Category Archives: Analytical Culture

Lab Store: Managing Customer Experience

Analytical Culture, Lab Store, Marketing thru Operations

When Ron wrote this great post on Marketing’s responsibility for managing customer experience (more on process improvement from me here), I thought I would relate this simple example from the Lab Store.

We sell some exotic pet food that is meant to be a continuity item – the customer buys it every 3 months or so.  This product offering is, of course, designed to extend the Customer LifeCycle.  The food is a “staple” meaning it is generally kept in the cage at all times to supplement the fresh foods fed to the animal.  This food is not as appealing to the anlmal as say, fresh fruit, but it’s an important part of a well rounded diet for the animal.  The feeding instructions on the web site are extensive – portion size relative to fresh food, when to feed, amount to feed, etc.

So we start analyzing the repurchase rate of this staple food that is supposed to be our “back end” and it is dismal relative to expectations.  Why?  Have the customers switched to a different, cheaper source?  Are they not feeding the diet plan we suggest?  Is this even a “marketing problem”?  Well, in the Lab Store, anything related to customer behavior is a marketing problem.

So we grab a sample of the customers who passed the re-order point Tripwire of 3 months without ordering again and ask them, Why aren’t you ordering the staple food?  And the answer is “The critters don’t like it”.  Really?  That’s a surprise; we know the animals generally eat the food.  So we ask about portion size, are they following the diet plan?  And they say, “Not really, when they didn’t eat the staple food, we thought they would be hungry and so we gave them more fresh food.  They never ate any of the staple food”.

And there you have it.  We don’t need to ask any other questions.  The animal is not going to eat the boring staple food when they are being overfed the fresh food.  This is like asking a kid if they would rather have spinach or candy; one is good for them, the other tastes better.  And the customer isn’t going to buy staple food the animal will not eat.

The problem is, this “fresh food only” diet is unhealthy for the animal; they are not going to get critical nutrients they need from the staple food.  But, this exact feeding scenario is covered on the web site; we’re already communicating this issue to the customer.  So it’s not a marketing problem, right?

Wrong.  That is the marketing problem – the information is on the web site.  We started including a package insert with the staple food containing the very same info as on the web site, except now, of course, it was “contextual”; delivered in exactly the right place and at exactly the right time – when the customer opened the staple food package.  And magically, the repeat purchase rate on the staple food increased 32%.

The point is, if we had been off “marketing” and not paying attention to the Potential Value of the customer by setting up the Tripwire, we’d have never found this flaw in the process.  And by fixing it, we increase the return on all the acquisition marketing we do, because the LifeCycle of the customer has been extended.

Marketing Productivity, indeed.  More Lab Store tales to come.

Is Your PPC Incremental?

Analytical Culture, Web Analytics

Something that analytical folks talk a lot about is “the incremental”.  In customer marketing, it’s not enough to get response, what we want to know is how much of the response was above and beyond what we could be expected had the test or promotion not been done.  Typically incrementality is measured using control groups – people just like the people you are sending the campaign to who do not receive the campaign.  Then you compare the profitability of the people who received the campaign versus the profitability of those who didn’t.  The difference is the true, incremental profitability of the campaign.

Kevin over at the MineThatData blog relates that Blue Nile has decided to lower prices as opposed to chasing rising ad costs.  I don’t know enough about their business model to really comment on that action, but I do know one thing – they (and many, many other companies) are wasting Pay-Per-Click spend on non-incremental clicks.

Check out this shot.  Search for Blue Nile in Google, you get a Pay-Per-Click ad for Blue Nile, and Blue Nile has the fiirst natural listing:

Search: Blue Nile

 

 

 

 

 

 

Now someone, somewhere, back in the beginning of PPC probably had a conference speech that told everybody to buy the search for your company’s brand name, maybe for “branding” or “exposure” purposes.  But almost every web site ranks first in the natural rankings for their own brand name.  So I ask you, is there any incremental here?  What are the chances, if the PPC ad was not there, that the visitor searching “Blue Nile” would not click on the first natural listing?

What do you suppose the volume of this search is, and how much money is being wasted by people clicking on the paid ad who would have clicked on the natural link anyway?  I asked the same question back in 2003, and though the structure of the test wasn’t as pure as most hard core test & control folks would like to see, the results were so dramatic that you can’t really argue much with the methodology.  A few percentage points here or there and you still get to the same place.

In this particular test, on a high volume PPC phrase for a site that also had a top 3 natural ranking, 77% of PPC sales were non-incremental – stolen from the natural side – and would have happened anyway without the PPC link.

I will be the first to say that results are going to vary a lot by the type of site, the phrase, the target audience, the search engine, and so on.  But Golly Gee folks, has anybody else ever questioned the wisdom of “railroading” a top natural listing with a paid listing – and especially for your own brand name?  I bet a lot of analytical folks have, they just couldn’t convince the marketing folks to test it.  After all, addressing / fixing this by taking down the PPC ad means:

1.  There will probably be a few lost sales, perhaps from people who for whatever reason, always click on paid ads (newbies?)  However, profits will increase.  Some folks will not believe in this idea, it’s that whole analytical culture problem.  You have to trust the numbers, not fear them.  Unless, of course, you have been specifically told to grow sales and not profits.  Rare, but it does happen.

2.  Then there is the whole “How could you not know this was a bad thing and continue doing it for so long?” problem.   That’s more analytical culture stuff.  Failure is a learning experience in the analytical culture, not a cause for whippings and firings and demotions.  The question is not how much money was lost, the question is how much will be saved going forward.  Right?

3.  Potentially, some PPC budget will be reallocated to other, more profitable marketing activities.  This could be a problem if there is “ego spend” involved in the management of PPC.  I wouldn’t move the money out of PPC, I would just find better ways to use the existing budget.  But the potential exists for losing it for a higher and better purpose that is proven out by the numbers.  Just optimizing the system, no hard feelings, right?

PPC Marketers, if you’d like to free up budget for something else, ask your web analytics folks if they can track this test for you.  Locate a high volume search phrase that you buy PPC for ads for where your web site naturally ranks as #1 or #2 for the same phrase.  Try shutting the PPC for that phrase off.  How much click volume do you lose versus the cost of the clicks when PPC is tuned on, and what does that translate into in terms of increased profit?

And I am really not picking on Blue Nile here – search any brand name, online or off.  Go ahead.  What do you see?

Would you fail to click on the organic link if the paid link was not there?  Really?  If you think you’d miss the organic link if the PPC link wasn’t there, send me a pic of the example.

LifeCycle Marketing

Analytical Culture, DataBase Marketing

Lisa Bradner from Forrester Research called to discuss LifeCycle Marketing, which is kind of a coincidence given the Sense and Respond post below. Apparently folks are having some difficulty with implementing the concept…

The Customer LifeCycle is really just a process that you can map, just like any other business process. At each stage of the LifeCycle you have an expected result based on the behavior of other customers as a whole or in the customer segment. You measure the behavior of individual customers against the process benchmarks, and when the customer is behaving as expected, you do nothing, taking no action. If the customer behavior is “out of bounds” with the expected result, you take action. This method generally allocates marketing spend to the highest and best use. If this sounds a bit like Six Sigma for Marketing, well, you’re right, it does. You have a problem with that?

Another way to look at it is this: there is a “tolerance” band for behavior and the ability of marketing to affect behavior depends on where the customer is within that band. If the customer moves too far outside the band, it becomes impossible for marketing to really do anything at all to affect behavior. So as long as the customer remains in that band, it conserves marketing resources to take no action. As the customer begins moving towards the band, significant marketing action is triggered and needs to be taken before the customer moves too far outside the band. So you have a reallocation of marketing resources towards highest and best use, always pushing marketing spend to where it will be most effective. It’s a marketing resource allocation model of sorts.

Let’s take a simple retail example of how this works. Let’s say you look at new customer purchase behavior, and you see for new customers who make a second purchase, they usually make the 2nd within 45 days of the first purchase. So, you can look at new customers and divide them into 2 groups; those that are doing the “expected” and those that are not, based on the 45 day rule. Applying the LifeCycle concept, any new customer that makes a second purchase within 45 days of the first, marketing does nothing (inside the band). This conserves marketing resources and margin dollars that would have been lost to discounting. That money is then reallocated and spent on the customers crossing over the 45 day tripwire without a second purchase (outside the band), and since you have more to spend (courtesy of the reallocation), the programs can be more effective.

Further, let’s say that you analyze this 45-day idea looking at the marketing campaign that generated the new customer. You have only 2 campaigns and the days between 1st and second purchase is 60 days for one and 30 days for the other (average 45 days). So, the first thing you ask yourself is why is the behavior different – media, copy, offer? The second thing you ask is should we reallocate spend from the campaign with a 60 day window to the campaign with the 30 day window, which would generally increase cash flow? And the last thing you do is adjust the original 45 day trip wire to 2 distinct tripwires, one for the 30 day campaign and one for the 60 day campaign (if you keep the 60 day campaign). You are optimizing the marketing system based on the unique LifeCycle profiles of these new customers, generally lowering costs and increasing margins as you optimize.

The thing is, this is really fundamentally the same as optimizing a web site. It’s the same idea, only with different variables and more detailed data. I think that’s why many of the web analytics folks seem to “get it” and are now working on systems to automate it. I saw a shopping cart demo last week with this kind of LifeCycle profiling built right into it. You could run the profiles and execute the LifeCycle-targeted e-mails right within the same interface.

Behavior predicts behavior. If you use behavioral metrics like Latency and Recency, you can discover these LifeCycle patterns and use them to your advantage. Every marketing system, B2C or B2B, has LifeCycle processes in it. By understanding these processes you can focus resources and increase the overall profitability of all your marketing efforts.

Why are companies having troubles implementing such a relatively simple concept? I dunno, guess we will have to see what Lisa has to say in her report…but why do companies have trouble implementing just about every data-driven Marketing or Service effort? More often than not, the root cause is lack of a proper analytical culture to support the effort.