Marketing Productivity Blog

Ron Shevlin of database marketing powerhouse Epsilon thinks a new core competency requirement for marketers is the “ability move customers through the buying cycle with a sense-and-respond capability”.  This is something I often talk to people about, it’s really a subset of the “I have the data, now what do I do?” problem.  Marketers are more familiar with creating campaigns based on nameless, faceless GRP’s than the behavior of real people.  And that’s the problem. 

I think part of the problem is in segmentation, they simply don’t understand how powerful behavioral segmentation is, how different it is than using demographics - and they lack the ability to ask for / get this information in a format that drives action-oriented thinking.  The granularity of “people” as opposed to GRP’s throws them off.  With Sense And Respond Marketing, or what I would call Relationship Marketing, you use the Customer LifeCycle to influence messaging which is meaningful to people based on behavior, not demographics.  The behavior is the message, not the age, income, make of car, or whatever.  Using behavior makes so much more sense when you see an 80 year old on a Harley.

Here’s an example.  One thing that happens with interactivity is people tend to “gorge” themselves on something, get tired of it, and move on to the next experience (video games, Friendster).  So you have to work very hard to hold on to them.  At HSN, we used to listen very carefully to what customers said on the air and reviewed comment trends in customer service every single day.  One thing we started hearing was “I’ve only got 10 fingers” which is the customer saying “you are selling too much jewelry”.  At the same time, we were looking at the LifeCycle of best customers and found that most of them were fashion buyers who started buying in jewelry - regardless of how old they were or what their incomes were.

So we have customers telling us we sell too much jewelry, and we end up losing a lot of them because they get bored.  But at the same time, best customers are created when someone starts buying jewelry and moves into fashion.  We have a natural transition from new customer / jewelry to best customer / fashion that some customers found their way to and others did not.  Knowing this behavior exists and that it’s very profitable for HSN, can we influence it?  Can we get more people to make the jewelry to fashion transition with a marketing campaign of some kind?

Well, the first thing is timing.  When to drop the campaign?  You can’t drop it on a “date” to all customers, you have new customers coming on each day and they are going through a LifeCycle.  However, the data said if the customer did not start buying fashion by the 120th day of their LifeCycle, they would probably never buy fashion.  So somewhere in that 90 - 120th day after becoming a new customer, we need to hit them with a “buy fashion” message.

OK, so what is the message?  Well, we know from customer comments (and remote selling in general) that people are reluctant to buy fashion remotely because they are worried about fit.  So what would be the easiest fashion item to sell a remote customer?  How about something like a running suit, you know, Small-Med-Large-XLarge?

So we put together these special fashion shows geared to “no brainer fit” fashions and had them run at very specific times on the network that we could promote to the customer in advance.  We dropped a very simple piece that said, “We’d really like you to try our fashions, here is $10 off, here is when to watch” kind of thing.  And we dropped it somewhere in the 90 - 120 day window after the customer’s first purchase.  Understand, these pieces went out every week but they went to very specific people with specific behavior who were entering “the zone” of 90 - 120 days after first purchase of jewelry.

And we literally printed money from that point on with this program.  For every $1 in cost, we generated $25 in incremental (versus control) profit in the first year of the customer life, every day, day in and day out, as a higher percentage of new customers converted into long-term, highly profitable fashion buyers.

Was that a hard program to design?  Not to me, seems completely logical.  You have behavior, you know the customer, you have timing points, copy is simple and direct.  I think Ron probably had something a little more sophisticated in mind when he wrote Sense And Respond Marketing, but the basic concept is the same (and after all, we were dealing with mainframes and snail mail at HSN in 1994, so cut me some slack!).

So why is it again that people have this “I have the data, now what do I do” problem?  I suspect it’s because they may have the data, but it’s not in any kind of actionable report format that generates ideas.  GRP Marketers simply don’t know how to ask for the data / can’t get the data in a format that lends itself to creating effective campaigns.  And that’s a shame, because it’s pretty simple to have someone do it for you or you can do it yourself.

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.

Internet Retailer Magazine provides this article based on interviews with 2,472 online shoppers.  Shoppers ranked the “helpfulness” of a list of functions on retail websites; merchants ranked the “value” of these same functions. 

Areas where the consumer gave high rankings but merchants gave low rankings:

Product Comparison
Customer Reviews
Order History
Loyalty Program

Areas where the consumer gave low rankings but merchants gave high rankings:

What’s New
Upsell / Cross-sell
Top Sellers
Gift Suggestions

The author of the article does a good job of laying out what this all means about customer behavior and I concur so I won’t get into it.  It’s pretty clearly an example of Marketing Non-Productivity though.  How could this happen?

Well, probably because there were no marketing people involved with the design of the basic shopping cart, or if there were, they didn’t know anything about customer behavior.  The myth of cross-sell and upsell continues today.  You don’t cross-sell or upsell anything to somebody they didn’t already want.  Trust me.  So to waste all this time on cross-selling and upselling instead of producing better marketing, design, and systems is ridiculous.  Offering someone a related product that they would have bought anyway if they had only been able to find it is highly unproductive.

However, the above situation does sound like a very good setup for my friends at Bazaarvoice and Kobie 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.

Chief Marketer newsletter provides us with a list of 10 non-obvious benefits of loyalty programs.  Funny thing, these 10 could be applied to almost any customer-data-based marketing programs.  Loyalty programs are among the most difficult of these programs to execute properly, but they can drive a huge return on the investment when designed and executed correctly.  Unfortunately, Loyalty Programs have a bad “ROI rap” because many are designed poorly and have to be killed.

I beg to differ on this statement in # 10 though: “There is always selection bias in any voluntary program, and loyalty programs are no different.”  That’s a design issue.  The recruitment design doesn’t have to be “voluntary”.  You can usually find a way to selectively and specifically invite different types of customers, at least in the beginning, so that you can look at profitability versus a control group.  That is what was done in the cellular case study linked to above.

Not sure Crayons are the best compare, but Calculators work for me.  In this article from CRM Magazine we hear about how the accountability movement is affecting marketers, and about the need for closer alignment with other silo functions to increase Productivity.  That’s pretty much what my blog is about; what do you think?

The “alignment with IT” thing is the really sticky part; it’s interesting that more IT people seem willing to learn marketing concepts than the other way around (see web analytics).  But I have to tell ya, every place I have worked it has paid off big time on the marketing side to get with the engineering or IT folks and try to understand the basics of what they do and how things work in the company.

When I was in cable TV, I went out with the installers and engineers on a regular basis just to figure out what they cared about and what they did.  This interaction led to a string of marketing programs based around engineering issues that not only improved productivity on the technical side of the business but also generated good returns on the marketing side.

The classic was running contests on the system that only cable subs could see, targeting areas where we suspected there was a high theft of service level.  People hooked into the system illegally would call up to claim their prize and we would politely ask them if they would like to subscribe… “Mr. Smith, the contest is for cable customers only and we have no record of service with you.  If you’d like, I can sign you up and then you will be eligible for the prize…”

Yes, engineering, marketing, and customer service had to work together to pull it off.  Is that really such a weird idea?

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.