There’s a reason you’ve been on hold with customer service for an hour…

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And it may hurt your feelings.

There’s a reason you’ve been on hold with customer service for an hour…

The Wall Street Journal reports that companies use a secret scoring system called CLV to determine the caliber of treatment a customer will get based on how “profitable” they could potentially be for the company.

In other words, you’ve been on hold with Macy’s for 3 days because you don’t buy enough business-casual leather jackets.

Or, as Harvard marketing professor Sunil Gupta put it, “There’s no free lunch. The more profitable you are, the better service you will get.” And to that we say… don’t get stuck sitting next to that guy on a train.

You down with CLV? 

No, actually, we’re not.

CLV, or “customer lifetime value,” is a common metric used in the customer service biz to determine how long you’re kept on hold over the phone, or whether you’re worthy of getting a seat upgrade on a flight.

Everyone with a bank account, cellphone or online shopping addiction has at least one CLV score (most of us have many at various companies).

The scores take into account how much money a customer spends, the number of returns they make, even their ZIP code — which can determine targeted ads, perks you receive, and even prices you get on items.

Worth its weight in data

The data that goes into a score could be literally anything — transaction records, website interactions, customer-service conversations (this call may be recorded), social-media profiles and others, to predict a consumer’s behavior. 

The data puts people in tiers based on factors like marital status (some companies assume singles are better customers) and age, because, you know… shorter lifespans mean smaller returns on a “lifetime loyalty member.”

Everyone’s doin it

This is basically just a sci-fi version of what store owners have been doing since the beginning of time — judging a person’s worth based on how they look or behave. 

Only now, there are hundreds of analytics firms using hard data to judge the book by the cover they built.

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