Tag Archives: Marketing thru Operations

The Cost of Queuing Customers

Analytical Culture, Brand Management, Customer Experience, DataBase Marketing, Driller Q & A, Measuring Engagement,

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

If customers have to “wait” for service, does the inconvenience / possible frustration impact their value? Great question; problem is, most businesses don’t know how to answer it in a way that will be meaningful to the value of the business. You know our Drillers though, they’ll get about it with actionable results in mind. On to the Drillin’!

Q:  Are you familiar with (or can you refer me to someone who is familiar with) customer satisfaction around queuing up for service?

A:  This is a Frequently Asked Question for sure, and not one there is a lot of statistically believable data on…at least that people are willing to release.  Kind of a sensitive subject, as you might think…

Q:  I work for a large bank.  We have perceived queuing problems in some of our branches – generally due to layout restrictions. I say perceived because although a queue is long, it moves fairly quickly with the actual wait time to see a teller often less than 5 minutes (considered at par with our competition). 

However, customers grumble when they walk into the branch and see the line and continue to grumble out loud until they reach the teller  and then continue to communicate their dissatisfaction to the teller.  Do you know if any work has been done in this area with other large companies that tend to have long queues (like airline ticket counters, large retailers)?

Thanking you in advance for your response.

A:  I think this issue can be an illusion; let me tell you what I mean. 

For e-commerce, somebody like Gartner does a survey that says people hate shipping charges, and every web site kicks in “free shipping.”  Guess what? People have always hated shipping charges since 1850 when the catalog business started.  And why not?  It looks like extra cost to the customer.  But if you run your business correctly, you price with shipping in mind and manage costs so that you still make a profit.

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Free / Pay Web Site Optimization

Analytical Culture, Customer Experience, DataBase Marketing, Digital Analytics, Driller Q & A, Lab Store, Marketing thru Operations, Measuring Engagement,

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

How do we make money on a content site? Free? Pay? Some combination of both? There’s been a lot of guessing and testing by the big media guys on how to work this, but how do the the small segments / little guys make this work, what can be measured to help? What about newer platforms like Substack, how do you measure optimization? On with the Drillin’ …

Jim’s Note: If you don’t know what Recency and Frequency are they are explained here, and RFM is covered here.  “Intensity” is Views per Session, in this case a “proxy” for visitor value.

Q: Hi Jim,

Should we use:

RFI – Recency, Frequency, Intensity
RFM – Recency, Frequency, and Monetary
or
RF – Recency, Frequency

to measure visitor value, and what should these terms ideally mean?  Total Sessions, Total page views, etc.  Also, when you measure Frequency, do you only include the Frequency during a specific period of time (i.e. one month, or one week), or do you include total lifetime activity per user?

A: On the advertising side of the business, I think the page views/session stat is probably the best to use.  The reality of the ad-based business is it doesn’t matter if they come back, you are selling impressions, not people.  I don’t think you have to overcomplicate it with formulas like RF or RFM, because you are primarily dealing with audiences, not individuals.  RF and RFM are about predicting if individuals will come back.

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Profiling Subscription / Service Customers

Analytics Education, Customer Experience, DataBase Marketing, Driller Q & A, Marketing thru Operations, Measuring Engagement,

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

This Driller knows his stuff, using advanced database marketing techniques on the customer acquisition side. But in a business where the bill gets paid every month and it’s about the same (electric utility), how do you get to the R and F (Recency and Frequency) to model potential customer defections? Great question, and a pithy answer.

Remember, you can use RF profiling on any behavior not just payment related activity! If you don’t know what we’re talking about with this RF stuff, see explanation here.

Q. Jim, Ordered and read your book AFTER reading EVERY page in your website. Your newsletter is outstanding and you seem to be one of the few with real life experience in database marketing with the skills to simply explain with pragmatic examples of how RFM and LTV should be used.

We are a technology based Call Center company with over 70 clients – we do a lot of the “operational” CRM stuff you refer to – Siebel, Onyx, Kana, Webline, as well as a lot of custom developed SFA solutions and data warehousing solutions we developed – mostly the premise of investing to collect enough information to do the 360 view of the customer across communication medium (email, chat, phone, fax) and reason for calling (campaign, sales, orders, info, customer service).

We have a good mix of B-B as well as B-C. We already do a lot of the demographic modeling for list acquisition (SIC codes, size, number of computers, Geo …). One thing I noticed is that we do a lot of lead generation based upon list acquisitions along with inbound marketing campaigns that seem to address one shot Sales, not recurring sales.

For example, we sell and service de-regulated energy for one client – this is sell once, then service. Since they pay every month for the service, how do you suggest the RFM model be used for service based sales since there is not really an R or an F??? We still have acquisition and retention problems, but we mainly focus on operational efficiency through technology, not strategic use of CRM data. I would really like to be able to add real value based upon the data collected.

I know this is not your forte, but I was just curious if you had any opinions using CRM data in an RFM model when the product is basically recurring service.

A: Thanks for the compliments on the site, book, and newsletter. I hope they will be helpful to you as we try to get a firmer grasp on these subjects this year!

It’s a little tough to provide you a direct answer to such a broad question without more details, but in general, R and F are highly predictive of any action-oriented behavior. In a “billing / service” business like a utility, you sometimes have to hunt a bit harder for the action you want to model as predictive.

For example, at Home Shopping Network, use of the automated ordering process (touch-tone interface to the ordering system circa 1990) was very highly correlated with Future Intent to Purchase. Not exactly a traditional RF action, to be sure, but a falling RF score on use of the interface was very highly predictive of a defecting customer.

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