Marketing Productivity Blog

Timing, Counting, & Choice.  “Most real-world business problems are just some combination of those building blocks jammed together” - Peter Fader

Over at CIO Insight we have this very practical article on Data Mining by Fader.  What it’s good for, what it’s not good for.  If you have wondered how you might use this tool, especially if you are a Marketer, you should read this article. 

I say the article is practical because even though there are many ways to create mathematical models of customer data, if the end result is not something a Marketer can use to actually increase Marketing Productivity, then you really cannot do much with the output.  The models have to create leverage of some kind that can be used to take real world action.  In other words, a model can be “technically correct” but completely useless to a Marketer.

For example, just because you can identify a segment doesn’t mean it is practical or viable to address that segment with a unique marketing treatment.  And just because the segment has unique characteristics doesn’t mean those characteristics create any real marketing opportunity.

Key takeaways for Marketers from this article should be:

1.  Too much data tends to mess up a model.  This is especially true if you try jamming all kinds of demographic crap into a model that is trying to predict behavior.  If you want behavior as an output, use behavioral variables in your models.

2.  Data mining is a great classification tool; it is good at telling you why segments are different.  But in order for this to be useful, you need actionable segments to begin with.  For example, data mining can tell you the demographic differences between people likely to respond versus people not likely to respond - if there is a demographic difference.  But you have to know this “likely to respond” element first.  While we’re on this topic, the same idea holds true for surveys.  If you want the survey output to be actionable, get to known behavioral segments first, then do your surveys of each segment.

Often, people use technical tools for the wrong Marketing reasons.  I see this problem coming down the tracks in web analytics, people are getting so wrapped up in the minutia and the automation of testing they are missing out on the basic stuff.  Just like the data mining wave got people off track and into the bushes with “collecting all the data so we can mine it”.  But it doesn’t matter how much data you have, the tool does what it does and doesn’t do what it doesn’t do.

Check out the article What Data Mining Can and Can’t Do here.

Any thoughts from the Data Miners out there on this?

I had a request to publish my “About the Blog” page as a post so people could comment on it.  Here ya go Jacques.

From the Drilling Down newsletter, 12/2004:

What is the number one characteristic shared by companies who are successful in turning customer data into profits?  The company fosters and supports an analytical culture.

Web analytics and Pay-per-Click Marketing in particular have served to teach many people the basics of applying the scientific method to customer data and marketing - creating actionable reporting, tracking source to outcome, KPI’s, iterative testing, etc.  The web has allowed companies to dip a toe into the acting-on-marketing-data waters at relatively low cost and risk when compared with offline projects.  And many have seen incredible ROI.

I think web analytics could be poised in the future to serve a greater role - teaching people / companies the optimal culture for success using analytics, also at relatively low cost and risk.  It’s going to be much harder to drive this concept but more rewarding if as users we can make this happen, because today’s web analysts (and maybe analytical apps) could potentially be among tomorrow’s leaders in a data-based, analytics-driven business world.

For example, do you think analyzing / understanding new interactive data streams where the interface is not a browser will be any different, in terms of the culture required to turn interactive customer data into profitable business actions?  I don’t.

Look, a “request” is a request, whether a click, IP phone call connect, cable TV remote button push, verbal command, card swipe, RFID scan, etc.  You’re still asking a computer to do something.  The request has a source, is part of a sequence (path), and has an outcome. 

Analysis of these requests will face challenges and provide potential benefits similar to those provided right now in web site analytics.  This is the beginning of analyzing the interaction of computers, people, and process.  

Without a doubt, no matter what form these requests take, there will be a “log” of some kind to be analyzed.  Usability?  Conversion?  ROI?  These issues are not going to go away, and companies need to develop a culture that properly embraces analyzing and addressing them.  Companies not developing this culture will find themselves continuing to bump along the “drowning in data” road and will never optimize their interactive customer marketing.

As I see it, here’s the “culture” issue in a nutshell: as a company, you have to want to dig into data and really understand your business.  This pre-supposes that you (as a company) believe that understanding the guts of your business through analytics will drive actions that increase profits.  If the company doesn’t generally support this idea, there is no incentive for anyone to pursue it and the company just happily bumps down the road.

Of course most people don’t really relate to the “company”, but their own division or functional silo.  So you might have manufacturing / engineering groups who live and die through analytics but marketing is not held to the same standards and thought processes.  This is where the idea of Six Sigma Marketing comes in, it’s a “bridge” of sorts that tries to say (perhaps to the CEO and CFO), “Hey folks, if the engineers can engage in continuous improvement through ongoing analytics, so can the Customer Service silo and the Marketing silo and perhaps others.”

At a higher conceptual level, analytical culture takes root when management makes it known they are not afraid of failure, and want employees not to be afraid of it either.  

Another way to say this is experimentation and testing are encouraged throughout the company.  Failure is a regular occurrence, and is even celebrated because through failure, learning takes place.  Show me a company with no failures or that hides failure and I’ll show you a company that is asleep at the switch, afraid of its shadow, a company soon to be irrelevant to the market it serves.

Hand in hand with accepting failure must be continuous improvement.  Even though failure is embraced as a learning tool, the lesson of the failure both prevents it from happening again and results in new ideas with a higher potential for success.  These twin ideas of embracing failure / continuous improvement are at the heart of every business successful in using analytics to improve profitability.

“Evidence” of a company with the right bones to grow an analytical culture is this: you see the various levels of employees working in cross-functional teams with a common problem-solving mission.  Instead of people in a silo groaning about members from other silos being present at a problem-solving meeting, people are instead asking, “Where is finance, where is customer service?”

The most common place “analytics” live in a company is in Finance with the “Financial Analysts”, who are mostly tasked with analysis related to financial controls and producing financial reports.  If marketing or customer service was willing to expose themselves to the rigor of these analysts, they would undoubtedly be able to improve their business areas.  But that exposure takes substantial guts and confidence in your abilities, and a “culture” that supports a scientific process.

And you can’t engage in this process without analytics; success and failure need to be defined and measured.  The easiest way to encourage this culture to take root is to team a department head with a Financial Analyst familiar with the area.  

Often, you find this finance person already has insightful questions that could lead to improvement, but “never asked” because “it’s not my job”.  And often, to make changes in a business today, you need IT support of some kind.  That’s the basic cross-functional unit - Finance rep, IT rep, and a department head.  

I would also argue that if Marketing has a seat at the table in the strategic, “Voice of the Customer” sense (as opposed to being relegated to Advertising, PR, and Creative), then marketing is part of the core unit.  Then you add other disciplines as needed based on the particular problem you are trying to solve.

If the culture is flexible enough, this can turn into “Business SWAT” where the best and brightest cross-functional teams roam through the company as “consultants”, tackling the hardest business problems, which (surprise) are usually cross-functional in nature.  And “blame” is never on the agenda, it’s about “how can we help you make it better?”  You need a culture that is clear about this idea in order for people to expose themselves to the analytics-based scientific process.  Success and failure are defined by the analytics.

If you think about it, web site management ruled by analytics is a microcosm of this Business SWAT set-up.  You have marketing, finance (ROI component), and technology all working together based on the data.  That’s why I think there is a higher mission for the web analytics area / people; they are building the prototype that can teach companies how to go about measuring, managing, and maximizing a data-driven business.

At the highest level of this culture, managers “demand” these SWAT teams because the success rate and business impact is so high.  As the various departments or functional silos produce wins and losses, capital (budget) flows to where the successes are and away from the failures.  When managers see this happening, they jump on board, because they want the budget flowing their way.  This creates a natural economic supply and demand scheme with a reward system for participation built into the process.

One caution: when the culture gets to this level, the analytics group must be sanitized from the reporting hierarchy.  It can’t report to finance, or marketing, or IT anymore.  It has to be completely independent, which usually means reporting directly to the CEO.  There has to be confidence in the integrity of the results of all testing based on standards.  All the little “pools” of analytical work throughout the company must be gathered into one.

What kind of companies do you see really engaging in this kind of culture right now? Those that for legacy reasons have always had access to their operational and customer data and have been using analytics for years.  For these legacy players, web analytics is a “duh” effort - they get it right out of the box, because it’s more of the same to them.  But many types of businesses have not had this access to data before and web analytics is the first taste they are getting of the power and leverage in the scientific method.  I think this “accountability” disease we’ve created in web analytics and search marketing will continue to spread and infect every business unit.

The longer-term question is, can we flip this model over, can the successful culture of cross-functional approach and continuous improvement used in web analytics be used to create a “duh” moment for other areas of the company?  Will “best practices” and success stories create an environment where people say to the (web?) analytics team, “Hey, can I get some of that over here?”  In other words, will the analytical culture develop?

Methinks there is more going on with web analytics than meets the eye; it’s potentially a platform for the creation of a new business culture, a culture based on the scientific method - Six Sigma Everything.  Sure, it’s awkward and maybe the web is not meaningful enough yet to many companies.  But as we thrash all this out, there is something greater being learned here.

Right now, many CRM projects can’t show ROI because nobody knows what to do with the data, how to turn it into action that improves the business.  Sounds very much like web analytics 5 years ago…and look what we talk about now.  KPI’s, turning data into action.  The analytical culture playing out.

What does this mean for the people currently involved in web analytics?  If I was a young web analytics jockey, I would be preparing for the spread of the analytical culture, and seriously thinking about learning some of the tools traditionally used in offline analytics - the query stuff like Crystal Reports, the higher end stuff like SAS, SPSS, and so on.  Search the web for “CHAID” and “CART” and see if you like what you read about these analytical models.  If this kind of stuff interests you, you are much closer to being a business analyst than you think.  And guess what?  Analysts who can both develop the business case and create the metrics and methods for analysis - like you have to do for a web site - are rare.

It takes a particular mind set, and that mind set is not common.  Most of the people with the right mind set go into the hard sciences, but demand on the soft side of business (marketing, customer service, etc.) is just beginning in our data-driven world.  

On the hard side, (with all apologies to the real engineers out there for the exaggeration) the drug works or it doesn’t, the part fits or it doesn’t.  The development of softer-side marketing and service analytical techniques is always going to be populated with a lot more gray area than there is on the hard side, and it takes a special skill to conceive of and develop the metrics required.  But we should be trying to bring the same analytical rigor to the soft side of business that the hard side has always had to deal with.  The trick is to apply that rigor without damaging the mission.

For example, the whole “fire your unprofitable customers” thing from some factions in CRM.  That’s ridiculous.  What you want to do is identify them and then act appropriately, whether that means controlling their behavior, not spending additional resources on them, or not doing the things that create them in the first place.  That’s the gray showing.  You don’t just hit the “reject button” on a customer.

Customer data is customer data.  It’s all going to end up in one place eventually as the analytical culture spreads, and those with the skills to apply the scientific method across every customer data set are going to be rare and in very high demand.  Don’t spend all your spare time watching the Forensic Files on Court TV.  You’re a business analyst.  Get out there and learn the rest of your craft!

And, please consider doing whatever you can, whenever you can, to spread the analytical culture within your company.  If most of what your analytics involve is “online marketing”, reach out to “offline service” or another silo and ask if you can help them with anything.  What’s the call they would like to take less of, can you use the web site to make that happen - and prove that it worked?  Can you use the web site to generate offline ROI?  

Web analysts, you are the cross-functional prototype.  Please teach others how to optimize the entire business.

Here’s another Customer Experience kind of test that proves you can generate incremental profit by improving the Experience.  You just have to make sure customers want the experience “improved”.  This example is from the Lab Store and the ROMI on this little program is a real eye popper.

Back in the old days (meaning the 80’s), what I guess is now called WOW was referred to as “surprise and delight”.  Essentially, this 2-step idea works like this: when you surprise the customer, you really get their attention.  If you can get their attention by surprise and delight them at the same time (instead of pissing them off with your surprise), then you are going to have a more loyal customer.  The trick, of course, is to somehow make more money doing it…

New Customer Kits are a very simple way to do this, and in my remote retailing experience, it works every time.  First impressions, in case you didn’t know, are really important - and especially so in remote retailing, where there is no way for the customer to get any tangible “feeling” for the company.  Sure, you have copy on the web site that paints a picture.  But how many times have people read all this wonderful copy only to be screwed when delivered the tangible experience?

The challenge is to design a kit that is relatively inexpensive yet packs an emotional delight.  Lots of people toss extra stuff for the customer in the first order, but that stuff is usually company-centric, for example, “Here is a magnet with our URL on it” or “Here is a catalog of our other products”.  That’s fine, but it’s neither surprising nor delightful.

Here is what makes up a good New Customer Kit, based on years of testing:

1.  A letter or other message from the company that Welcomes the customer, talks about the people and philosophy behind the company, and reinforces any guarantees or promises that are part of the Brand.  This piece must be written carefully, and from a customer-centric point of view.  No “we we” stuff.

2.  A free gift.  This gift must be related to the merchandise or general category being purchased, and must not be discards, seconds, or defective merch.  Giving a new customer something that is dented or discolored is not a gift, it’s an insult.  Giving a new customer something that is promotional (magnet) may be a gift, but it is expected and not particularly delightful.  Giving a new customer a “gift” because they made a first purchase (Buy today and we’ll include a…) might be delightful but sure is not surprising.  Ignore the above cautions at your own peril.

3.  Free Samples, if relevant to the business.  Anything that is consumable and generates repeat purchase is ideal.

Anyway, I suppose you’re expecting some kind of numbers to go along with all the fuzzy-wuzzy “Oh, if we just make their experience better, they will be more loyal” drivel you hear all the time online.  This is the Marketing Productivity Blog, after all, right?  OK, here are the stats on this technique from the Lab Store.  As usual, this promotion was tested versus control (new customers who did not receive a New Customer Kit are control) and we compare sales activity of both test and control over the next 90 days.  Why 90 days?  Well, if it makes money at 90 days, it sure makes money at 120…

Average cost of New Member Kit (there are several versions) - $.74

Increase in 90-day second purchase rate, test versus control - over 30%

90-day ROMI - 4,891%  ($36.68 in net profit for every $.75 spent)

Surprised and Delighted Customers - Priceless

Now that the bottom line has been presented, the black box folks simply interested in the “what happens” can skip the next part.  If you want to know why it works and maybe learn something useful you can port elsewhere, read on.

New Customer Kits are a great way to shape Theatre of the Mind. 

What you have with a remote retailing customer is a ”theatre of the mind” scenario, much like you have in radio advertising.  Customers can’t see or touch you, so “Cues” become extremely important; if you don’t populate the theatre of the mind for the customer, the customer will go ahead and populate it themselves.  If you want some control over the image of your company people create in their head, you need to be proactive.  Theatre of the mind, folks.  Very powerful stuff. 

Our New Customer Kit generates absolutely tons of “Thank You” e-mails from new customers who want to tell us all about how great the experience was purchasing from the Lab Store.  Now, I think you’d agree that purchasing from a web site isn’t a particularly thrilling experience in any way, but if you really listen (and understand a bit of Consumer Psychology) these customers are not really talking about the web site, or even our company.  

What they really are saying is they are very happy with themselves for making a first purchase from us; our actions have confirmed they made a good decision.  Remember, this is remote retailing.  There is risk to the customer, especially on that first purchase; they have no idea if their expectations based on the web site copy are going to match the reality of delivery.  They are concerned about what might happen - will they be proven smart or dumb for taking this risk?

When we deliver the products they ordered in a timely way we meet expectations.  When we deliver these products carefully packed in a pristine new box packed with fresh blank newspaper, we probably exceed expectations by a bit.  But when these new customers get to the Welcome letter, the free gift, and the samples, we blow out their expectations. 

The picture these new customers had in their mind of our company based on the web site experience is then permanently altered; we’re doing brain surgery for 74 cents a head.

Now, I have a question for you - is this program Marketing or Customer Experience Management?

The top issue in Training today is:

Accountability

Execs want to know what the “ROI of Training” is.  To find out what the ROI of Training is, one should create:

KPI’s - that’s Key Performance Indicators, in case you didn’t know.

To facilitate the use of KPI’s - to provide something to measure - one should design Training so rather than being Content-based, it is Performance-based.  In other words, the Training should be designed to have a measurable outcome.

Another way to say this is the Training should have a clearly defined Goal which directly addresses the “Gap” between actual performance and desired performance.

Geesh…and I thought Marketing was up the creek…these folks are just getting started.

Yea, I know, kind of weird.  What the heck is a Marketing / Web Analytics guy doing at this event?

The Training Conference and Expo is the largest conference of training professionals in the US.  It’s the first conference I have been to in 10 years that I’m not speaking at.  Probably the first conference I have been to in 20 years where just about everybody knows more about the topic than I do. 

And I have to tell you, that’s incredibly refreshing. 

I’m thinking I have to do this more often!  After all, what exactly is the point of going to conferences on material you already have deep knowledge of?  Unless it is to present, of course…

I’m here on behalf of the Web Analytics Association scouting out vendors to administer the Certification test we are developing for web analysts, and to learn everything I can about best practices in Certification.  One of the challenges is we are looking to certify folks not on “software” related issues like implementation / set-up (the vendors do a fine job here) but on the business side, where the issues are often not as quantifiable as they are in software land.  So we need a vendor that can work with us on a more flexible testing methodology than many are used to.  If you have any suggestions / advice on certification test vendors, let me know.  There are 9 vendors here.

Here are some interesting things I have learned so far:

1.  Virtually none of these Training / HR folks have ever heard of web analytics before.  They have no idea what the heck I am talking about, or that web analytics people even exist from an HR perspective.  The typical response is “we could have used somebody like that when we were setting up our Intranet … what is their typical job title and who do they report to?”

 2.  The primary model used in training course development is called ADDIE.  It stands for:

Analyze
Design
Develop
Implement
Evaluate

which is a formal sequence of tasks where “Evaluate” has an arrow looping back up to the top pointing to Analyze, meaning you repeat the sequence and there is a continuous improvement process.  Hmm, that sounds kind of familiar, where have I seen this before?  Perhaps filed under Best Practices for web site development?

3.  Lots of the communication and behavioral models used in Marketing are used in Training - Training is in many ways a specialized kind of Marketing.  I initially thought I was dead wrong about this but when I put forth the idea, nobody threw me out of the room or called me a Newbie.  So I think there is something worth exploring about this parallel, especially since e-Learning delivered through web interfaces is a big deal to these folks.

More to come as the event unfolds…

Seems to me these days “Marketing” is being deconstructed into a bunch of pieces.  When I was coming up through the ranks, Marketing included Customer Service plus all the stuff now called CRM, Customer Experience, and all the related ideas.  The person in charge of Marketing was in charge of all these things.  It made so much sense to manage a business this way, because to control your fate as a Marketer, you had to control or at least influence all the customer touchpoints.  So why are these responsibilities being split off into little sub-cultures today?

The answer is they’re not really; that’s just the way it looks to me, because every industry I worked in for 25 years was rich with customer data and we used that data to prove why it made so much sense for Marketing to be in charge of all these aspects of the company interface with the customer.  We proved time and time again that by exerting cross-silo influence where the customer was involved, Marketing could generate much improved profitability.  Every Marketing program worked even harder towards generating profits when Marketing got all the silos aligned.

So I guess it just looks to me (and some other data-driven Marketing folks) like these functions are being split out of Marketing.  The reality is that many companies never had any of these data-driven functions before, and when they start getting access to customer data, they created these areas as new entities.  The question: why not create them under Marketing?  This approach sure would have saved a lot of trouble in CRM, for example. 

And I suspect the answer is the Marketing folks took one look at this new data-driven world with the associated need to have a basic understanding of technology issues, and said, “No thanks, I’ll stick to Advertising and PR”.  And as Marketers let go of / failed to capture control of these key operational touchpoints with the customer, they essentially devolved Marketing from a strategic C-Level force into “MarCom”.

And that’s a real shame.  This splintering of Marketing Management by technological issues is a waste of time at best and a long term problem at worst.  Ultimately, after we go through all this CRM and Chief Experience Officer stuff and whatever else you want to call it (seems like a new name every day), people will realize that all of this belongs in Marketing.  And then we’ll just need some brave Marketing folks who think they can handle it to step up to the plate and really make it work.  If you’re a mid-level MarCom person and want to start preparing for this transition, start making some friends in Finance, Technology, and Customer Service.  Find out what it is that keeps them awake at night, and think about how Marketing could help solve their problems.

And to jump-start your brain towards making Marketing decisions based on customer data rather than using nameless, faceless GRP’s, try taking a look at the business side of web analytics.  You’ll be amazed at how much of it transfers directly to Data-based / CRM / Customer Experience Marketing.  Why?  Because the web analytics community has decided best practices require a cross-functional team approach with a focus on Customer Experience and a requirement to examine the Financial implications of actions taken.  Web analytics teams are a functioning microcosm of what Marketing used to be, and what it should be in the future.

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.

There are many marketing productivity situations you will encounter where a change in the metrics, positive or negative, is being caused by something you or your area has no control over. For example, your marketing campaign generated a lot of leads but these leads failed to convert at an acceptable rate. Since this campaign has always generated good leads in the past, you ask yourself, “What happened? What was different this time?”

Upon further research, you find that the leads were of the same quality, but for some reason most of the leads failed to make it to the salespeople they were intended for, and instead went to a brand new salesperson in training. This “process failure” resulted in a low conversion rate, and is the root cause of the campaign failure.  Here is the head’s up on root cause: make sure when analyzing campaigns and other metrics that you understand what “failure” you are really dealing with. Relentlessly search for root cause.

Getting to the Root of It All

I often speak about cross-functional teams in the management of the analytical culture, and the concept of root cause is the driving reason for this, as the road to root cause is often cross-functional in nature. Having a cross-functional mentality in place ensures that these complex root cause issues are addressed without finger-pointing. In a good cross-functional team, there is no “blame”, only learning and continuous improvement. If you don’t chase down the root cause of your issues, the problem likely will continue, creating pain for all members of the team. 

We can look to the practice of Six Sigma for some help in performing Root Cause Analysis. A popular technique is known as “5 Why’s”. The “surface” problem or “effect” as it is called in Six Sigma is written down, specifically, at the top of the page. Then the team asks, “Why did this happen?” This answer, or “cause” in the language of Six Sigma, is written down underneath the effect. “But what caused this to happen?” is asked, answered and written down under the previous cause, and the process repeats until the team agrees that the “real”, or “root cause” of the problem has been arrived at. 

If you solve this last problem, you will fix the root cause, which typically means you will solve all the other “causes” above it.

For some reason, the root cause is often reached around the 5th “Why”, hence the name. You may reach your root cause sooner or later depending on how well the problem is understood and defined in the first place.

Let’s take the example of the lead generation campaign above and run it through the 5 Why’s process:

Effect: The campaign failed to generate leads that converted at an acceptable rate.

Why?

Cause: Because the leads were distributed to a sales person who was in training

Why?

Cause: Because the sales manager who usually distributes the leads was out of town and the only person available to distribute leads did not know the leads are not supposed to go to sales people in training

Why?

Cause: Because there are no rules in place to guide somebody on how to distribute leads when the sales manager is not available

Why?

Root Cause: Because the sales manager has not provided specific instructions on how to distribute leads

Solution to problem of under-performing campaign: 

Have sales manager create lead distribution rules and appoint a person to control distribution of leads in her absence. Probably a good idea to appoint someone to control distribution of leads if both the sales manager and the 1st level appointee are unavailable as well, so any “cascade” effect is stopped and campaign budget not wasted.

See how that works? The root cause doesn’t have much to do with web analytics or marketing, but the impact is felt there and as such, the cross-functional root cause for failure should be uncovered and repaired.

Now, as an analyst, you may want to “tweak” the “5 Why’s” process a bit. While useful in getting a discovery process going, particularly in cross-functional team settings, there is a real problem for the analyst. Do you see it?  

Here it is: where is the analytical rigor in this process?  For each cause the team agrees to, I would ask for proof or evidence of the causal relationship, or else you might end up going down a dead end road.  Examine this proof and determine if it completely explains the relationship between the effect and the cause.

If you want to do anything else with your life for a year and a half, I would not suggest you take on the creation of a complete set of continuing education courses on Web Analytics.  But then again, you don’t have to, because I did.  The courses are a joint effort between the Web Analytics Association and the University of British Columbia.

And you wondered what took me so long to start a blog…or why I’m starting it on Christmas Day, for that matter…

Introduction to Web Analytics, Web Analytics for Site Optimization, Measuring Marketing Campaigns Online, and Creating and Managing the Analytical Business Culture are all available for your analytical growth path, delivered 100% online.  Students are raving about the immediate applicability and usefulness of the content.

Many thanks to the heroes who contributed.