April 26, 2015

How Does The Catalog Influence Sales? 2015 vs. 1995 ... A Cataloger Must Read

Ok, folks, this is becoming a really big deal. In nearly every project I work on, the way customers, channels, and merchandise all interact has changed, and the changes are not well understood. So let's explain the changes.

Let's pretend you have three product lines ... WIDGETS ... WUDGETS ... and WEDGETS.

Let's pretend you mail one catalog a month ... a 96 page catalog.

In 1995, your catalog merchandise assortment was as follows:
  • 64 pages of WIDGETS.
  • 32 pages of WUDGETS.
  •   0 pages of WEDGETS.
In 1995, based on your advertising / merchandising strategy, here's what you sold:
  • $5,000,000 of WIDGETS.
  • $2,500,000 of WUDGETS.
  • $0 of WEDGETS.
  • $7,500,000 total.
Do you see what happened there? Your sales were roughly similar to the page distribution offered. You didn't offer any WEDGETS in your catalog, and you didn't sell any WEDGETS. 

A generation of catalog marketers grew up with these rules. The rules became hard-coded. If you are in a meeting, and you are dealing with a catalog professional older than sixty years old, the hard-coding becomes problematic, doesn't it?

In 2015, the world is fundamentally different. Let's review what I see across all of my projects.
  • 64 pages of WIDGETS.
  • 32 pages of WUDGETS.
  •   0 pages of WEDGETS.
But in 2015, sales happen two ways (assuming you don't have a retail store ... if you do, then the story gets even more interesting). First, we have sales attributed to the catalog.
  • $2,300,000 of WIDGETS.
  • $1,300,000 of WUDGETS.
  • $300,000 of WEDGETS.
  • $3,900,000 total.
What do you see in that summary? What is different? Discuss!

And then, second, we have sales that happen online, without the aid of a catalog. Yes, a ton of sales happen even if catalogs are not mailed. Your mail/holdout tests prove that this happens.
  • $1,500,000 of WIDGETS.
  • $1,500,000 of WUDGETS.
  • $600,000 of WEDGETS.
  • $3,600,000 total.
What do you see in that summary? How did sales vary?

So we add catalog-driven sales to pure online marketing and organic sales, and we get the following story for 2015:
  • $3,800,000 of WIDGETS.
  • $2,800,000 of WUDGETS.
  • $900,000 of WEDGETS.
  • $7,500,000 total.
And to repeat, here is the story that's been hard-wired into the minds of many catalog professionals:
  • $5,000,000 of WIDGETS.
  • $2,500,000 of WUDGETS.
  • $0 of WEDGETS.
  • $7,500,000 total.
Do you understand what happened there? Several things happened ... several moving parts, right?

In 1995, if you didn't feature an item, you didn't sell the item. In 2015, if you don't feature an item, you will still sell the item online ... and I know, I know, there's going to be an outcry of anger from many catalogers ... "Kevin, you're wrong and I'm going to tell you why, we have internet-only items and they don't sell at all, so you're an idiot." Might I posit that you aren't featuring internet-only items properly? How often are they featured on the home page? How often are they featured on key landing pages? How often do they appear in email campaigns? Do you feature those items in magazine ads? Television? Pop-up stores? Amazon? When you bury items on the website, of course the items won't sell ... but they aren't selling because they aren't in the catalog ... they aren't selling because you aren't even trying to sell them!!!!

In 1995, 100% of the sales happened because you mailed catalogs. In 2015, 50% of the sales happen because you mail catalogs (20% of those catering to a 40 year old customer, up to 70% for those catering to a 70 year old customer).

In 1995, you had one audience ... a catalog audience ... and that audience had a consistent merchandise preference. In 2015, you have multiple audiences, different audiences by channel (be very skeptical of the omnichannel crowd's suggestion that you have one audience ... look at sales by channel ... sales are fundamentally different by merchandise category ... strongly suggesting different audiences). Why not serve multiple audiences with different merchandise assortments?

In 1995, WIDGETS dominated, capturing 67% of sales. This was because there was one audience and one advertising strategy. In 2015, WIDGETS capture less than 50% of sales. This happens because you have multiple advertising strategies, varied customers across channels, and featured WIDGET items in the catalog drive WEDGET sales online. When I worked at Nordstrom, we learned that you didn't have to feature MENS merchandise in a catalog ... ever ... mail/holdout tests by product category showed that featuring WOMENS items in the catalog caused customers to shop MENS online and in the store. Have you performed a comparable analysis for your business?

In 1995, the catalog merchandise assortment determined everything. In 2015, the catalog merchandise assortment may well be holding back the growth of your business, especially if your merchandising and marketing teams ignore the true merchandise assortment sold online without the aid of a catalog.

I see these trends in nearly every project I perform. The longer we hold on to our catalog heritage, the longer we stunt growth of merchandise categories that appeal to online buyers. We hurt the future by holding on to the past.

Does this make sense to you?

Do you have reporting to help you understand this dynamic?

Contact me (kevinh@minethatdata.com) if you want to better understand what is happening in your business.

April 24, 2015

Cabela's Campaign

Two things that need to be pointed out (click here):
  1. The article header says "amid strong sales" ... then the author buries at the bottom of the article the fact that retail comps were -1.3% (i.e. the opposite of strong). Though to be fair, currency changes do impact business.
  2. The ad agency running the "disconnect from mobile" campaign then encourages users to use mobile to share their "disconnect from mobile" experience with their friends.
#Sigh.

April 23, 2015

Your New Department - First 90 Days

Maybe you just took over a department? It's your first crack at dealing with ten or more individuals. You probably feel overwhelmed, like the new Director of Marketing in this image. But you're also optimistic and talented, like the new Director of Marketing in this image.

The first ninety days in this new job are the most important ninety days, make no mistake about it!

I took over a department at Nordstrom Direct, way back in 2001. On my very first day in the job, a pair of individuals entered my office, and asked me to fire a person. Within a half-hour, the person who these folks wanted me to fire entered my office, and asked me to fix the department. Who do you think I sided with? And what do you think those introductory statements said about each employee?

Make it clear to each employee you inherit that you are using week one to "evaluate and plan". You are not making any decisions that first week. You are getting to know people. Observe work habits. See who leads in meetings. Who gets along? Who hates other people? Who gets run over by other departments? Who produces accurate work, and who produces inaccurate work? Who produces, period?! Document everything.

Sit down with your Human Resources team, and ask for all performance reviews. Also ask for documentation about each employee ... stuff like interpersonal problems, office relationships, problems with the law, the whole nine yards. Some of it will read like an episode of Downton Abbey.

Then craft a plan.

Create annual goals and objectives for each employee. These are the goals and objectives you will use to evaluate each employee. Set expectations from day one, folks. Then, every Monday morning, produce a dashboard that shows how your department is progressing against your goals and objectives.

If you take over on a Monday, make sure you have a mandatory department-wide meeting the following Monday. Have somebody from Human Resources in the room - this sets a tone that you are dead serious about having a well-functioning department that works with honesty and integrity. It also prevents inaccurate gossip - you don't want the malcontents on your team to go out there and publicly lie about what was said in the meeting.

In this meeting, set expectations. Be firm. When I took over the most dysfunctional team I'd ever observed (Nordstrom 2001), I made it very clear what I expected. In my case, this is what I shared:
  • We are a family. We love each other.
  • When we disagree, we disagree internally. Publicly, we are a unified and confident team more than willing to defend the work of each individual in the department.
  • Say whatever you want in my office and get it out of your system.
  • We are here to serve.
  • We are here to generate a ton of profit (I then outlined goals and objectives and told everybody what work they would focus on for the next year).
  • We are going to work hard - no more three hour work days.
  • We pursue excellence and innovation.
  • Our work is accurate and trustworthy.
  • We do not have a political agenda.
  • If you are not on-board with this agenda, please go find a new job as soon as you can.
You'd think a message like that would be well-received.

You'd be wrong.

The message was received much in the same way a hive of bees would receive a dozen rapidly fired darts at their queen. Oh, the message created a buzz alright. One employee asked me to "make things like they used to be". Another quit. Then another. Then another.

After your first two weeks, you can begin the process of building the department in your image. Do not copy Steve Jobs, or your Mentor. Do it your way.

Pay attention to those who are not "onboarding", to use a term a former boss enjoyed using, and determine why they are not onboarding.

Each week, reinforce your message via your dashboard. Show every employee where the department stands against goals and objectives. Reward those who adopt your program. Overpay for talent now, because your compensation department will put the clamps down on you soon. Make it clear to everybody else that they are not meeting expectations. Hire folks who you trust, who are talented, and who implement your program.

Never waver.

Always communicate - and repeatedly communicate the same message. Your employees seldom hear what you want to communicate - so the same message said 137 times has a better chance of being understood how you want the message to be understood.

Once you get past your first ninety days, you've begun to put your program in place, and you'll learn quickly whether you are going to be successful or not.

But those first ninety days are critically important - the most important of any period. Make good use of your first ninety days.

April 22, 2015

Lousy Website Optimization

This problem keeps coming up in the projects I work on.

I create a model that predicts how many orders a customer will place in the next month.

Then, I create a model that predicts how many days (called "monthly visits" in this example) a customer will visit your website next month.

Finally, I segment customers based on the two predictions.

The lower left cell (green) represents customers who are unlikely to purchase, and are unlikely to visit. Notice that this cell has the second best daily conversion rate (purchases / days visited).

The upper left cell (orange) represents customers are are likely to purchase, but are unlikely to visit. Notice that this cell has the best daily conversion rate (5.5%). In many ways, this is the customer your visit-centric metrics are trying to optimize ... their conversion rate is good, but they don't use your website much.

The lower right cell (blue) represents customers who are not likely to purchase, but are likely to visit. You'd expect a lousy daily conversion rate, and you get precisely that (1.9%). Marketers HATE this cell ... they do anything they can (discounts/promotions/begging) to get this customer to purchase. You won't get this customer to purchase ... this customer likes to visit, to browse.

The upper right cell (yellow) represents customers who are likely to purchase, and who are likely to visit your site often. This is the dream customer - fully engaged with the site and very willing to purchase. What is the daily conversion rate for this segment? A paltry 2.1%. Your best customers have horrible conversion rates, in this example (happens all the time, folks).

Your staff will work overtime to get the customers in the upper right quadrant to purchase NOW!! Cart abandonment programs, programmatic approaches & retargeting, keyword bidding, discounts/promos in email campaigns. STOP IT! Just STOP IT! These customers already love your brand - they just love it so much that their visits overwhelm their purchases. You DON'T CARE that this customer has a low conversion rate ... so what?! Collect the profit.

Show of hands ... how many customers do you have that fit into each cell above? If you don't know the answer, send me an email (kevinh@minethatdata.com) and I'll get busy creating the cells for you.

April 21, 2015

Triggers & Grids: Combining Attributes

Let's look at an example ... in the table below, I illustrate Logistic Regression coefficients for the likelihood of a customer buying from email marketing in the next twelve months. The rows represent recency  ... the columns represent prior purchase channels.


Let's pretend we have a customer who has only ever purchased one time, and it was via email marketing, and the customer spent $100, and the purchase happened one month ago. For that customer, the probability of buying from email marketing in the next year is ... (-5.216 + 2.423 + 1.841*(100/1000)) ... we obtain a logit value of -2.519, which when transformed (EXP(-2.519) / (1 + EXP(-2.519)) = 7.5%.

Now let's pretend that the customer also purchased ($100) via Amazon in the past month ... the equation changes to (-5.216 + 2.423 - 0.031 + 1.841*(100/1000)) = -2.550, which is then transformed (EXP(-2.550) / (1 + EXP(-2.550)) = 7.2%.

Do you see what happened there? The very fact that the customer just purchased from Amazon actually caused the customer to become less likely to buy via email marketing. #OhBoy.

Each of our businesses possess customers who exist within an ecosystem. A very interesting ecosystem! We've been trained that each incremental purchase is good. Most of the time, each incremental purchase is good! But sometimes, odd dynamics occur. We need to understand odd dynamics.

In subsequent posts, I'll show you how these models can be used to combine attributes, and when attributes are combined, we can understand how customers behave and evolve as we promote different channels. The activity leads us to create different trigger strategies for various customers.

For instance, here are a set of customer attributes (the customer bought via the phone 10-12 months ago, spending $100), and the predictions by channel.


This customer has a 9.9% chance of buying via phone next year ... that's 60% of all outcomes. Now, look at what happens when the customer reactivates via Amazon ... becoming a 0-1 month $100 Amazon customer and staying a 10-12 month $100 Phone customer.


In the short term, the Amazon purchase helps catalog responsiveness ... trigger off a catalog, folks!

But not so fast. Let's let one more month pass ... now the Amazon purchase is 2-3 months ago.


Within just a month, the Amazon purchase helped phone response (catalogs), then hurt phone response (catalogs). Also, look at what happens to Search response in each grid ... low ... then high ... then higher. Yes, the Amazon purchase pushes the prior catalog-centric buyer online, where the prior catalog-centric buyer "engages" in online activities that will cost you even more money.

In other words, the Amazon purchase should trigger a catalog, and then, it is quite possible that you might cut back on mailings because response drops and paid search response increases, costing you more money.

So this is the stuff we're going to talk about ... your customers interact with your business in fascinating ways, yielding an ecosystem that is not well understood. By combining attributes in a Logistic Regression equation, we set off all sorts of interesting ecosystem findings, don't we?

April 20, 2015

The Customer Resume

Allow me to tell you a brief story. Let's go back to November 1990. Yes, 1990. I was in my first week of work at Lands' End. One of the aspects of my job (statistical analyst ... today that job would be titled a digital analyst or a data scientist or a growth hacker) was to audit my statistical models.

I submitted a request each Friday to print the customer purchase resume of one of every ten-thousand customers. Over the weekend, the customer file was scored, and when I arrived at work on Monday, a stack of printed customer records magically appeared on my chair. Every Monday morning, I thumbed through each record, hand-calculating that my scores were being applied properly.


The best part of the process was to watch how customer behavior evolved. Not overall customer behavior, but rather, the behavior of an individual customer. I can still remember customer # 1000004 ... her record was always on the top of the stack (no, I am not going to share her name with you, though I can still remember her name). She hadn't purchased in a long time, so every Monday there was drama ... had she reactivated over the past weekend?

Every marketing employee should be required to look at a customer resume. Every one.

What do you see when you look at the resume at the beginning of the post? Be honest. Study it. How does this customer behave? This isn't much of a "digital" customer, is it? Or a seasonal customer. But this customer is a very, very good customer, make no mistake about it. So enjoy this customer - quit demanding that this customer engage with you digitally. Collect profit. Ok?

By the way, there was a Friday back in 1992. I submitted my request to print one out of every 10,000 customers ... except I typed in 1 in every 100 customers. On Monday morning, our IT team, who clearly saw the request and knew I made a mistake, elected to initiate a "teachable moment" and dutifully printed the resume of one out of every 100 customers. They deposited the 40,000 sheets of paper in my office. You learn a lot when you audit your model scores, don't you?

Catalogers - Read This


This person talks about his startup and finding customers on Facebook. When performance (due to cost) struggled, he decided to go find new customers elsewhere.

The next time your favorite co-op shows even further reduced performance and takes your names for free and sells them to an online brand to help the online brand put you out of business, why not do something about it other than complain? Do what this individual did - try something different.

April 19, 2015

Triggers & Grids: Grading Strategies

Modern customer behavior is perceived to be much more complicated than it was twenty years ago. That may or may not be true.

Twenty five years ago, you created several hundred RFM segments and you called it good. Today, your three hundred RFM segments would overlay against twenty marketing channels, getting you ever closer to an infinite number of segment combinations. Is it any wonder folks want you to have a "one-to-one" relationship with a customer? It's become hard to segment the customer in a meaningful way.

It is perfectly reasonable to simplify the number of dimensions you deal with. I create simple models ... in the case above, a model for a product line called "Widgets", and a model for a product line called "Wudgets". The predictions for each model are reduced to five segments ... sort of like when you were in school ... A/B/C/D/F.

Then, I measure future "Widget" spend across the A/B/C/D/F grades for "Widgets", and A/B/C/D/F grades for "Wudgets". In other words, let's pretend that the customer is a prior "Widgets" buyer, but has never ever purchased "Wudgets". We'd look across the "A" row for Widgets, and then align with the "F" column for Wudgets ... the customer is worth $44.38 to the Widget merchandise category.

Say you have an email marketing campaign for Widgets ... you know that the customer must be worth at least $30 of future spend to generate a productive Widget email campaign. Even if the customer has not purchased Widgets in the past ("F"), a recent Wudget purchase might move the customer into A/B territory for Wudgets ... and when that happens, the customer has sufficient value to email the Widget campaign.

Better yet, you can build Wudget purchase intelligence into the Widget model ... and by doing so, you eliminate the need for the grid altogether ... you trigger/target based on the Widget grade.

April 16, 2015

Sports Commerce Session #2: Draft and Develop

In our second session, I describe how "draft and develop" strategies in sports are similar to "customer acquisition and customer retention" in e-commerce / retail. Click here if you do not see the video box below.


April 15, 2015

Incremental Value

Let's say I want to move 13-24 month 1x buyers to a second purchase.

How much might I be able to spend to make this happen?

In our table, the average 13-24 month 1x buyer is worth about $13.50.

In our table, the average 0-12 month 2x buyer is worth about $71.65.

Intuitively, you might say that you gain $58 of value, so you can spend a fortune.

Nope.

There are two things we need to know.
  • Actual repurchase rate of 13-24 month 1x buyers.
  • Incremental percentage that we will convert with incremental marketing activities.
  • Percentage of demand that flows-through to profit.
Let's pretend that the annual repurchase rate of 13-24 month 1x buyers is 10%. Let's also pretend that we can increase the 10% annual repurchase rate to 12% by performing various marketing activities. Finally, let's assume that 35% of demand flows-through to profit. We now have the pieces necessary to determine how much we can invest.


Look at the "Marketing Cost" line ... you could invest an additional $0.77 per customer, and if you can achieve a 20% increase in repurchase rate, the math yields more profit.

This is how a modern marketer can leverage lifetime value style metrics to improve business performance. In our example (assuming that we can truly get a 20% increase in repurchase rates by marketing more to a customer), we are able to grow the active 2x buyer file - and that's a good thing, right? These customers will spend a ton of demand next year.

Have your analytics team run this analysis for you today. If they cannot run the analysis for you, contact me (kevinh@minethatdata.com), and I'll gladly do it for you.

April 14, 2015

But A Recent Buyer Is A Good Buyer, Right?

For the most part, a recent buyer is a good buyer ... right?

Let's take a second look at the grid from last Friday.



This table measures direct-channel value for a business that has retail stores and an e-commerce website. So read down the 7-12 month direct recency column ... if the customer has never purchased from retail, the customer is worth $42.66 demand to the direct channel. But now, the customer (surprisingly) walks into the store and buys something. Everybody is happy! Everybody, that is, except for those who manage the website.

Why?

The value of the customer to the website went up, quite a bit, from $42.66 to $85.97. But the customer is nowhere near as valuable as a recent online buyer (between $141.77 and $303.42).

I know, I know, the omnichannel experts will tell you that this doesn't matter.

It matters if it is your job to forecast online sales, right?

It matters if it is your job to forecast online inventory, right?

It matters if it is your job to forecast online traffic, right?

The omnichannel movement is sweeping vital business details under the carpet. Omnichannel advocates don't care where the customer buys.

Your CFO cares deeply where the customer purchases ... where the customer purchases dictates future sales, and future sales require staffing and inventory and proper forecasting techniques ... and ... they require proper triggers/targeting strategies. In this case, the customer just bought from the store ... why send emails demanding that the customer take advantage of a free shipping offer when the customer just bought from a store?

Our future includes a full incorporation of purchases across all channels ... we encourage the customer to purchase anywhere ... but we react VERY DIFFERENTLY when the customer buys from a specific channel. The omnichannel thesis of "do everything digital" simply makes no sense in a world where we can clearly see how the customer will behave in the future.

Send me an email (kevinh@minethatdata.com) if you need assistance with grids and triggers.