Customer Modeling Services
Marketers who use customer data often talk about "customer
modeling" instead of customer profiling. Modeling is kind of like
profiling, but it is action oriented. Models are not about a static state,
like "Customer is 50 years old." Models are about action over
time, like "If this customer does not make a purchase in the next 30
days, they are unlikely to come back and make any further purchases with
This kind of model sounds so mystical, and it is. To see a mathematical
model predict customer behavior is astonishing, to say the least. The
model says, "Do this to these people and they will likely do
this." The marketer goes out and does what the model says, and a good bunch of the customers do exactly what the model said they
What is a model? Simply, it looks at customers who are
engaging in a certain behavior and tries to find a commonality in them.
The marketer might say to the modeler, "Here’s a list of our very
best customers, and here’s a list of our former best customers. Is there
any behavioral signal a best customer gives before they stop shopping?
What does the data say?"
Here are some examples of customer modeling in action to give you a
better idea of what is possible:
Example: What kind of web site reporting are your clients using, if
any? Are they just looking at page views, or are they looking at
metrics that matter, like what % of people who enter the site through
a certain page make a purchase, or what % of them look at this entry
page and just leave? Understanding and tracking metrics like these
lead to site redesigns that make a difference.
Example: Looking at response rate and sales versus costs of
advertising is the first step to optimizing campaigns. Buy what
if you could predict the future sales of customers by keyword
by search engine? Some campaigns that looked like losers
actually turn into very big winners when looked at this way. Do
your clients really know how to optimize an Overture or Google AdWords
campaign for maximum benefit?
Example: Of course, it's not enough to get customers to buy
the first time. Your clients need customers who will buy again
and again. My models will tell you where to find these
customers, and how to create more of them out of the customers you
have. And in the area of customer retention, you can use these
models to predict which customers are most likely to stop buying, a
critical element of best customer management.
Example: I can rank the customers of your clients by
likelihood to respond to an e-mail campaign. Instead of sending
them all 1 e-mail, if you send 2 e-mails to the top 50% most likely to
respond, you spend the same money on e-mails, but drive higher sales.
This increases ROI, and makes paying for more e-mail campaigns
attractive to clients.
Example: Many retailers over-discount. They always
wonder how many of the people who used the discount would have bought
anyway without it. I can tell you who these customers will be,
and what's more, show you how to set up a discount customization
strategy that only delivers enough discount to get each customer to
buy, and no more. Customers who need no discount get none, and
still buy. This increases response rate while lowering overall
promotional discounting costs.