Customer Analysis: Auto Dealership
Drilling Down Newsletter #88 4/2008
Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
Customer Valuation, Retention,
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Hi Folks, Jim Novo here.
The auto dealership business is a complex one from a customer
analysis perspective. You have 3 or 4 separate businesses going
on at the same time and each of them has a different natural cycle to
them. How do you start to unravel what is going on from a
customer perspective and take action to "drive" increased
profits? That's the subject of the Driller Question this month.
Over on the blog it was Desirability month, kicked off by a
Forrester conference on what "Engagement" really means to
Marketing. If you're interested in this topic, we cover both the
Strategic and Tactical levels of the model.
For articles, we have Lester Wunderman weighing in on what
Engagement means to Advertising, and Roy Young talking about how Silo
Busting is good for Marketing.
A lot on the menu, let's get to that Drillin'...
Best Customer Marketing Articles
Ad Engagement & Silo Busting
Two article links on this page which stand by themselves and
also compliment the Desirability Series on the blog (see below).
First, Lester Wunderman provides his view of what the concept of
Engagement means to advertising. Then, Roy Young talks about how
to bust down Silos, a critical component of success to a
To access the full article review and links to the articles
Sample Marketing Productivity Blog Posts
Forrester’s Marketing Forum this year covered Engagement, but not the kind of Engagement so often discussed in web analytics.
Nope, Engagement from a Marketing perspective, you know, surprise and delight leads to
great customer experiences leads to better retention of customers and higher profits.
The first post includes links to the two keynotes. I've spent
a decent amount of time speaking with Brian Haven at Forrester about
measuring and acting on Engagement from a Marketing perspective.
Brian puts forth a Strategic model and Kerry talks about Desirability
- that which creates Engagement.
The next six posts outline a framework for understanding,
measuring, and acting on the Desirability / Engagement model yourself.
To view this Series on Desirability, click
Questions from Fellow Drillers
Customer Analysis: Auto Dealership
Q: First of all thanks for sharing your experiences in your
blog / book.
I bought Drilling Down last week and I found it extremely useful, it’s easy to read and full of good advice
for analyzing customer ROI and building models of performance.
A: Thanks so much for the kind words!
Q: After reading Chapter 16 –on how to score customers with a spreadsheet- I was asking myself how much data is enough to do a good RF score for a car maintenance business.
A: Hmmm... is a "car maintenance business" in Ecuador the same thing as a "garage" in the US?
What exactly is the business? About how many customers do you have?
Can you buy a car at your business? Or are cars just repaired there?
Is it a single location or chain operation with multiple units? Do people come in for an oil change or is it just for mechanical trouble? Or are you just washing / cleaning cars?
I'm just trying to get a better picture of what we're talking about if you don't mind...
Q: I'll give you some business facts:
· The company has two channels: car sales - new & used cars, and services - repair, maintenance and painting.
Each channel is managed almost as an independent business
· It's a chain operation with 4 units across the country, each unit has both channels.
· On the services channel, customers come to us seeking oil changes, brakes and engine maintenance.
We also do some serious mechanical repairs - crashed cars, broken engines, etc. and painting works.
We do not wash cars as a service.
· Yearly we pick around 1200 service orders on 850 customers, coming from
a base of about 2000 different customers since we started the business
A: Impressive customer knowledge! Somebody has
been reading a book on this...
OK, I think we have enough to start! First, if you have not already,
piece, it deals with the oil change business in particular and the dealership business model in general.
Now to the questions:
Q: Do you think a year of data can give us some
results with a certain degree of confidence? If the answer is
no, then how much data do you think we need in order to achieve some
A: You probably have enough data, but this is a complex, hybrid model because it actually involves at least 3 or
4 businesses, so you'll need some "hybrid" thinking. You clearly have some repeating behavior and what you
really need to understand first is what that behavior consists of.
Let the data tell you the story.
The first thing I would do is try to understand these repeating segments.
Prediction really works best when the segments are clear and differentiated (see oil change piece above).
So, for example, you have probably at least these important businesses:
1. Vehicle purchase
2. Mechanical service
3. Oil change
These categories are different because the demand cycles are different:
1. Buying vehicle is almost like a 1x purchase, though you hope they come back, of course.
2. Mechanical service is an "on demand" thing, very hard to predict.
3. Oil change is (supposed to be) a routine thing, should be easy to predict at least the *need* for an oil change.
Whether it happens or not is another story. Also, If you take everybody who has had any oil change,
that is also probably the largest group of customers.
So, if you are looking for segments, you probably find they look something like this:
1. Bought a vehicle, also gets mechanical service, and oil change
2. No vehicle purchase, but gets mechanical service and oil change
3. No vehicle purchase, no mechanical service, but gets an oil change
Given these segments, a few of the questions you might ask would be:
1. Of people who get an oil change, why do they stop with oil change / not repeat?
2. Of people who get an oil change, why don't they get mechanical?
3. Of people who get an oil change and mechanical, why don't they buy a vehicle?
Is their some common Action prior to them stopping that may have
caused them to stop? A certain kind of repair? Buying a
certain kind of car? Waiting a very long time past when they
were due for an oil change?
I'm not saying this is the data you will find, though it seems like a good guess.
What I am saying is the place to start all this is with a
behavioral segmentation, and then asking the question, Why do they behave like this?
Is it pricing, business practices, customer service issues, scheduling, etc.?
Try to answer the questions raised by the behavior first.
Then, you have some basis to think about scoring / marketing.
Otherwise, you're just wandering around in the wilderness. You have to start with a base, understand what the data tells you about customer behavior first.
My bold-faced guess is that the oil change business has the most total volume, and is most likely to repeat.
So what you want to do is upsell into mechanical and then when you have an oil and mechanical customer, upsell into
So, for a marketing example, when you do an oil change, you check a few common maintenance things and say, "Hey, did you know you will need brake pads pretty soon? Would you like us to do that when you come in for the next oil change?
If you get the brake pads when you come in for the oil, we'll give you a 20% discount on the labor".
That kind of thing. If you were going to actively market this, you would send a reminder for the oil change when it's coming due, and in the reminder say
"Remember, we offered you 20% off the labor if you get those brake pads changed".
Likewise, when they're now into both oil and mechanical (they are buying 2 products from you), you talk about buying a vehicle, usually based on a major mechanical problem of some kind.
"Since you get a lot of service here, we'll give you a deal on a vehicle".
It's a long, somewhat unpredictable cycle - except for the oil.
So you use the oil as a "base" and try to grow people into repeats up from there.
The only thing you really try to predict is "time for an oil change" and the rest is marketing, because the mechanical and vehicle purchase are fairly unpredictable.
If you are running something like the LifeCycle Grids to map customers, you would probably want to have a grid for each type of customer, segments 1, 2, 3 above.
The goal would be to migrate customers up into the higher value, multi-product line
Q: Another question I had after reading the Life Cycles chapter was: which kind of measuring does a better job?
Scoring through a fixed interval of data - picking the last 15 months of
sales - or scoring through some kind of data continuum - 15 months of data this month, 16 months the coming month and so
on? Personally, I'd choose a fixed interval with enough data, but some people tell me this would tag some returning customers as new customers, which would be imprecise.
A: I'd have to agree with "some people".
In this kind of business, which is a long-cycle, relationship business, I would use "Life to Date" sales to build the LifeCycle Grids, the "15 months of data this month, 16 months the coming month" idea.
It's the same as the example in the book, where the last column is "18+ months."
I wouldn't cut it off, unless perhaps at 5 years or so, when it is clear the customer is not coming back to by a vehicle.
Or maybe 10 years.
You want the time frame to match up with the cycle of the longest product plus another 20% or so in terms of time, so you catch any behavior lagging the averages.
Now, some of the decisions surrounding these ideas you will have to make based on your internal knowledge of the business.
If there is really not much profit in vehicle sales, or the volume is so low that it's only (say) 10% of profits, then it might not be worth your time focusing on.
You focus on profiling the oil and the mechanical, and the vehicle sales come when they come because you deliver a great customer experience and they trust you.
Q: Thanks for your help, your words helped me to get a fresh perspective of the analysis I need to do.
By the way, your book is the most practical thing in data analysis I've seen in years.
Keep giving us your valuable insights!
A: Thanks, you are most welcome, and I intend
to. Hope this has helped you decide on how to approach the marketing challenge!
If you are a consultant, agency, or software developer with clients
needing action-oriented customer intelligence or High ROI Customer
Marketing program designs, click
That's it for this month's edition of the Drilling Down newsletter.
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'Til next time, keep Drilling Down!
- Jim Novo
Copyright 2008, The Drilling Down Project by Jim Novo. All
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