The New Way to Segment For a 6x Greater Return

I have been thinking about this for some time (BTW, this is a short post – hope to ignite some discussion with this), would love to get your thoughts.

Traditionally (as in most everybody I know in this world) we use financial metrics for customer segmentation, right? Either lifetime-spend, latest-spend, last-year-spend, or profitability, or what-not.  We may use other aspects of segmentation for marketing (like demographics, products purchased, support requested, etc.) depending on what someone in someplace decided it would help us find the “right” people to buy our product (usually that someone was a marketer, or a focus group, or an MR firm we hired – or something altogether).

This has — well, worked for us until now since we have been focused on the shotgun approach to marketing and sales for the most (yes, I know that means anybody but you who have done a masterful job of hand-selecting your clients, unlike your competition).  That is, we loaded the shotgun with pellets, shot in a general direction (segment) and some hit and some missed, if we did a decent job of segmenting we shot into a bush with tons of birds and we hit more than we miss.

This is not the bestest model in the world, but it works.  Sells product, mostly targeted at the right people.

As I was doing research for a deck I did on long tail CRM, I found a case study that was too good to pass up.  I have been using it for the past few weeks in presentations and talks, but wanted to get your thoughts.  This is from a company that chose to remain nameless, but can tell you that they are in telecommunications.  I can assure you, their work applies to either B2B or B2C or whatever letters and numbers you want to put together. OK, stage is set.

They used email marketing.  As we all know, email is “virtually free” to send; but that is irrelevant.  See the table below, first column is past, second column is the new model they use for segmentation (more on that after the fold).

mass market segments long tail segments
segment size 20,000 200
emails sent 18,762 200
emails opened 15,449 162
emails clicked 817 98
leads 42 52
deals closed 2 12

Now, anyway you want to look at that — it is good.

Either because they sent fewer emails, got more of them opened, more clicks,, generated a similar number of leads as percentage of people reached — and 6x more closes.  These are good numbers, no matter how you look at them.  As I said, they are based on a real case study from a company I talked to at length and you can see that they knew what they were doing, the number of emails opened was outstanding before the long tail segments were created.

Of course, now you want to know how they did that, what is the long tail they aimed for.  That is the purpose of this post anyway…

Use Case Segmentation.

Instead of focusing on profitability, past purchases, ownership, time, dollars, or similar this company used analytics to find a very specific use case (sorry, cannot reveal details here) among their customers and found a service that applied to those people.  By using the data available to them, they were able to fine-tooth-comb their customer base and found these few people who were more receptive to the message (which was also carefully crafted to reflect the use case) and make more money, for a lower cost (we won’t debate that now, but let’s assume a lot of sunk costs and just a per-email cost was used to calculate it).

What do you think?  Would love to hear your comments…