Clouds / Thunderstorms

It's a Monday, and you're not doing anything productive today anyway, so take a few minutes and watch this video ... watch how all the clouds evolve / adapt / change over time.

Your business is like a cloud (no, it isn't "in the cloud" like vendors want it to be). Your business is a dynamic, changing ecosystem ... while at the same time, it is part of a much larger ecosystem ... the upper level low in the Pacific Northwest fuels the low level winds that interact with the jet stream and create severe weather across the Plains and Midwest.

Do you treat your business like a dynamic, changing ecosystem that is part of a much larger ecosystem? Well, yes and no.

In most cases, the answer is no. We treat our businesses like a snapshot. We execute an email campaign. Or we mail a catalog. We change the home page and landing pages and the retail floorset. All are snapshot executions of our business ... a picture at a point in time. Is the picture pretty? Yes? Then we succeeded. Never mind that the pretty picture becomes a tornado at a later point in time ... the picture is pretty.

Sometimes, the answer is "yes". When we change our bidding strategy on various keywords, we're treating our business like an ecosystem. When we offer 30% off plus free shipping in response to a competitor offering 25% off plus free shipping, we are treating our business like an ecosystem. Whether we positively or negatively impact our ecosystem, well, that's another story.

But the problem with business today is that we treat too many aspects of our business like a snapshot, and not like the videos shared with you in this blog post.

When we don't generate enough new, winning products, we stop fueling the thunderstorms in the video above.

When we don't generate enough new customers, we stop fueling the thunderstorms in the video above.

When we don't run the best selling items in the front of the catalog because we want to "make a statement", we stop fueling the thunderstorms in the video above.

When we put 25% off plus free shipping in an email campaign to generate more opens and clicks, we stop fueling the thunderstorms in the video above.

Do you understand the message?

An Omnichannel Quiz

Take the omnichannel quiz. See how you perform.

Question #1: You mail a catalog. The customers driven into the store by the catalog are fundamentally different than the core customer who shops in the store. Do you ....

• A) Align the catalog with the retail assortment, and reduce catalog productivity.
• B) Change the retail assortment to match what the catalog customer prefers to purchase.
• C) Let the business evolve naturally.

Question #2: Your retail business is so good and the experience is so compelling that your e-commerce business only comprises 7% of total net sales ... and ... customers within 50 miles of the store are simply unwilling to shop via e-commerce ... they go to the store. How would you treat your e-commerce marketing team?

• A) You plan on firing them because they do such a poor job of driving e-commerce business.
• B) You let the customer do whatever the customer wants, rewarding all employees on the basis of total sales.
• C) You build an e-commerce team with subject matter expertise in growing retail sales via digital marketing techniques.

Question #3:  You have two email marketing campaigns per week ... on Monday, and on Friday. Which strategy would you employ?

• A) The Monday campaign is designed to drive customers online, the Friday campaign is designed to drive customers into stores.
• B) The campaigns are brand-centric, ignoring channels.
• C) The campaigns are personalized, are customer-centric, based on the merchandise the customer purchases and the channels the customer buy from.

Question #4:  Customers who buy from multiple channels ...

• A) Are the best because of the channels you offer, and therefore, require businesses to be active in all channels.
• B) Are the best simply because they buy often and, by default, touch many channels ... in the same way that people who like to eat out go to many restaurants.
• C) Are the best because they love your merchandise assortment.

Question #5:  Is it your belief that ...

• A) You align your marketing, merchandising, and creative teams across channels, even if it means that the productivity in any one channel is lower, because you want all employees focusing on the core omnichannel customer.
• B) You do not align your marketing, merchandising, and creative teams across channels, allowing each channel to achieve maximum sales potential.
• C) Organizational structure is irrelevant ... smart people self-organizing and working well together matters most.

Question #6:  If you were CEO at Macy's, and you were not happy with business performance (and you shouldn't be), who would you fire?

• A) The omnichannel strategy team.
• B) The merchandising leadership team.
• C) The marketing team.

Question #7:  If a business generates $1,000,000 of profit, annually, how much of the $1,000,000 is caused by a great omnichannel strategy, and how much of the $1,000,000 is generated by a great merchandising strategy?

• A) More profit comes from omnichannel strategy than from your merchandising strategy.
• B) Profit is about equal ... both contribute equally.
• C) More profit comes from the merchandising strategy than from your omnichannel strategy.

Now, count how many times you answered as follows below:

• Question 1 = A.
• Question 2 = B.
• Question 3 = B.
• Question 4 = A.
• Question 5 = A.
• Question 6 = B.
• Question 7 = A.

If you gave the answers listed above in at least four of the seven cases, then you are an ardent omnichannel advocate.

If you gave the answers listed above in two or fewer of the seven cases, then you do not align with the omnichannel thesis.

How did you perform?

Why did you answer the questions the way you answered them? Do you have financial results to back up your answers? Discuss.

Online Visitation Evolves Over Time

When I am analyzing an online ecosystem, I create a series of logistic regression models that predict next-month visitation within online advertising channels.

What is interesting about the equations is that customers exhibit behavior that is far more consistent than what you're taught to believe. You're taught that customers "do everything". Once you are taught that customers "do everything", you're taught that you must use attribution algorithms to parse out the activity that leads to a purchase.

In a recent project, more than half of visitors had just one daily interaction with the website. When predicting what should happen the next month, the models indicated that customers are far more likely to stay within the advertising channel they were in the month prior ... in other words, when a customer visits via an affiliate last month, we can expect that customer to visit via direct load next month, with a scattering of visits across all other advertising channels.

The projects consistently point out three things.

1. Direct Load visitation is most important, and obviously, most cost effective. Most visitors, even toll-based visitors, migrate back to direct load over time.
2. Push-based visitation (email) is second most important - and obviously.
3. Toll-based visitation (catalogs, affiliates, remarketing, Facebook, search/Google) matters, and ultimately pushes a customer to direct load over time.

The projects also point out a consistent trend, over time.

• Early customer life cycle visits are skewed to toll-based channels.
• Later customer life cycle visits are skewed to push-based (email) and direct load (customer loyalty) visits.

The projects also illustrate that discount/promo centric companies drive more toll-based traffic ... imposing a double-toll on the business (pay an affiliate, generate less profit because of the discount/promo).

The interesting thing about all this stuff is that the vast majority of what we read in trade journals or from vendors focuses on toll-based traffic that converts via discounts/promotions. The vast majority of quality profit we generate comes from direct load (customer loyalty) and email push-based visits.

Yes vendors, I hear you yelling at me from afar ... "you're wrong, and I'm going to tell you why". Go ahead and run the monthly ecosystem models I'm running, and see if you can see something similar in your information.

Contact me (kevinh@minethatdata.com) for your own, customized, online ecosystem analysis.

Ad Blockers

You've been reading about ad blockers, right (click here)? Here's a popular version for Chrome ... with downloads allegedly exceeding 200,000,000 (click here).

In my projects, there are three types of traffic.

1. Earned Traffic (i.e. customer visits your site because the customer loves your brand).
2. Pushed Traffic (i.e. catalogs, email campaigns).
3. Toll-Based Traffic (i.e. retargeting, Facebook, Google, YouTube, all the stuff you love to focus on).

It takes a tremendous amount of talent, effort, and merchandising/marketing brilliance to achieve earned traffic. The outcome is a phenomenal amount of high-quality profit.

It takes a tremendous amount of talent, effort, and merchandising/marketing brilliance to generate sales via Pushed Traffic. The outcome is a large amount of sales and a fair amount of low-quality profit (in the case of cataloging), or a smaller amount of sales paired with high-quality profit (in the case of email marketing). Either way, something gives.

It does not take a tremendous amount of talent, effort, and merchandising/marketing brilliance to generate Toll-Based traffic. It takes money and some amount of technical chops. The outcome is frequently a fair amount of sales paired with low-quality profit.

Almost everything you read demands a focus on Toll-Based Traffic generation. Many call this "omnichannel". Vendors, trade journalists, and consultants love omnichannel Toll-Based Traffic, because they get paid when you listen to them.

Now, imagine a world where 65% of your customers are using ad-blocking software. Can we agree that, in a world where the majority of customers are using ad-blocking software, it becomes much, much harder to grow your business via Toll-Based Traffic?

In that world, the omnichannel theorists correctly assess that your customer is using many channels ... but your efforts to have a relationship with the customer outside of your site are increasingly thwarted. What do you do? Be honest with yourself.

Success in five years comes from efforts to build Earned Traffic today. It's probably time to get busy, don't you think?

Marketers Influence Merchandise Ecosystems

Some marketers raise a champagne glass every time somebody engages with brand, or every time 55% off plus free shipping results in an incremental order.

Maybe we should celebrate when we cause positive downstream change.

Recall our example? Category 03 negatively influences the entire ecosystem, whereas other categories positively influence the entire ecosystem.

So let's run a simulation. In my simulation (won't get into the geeky math here in this post, there's no easier way to lose an audience than to focus on math), I increased annual demand in Category 03 by 20%. Here's how many of last year's customers are forecast to shop next year, based on this change to the ecosystem.

• Category 00 = 62 fewer.
• Category 01 = no change.
• Category 02 = no change.
• Category 03 = 1,522 more.
• Category 04 = 168 more.
• Category 05 = 220 fewer.
• Category 06 = no change.
• Category 07 = 29 fewer.
• Category 08 = 58 fewer.
• Category 09 = 221 fewer.
• Category 10 = 45 fewer.
• Category 11 = 97 fewer.
• Category 12 = 71 fewer.

Essentially, half of the customer gains in Category 03 are wiped out by customers lost in Categories 00, 05, 07, 08, 10, 11, and 12.

Now, look at what happens if we increase Categories 04/05 by 20% (these categories, in total, are about the same size as Category 03).

• Category 00 = 76 more.
• Category 01 = 62 more.
• Category 02 = 7 more.
• Category 03 = 350 more.
• Category 04 = 1,125 more.
• Category 05 = 560 more.
• Category 06 = no change.
• Category 07 = 38 more.
• Category 08 = 33 more.
• Category 09 = 338 more.
• Category 10 = 57 more.
• Category 11 = 205 more.
• Category 12 = 198 more.

Here, all other categories benefit as much as 04/05 did, downstream. Everybody wins.

Ok, you are a marketer, and you now know how your ecosystem works. What do you do about it?

• Be willing to pay more to acquire customers outside of Category 03.
• If you have a catalog, feature Categories 04/05 at the front of the catalog.
• Feature Categories 04/05 more often on your home page and landing pages.
• Feature Categories 04/05 more often in email campaigns.
• If you must offer discounts via promotions, do so more often in Categories 04/05.
• Pay Google more for Category 04/05 keywords.
• Feature Categories 04/05 more often on Pinterest.
• Try something!

Do you know understand why it is so important to gain knowledge of your merchandise ecosystem?

When One Category Works Against Most Of Your Categories

Sometimes, you have a merchandise category that works against the rest of the business. It happens more often than you'd think.

When I worked at Nordstrom, we had Cosmetics, Mens Footwear, and Womens Footwear. These categories helped all other categories - meaning that when a customer purchased Cosmetics, the customer instantly became more likely to buy from Accessories, for instance. But the opposite wasn't necessarily true. Growing Accessories helped Accessories. Growing Cosmetics helped Cosmetics and helped Accessories.

In my Nordstrom example, which category should be featured in marketing, on landing pages, in email campaigns? Which keywords would you pay more for on Google? Cosmetics, right? Cosmetics helps Cosmetics and Accessories. Accessories only helped Accessories.

Your business is a big, bubbling ecosystem. You've been trained to ignore the ecosystem. You've been trained by vendors to focus on campaigns, to focus on how campaigns convert.

Look at Category 03 in the table above. Are the coefficients positive, or negative? Positive coefficients mean that dollars spent in that category today will help other categories in the future. Negative coefficients meant hat dollars spent in that category today hurt response in other categories next year.

Category 03 hurts nearly every other category in the next year. When a customer buys from Category 03, the customer will spend less next year in the following categories ... 00, 05, 07, 08, 09, 10, 11, and 12.

In other words, the merchant responsible for growing Category 03 is the same merchant who hurts the future performance of the merchants responsible for categories 00, 05, 07, 08, 09, 10, 11, and 12. And the marketer who actively promotes Category 03 is the marketer who hurts his/her efforts to properly market categories 00, 05, 07, 08, 09, 10, 11, and 12.

Read across the row for Category 11. This category doesn't harm the future performance of a single category. The merchant responsible for Category 11 helps the entire business.

These relationships happen in your business too. Absolutely! The best marketers know these relationships. They know that Category 03 is hurting the future potential of the rest of the business. They know that when they have a choice, they give Category 11 marketing priority over Category 03. They protect the future of their business by not promoting one category in a way that harms other categories.

Show of hands ... how many of you thoroughly understand how your merchandising categories interact with each other?

Merchandise Category Interaction

You've enjoyed an annual physical, right?

You learn that your cholesterol is too high (too many nachos), so you are prescribed a drug. Before the drug is prescribed, however, your doctor determines if the drug will interact with other drugs you are taking.

You don't want drugs interacting negatively, do you?

The same issue happens in your business. But we're not trained to measure interactions. The vendor community prescribes solutions. What if their solutions cause negative interactions within your business?

I assure you, the solutions some of those folks prescribe for you yield negative and unfavorable interactions.

The table above is a geeky table of logistic regression coefficients for a business with thirteen merchandise categories (categories 00, 01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 11, 12). The dependent variable is a 1/0 indicator, measuring whether a customer purchased from that category in the past year. The independent variables are demand ($/1000) amounts for each category for the period 13-24 months ago (this is the point in the discussion where some in the vendor community will tell you I'm nuts - remember, they are prescribing drugs, we are diagnosing problems, two very different disciplines).

Read down the "Category 05" column. Here, I am measuring the merchandise categories that positively/negatively interact with future purchasing in Category 05 (yes, these are actual equations from an actual business ... I just omitted what the actual category meanings/definitions are). What do you see?

• Category 00 interacts positively.
• Category 03 interacts negatively.
• Category 04 interacts positively.
• Category 05 interacts positively (duh).
• Category 06 interacts positively.
• Category 07 interacts positively.
• Category 08 interacts positively.
• Category 08 interacts positively.
• Category 10 interacts positively.
• Category 11 interacts positively.
• Category 12 interacts positively.

This is one, big, bubbly ecosystem, don't you think? Only two of the thirteen categories (01, 02) don't interact with this category. Ten of the interactions are positive. One interaction (03) is negative.

This category goes as the entire business goes. When a customer purchases from Category 08 today, this category gets benefit tomorrow.

Let's preview something for tomorrow. Read across the row for Category 03. What do you see? Given what I've explained so far, what does this mean to you?

You Are A Doctor, Not A Pharmacist

The modern theme of marketing misses out on all of the magic and glory bubbling within your merchandising ecosystem. You are asked to market in all channels (#omnichannel), and you are asked to pay tolls (Google, Facebook, Abacus) in an effort to get customers to purchase.

In other words, the industry wants to help you prescribe a drug ... the industry wants you to count pills and put the pills in a bottle and then communicate side effects (omnichannel sales gains).

Your job, quite honestly, should be the opposite. You should be a doctor. You should diagnose problems, and then you, yes you, should prescribe the solution.

Do not be a pill counter. (in the medical world, by all means, I fully encourage you to be a pharmacist - I'm talking about marketing, not medicine).

We don't have enough doctors in our industry.

Let me give you an example. Let's go back to 1998. Yes, I'm at Eddie Bauer, Director of Circulation, fingers in every pie. The Home business was awful. Those folks always lost money. And those folks somehow kept their jobs in the process ... posting -10% earnings before taxes year after year. But now that I'm the circulation director, I'm accountable for that -10% as well. I don't want to be responsible for posting -10% earnings before taxes. 

Bad business is not going to be my fault.

*** Here is where the vendor community will tell you that I'm using math incorrectly - patiently listen to their complaints, then get busy implementing solutions ***

I created a series of logistic regression models. The independent variables were demand spent by twelve-month buyers, by merchandising category, in 1996. The dependent variables were 1/0 indicators ... did the customer purchase from a series of merchandise categories in 1997? Each logistic regression equation featured prediction of a 1/0 buy/no-buy variable regressed against demand spent the year prior in each merchandise category.

Have you ever run these equations? The coefficients reveal the secrets embedded within your business!! The coefficients tell you why some categories never grow, while other categories grow by default.

In the case of the Home division - the coefficients told a very interesting story.

1. Existing Eddie Bauer customers did not want to buy Home product.
2. Home customers, after buying Home product, did not want to buy Home product. Home customers wanted to buy Apparel next.

When you see (1) and (2), what would you do to grow the home business, knowing these two facts?

#Omnichannel? 

Heck no.

Here's what I did:

• I rented every single Williams Sonoma and Pottery Barn name I possibly could. Often. All of them.

In fact, half of my circulation plan (it took WS/PB two years to figure out what was happening) consisted of Williams Sonoma and Pottery Barn names. 

Oh, I caught heck within Eddie Bauer for doing this. "Why aren't you mailing our own customers, you idiot?" Well, I'm not mailing them because our own customers won't buy the product, that's why!!

Not surprisingly, the business went from losing a couple million dollars a year to losing a hundred thousand dollars within a year. The business wasn't fixed - but the business was no longer floundering into oblivion, either.

Do you understand, dear marketers, that you have power? You - yes you - can fix major problems on your own, if you simply act as a doctor and diagnose a problem instead of being a pharmacist who counts omnichannel pills.

Tomorrow, I'll share more information on the methodology I used at Eddie Bauer, way back in 1998. Vendors will tell you that I'm using math incorrectly. I'm here to tell you that I work in the real world, and the technique works very, very well in the real world.

Ecosystems: The Social Visit

Most of us analyze online / digital information in the context of a campaign or a visit. How can we improve email? Did remarketing drive business? Why does a tablet visitor have a low conversion rate?

Each digital interaction is part of the ecosystem you manage. You cannot see that you are managing an ecosystem when you analyze campaigns - campaigns are point-in-time activities with visit-centric ROI windows, or time-based ROI windows. Campaigns blind you to all of the magic that happens in your business!

Here's a recent analysis - the customer visited one time last month, via a social source. My job is to measure how this customer evolves/changes in the next month. Does the customer purchase? Does the customer utilize other channels. Here's a sampling of the ecosystem analysis.

• 10,000 simulated visitors, only one visit, from a social source.
• 4,015 visit again next month ... 40.2% active rate.
• 11,025 unique days visited ... nearly three days visited per active visitor.
• 5,729 days of direct-load visits.
• 285 days of visits from affiliates.
• 1,128 days of visits from remarketing.
• 2,511 days of visits from social sites.
• 326 days of visits from paid search.
• 773 days of visits from search engine optimization.
• 899 days of visits from branded content.
• 209 days of visits from triggered strategies.
• 438 days of visits from email marketing.
• 464 visitors purchased.
• $53,388 sales.
• 522 total orders.
• Each visitor last month was worth $5.34 next month.

This user looks pretty tame, to me. Reasonably low value, unlikely to use search in the future (paying a toll), unlikely to use an affiliate next month (paying a toll).

The story doesn't always look like this. In an ecosystem analysis, we frequently see visitors who migrate to many paid channels, multiple times a month, running up tolls. This customer is most likely to use direct load, not running up tolls, and therefore, is a customer we like (even if the customer has low value in the next month).

What are you seeing in your ecosystem analytics? What does the customer do next month, given what the customer did last month?

Online Brand Competition

There's no shortage of interesting tools that can be combined to understand our competitive online marketplace.

Quantcast is one such tool. Type in your URL. The tool estimates your daily traffic, monthly unique visitors, the websites your visitors frequent, and various demographics. Directionally, it isn't a bad tool.

By looking at the websites that your visitors frequent, one can apply the concepts of Multichannel Forensics, yielding this "map-in-progress" (click once on the map for a larger image) of the relationship between various online retailers and the visitors who frequent their sites.

At first, I was looking at two dozen apparel retailers --- then the project expanded, resulting in nearly 120 online apparel businesses, as well as businesses closely aligned to the apparel industry.

While the individual observations yielded by Quantcast are undoubtedly biased and somewhat incorrect, the relationships depicted in the map are largely intuitive.

Higher-end department stores "anchor" the middle-left area of the map (Saks, Nordstrom, Neiman Marcus, Bloomingdales). Visitors frequent these sites, and also visit sites in a circle around the department stores.

"North" of the department store "anchor" you find businesses that appeal to the upper-end of the Baby Boomer generation.

"South" of the department store "anchor" you find businesses that appeal to younger customers. You can almost see the "Marketing Digital Divide" at play here, as Zappos, Piperlime and Endless appear in this general area --- along with other youthful brands.

Moving across the map to the right, you see a department store transition occur --- from Saks to Dillards to J.C. Penney to Sears/K-Mart/Wal-Mart. Kids and Shoe retailers appear just below and to the right of this general progression.

Most interesting to me is the competitive bloodbath that occurs in the middle-left section of the map. Surrounding the department store "anchors" are largely catalog-based (above) and online-based (below) websites. Because these retailers are plotted close to each other, the map suggests these retailers "share" the same customers. Quantcast suggests that website visitors are visiting many of these sites.

Quantcast is suggesting that these businesses largely share the same customer base. Marketing, merchandise assortment, price/value and creative/branding strategy become key differentiators among similar businesses with similar customers.

Multichannel Forensics can also be used to demonstrate that the competitive forces illustrated in this map occur within your very own company! In other words, the same competition/cooperation that occurs between Gap and Gymboree in this map also occur between the products, brands and channels that you use to sell merchandise to consumers and businesses.

Intuitively, we understand the competitive forces that happen between companies, and across industries. Within our own businesses, we sometimes have a harder time conceiving these trends. And yet, it's these trends that give us the opportunity to think strategically, to consider what is best for our customer, to chart a path to increased sales and profits.

Over the next decade, as we cross the Marketing Digital Divide and manage web-based businesses, we'll need to better understand external and internal ecosystem interactions.