January 03, 2009

Customer Resume

Take a look at this customer:
  • One order, on October 29.
  • Spent $200 on one item.
We like to classify customers in some sort of RFM segment. In other words, this customer is a 0-3 month, 1x, $150+ AOV customer. Based on this classification, we develop targeting strategies and we analyze business performance against this segment.

The customer resume demands that we compile a robust profile about the customer.
  • Customer received a catalog on October 1.
  • Customer did not return any of the merchandise ordered on October 29.
  • Customer paid the standard fee for shipping.
  • Customer did not use a discount code when placing the order.
  • Customer is an e-mail subscriber.
  • Customer only purchased one item.
  • Customer ordered on a Wednesday, one day after receiving an e-mail campaign.
  • Customer had a referring URL from a social media site.
  • Customer ordered 28 days after receiving a catalog.
  • Customer did not use a catalog key-code when ordering.
  • Customer lives in a Zip Code Forensics zip code classified as "Online Bliss".
  • Customer ordered from merchandise division "X", and did not order from merchandise division "Y" or "Z".
  • Customer has not visited the website since.
  • This was the first order placed by this customer.
  • Customer lives more than 100 miles from a store.
The Web Analytics professional seldom deals with the customer, she is always evaluating anonymous outcomes, always looking into the past. The Business Intelligence professional is always summarizing customer data down to a small number of manageable dimensions. Mind you, this isn't the fault of the Web Analytics or BI guru --- software makes it difficult to create a "customer resume".

The Customer Resume demands that we evaluate the customer on the basis of everything we know about the customer. Here, we have a rich profile of who this person is, and if we know more about who this customer is, we can imagine what our relationship with the customer could be.

For instance, the fact that this customer ordered 28 days after receiving a catalog tells us that the catalog, at best, mildly influenced the order. The fact that this customer ordered on a Wednesday, one day after receiving an e-mail marketing campaign, tells us that the e-mail may have had a strong influence. This customer paid full price, a positive harbinger for long-term value. This customer only purchased one item, often a negative indicator of long-term value. This customer did not return to the website, which might be a negative harbinger.

The goal of the customer resume is to know as much about a customer as possible, to be able to learn about subtleties in customer behavior that may indicate changes in future behavior. We want to derive information about the customer, we don't want to reduce behavior to a small number of esoteric dimensions --- we can always do that later.

If you want to liven up a boring "Information Technology Steering Committee" meeting, bring the resume for just one customer to the meeting, hand it out to every attendee, and then ask each attendee to craft a communication strategy for this one customer.


  1. Interesting take on segmentation.

    Even if you could create a strategy for this individual, there is no way it would be scalable...how could this approach be pragmatic? Would this just be a exercise to spur discussion?

  2. This works extremely well from a statistical modeling standpoint. If you are building models, these variables work well. The models determine who receives e-mail campaigns or catalog marketing campaigns.

    You can build these fields into an OLAP-style application that allows you to analyze 2-3 customer dimensions at a time, if you want to simply understand customer behavior better.

  3. Another point --- when I worked at Lands' End, some twenty years ago, every Monday morning I looked at the "Customer Resume" of about a hundred customers. I would evaluate key customer attributes, comparing them to the mathematical score I created to determine if the customer received catalogs or not.

    You learn an awful lot about customers when you physically look at the resume of 100 or 200 different customers every Monday morning.

  4. Anonymous4:48 AM

    When you explain it in your comment as 100-200 screened, vs the one you bring to steering committee, it makes a bit more sense to me.
    Have you encountered any difficulty when customer resume runs counter to the market research?

  5. You always run into difficulty when the data runs contrary to customer research!


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