Clario and Vendor Modeling Review - An Inexpensive Project

I've conducted a handful of "Clario Analytics Reviews" in 2014.

Here's a link to Clario Analytics (click here). They perform catalog optimization modeling. They generate profit for their clients. They use geeky math - you'd have to in order to do a good job. Business leaders do not understand geeky math - they understand business!

So I'm called in to analyze the performance of the customer file, given the mailing strategy employed by Clario.

Here's what I do in a Clario Analytics Review (the 4th most popular project I've worked on in 2013, behind Merchandise Forensics, Catalog PhD, and Persona / Omnichannel Analytics, ahead of Hillstrom's Health Index):

1. Project Cost = $4,900.
2. Client Sends File #1 and File #2 From This Document (Click Here).
3. I run your data through a shortcut version of my Catalog PhD process (purchase on Amazon - click here).
4. I clearly explain to you how Clario is mailing different customer segments - highly catalog-centric phone/mail customers, rural customers, urban customers, those living near a store, those living far from a store, high value customers, low value customers, email buyers, search buyers, affiliate buyers, mobile buyers, retail buyers. Many cuts, many views, all of 'em are important. You'll know what Clario is doing and why they are doing it.
5. I will point out strengths, and areas of opportunity.

Now, I know many of you are paying Clario a hundred thousand dollars a year, sometimes more, for catalog optimization.  A meager $4,900 to validate your investment isn't asking too much, is it?

Email today (kevinh@minethatdata.com) for your own Clario Analytics Review. Click here for the file layouts you'll need.

In fact, I'll perform this analysis for any of the vendors you work with for modeling purposes or RFM selection analytics - $4,900 - it's virtually free, when you consider how much you spend on modeling services:

• Experian.
• Epsilon / Abacus.
• Merkle.
• InfoGroup.
• Any of the other co-ops.
• Independent Consultants.
• Any other vendor.

MineThatData Radio - #Omnichannel / #shoporg13 Edition

Loyal MineThatData followers - here's something new for you - it's the first episode of MineThatData Radio!

In this first episode, I talk about one of the themes at this year's Shop.org conference - Omnichannel! It's just me, sharing a lot of information about omnichannel, based on an awful lot of project work conducted over the past few years.

Click Here To Listen To MineThatData Radio.

Today's episode is all business, and for good reason - omnichannel is a big topic. In future episodes, you may find a little business humor sprinkled in as well.

VENDORS - CONSULTANTS - POTENTIAL INTERVIEWEES

I'm going to do something different with MineThatData Radio. I am repeatedly hounded by folks who want free access to this blog ... "your readers would love to learn how we helped a brand increase engagement by 943%, please publish this guest post immediately, and thanks for your help."

Within the radio show, and only within the radio show, I am willing to conduct interviews, as long as they are beneficial to the audience who chooses to listen to MineThatData Radio. And I am willing to interview anybody - CEOs, EVPs, Vendors, Web Analysts at Williams Sonoma, Independent Consultants, Trade Journalists.

If you would like the opportunity to share what you've learned about customer behavior, to an audience of 2,500 blog subscribers, 4,900 Twitter followers, and the 325,000 folks who've previously visited the MineThatData Blog (shared only via MineThatData Radio, not through any other content here on this blog), here's the conditions for inclusion - email me (kevinh@minethatdata.com) answers to the following questions:

1. What is the topic you wish to discuss? The topic must be related to e-commerce, retailing, modern catalog marketing, or analytics. I'm not going accept "Eight Ways Social Media Can Turbocharge Your Business", or "Four Ways To Optimize Your Website For Breakthrough Performance" or "Six Ways That Mobile Changes Everything Forever" or "Twenty-Nine Ways That Gen-Y Engages With Content". That stuff is nonsense. You must bring your A-game to MineThatData Radio.
2. What is the case study or information you will point to, in order to prove that whatever you want to talk about is important and will generate an increase in profitability? If you are a printer, and you have a new format for direct mail, and a client got an 11% increase in response over a control, you're well on your way to being on the show. If you are a web analyst, and you have a new way of analyzing data that my clients can benefit from, you are well on your way to being on the show. If you are an e-commerce vendor, and you increased conversion rates for a large client by 9%, and you are willing to share specific, in-the-weeds details, you'll be considered.
3. How might you promote the podcast and MineThatData services, where appropriate?

Answers to the three questions listed above are mandatory for consideration. Following consideration, I promise to be respectful, honest, kind, to not demean you, and to give your thoughts a fair hearing. Hopefully, you will enjoy the experience.

Let's give this a try, folks!

New Item Failure

Folks, this story repeats more often than old episodes of M*A*S*H.

Take a look at this table. This is the outcome of a comp segment analysis on an e-commerce business. The comp segment analysis evaluates customers who, for instance, purchased two times in the year ending September 30, 2012. We then measure how much these customers spent in the year ending September 30, 2013. I've found that this style of analysis is the most reliable way to determine if a business is generating improved merchandise productivity or if merchandising issues are hurting the business.

Guess what? This business is being hurt by merchandising issues.

Comp segment demand was -3.9% last year, and was -2.8% in the past twelve months. This business is suffering from two consecutive years of merchandise failure.

Now look down the Existing Comp column. This column represents comp performance for existing items. For each of the past five years, existing items have remained flat, or have marginally improved in value.

Now look down the New Comp column. Oh boy. Ohhhhhh Boy.

The entire reason that the business is struggling is because new item comps were -26.5% last year, and are -25.2% in the past twelve months. In fact, new item performance is down more than 44% over a two year period of time. 

That's a catastrophe, folks.

Look at the 2007/2008 timeframe. Both new and existing items were down, suggesting that the economy may have been to blame for poor performance.

But in 2012/2013? It's new items.

And guess what new items in 2012/2013 become in 2014/2015? Yup. Existing items. We can confidently project that, without an infusion of highly productive new items, existing item performance is about to go in the tank as well.

That's what we do with a Merchandise Forensics project. We identify what the core issue is with a business. And in most cases, the core issue is merchandise productivity, not a failure to employ a proper omnichannel marketing strategy.

When you are at Shop.org today, ask anybody if they are measuring new item and existing item productivity. When you learn that few folks do this, you will realize that you are on the cusp of getting a head start on the competition.

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

Click here for file layouts and pricing information.

Or buy the booklet on Amazon (click here).

Dear B2B Catalog CEOs: Average Order Value

Dear B2B Catalog CEOs:

Hi there - a special message just for you!

B2B cataloging is a bit different than B2C cataloging. Not as different as the pundits would have you believe, but different enough to create unique surprises.

Average Order Value is one of those surprises.

In B2C, you're likely to see something like this:

• Response Rate = 2%.
• Average Order Value = $130.
• Dollar per Book = $2.60.
• Book Cost = $0.50.
• Profit Factor = 40%.
• Profit per Book = $0.54.

In B2B, you're likely to see something like this:

• Response Rate = 1%.
• Average Order Value = $600.
• Dollar per Book = $6.00.
• Book Cost = $0.50.
• Profit Factor = 40%.
• Profit per Book = $1.90.

Average Order Value plays a major role in B2B catalog marketing. For B2B folks, AOV is dramatically bigger than it is for B2C. This causes each individual catalog to simply be more profitable, even if response rates are half or less of what is observed in B2C marketing.

As a result, the catalog must be part of the B2B marketing strategy, even if almost nobody responds to it.

It addition, large AOVs allow page counts to be inflated, compared to the B2C world where page counts are going to be pushed down in Darwinian manner.

When I started my consulting work back in 2007, the differences in circulation strategy between B2B marketers and B2C marketers were not all that much different. In 2013, for B2B marketers with large AOVs, the catalog marketing strategy is frequently going "Back to the Future", if you will - large AOVs promote a 1990 style catalog marketing strategy, opposite of almost every piece of advice you get anywhere else.

This only happens, of course, if your AOV is greater than about $400.

Ponder the consequences of AOV - B2B vendors love to capitalize on large AOV's, and for good reason.

Last Chance!

Here's your last chance to get Hillstrom's Health Index (HHI) at $2,900. 

Nobody accepted the free offer.

But demand for the $2,900 offer has been good.

Next week, I'll have enough data via the trial offer to begin offering this as a full-price product ... the price point will be $4,900, based on the test cases I've analyzed and the results obtained. That's a spectacular deal - one any business can afford. If you're wondering what it might be like to work with me, here's an entry-level opportunity to find out.

I've revised my product offering - click here for details - you'll read a brief description of the work that is most popular, you'll see pricing information, and you'll see file layouts. 

From this point forward, Merchandise Forensics is being sold at full price, all test cases have been analyzed, reported on, and completed - 2013 test pricing for Merchandise Forensics is no longer available.

Also, I'm getting feedback for four other types of projects:

1. Clario Optimization Review: This has come up numerous times in 2013 - so far, 100% approval of Clario's work. If you have concerns, I'll be happy to review the impact they have on profitability.
2. Advisory Role: It came up this week - a business wants on-demand assistance with various strategic issues. I'm available for advisory work - I don't just do data mining and geeky math. Contact me for details.
3. Buying/Selling a Catalog Business: I get many private equity inquiries - folks looking to evaluate businesses. I also get inquiries from CEOs who lead struggling businesses. Sometimes, I get the inquiries from each side! If you're on either side of buying/selling, we can use the HHI framework above as a starting point for evaluation.
4. Omnichannel Evolution: Specifically, folks want to understand what role mobile plays in the evolution of traditional e-commerce. There's data that supports growth opportunities, and there's data that suggests that mobile completely cannibalizes and obliterates traditional e-commerce. Hire me to find out what end of the spectrum your business is on!

Again, here is the link to the spiffy new project document, click here!

Business Is Bad - Blame Marketing?

This table, from the Merchandise Forensics booklet, illustrates A/B/C items for an actual business.

Remember, I categorize A/B/C/D/F items in the following manner ... "A" = Top 5% in Demand volume and Top 5% in Unit volume ... "B" = Top 5% in Demand volume, Bottom 95% in Unit volume ... "C" = Bottom 95% in Demand volume, Top 5% in Unit Volume ... "D" = Top 45% in Demand Volume, Not In A/B/C Category ... "F" = All Other Items.

Ok, back to the business being analyzed in the booklet.

In total, A/B/C items dropped from 120 in 2011 to 105 in 2012 to 94 in 2013. In other words, the number of highly successful items (which comprise 6-9% of items and 50% of annual demand) is on the decline.

Look at the middle portion of the table. This is where we depict the number of existing items. This business reasonably maintains high demand items (A/B), but has cut way back on the number of low demand / high unit volume items. In other words, this business is de-emphasizing low price point items.

Look at the bottom portion of the table. Here we observe a complete meltdown. The merchandising team sold 29 A/B/C new items two years ago - and only sells 18 A/B/C new items today. Notice that new "B" items remain relatively flat - suggesting that the merchandising team continues to churn out new, expensive items. Notice that both "A" and "C" new items are in free fall - these have lower price points.

This is a case where the merchandising team is fully accountable for the meltdown of the business. They are not offering enough new items, and they are de-emphasizing low price points.

I've been in a lot of meetings in my career. Of course, merchants are under a tremendous amount of pressure, and for good reason. But at some point in a meeting, especially when business is below plan, the merchandising team turns on the marketing team. It's "their" fault. If it is a catalog business, then the wrong customers are being mailed. If it is an e-commerce business, then email and search programs are not targeting the "right" customer.

The marketer must have this data at their disposal. Must. Have. This. Data. The marketer has all the metrics in the world to prove that catalogs, or email campaigns, or paid search, or social, or mobile works. None of it, and I mean none of it, matters when the merchandising team is making glaring mistakes.

This example, which I see happen all the time, has nothing to do with the marketing team. The merchandising team is hurting this business.

Purchase on Amazon (click here).

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

30% Off Plus Free Shipping!

When you see a whopper like this, there are three things I want you, the intrepid business leader, to do.

First, you're going to do your best to perform some sort of holdout test. Since you have retail stores, maybe you do a geographic holdout test - nobody in Arkansas gets to participate at this level of discounting. I'll get to why the holdout test is important in a moment.

Second, you're going to simulate what it takes to generate profit, before running the promotion. If you have 65% margins and you can expect your holdout group to provide shipping/handling revenue 40% of the time (at $12 per order), your profit and loss statement might look something like this (your mileage will vary).

You need a 115% increase in demand during the promotion, in order to cause the promotion to generate profit. Here, I am assuming no incremental ad cost whatsoever, that's why profit looks so dandy in a normal business situation.

Look at the "Increment" column - this is the true value of the promotion (more on that in a moment). Under normal business circumstances, we're actually making money on shipping and handling, so we generate 71% profit (you can do that when your gross margins are 65%). We generate about $71,000 profit on $100,000 of sales. The promotion generates $1,670 profit on $115,000 of sales, a bit greater than a 1% profit level.

Here's the third (and most important) part of the analysis. When the promotion ends - KEEP MEASURING THE DIFFERENCE BETWEEN TEST AND HOLDOUT - preferably for a month (or longer).

Why? Here's why!

• Week of the Test, Promo Group = $215,000.
• Month After the Test, Promo Group = $400,000.
• Total Volume, Promo Group = $615,000.

The promotional group generates $615,000 in the five weeks, total. Now, let's see what happens to the holdout group, the group in Arkansas not offered the promotion:

• Week of the Test, No Promo = $100,000.
• Month After the Test, No Promo = $500,000.
• Total Volume, No Promo = $600,000.

This happens all the time. Promotions pull sales "in early". The customer would have spent money in week three, but the promotion pulls the sales (and 30% off and free shipping) into week one.

THIS IS SO IMPORTANT!

I'll bet fewer than 15% of marketing analysts measure results this way. When you do this, your profit and loss statement changes, dramatically.

The profit and loss statement illustrates reality, doesn't it? In reality, the promotion causes the business to bleed profit. Sales are barely impacted, we give away precious gross margin dollars to bump up a promotional period, and then we wonder why business is flat in the following weeks?

And guess what happens when business is flat or down over the next four weeks? Somebody will want to add a promotion!!

So please, please, run this three-step analytical process. This isn't rocket science. Just do it! Whether you are the CEO, the CFO, or a smart marketing analyst, just do the math. Then, when you have the facts, you're free to decide whatever you want. But please do the math. Heck, the math might work out in your favor - it might be appropriate to discount and promote your business like this. But how else would you know it to be true?

And finally - yes, I get it, there's a viral component to these type of promotions - that's why you have to perform your test on a geographic basis, so that you minimize spillover of viral effects. All those allegedly "new" customers who would not have purchased need to be part of the profit and loss statement. Again, that's why this is done on a geographic basis, not on a mail/holdout basis.