Archive for the ‘DataBase Marketing’ Category

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Loyalty Program Structure & Tracking

Friday, July 31st, 2009

The following is from the July 2009 Drilling Down Newsletter.  Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, feel free to leave a comment. 

Want to see the answers to previous questions?  Here’s the blog archive; the pre-blog newsletter archives are here.

Q:  I’m involved in a loyalty program analytics project.  This client is a local pharmacy.  All sales are done directly in store, the web site is just for communication purposes.  The general problem we are trying to solve is the manager doesn’t have any detailed ideas about shoppers behavior apart from human observation. 

The idea is to launch a card-based loyalty program which will track sales activity and give insight into customer behavior.  The program will be points-based calculated on amount spent.  Points can be redeemed as rebates, coupons, gift certificates, or use points to buy items in loyalty program catalog.

The task is to segment customers according to their recent purchase behavior and determine the customer lifecycle.  I’ve been able to do some basic analysis using the R package and MySQL database, but am unable to detect customer lifecycle. 

Can you please give me guidance on this?

A:  What is the Objective of detecting the LifeCycle, to create a more “active” customer retention program?  Loyalty programs can be quite “passive” and often benefit from a more active overlay.  But there can be many reasons to want to understand the LifeCycle…

Q:  My 2nd task is to use the behavioral data with demographics to  build a direct marketing strategy and provide management with insight into the customer base, for example: percent new customers, % of Gold customers who passed to Silver in last quarter.

A:  Again, it would be helpful to understand how management would take action on this data.  But I suppose you are in the common position of not knowing the tactical approach, and nobody will lay it out for you (a.k.a. they are clueless)…and you don’t know the right questions to ask or how to ask them.

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Posted in DataBase Marketing, Newsletters | No Comments »

The Other 3 P’s

Friday, July 24th, 2009

It’s interesting most folks that consider themselves Marketers, especially of the online variety, seem to only discuss and have ideas about Advertising.  But of the 4 P’s that make up Marketing - Product (which includes People), Price, Place, and Promotion – Promotion (Advertising) is the weakest of the four.

I say weakest because Advertising cannot fix a poorly thought out Product, Pricing Strategy, or Distribution system.  It just can’t.  Yet huge amounts of money are wasted trying to do exactly that.

Perhaps this why someone feels they need to publish a book that tells people Product is important in Marketing.  To me, that’s the most circular or redundant idea for a Marketing book I’ve ever heard.

Marketing starts with Product, which should include all the audience or market segmentation studies (People) that drive the creation of the Product - defining the need.  If you do this first and develop a Product which truly fills the need, AND you get the Pricing and Distribution right, the Product will literally sell itself to the core audience.

If you can make it that far, THEN the Product can perhaps be sold to the next segment out from the core through Advertising.  All “Marketers” should know this.

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Posted in Customer Experience, DataBase Marketing, Marketing thru Operations | 7 Comments »

Lead Scoring and Nurturing

Friday, July 3rd, 2009

The following Q & A is from the June 2009 Drilling Down Newsletter.

Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, Feel free to leave a comment.  Want to see the answers to previous questions?  Here’s the blog archive; the pre-blog newsletter archives are here.

Q: I received this article (Norms of Reciprocity, measuring value of Social Marketing) via a friend’s Twitter account.  Very interesting.

A:  Glad you enjoyed it!

Q:  It has made open up my ACT! database, and my Outlook databases and add the metric of Growing / Strong / Weakening / Failed to my normal Sales and Business progress metrics.  If I group those categories and correlate to traditional metrics, it’s impressive how they reflect each other.

A:  Yes, most people are surprised.  It’s a very, very simple idea that seems to work across just about any human activity including crime, attendance, and so forth.  

The more Recently someone has done something, the more likely they are to do it again.  Conversely, the longer since an activity last took place, the less likely the person will do it again.  Often called Recency in Psychology and studied quite a bit.

Q:  Now I have to think about how I really use and apply this. : )

A:  Well, if I can guess you are in Sales from your title, typically one of the best applications is in what Strategic Marketing folks might call “allocation of resources”, which probably translates into “lead nurturing” for you.

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Posted in DataBase Marketing, Measuring Engagement, Newsletters | 2 Comments »

Norms of Reciprocity

Friday, June 26th, 2009

Social Marketing Doesn’t Rely on Social Media

Do you believe human beings share certain fundamental traits that define “being human”?

If so, do you believe that human beings tend to behave in certain ways under certain circumstances?

If so, do you then believe since human behavior has these tendencies, it can often be predicted?

If so, then do you think perhaps the study of Psychology and Sociology might provide you some clues to creating successful businesses, campaigns, products, and services?  While your friends and competitors are all iterating their way into oblivion?

On the web, time and time again, we see the same themes repeating.  Yet with each introduction of a new technology, these themes tend to be treated like a new discovery, even though the theme has been well established in the past.

Norms of Reciprocity is a constant human theme.  You may know the expression of these norms as ”Sharing”.  Web old timers will probably recognize this idea as “Give, then Take” from the I-Sales discussion list as early as 1995.  In various forms, this theme goes back to the beginning of human history, all the way back to the handshake and other greeting gestures.  This same theme is embedded in countless Religions all over the world: “Do onto others as you would wish them do onto you”.  At least a couple centuries old, this idea.

Norms of Reciprocity simply means this: When you do something nice for a human being, help them in some way, this human tends to feel Gratitude towards ”the doer” and tends to do something nice back.  Gratitude drives the desire to Reciprocate, because it’s just what humans do, it’s normal, a “norm”.

Norms of Reciprocity.

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Posted in Analytical Culture, Customer Experience, DataBase Marketing, Measuring Engagement, Web Analytics | 9 Comments »

Hacking the RFM Model

Friday, May 29th, 2009

The following is from the May 2009 Drilling Down Newsletter.  Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, feel free to leave a comment. 

Want to see the answers to previous questions?  Here’s the blog archive; the pre-blog newsletter archives are here.

Q:  First of all thank you for your help.  I have some questions I would be pleased if you answer them for me.

A:  No problem!

Q:  1. RFM analysis – is it possible to use some other ranking technique rather than quintiles? Using quintiles for bigger databases will cause many tied values, isn’t it a problem?

A:  Sure, you can use it any way it works best for you.  There is no “magic” behind quintiles, you can use deciles or whatever works best. It’s the idea of ranking by Recency, Frequency, and Value that is the key concept in the model.

I’ve seen dozens and perhaps hundreds of variations on the core RFM model, depending on how you classify a “variation”.  One change that’s common is changing the scaling, as you mention above, to accommodate the size of the database.  Smaller databases use quartiles or even tertiles.  Larger databases, choose the ordered distribution that meets the need.

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Posted in Customer Experience, DataBase Marketing, Measuring Engagement, Newsletters, Web Analytics | 1 Comment »

Got Discount Proneness?

Friday, May 15th, 2009

Discount Proneness is what happens when you “teach” customers to expect discounts.  Over time, they won’t buy unless you send them a discount.  They wait for it, expect it.  Unraveling this behavior is a very painful process you do not want to experience.

The latest shiny object where Coupon Proneness comes into play is the “shopping cart recapture” program.  Mark my words, if it is not happening already, these programs are teaching customers to “Add to Cart” and then abandon it, waiting for an e-mail with a discount to “recapture” this sale – a sale that for many receiving the e-mail, would have taken place anyway. 

The best way to measure this effect is to use a Control Group.

When I hear people talking about programs like this (for example, in the Yahoo analytics group) what I hear is “the faster you send the e-mail, the higher the response rate you get”.

That, my friends, is pretty much a guarantee that a majority of the people receiving that e-mail would have bought anyway.  Hold out a random sample of the population and prove it to yourself.  There is a best, most profitable time to send such an e-mail, and that time will be revealed to you using a controlled test.  The correct timing is almost certainly not within 24 or even 48 hours.

That is, if you care about Profits over Sales, and trust me, somebody at your company does.  They just have not told you yet!

When you give away margin you do not have to give away on a sale, that is a cost.  Unless you are including that cost in your campaign analysis, you are not reflecting the true financial nature of the campaigns you are doing.  If you are an analyst, that’s a problem.

If you are using cart recapture campaigns, please do a controlled test sooner rather than later.  Because once your customers have Discount Proneness, it will be very painful to fix.

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Posted in Analytical Culture, Customer Experience, DataBase Marketing, Measuring Engagement, Web Analytics | 8 Comments »

Heavy Lifting

Friday, April 3rd, 2009

Another eMetrics (Toronto) has passed and I have to say this:  Web Analysts and Marketers proved once again they are up to the task of continuously improving the Productivity of their efforts!

At the same time, (and as I expressed during the sessions on the analytical culture), I fear that many in the web analyst community are becoming very “inwardly focused”.  They tend to talk more among themselves about the pennies they are making / saving while tripping over the dollars that are right there to be had if they reached out to other analytical disciplines in the company or measurement community.

Many among us knew this was a danger from our BI experiences.  If all you ever do is talk to each other about new shiny objects, your contribution to the business effort can suffer.  BI struggles every day with this weight, the challenge of being labeled “really smart but irrelevant”.  I don’t think we want this to happen to WA.

So with this backdrop, some of the conversations I heard at eMetrics Toronto about certain measurement practices were disturbing.  For example, it seems very few people are measuring their customer contact efforts properly, and in time this lack of analytical rigor is going to damage the WA effort for all practitioners.

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Posted in DataBase Marketing, Web Analytics | 12 Comments »

Use Discounts for Customer Retention?

Friday, March 27th, 2009

The following is from the March 2009 Drilling Down Newsletter.  Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, feel free to leave a comment. 

Want to see the answers to previous questions?  Here’s the blog archive; the pre-blog newsletter archives are here.

Q:  Most CRM experts agree that discount is a terrible way to attract new customers.  They seem to all agree that these “transaction buyers” are money-losing customers and have no loyalty.

A:  I think using discounts profitably for customer acquisition depends a lot on your “Brand Personality” and your business model.  That said, often people screw this up and attract the wrong kind of customer.

Q:  But, I have seen a  lot of different opinions on the use of discounts to increase loyalty and retention among current customers.  I have seen experts contradicting themselves on this subject saying that discount is a terrible way to reward gold customers or to move up customers to a “better segment” and after some time they contradict themselves mentioning a successful discount case study (points are a common method used).  Jim, what is your opinion about using discounts as a weapon in a retention program?

A:  First, we have to define “discount”.  Price discounts have the effect of reducing margins, but so do “better service” ideas like “VIP phone lines” and loyalty programs.  So you can take your discount on the top line or the operational line, the fact is it costs money to provide good service to best customers in hopes of keeping them.  I mean, what’s the $10 million you spent on a CRM system?  Choose your poison, it costs money to retain customers.

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Posted in Brand Management, DataBase Marketing, Measuring Engagement, Newsletters | 2 Comments »

Analytical Culture – 3 Books

Friday, March 13th, 2009

The web analytics conference season is upon us and I find myself sitting on several panels dealing with analytical culture issues.

“The Culture” is a tremendously important issue and am pleased to see the progress since developing the Creating and Managing the Analytical Business Culture course for the WAA.

At eMetrics Toronto, I will be moderating a Round Table discussion group called “Getting Buy-in and creating an Online Analytics Culture” and on a panel moderated by Jim Sterne called “From Web Analytics to Online Intelligence“.  At Webtrends Engage, I’ll be on a panel called “Socialization of Data” moderated by Barry Parshall.

With all this activity surrounding the Analytical Culture, I can’t help but suggest 3 books for those of you who are interested in / struggling with these analytical culture issues.  The first book you probably know about, but for the sake of providing a complete toolkit, I include it - best book for “CEO buy in” I can think of. 

The 2nd two books are probably off your radar screen because they deal with organizational issues, but trust me, these are the concepts the senior people need to understand to get any action going.  I find the biggest impediment to creating a proper analytical culture is the “roadmap” problem, and these two books together pretty much spell it out for you, including lots of tools to get you moving.

Here’s the list:

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Posted in DataBase Marketing, Web Analytics | 1 Comment »

Relationship Marketing in Manufacturing

Friday, March 6th, 2009

The following is from the February 2009 Drilling Down Newsletter.  Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, feel free to leave a comment. 

Want to see the answers to previous questions?  Here’s the blog archive; the pre-blog newsletter archives are here.

Q:  Do the principals in the Drilling Down book apply to manufacturing?  I was first introduced to Relationship Marketing in an MBA course years ago.  I have been looking for an opportunity to test these ideas and now find that chance in this job (I was and still am a foot soldier, but now have more responsibility in these areas).  

Manufacturers typically look at the highest revenue-producing customer, then pull out the manufacturing directory and start calling every company in the same business.  Not really marketing.  Can CRM be used to mine the data we need to be predictive and focused on the value of customers and retention?

A:  Sure, same core issues and metrics apply:

1. Retention: Identify best customers, determine order cycles, set up a report that tells you who “should have” ordered but did not based past on past history, either market to them or send this info to sales, depending on the value of the customer.

2. Recapture / Defection: Identify best customers who have stopped purchasing and find out why, take action aligned with the value of the customer.  You may not get these customers back, but you will learn critically valuable information that will help you retain customers in the future – is there reason in common why these customers left you?  Was there a common Salesperson?  A common Product line?  A common type of Machine used?  A common Material?  Take these findings back into Operations and find out if the issue can be corrected.

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Posted in DataBase Marketing, Marketing thru Operations, Newsletters | 1 Comment »

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