in your office, promising to use digital marketing to optimize the customer experience via the right ad to the right customer at the right time.

September 30, 2015

"The Eagles", Featuring "Catalog" Craig Paperman

Yup, this is fiction, albeit dripping with truth. If this isn't your cup of tea, move along, we'll have more for you tomorrow.

A Discussion With "Catalog" Craig Paperman

Kevin: You don't look very happy today?

Craig: I'm not happy.

Kevin: What could possibly be frustrating you on a gorgeous Fall morning?

Craig: It doesn't work anymore.

Kevin: What doesn't work anymore?

Craig: I did everything I was supposed to do.

Kevin: Specifics, please.

Craig: They told me if I integrated my catalog and my website that customers would love me.

Kevin: And?

Craig: Sales didn't grow.

Kevin: Oh.

Craig: I thought that omnichannel customers spent nine times more than single channel customers?

Kevin: That's what they tell us.

Craig: My team worked hard to create a seamless, frictionless omnichannel customer experience. Same merchandise across channels, same pricing, same promotions. It's beautiful!

Kevin: Great!

Craig: Our share of omnichannel shoppers increased from 3% to 22%.

Kevin: If omnichannel customers are worth nine times a much, then simple algebra dictates that your business should have more than doubled.

Craig: But nothing happened. If anything, after accounting for inflation, my business is shrinking.

Kevin: #OhBoy.

Craig: How is that possible?

Kevin: How is what possible?

Craig: I did what the experts told me to do. And it didn't work.

Kevin: Maybe the experts were wrong? Or maybe they weren't experts to begin with. Maybe they were just selling you a message that you wanted to hear, a message that they generated profit from.

Craig: When I ask industry experts, they tell me it is my fault.

Kevin: Of course they do.

Craig: I sat down with my co-op sales rep. She told me to focus on their new "coherence" model. She said that clients were experiencing breakthrough results. She told me that JCP used it in their new catalog. She said it was "proof" that cataloging is the linchpin of the omnichannel experience.

Kevin: And?

Craig: Not so much.

Kevin: Did sales increase?

Craig: Response rates increased from 0.55% to 0.58%.

Kevin: Wow!

Craig: But the average age of the customer we acquired was still 62 years old.

Kevin: Oh.

Craig: Why are my co-op customers always 62 years old? And getting older?

Kevin: Because you are using catalogs as a linchpin in your omnichannel strategy.

Craig: Oh come on. Customers love paper.

Kevin: 62 year old customers love paper.

Craig: That's not true. Five percent of our customers are under the age of forty-five.

Kevin: Half of the population in the United States is under the age of forty-five.

Craig: That can't be true.

Kevin: Would the Census Bureau lie to us?

Craig: Would the Government lie to us?

Kevin: Think about it this way. Who is your favorite band?

Craig: The Eagles.

Kevin: Let's say you hosted a party. You played The Eagles on that speaker shaped like a faux rock in your back yard. You played The Eagles on your home theater. You played The Eagles on that bluetooth speaker in your office. You integrated the entire listening experience across the house.

Craig: Giving my listeners a "Peaceful, Easy Feeling".

Kevin: Right. You're giving your party attendees an integrated omnichannel listening experience. You are even using a bluetooth speaker - employing digital technology along with your old-school home theater. Nicely done. Who would be most likely to listen to the music?

Craig: My friends would love it.

Kevin: Precisely. How about your kids, and their friends?

Craig: They'd probably put their earbuds in and listen to something on Spotify.

Kevin: Or they'd leave the party.

Craig: Maybe.

Kevin: They wouldn't enjoy listening to The Eagles, would they?

Craig: I could sprinkle in some Boz Scaggs. Make a playlist. Bread. Jefferson Airplane. Boston. I'd "get jiggy" with it.

Kevin: Do you know who Jason Derulo is?

Craig: Jason Alexander?

Kevin: Never mind.

Craig: What does this have to do with my business?

Kevin: This has EVERYTHING to do with your business!

Craig: I don't get it.

Kevin: You provided a wonderful omnichannel listening experience at your party. You integrated music channels across your home and yard. And then, after doing all of the hard work to integrate everything and make everything the same, you drove away every guest under the age of 50 because you played The Eagles at your party.

Craig: But people love The Eagles. They're one of the greatest bands of all time.

Kevin: Your target audience loves The Eagles.

Craig: Alright.

Kevin: Don't you eventually need new friends?

Craig: Now that you say it, I am sick of that gossipy Agnes Myers. She's always peeking over my fence, looking at my faux rock speaker.

Kevin: If you need new friends, you can play The Eagles, and maybe you'll find new friends who share your current musical interests. Or you could play Jason Derulo. But if you play Jason Derulo, you're going to have different people, younger people, at your party. Their needs are different. Are you willing to take care of their needs?

Craig: I hear they love Mountain Dew.

Kevin: Red Bull.

Craig: Whatever.

Kevin: You're proving my point.

Craig: As long as younger people love nachos, I could probably adjust my playlist.

Kevin: An omnichannel strategy focuses on your core customers. Those are the people who share your interests. You do everything for them, and in the process, you shut out everybody else. Do this year after year, and your customer base ages, along with you. Pretty soon, your merchandise only appeals to your core customer.

Craig: Maybe I could burn a CD that has The Eagles and Madonna and Carrie Underwood on it?

Kevin: Again, that's the problem with an integrated, channel-based omnichannel strategy. When we stretch, we alienate our core audience. We offer Madonna. The customer wants "The Eagles". How can we ever get to Jason Derulo if we can't build the bridge from The Eagles to Peter Cetera to Cher to Alanis Morissette to Sheryl Crow to Pink to Katy Perry to Fall Out Boy to Jason Derulo?

Craig: Isn't it ironic that you didn't mention Skid Row? They were awesome!

Kevin: #OhBoy.

Craig: So how do I get out of this mess? I'm left with a 62 year old customer, and no matter how hard I work with the co-ops, I keep getting 62 year old customers?

Kevin: You have to offer a merchandise assortment that appeals to a younger customer, and then you have to engage with those customers in the channels they prefer. And I cannot believe I just used the marketing buzzword "engage" in an actual conversation.

Craig: But if I do that, I'll alienate my 62 year old customer, right?

Kevin: Yes. It's exactly like playing The Eagles at your party.

Craig: So then I'm stuck. What a waste of time. Thanks for nothing.

Kevin: Why can't you host two parties? One for those who love The Eagles, and one for a different audience?

Craig: But that goes against the omnichannel playbook. I'm supposed to integrate everything.

Kevin: Build two brands. Your current brand generates profit from your current customer audience. Build a second brand that appeals to a different audience.

Craig: Can I create catalogs for that audience?

Kevin: We're right back to our parable about The Eagles.

Craig: But I love mailing catalogs. My printer says that catalogs are making a comeback.

Kevin: And Don Henley has a new album coming out. He's making a comeback.

Craig: See what I mean? Everything old is new again! I'll just keep doing what I'm doing. Everything will be fine. Now, if you will excuse me, I need to plan for my Summer 2016 merchandise assortment.

Kevin: Mobile brands are dynamically merchandising offerings to unique customers in real time, and you're busy planning your Summer 2016 merchandise assortment?

Craig: My paper rep needs a commitment as soon as possible. She says she can get me a 5% volume discount if I plan my circ levels through the end of 2016 and then promise to not alter the circ plans in 2016. It makes good business sense to plan ahead, don't you think?

Kevin: #OhBoy.

September 29, 2015

Deadline = Today!!!! Hustle!!!!

Today is the deadline to get in on the very first run of the MineThatData Elite program.

Get in. Now!!!! Be a pioneer. Blaze the Oregon Trail, don't wait until I-84 is built and then jump in and take advantage of the hard work of others.

If you want to understand what is happening to merchandise productivity ... and quite honestly, I have no idea why you wouldn't want to understand what is happening to merchandise productivity ... send me an email and get busy (kevinh@minethatdata.com).

If you want to understand the blended average (average of straight average across participants and weighted sales average across participants) of merchandise productivity across clients, this is the only place you're going to find out. The only one. Your co-op, who has all the data and could tell you what is happening in six seconds won't budge. This is the place where you find out what is happening in the competitive landscape.

The program has three runs per year.
  • June - July - August - September run ... participation due by 10/1, data/payment due by 10/15, analysis delivered by 10/31.
  • October - November - December - January run ... participation due by 2/1, data/payment due by 2/15, analysis delivered by 2/28.
  • February - March - April - May run ... participation due by 6/1, data/payment due by 6/15, analysis delivered by 6/30.
At just $2,000 per run, the work is completed, virtually for free! Why wouldn't you participate? Seriously - what would stop you?