Monthly Archives: January 2007

Do You Read IT Management Magazines?

Analytical Culture, Analytics Education, Marketing / Tech Interface

If not, why not?  Just because you are a marketer?  How then, do you talk to IT people in a language they can (partially) understand and get anything done?  How will you increase the Productivity of your marketing efforts without having a useful dialogue with IT?  If you can’t increase the Productivity of your programs and deliver better results, what will happen is your job will be “absorbed into the Network”, as Regis McKenna would say.

If you are in Marketing Management and are looking for a seat at the strategic table you have to understand some of this stuff.  The CEO, COO, and CFO do; why not you?

At least try to read these magazines:

Intelligent Enterprise – the data / architecture side of Marketing Productivity; Business Intelligence, Data Modeling

Optimize Magazine – More about Business Process Stuff; Modeling, Management, Sensing and Alerting, Six Sigma

BaseLine Magazine – This provides hard core, detailed case studies on Business Optimization.  Amazing stuff, hard to believe they get execs to fess up to some of these giant productivity disasters.  Mostly focuses on operations, but why is operations not of your concern?  Operations impacts the customer, the customer is your main focus (right?).  When you read these cases, imagine how these customer-touchpoint disasters affected the outcome of every marketing program running at the company.

DM Review – this one can be some tough sledding, a lot of it is about systems, but hey, how long are you not going to care about systems?

You will not understand everything these magazines are talking about (especially the last one), but that’s not the point.  The point is to learn what they are talking about, and try to figure out how you can take advantage of it when it happens.

Heck, even help it happen or make sure it happens in a way that is the most productive for marketing.  These magazines are must reads for any marketing person thinking of joining a Business Swat team.

Flat Rate Shipping?

DataBase Marketing

In Pricing and Ecommerce – Some Thoughts, Adelino points to some of the most common pricing models for shipping, including the traditional catalog “by order total range” and the Amazon “threshold” model and provides some spot-on analysis.

While one could argue that in the “range” model, the cost of shipping as a percent of order falls, I don’t think consumers really look at it that way. I think they wonder why they are “punished” with higher shipping costs for placing larger sized orders. Perhaps they don’t. But they sure like flat rate pricing for shipping when they see it.

We played extensively with S + H at Home Shopping Network in the early days, and what we found to be most successful was a flat shipping charge. I continue to use this approach with clients on the web today, where possible. It drives average order size like nobody’s business as people pile more stuff into the cart because “it doesn’t cost any more”. If you understand the financial model of the mail order business, you understand that boosting average order size drives profits like (almost) nothing else you can do. Also, being able to promote “Shipping is $6 per order, no matter how many items you order” in your advertising and all over the site eliminates any questions people have about shipping, which reduces cart abandonment.

This approach, of course, takes an intimate knowledge of the business, a study of UPS (if that is your carrier) rate structures, and understanding the general geography of your customer base. You have to know what your real average shipping costs are and peg your flat rate accordingly. For heavy products, you should build some shipping cost into price in order to lower the flat rate, which will not work in a commodity product environment.  And good merchandising that encourages customers to upsell themselves helps a lot to drive the average order size. We even have some people who put flat rate at under cost and charge the difference to marketing, which is an accounting view of this approach. It certainly could be argued that the flat rate is a retention marketing technique, if not an acquisition technique as well.

Amazon is perhaps a unique case in that both the margins and average prices are low relative to product weight; they’d probably get killed on flat rate and a threshold approach serves them best.

If you had a shipping bill of $120K last year and you shipped 20,000 orders, your average cost to ship an order is $6. Why not charge a $6 flat rate per order and see what happened to your average order size? Sure, your shipping costs will go up with average order size but unless your margins are thin you will drop a lot more money to the bottom line.

Clearly, the success of this approach depends on the breadth of your lines and their sizes / weights. But if you generally ship in a 12 x 12 x 12 box or less and you’re not shipping rocks, it should work out for you. Take a look at what each extra pound above 1 lb and 2 lbs really cost you versus a 20% increase in average order size. You’ll see.

As Adelino says, the trick is in pouring over the financial details of the business.

Top Exit Pages Data – Useless?

Web Analytics

Avinash says on his blog, “For the most part you should not care about this metric [top exit pages], for most websites it tends to be a hyped up metric that tells you little while, on paper, claiming to tell you a lot.” Most of the commentary on his blog seems to agree with him.

C’mon folks.  Methinks when you are as skilled as Avinash is, or you have been analyzing the same web site for a long time using advanced tools, sure, the metric can be next to useless. I don’t even look at the “Overview” stats for any of my sites anymore, because I have Custom Reports that tell me what I really want to know.  I advise clients to take the same approach.

But, when you sit down to analyze a site you have never analyzed before, there is nothing that can orient you like first looking at Top Entry and Top Exit pages. For me, it creates a visual map of the basic behavior on a new site and causes me to start asking the questions that will be the subject of further study. And for a person that is brand new to web analytics, simply seeing Top Entry and Top Exit stats for the first time has a huge impact, it gets them to the “First Why?”, if you know what I mean. It’s a very simple model that is easy to understand.

Perhaps interacting with the students in the UBC / WAA web analytics courses has made me more sensitive to this issue, but I think we might better qualify statements like this, for example, “For the most part, advanced users should not care about this metric…” because there are a lot of folks “listening” out there who might lack enough context to correctly parse a statement like this.