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Drilling Down Newsletter - August 2001 - Latency Metrics, Google AdWords

In this issue:
#  Best of the Best Customer 
     Retention Articles
# Tracking the Customer LifeCycle: 
    Behavioral Marketing
# Practice What You Preach:  
   Online Advertising Effectiveness?  
   Tell Me About It...  (Part 4)
# Questions from Fellow Drillers - suspended 
   for this issue, see below
------------------------------

Hi again folks, Jim Novo here.  This month we've got a little change in format.  We'll start with some hot links as usual.  But I was inundated with questions on the Latency piece from last month, so I'm answering these questions as part of the series on Tracking the Customer LifeCycle, and skipping the "Questions" section for this month.  Plus, we finally get some resolution on the Advertising Effectiveness question...or did we?

Let's do some Drillin'!

Best of the Best Customer Retention Articles
====================

This section usually has links to "must read" articles about to move into the pay-to-read archive at DM News.  I'm afraid the content has been a little less than "must read" from them lately.  So here's a few important articles from elsewhere on the web in case you missed them, all having a very specialized focus.  

Note to web site visitors: These links may have expired by the time you read this.  You can get these "must read" links e-mailed to you every 2 weeks before they expire by subscribing to the newsletter.

Points.com - Loyalty Builder or Loyalty Loser 
July 18, 2001   Colloquy
This article may require free registration to access; if you care about loyalty programs, you should already be registered at this site.  A critical, reasoned look at why "point exchange" or networked loyalty programs will not deliver the results you are looking for in a loyalty program for your business.

Your Best Customers May be Different Tomorrow
July 19, 2001   crm.ittoolbox.com
This is an excellent look at customer analysis in the banking industry.  Forget the 80/20 rule, how about 150/20, which means a huge amount of customers have negative value.  Great stats in this article - if you are into bank stats that is.

Acquire New Customers 
Without Spending $1000/M

July 26, 2001  Catalog Success
Web sites have had good results using targeted offline media like catalogs and direct mail to generate visits and sales.  Next step?  Targeted space buys.  This was written for catalogers, but it does apply to onliners - trust me.  Lots of tips on buying targeted space.

Tracking the Customer LifeCycle:  
Behavioral Marketing
=====================

Last month, I introduced the Customer LifeCycle metric of Latency, or the amount of time passing between two customer actions.  This time passed is usually measured in weeks or months offline, and in days or weeks online.  If you would like to review this article, here is a link to it:

Making Money with the 
Customer LifeCycle:  Latency


No question about it, the constant drumbeat of the CRM machine over the past several years has confused the heck out of people. I've been doing this stuff for almost 20 years now, and I can tell you it is not as difficult as it is often portrayed.  Sure, you can make it very, very complicated if you want to.  But if you don't start with the basics, you're going to end up wasting a ton of money.  Let's start simple, shall we?

I'm going to back up a second and explain in a more general sense how metrics like Latency are used, and in particular, address some of the misconceptions people have regarding customer value-based and relationship marketing techniques.  Much of CRM is based on these fundamental ideas.  Remember, CRM is an approach to managing a business, not a technology.  You do not need to live on the bleeding edge of technology to take advantage of a customer-based management philosophy.

Generally, CRM or Relationship Marketing attempts to define customer behavior and then looks for variances in behavior.  When you hear people talk about "predictive modeling" or looking for "patterns" using data mining, they are essentially taking a behavioral approach using the latest tools.  Once you know how "normal" customers behave, you can do two things with your business: 

*  Formally document normal customer behavior and internalize it systemically, leveraging what you know to improve business functionality and profitability.

*  Set up early warning systems, triggering events, or "trip wires" to alert you to customer behavior outside the norm.  This variance in behavior generally signals an opportunity to take action with the customer and increase their value - inline or offline.

Customers in the aggregate tend to follow similar behavioral patterns, and when any single customer deviates from the norm, this can be a sign of trouble (or opportunity) ahead.  For example, if the average new cellular customer calls customer service 60 days after they start, and an individual customer calls customer service 5 days after they start, this customer is exhibiting behavior far outside the norm.  Is there a potential problem, or opportunity?  Is the customer having difficulty understanding how to use advanced services on the phone, or is the customer happily inquiring about adding on more services?  In either case, there is an opportunity to increase the value of the customer, if you have the ability to recognize the opportunity and react to it in a timely way.

Understand, there is no "average customer," and a business will have many different customer groups, each exhibiting their own kind of "normal" behavior.  The tools available to identify and differentiate customer segments using behavioral metrics are discussed at length on almost every page of this web site.  For example, the type of media or offer used to attract the customer can have a dramatic effect on long term behavior, and customers who come into the business on the same media and offer will tend to behave in similar ways over time.

In the cell phone case above, the measurement of Latency (number of days until customer service call) serves as the "trip wire," a raising of the hand by the customer, to say to the marketer "I'm different.  Pay attention to me."  It is then up to the marketing behaviorist to determine the next course of action.  Metrics like Latency provide the framework for setting up the capability to recognize the opportunity for increasing customer value. 

This raising of the hand by customers, and the reaction by marketers, is the feedback loop at the center of Relationship or LifeCycle based marketing.  It's a repeating Action - Reaction - Feedback cycle.  The customer raises the hand, the marketer Reacts.  The customer provides Feedback through Action - perhaps they cancel service, or perhaps they add service.  The marketer reacts to this Action, perhaps with a win-back campaign, or with a thank you note.  It's a constant (and mostly non-verbal) conversation, an ongoing relationship with the customer which requires interaction to sustain.  It is not a relationship in the "buddy-buddy" sense.  Customers don't want to be friends with a company, they want the company to be responsive to their needs - even if they never come out and state them openly to the company

This relationship continues to cycle over and over as long as there is value in the relationship for both the customer and the marketer.  If the customer takes an Action and there is no Reaction from the marketer, value begins to disappear for the customer, and they may defect.  When value disappears for the marketer (the customer stops taking Action / providing Feedback), marketers should stop spending incremental money on the customer.

Notice I did not say "fire the customer" or any of the related drivel thrown around in some of the CRM venues.  All customers deserve (and pay for) a certain level of support.  The real question is this: for each incremental, or additional dollar spent on marketing to the customer, is there a Return On the Investment?  If I have the ability to choose between spending $1 on a customer returning $1.10, and $1 on another customer returning $3, I would be nuts not to choose the customer returning $3.  I have not "fired" the customer returning only $1.10; I have just chosen not to spend incremental money doing any special marketing to them. 

Do you see the difference?

In fact, much of the profitability typical of high ROI Customer Marketing techniques comes from knowing who not to spend on. Most of the decreased profitability in any marketing program is a result of over-spending on unsuitable targets with lowered returns.  But because marketers tend to look at results in the aggregate, or they are looking at demographically-based segments to measure a behaviorally-based outcome, they miss details like certain segments returned $5 for each $1 spent, and others lost $5 for every $1 spent.  The campaign as a whole may return only $1.10 for each dollar spent because the marketer spent money on low Return On Investment customers. 

When you are trying to encourage a customer to buy something, you are looking for a behavior to occur.  To measure the results of such a marketing campaign using only demographic segmentation without any behavior-based metrics (like Recency or Latency) is misleading at best, and lazy otherwise - it's apples and oranges.

Why is this all important?

Customers who are in the process of changing their behavior - either accelerating their relationship with you, or terminating their relationship with you - are the highest potential return customers from a marketing perspective.  They represent the opportunity to use leverage, to make the highest possible impact with your marketing dollar.  You may make money marketing to customers who are just cruising along the LifeCycle, acting like an "average customer."

But when you can predict the likelihood of an average customer to turn into a best customer, and you successfully encourage this behavior, or you can reverse a customer defection before it happens, there are tremendously profitable longer-term implications for the bottom line.  You discover these opportunities by understanding behavior and setting up trip wires (like Latency metrics) to alert you to deviations from normal behavior by a customer. 

What about all the rest of the customers, those who are not either accelerating or terminating the relationship?  Leave 'em alone.  Whatever background marketing you do (advertising, branding, service campaigns, etc.) is serving them just fine. 

High ROI data-driven marketing techniques are best used (and create the highest returns) when they are used to surgically strike at a trend in behavior, not when customers are comfortably plodding along.  However,  there's not as many comfortable plodders as you think; in fact, from 40% to 60% of your customer base is either in the process of accelerating or terminating their relationship with you right now.  The question is, how do you take advantage of the situation? 

Latency, and all the other metrics described on the Drilling Down site, are simply tools for recognizing the opportunity to take an Action in Reaction to the customer raising their hand.  If you don't have some kind of system to recognize customers in the process of changing their behavior, you will miss out on most of the highest ROI customer marketing opportunities you have. 

And don't count on the customer to e-mail you when they're thinking of changing their behavior - we both know that just is not going to happen.  A more likely scenario: they will just stop taking Action and providing Feedback.  And by then, it's too late for you to do anything profitable about it. 

Set up your trip wires and predict the behavior, folks.  It's the only way to sense when an average customer is ready to become a best customer.  And reacting to a customer defection after the fact is a truly sub-optimal way to "manage" a relationship. 
------------------------------
If you'd like to see more on LifeCycle-based marketing in future newsletters, be sure and let me know.
-------------------------------

Practice What You Preach: Online Advertising
Effectiveness?  Tell Me About It...  (Part 4)
=====================

Last month we took a look at the quality of visitors generated by my paid search listing ads on Google and GoTo.  The following table compares visitors using the 3 most popular search terms to find my site with the "average" paid search visitor.  RM = Relationship Marketing, CR = Customer Retention, CL = Customer Loyalty, and TS = Total Site statistics, all paid search listings:

Metric___________RM___CR___CL___TS
Avg. Visit Length     8.49   8.44   6.87   8.21
% 1 Page Visits      24%    22%   20%   43%
% Downloading     8.2%   6.1%   3.7%  3.1%
% Bookmarking    9.6%   7.6%  12.2%  5.9%
% Subscribing       4.5%   4.5%   2.4%   3.2%

Well, we're getting there.  We've previously proved visitors clicking on a paid listing are of higher quality than "free search" visitors for the same search term, and now we see there is also significant variability in quality of visitor by the term itself, according to the chart above.  Look at Customer Loyalty (CL).  Much shorter visits, and lower download and newsletter subscribe percentages, but much higher bookmarking percentages. What could this difference in behavior mean?

The stats above are a combination of all visitors for the same terms from both Google AdWords and GoTo, so it seems logical the next "Drill Down" would be to look at each source individually, and that is just what I have done.  For clarity, instead of creating two charts and having you bust your eyeballs trying to compare them, I have created a *ratio* between the Google and GoTo numbers.

Google to GoTo Ratio
================
Metric____________RM_____CR______CL
___________________________________
Avg. Visit Length        65%     125%      308%
% 1 Page Visits        110%     115%        91%
% Downloading          48%     112%      570%
% Bookmarking         72%       44%      160%
% Subscribing            85%       84%      140%

If you were to read down the Relationship Marketing (RM) column, this chart says:

"For the paid search term Relationship Marketing, the Average Visit Length for visitors from Google is 65% that of GoTo, the percent one page visits is 110% that of GoTo, the percent Downloading is 48% that of GoTo," and so on.  A number over 100% means Google is higher than GoTo, under 100% means Google is lower than GoTo. 

One thing is perfectly clear from this chart - Google dramatically under-performs GoTo for the paid search term Relationship Marketing, and outperforms GoTo on the paid search term Customer Loyalty, across the board, in every category (note a lower number on 
% 1 Page Visits is better).

Things are less clear-cut for the term Customer Retention, although I'd have to give it to GoTo because Bookmarking and Subscribing to the newsletter are highly correlated to future purchase of a book.

Where does this leave us?  Overall, it appears you can not attribute "quality" as defined here to either a search term or a search engine; there is a * combined * contribution which creates dramatic visitor quality differences.  This is a perfect example of the mistake people make when using "averages" or looking at the "average customer" - rarely does the average customer represent the true underlying behavior of the actual customers. 

Tactically, it means I should budget paid search expenses by term by engine, and in the case above, shift most if not all the budget for Relationship Marketing to GoTo, and most if not all the budget for Customer Loyalty to Google.  Customer Retention might need a little more work to resolve, but instead of running the budget 50 / 50 as initially set up, it would make sense to maybe run 70% on GoTo, and 30% on Google, from what I see here. Hey, it doesn't always come out black and white, you know? 

As far as why this occurs, it's fun to speculate, but a marketing behaviorist cares more that it  does happen - it's a fact, Jack - and takes action based on this fact.  There's plenty of time to wonder about it later, after the spending has been reallocated and the highest ROI possible is being realized. 

A "gun to the head" guess?  It's the content at the other end of the click making the difference.  The content on the Customer Loyalty page appeals more to a Google user, and the content on the Relationship Marketing page appeals more to a GoTo user. 

Why?  I haven't got a clue.  Check them out for yourself:

Customer Loyalty (favored by Google user)

Relationship Marketing (favored by GoTo user)

Let me know what you think.  If the responses seem to be trending one way or the other, I'll present the arguments in the next newsletter.  Meanwhile, the idea of content making the difference (a 3rd variable in addition to term and engine?) is kind of interesting - maybe there's a way to test the idea. 

I'll let you know...

--------------------------------
If you'd like to see more on web log analysis
in future newsletters or comment on the Google versus GoTo page preference issue, contact me using this address.
--------------------------------

That's it for this month's edition of the Drilling Down newsletter.  If you like the newsletter, please forward it to a friend!  Subscription instructions are at the top and bottom.

Any comments on the newsletter (it's too long, too short, topic suggestions, etc.) please send them right along to me, along with any other questions on customer Valuation, Retention, Loyalty, and Defection, to me.

'Til next time, keep Drilling Down!

- Jim Novo

Copyright 2001, The Drilling Down Project by Jim Novo.  All rights reserved.  You are free to use material from this newsletter in whole or in part as long as you include complete attribution, including live web site link and/or e-mail link.  Please tell me where & when the material will appear. 

 

 
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