Don’t abuse your best customers Part I: Amazon Case Study

I have a love-hate relationship with Amazon.  Love their product selection, user reviews and especially the ease and price savings of Amazon Prime.  Hate the fact that for some reason Amazon refuses to use the data they have about their own customers in the most simplistic “pre-web 1.0” ways.  We wrote about this in the white post “The 4 R’s,” but here’s an even better example.

I love the Amazon Kindle (e-newspaper, blog, magazine and book reader) so much that I recently sent my own glowing review of the product to everyone I know, something I had never done before, despite my genetic need to tell people about great products and services I encounter.  My wonderful wife bought me a Kindle for our August wedding anniversary and within days I had uploaded 5 newspapers, 10 blogs and 4 books. I am clearly one of Amazon’s better customers and even became an “Amazon Associate,” so when friends buy a Kindle after reading my review, Year Up, my favorite nonprofit, gets a 10% rebate.

Despite all of this data that Amazon has telling them I am a Kindle owner/maven, look what Amazon greets me with when I recently logged to their site:

Amazon is using perhaps their most valuable online real estate – their home page – to tell me what a Kindle is.

But wait, there’s more:

What happens when you don’t use the data you collected to recognize and reward (or at least don’t abuse) your best customers.

A few weeks after I received my beloved Kindle, I fell asleep reading it.  When I turned it on the next morning, the screen had several thin lines running across the top.  At certain points, the cumulative effect of the lines was to block out almost ½ inch of text.  Up until this point, I had good experiences with Kindle customer service: their number is easy to find; the service agents speak English well; and they had been able to answer several questions, including helping me find an AC adopter in NYC when I forgot mine on a recent trip.

So, I called Kindle service with high expectations.  I volunteered that I had fallen asleep with the device and most likely rolled over on it and damaged the screen.  I asked if there was a program to replace, repair or offer discounts to “clumsy customers.”  To my surprise, the agent responded:

“We have many customers who have slept on, stepped on and even dropped their Kindles in the bath tub.   Amazon used to have a program to replace damaged Kindle’s, but we are not running that right now.”

Somewhat stunned, I asked for clarification, asking something like;

“Are you saying that if I had broken my Kindle at another time earlier in the year, Amazon would have replaced it or at least offered a discount?

He confirmed this was the case, but went on to say:

“If you would like, I can have your name added to our email list and if we bring back that program, we will contact you.”

Only then did he ask for my email address, which could have and should have alerted him to the fact that I am heavy Kindle user and also spent over $10,000 on Amazon last year for business and family purchases.

So, despite having the data to identify me as a very good Amazon customer, the customer service agent was not instructed or trained to use that information to at least recognize and thank me for being a loyal customer.

Not only did Amazon fail to recognize me as a good customer, they added insult to injury by telling me that I had to spend another $350 to replace the Kindle, something other – and presumably less profitable customers – did not have to do, due entirely to the unfortunate timing of my clumsiness.

In the white post “Amazon, Facebook, Eons and the 4 R’s of Relationship Marketing,” we introduced the concept of the 4 R’s using a hand written version of this virtuous cycle:

We believe that companies who collect information about customer purchases through their direct sales businesses, reward programs, or “convenience” programs like Amazon Prime or Hertz Number 1 (see Part II) need to recognize that they are rewarding both the purchase of the good or service and the sharing of information by the customer to the business.

Customers are sharing information about what they buy and when they buy it.  We also believe that customers know businesses are collecting that information and will increasingly expect those companies to recognize and reward them for their loyalty.  At a minimum, they will expect to be treated as well as other, less profitable customers or will become highly susceptible to being poached by a competitor.

Questions:

• What data do you have on your best customers that you are taking advantage of today?
• Are there similar examples of “best customer abuse” happening in your company?