I enjoy the methodology so much (in my opinion), that I devoted a whole chapter to the application of the life table in catalog marketing in my Database Marketing Book.
These days, e-mail marketing is tailor-mailed for adaptations of the life table.
In multichannel retailing and cataloging, we're told not to over-mail our customers, as we might damage our reputation with ISPs or damage our reputation with our customers. This is probably good advice. Still, the analytical side of me wants to have the customer tell me when too much is too much. Here's where a modified version of a life table, called "conditional response", can help.
Basically, we ask the question "what is the probability of a customer clicking-through an e-mail campaign to visit your website, given the fact that the customer failed to click-through the past 'x' e-mail campaigns?"
For e-mail marketers in the multichannel world, this is ultimately the core issue. Successful e-mail marketing should cause a customer to want to act (on a website, in-store, over the phone).
So we want to look at the number of times a customer fails to act when receiving e-mail marketing. If a customer failed to act after twenty consecutive e-mail campaigns, what is the likelihood of the customer acting in a positive way on the twenty-first e-mail campaign?
Take a peek at the sample table below:
|E-Mail Campaign Performance By Conditional Response|
|Campaigns||(Open Rate *||Conversion||Order||$ per||Opt-Out|
|0 to 4||14.39%||2.43%||$100.39||$0.35||0.53%|
|5 to 9||10.07%||2.36%||$101.39||$0.24||0.61%|
|10 to 14||7.05%||2.29%||$102.41||$0.17||0.70%|
|15 to 19||4.94%||2.22%||$103.43||$0.11||0.81%|
|20 to 24||3.46%||2.15%||$104.47||$0.08||0.93%|
|25 to 29||2.42%||2.09%||$105.51||$0.05||1.07%|
|30 to 34||1.69%||2.02%||$106.57||$0.04||1.23%|
|35 to 39||1.19%||1.96%||$107.63||$0.03||1.41%|
|40 to 44||0.83%||1.90%||$108.71||$0.02||1.62%|
|45 to 49||0.58%||1.85%||$109.80||$0.01||1.86%|
In this table, we observe key e-mail metrics by consecutive e-mail campaigns that the customer failed to act upon.
Notice that after saying "no" to fifteen to twenty-four consecutive e-mail campaigns, the customer becomes much less responsive (in this example). This is the stage where the e-mail marketer considers changing strategic direction, because the customer is no longer responsive --- and the table suggests that the customer will become even less responsive in the future.
Catalogers can do the same thing --- measuring how responsive online customers are after saying "no" to the past fourteen catalogs.
So give the tool a try, it's a great way to identify the point where customers "just say no" to you!!
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