More On Giving Away Books Before They Are Available To The Public

I didn't expect a lot of feedback when I shared the results of free downloads of the book vs. paying for the actual copy. I was wrong! E-mails were flying this afternoon!

First of all, I am not grumbling. More than anything, I want to share facts, metrics that others wouldn't share with you. I want to be as transparent as possible, transparency is one of the things you tell me you appreciate about this forum. I want for folks to learn how new marketing techniques work. And I sincerely appreciate all of you who e-mailed me to say that you got a free copy and purchased a copy of the book, much appreciated!!

Let's assume that 100 units have been distributed, to-date. Here's the distribution (as of this afternoon ... the metrics changed since the last post due to incremental paperback sales):

• Free Draft Of Pre-Published Book = 72%.
• $7.95 Download Of Finished Product = 14%.
• $14.95 Paperback Copy = 14%.

If my only purpose were to sell books (which it isn't), revenue per unit would be (0.72*$0 + 0.14*$7.95 + 0.14*$14.95) = $3.21. Net profit per unit would be about $1.80.

The $3.21 net revenue per unit metric is probably most compelling. Comscore's disputed statistics in the Radiohead promotion suggested 60% of the units were free downloads, and suggested that the weighted average net revenue per download was about $2.50.

So you can see that there's a level of directional similarity in the numbers. Hey, I have something in common with Radiohead!!

The books are not written for the sole purpose of selling books. They are part of what I would call a "micro-channel" strategy to running my business. There's a ton of free information available on this blog. I speak at conferences. I offer free spreadsheets. I write books for fun and to document important (and theoretically more-valuable-than-free) concepts.

I have learned that, as of today, the most effective strategy in growing my business is the combination of a transparent and informative blog, coupled with books that offer increased insights and sophistication. So if we allocated book costs and revenue across actual projects that were sourced from the blog/book, book sales are "sizzling"!

And that's what makes this whole thing so interesting. The giveaway doesn't work on a "linear" basis --- measuring sales as a function of each unique marketing strategy. A whole slurry of micro-channels work together, and at the end of the day, the whole is FAR greater than the sum of the parts. The giveaway as a sole marketing channel wasn't highly effective. The entire strategy is highly effective.

That's probably the takeaway I needed to share in the original post!

Now go buy the book!

Does Giving Away A Draft Copy Of A Book Help You Sell More Books?

You can't throw a rock in the book blogosphere without hitting a pundit telling you to give away your book prior to releasing it, in an effort to build momentum for the release of the book. Heck, Suzy Orman and Oprah gave away versions of Ms. Orman's already-published book, and it worked! So the strategy HAS to work!

Recall that I attempted this strategy with Hillstrom's Multichannel Secrets. I freely gave away a copy of the draft version of the book to anybody who asked for a copy.

I am here to tell you that the strategy created buzz. It created anticipation. It got folks talking about the book. I gave away a boatload of free draft copies of the book.

One month into the release of the book, I have metrics that tell me whether the strategy worked.

To date, I gave away nearly three times as many books as I sold.

Imagine if I had done this with the money a publisher invests in a new book? Self-publishing allows you to trade-off popular strategies with financial rewards.

The internet is filled with success stories, filled with interesting hypotheses. It isn't always filled with acknowledgement of failure. In my case, the strategy of giving away draft versions of a book to help sell the book failed miserably. The next book will have a very different marketing plan!

Social Media, Competitive Intelligence, And Web Analytics

Have you ever wondered why I occasionally write obtuse articles like this one on free shipping at Lands' End (check the organic/natural results for Free Shipping Lands' End on Google).

Or this article about Williams Sonoma and Multichannel Growth?

Or an article about Abacus, a popular co-op in the multichannel catalog world?

All are part of a strategy to gain what I call "Competitive Intelligence".

Maybe you noticed that Father's Day is just around the corner? There's a veritable plethora of folks who are interested in getting Dad a lightweight coat from Lands' End. They also want free shipping. Because I wrote the article about Lands' End free shipping, Google sends visitors to my site. In kind, I use Google Analytics and SiteMeter (here are my site statistics) to understand the rhythm around free shipping for Father's Day. I get to see the build-up prior to Father's Day, the days customers are most interested in obtaining Free Shipping, and the drop-off prior to shipping cutoffs.

Now if I can do this with my humble little blog, imagine what L.L. Bean could learn about Lands' End, Eddie Bauer, Orvis, you name the competitor, by hosting comparable content? And imagine how much more effective these brands would be, given their scale, compared to my humble efforts?

Miller Brewing Company accomplishes this style of competitive intelligence with their "Brew Blog", writing about their competitors on a daily basis.

This stuff isn't rocket science.

For me, the Lands' End example is more fun than anything else. More important is the work I do to understand my competitors.

For instance, I frequently write about matchback analysis, especially as it relates to co-ops like Abacus. Because Multichannel Forensics indirectly compete with matchback programs from companies like Abacus, it is a good thing for me to have folks searching for matchback solutions, searching for products from Abacus, to visit my site.

I get to track the evolution of terms that folks use. Catalog marketers use the phrase "Lifetime Value" to understand the long-term potential of customers. Online marketers and E-Mail marketers seem to prefer the term "Return on Investment" or "ROI". If I want to partner with online marketers on long-term customer value studies, I won't attract them to my site by writing about Lifetime Value.

I also have numerous competitors, folks who provide similar products and services to those offered by yours truly. By writing about these folks, or by hosting their RSS feed on my site, I get occasional visitors from Google who are searching for information about my competitors. I assure you, this information is very enlightening!! I get to see who the companies are that want to hire my competitors. I get an idea for the type of service the company has a need for. If necessary, I adjust my content, products, and services accordingly. I get to see the articles you like, ones written by my competitors.

Once, a competing organization fired a long-standing and high-ranking employee. The company announced the firing on a Tuesday. One day earlier, I had numerous visitors who arrived via Google searches that combined the competing brand name and the name of the individual who was fired. If I wanted to, I could have fact-checked the story and "scooped" the mainstream media.

Hosting a blog is so much more than the social media pap spewed by the punditocracy. The competitive intelligence gained from this effort means everything to a small business like mine. And best of all, the tools needed to obtain the competitive intelligence are free. FREE!

Now imagine for a moment what your brand could accomplish with a combination of Social Media, Competitive Intelligence, and Web Analytics?

Great Moments In Database Marketing #1: Incremental Value

Our top rated Database Marketing moment takes us back to 1993 - 1994. Yeah, way back then, people were doing sophisticated work. Honestly!

Way back in the early 1990s at Lands' End, we had seven different business units that marketed to customers, either through standalone catalogs, or though pages added to catalogs.

As growth became more and more difficult (pay close attention online marketers ... your world is heading in this direction), management elected to mail targeted catalogs to targeted customer segments.

In other words, a Mens Tailored catalog concept was developed, with a half-dozen or more incremental catalogs mailed to customers who preferred Mens Tailored merchandise. A Home catalog concept was developed, with nine or more incremental catalogs mailed to customers who preferred Home merchandise.

Seven concepts were developed. Each concept was growing.

But the core catalog, the monthly catalog mailed for three decades, was not really growing anymore. And total company profit (as a percentage of net sales) was generally decreasing over time.

Something was amiss.

We studied the housefile, and learned that the "best" customers were being "bombed" by catalogs ... upwards of forty a year. Every business unit, making independent mailing decisions, mailed essentially the same customers. And all of our metrics, when viewed at a corporate level, indicated that customers were not spending fundamentally more than they spent several years ago when the new business concepts didn't exist.

So we developed a test. We selected ten percent of our housefile, and created seven columns in a spreadsheet. We randomly populated each column with the words "YES" or "NO', at a 50% / 50% proportion. Each business unit was assigned to a column. When it came time to make mailing decisions for that business unit, we referred to the column assigned to the business unit. If the word "NO" appeared, we did not mail the customer (if the customer qualified for the mailing based on RFM or model score criteria).

In statistics, this is called a 2^7 Factorial Design.

There are two reasons for designing a test of this nature.

1. Quantify the incremental value (sales and profit) that each business unit contributes to the total brand.
2. Identify, across customers segments, the number of catalogs a customer should receive to optimize profitability.

What did we learn?

1. Each catalog mailed to a customer drove less and less incremental increases in sales. If a dozen catalogs caused a customer to spend $100, then two dozen catalogs caused customers to spend $141, and three dozen catalogs caused customers to spend $173. The relationship roughly approximated the Square Root Rule you've read so much about on this blog.
2. Each business unit, on average, was contributing only 70% of the volume that company reporting suggested the business unit was contributing. In other words, if you didn't mail the catalogs, you'd lose 70% of the sales, with customers spending 30% elsewhere.

The latter point is critical.

Take a look at the table below, one that illustrates the profit and loss statement reported by finance, and one that applies the results of the test.

Test Results Analysis		Finance	From
		Reported	Test Results
Demand		$50,000,000	$35,000,000
Net Sales	82.0%	$41,000,000	$28,700,000
Gross Margin	55.0%	$22,550,000	$15,785,000
Less Marketing Cost		$9,000,000	$9,000,000
Less Pick/Pack/Ship	11.0%	$4,510,000	$3,157,000
Variable Profit		$9,040,000	$3,628,000
Less Fixed Costs		$6,000,000	$6,000,000
Earnings Before Taxes		$3,040,000	($2,372,000)
% Of Net Sales		7.4%	-8.3%

The test indicated that what appeared to be highly profitable business units were actually marginally profitable, or in some cases, unprofitable. In this example, the business unit is "70% incremental", meaning that if the business unit did not exist, 70% of the sales volume would disappear, while 30% would be spent anyway by the customer, spent on other merchandise.

Imagine if you were the EVP responsible for a business unit that appeared to generate 7.4% pre-tax profit, only to have some rube in the database marketing department tell you that your efforts are actually draining the company of profit?


Why Does This Matter?

This style of old-school testing (which is more than a hundred years old, with elements of the testing strategy now employed aggressively in online marketing) tells you how valuable your marketing and merchandising initiatives truly are.

Catalogers fail to do this style of testing, not realizing that a portion of catalog driven sales would still be generated online (or in other catalogs). In 2008, most catalog marketers are grossly over-mailing existing buyers. Catalog Choice, in part, exists due to catalogers mis-reading this phenomenon.

E-mail marketers seldom execute these tests, not realizing that in many cases almost all of the sales would still be generated online. E-mail marketers, ask your e-mail marketing vendor to partner with you on test designs like the ones mentioned in this article. You may be surprised by what you learn!

Online marketers are more likely than most marketers to execute A/B splits at minimum, with some executing factorial designs. Many online brands evolve in a Darwinian style, fueled by the results of factorial designs. Online marketers know that you make mistakes quickly, and you correct those mistakes quickly.

Web Analytics folks have the responsibility to tell management when sku proliferation no longer contributes to increased sales. It is important for Web Analytics folks to lead the online marketing community, shutting off portions of the website in various tests to understand the incremental value of each additional sku.

What are your thoughts on this style of testing? What have you learned by executing tests of this nature?

Great Moments In Database Marketing #2: Multichannel Forensics

We've talked an awful lot about Multichannel Forensics on this blog. Maybe you noticed? Many of you purchased the book on Multichannel Forensics. Close to four thousand of you read the Multichannel Forensics white paper. In just the past year alone, I've put about forty brands through the Multichannel Forensics filter. Who knows how many you've analyzed?!

The reason we spend so much time talking about this topic is because it can be a challenge to understand micro-channels without having a tool that identifies how customers migrate between micro-channels.

E-Mail marketers typically evaluate the performance of their marketing strategies across only customers who click on an e-mail campaign. Catalog marketers are obsessed with allocating online orders back to catalog marketing. Web Analytics experts are focused on visit-specific conversion rates. Retailers focus on customer intelligence that drives comp store sales increases. Online marketers care about online marketing channels. Few people focus on long-term customer value. Almost nobody at your company can tell you what the five-year sales trajectory of your brand looks like, by product, brand or channel.

So many of you found Multichannel Forensics valuable because it provides a framework for understanding how customers interact with advertising, products, brands and channels.

Multichannel Forensics were born at Eddie Bauer in the late 1990s, when we tried to understand how markets evolved as new stores were opened in combination with the birth of e-commerce.

Multichannel Forensics allowed us to demonstrate that catalog marketing wasn't needed at Nordstrom, that e-commerce and stores interacted in a way that benefited the customer (customers evolved from catalog to e-commerce, then e-commerce to stores).

As micro-channels continue to proliferate, Multichannel Forensics will be the preferred method for understanding how customers migrate through the many "touchpoints" a brand possesses.

Is Your Business Down 42%?

When you're lamenting the fact that your business is down 5% or 12% or 20%, be glad you aren't working in the Recreational Vehicle industry, with industry-wide sales expected to be down 42% this year.

Ok marketers, what do you do when your industry is ravaged by the price of gasoline? How would you take care of your employees, how would you devise a plan for the long-term health of our business?

Great Moments In Database Marketing #3: Micro-Channels

A small number of marketers are doing an exceptional job of evaluating micro-channels. The focus on micro-channels yields actionable and strategic insights that are not part of the mainstream marketing conversation.

These folks are linking data from various systems. These folks don't care whether they have 100% coverage or not, they simply link what they have. If they can't link visitation information to every purchaser in the database, they don't. They work with what they have.

These folks maintain a customer database with fields like these:

• Months Since Last Purchase, Life-To-Date Purchases, Life-To-Date Items, Life-To-Date Demand/Sales, Life-To-Date Returns, Twelve-Month Purchases / Items / Demand / Sales / Returns
• Total Company
• By Physical Channel (Mail, Telephone, Internet, Retail).
• By Advertising Channel (E-Mail, Catalog, Google Paid Search, Yahoo! Paid Search, MSN Paid Search, Portal Advertising, Affiliate Marketing, Shopping Comparison Marketing, By Most Popular Blogs).
• By Merchandise Division.
• By Store Or Region
  

• Months Since Last E-Mail Click-Through, Total E-Mail Click-Throughs, Total E-Mail Twelve-Month Click-Throughs.

• Website Visitation Data
• Months Since Last Visit
• Number Of Life-To-Date Visits, Number Of Twelve-Month Visits.
• Average Time Spent On Site Per Visit.
• Number Of Pages Visited.
• Months Since Last Visit By Key Landing Page, Merchandise Division, Key Links.
• Months Since Last Shopping Cart Abandonment, Number Of Carts Abandoned.

• Outbound Marketing History
• Catalogs Mailed, E-Mails Mailed, Telemarketing Calls, Direct Mail Pieces.

• Self-Service Marketing Initiated By Customer
• RSS Subscriber And Items Subscribed To.
• Paid Search And Natural Search Activities.
• Visits From Key Blogs, Facebook, MySpace, Social Media.

When I speak with the marketers who maintain this information, they most important thing is to simply accumulate what you can accumulate. Then, you get busy analyzing the information!!

I've worked on a few projects with data of this nature. The findings are fascinating.

• Websites are a separate channel from e-commerce. There is an information element to the website that supports other channels. There is a social element to a website that allows customers to interact with each other. There is an entertainment element to a website that causes customers to visit again. And there is an e-commerce component to the site. Customers self-segment themselves into one of these micro-channels.

• E-commerce customers have unique dynamics.
  
• Those from paid search have a very different relationship with your brand ... unless they use another form of advertising (e-mail, catalogs) in combination with paid search.
• Once the catalog customer tries e-commerce, they become unlikely to go back to ordering over the phone.
• Once the e-commerce customer purchases in a store, they become less likely to go back to ordering via the internet. This does not mean they become unlikely to use the internet --- in fact, they become information/entertainment/social users.

• Trigger-based e-mail marketing is ideally suited for customers who last visited the website within ten days.

• You learn that you have a couple hundred important micro-channels, combinations of advertising, self-service activity, and purchase channel. You learn not to "force" customers into micro-channels --- instead, you let customers self-select themselves into a micro-channel, and work with the customer based on her natural, subsequent behavior.

• Customers evolve across micro-channels, often migrating to a "most popular" micro-channel over time.

Examples of micro-channels:

• E-Mail click-through customer who visits website frequently and buys merchandise in-store.

• Paid search customer who does not subsequently repurchase.

• Rural customer who buys online after receiving a catalog.

• Customer who visits site after reading a blog post about merchandise, visits frequently, does not buy merchandise.

• Customer visits site after seeing portal ad, signs up for e-mail marketing.

• Customer buys in-store only.
  

• Customer only shops via landing pages (i.e. needs a merchandising assortment presented to her).

• Customer only shops via site search (i.e. a self-service customer who picks and chooses what she wants).

From what I've observed, the future of database marketing is the identification of micro-channels, the classification of customers into micro-channels, and then market / no-market decisions based on micro-channels.

The folks I've seen do this style of marketing are producing very interesting results.