The Long Tail

One of the ideas from the dot-com boom was that of the "long tail". If one ranks their customers by sales, then the best customers -- the ones that order the most -- are clumped to the left, and the customers that order the least are in a long thin grouping to the right. That long, thin grouping is "the long tail".

This idea came about in the mid-2000s. It was considered revolutionary by some (mostly those who pushed the idea) and it was, in retrospect, a different way of doing business. It relied on a reduction of cost to serve customers.

Prior to "the long tail", businesses marked certain customers as unprofitable, and built their pricing to discourage those customers. (Banks, for instance, want a minimum amount when opening a new account. There is a cost to manage the account, and the profits from a low-balance account fall below that cost.)

The "long tail" advocates recognized that computers and the internet allowed for low-cost interactions with customers, and saw profit in small purchases. The efficiencies of self-service, or fully automated service, allowed for customers with smaller or fewer purchases. New businesses were formed, and became successful.

Yet there were some aspects of long-tail businesses that weren't predicted. Those aspects are the absence of customer service and the treatment of customers as disposable entities.

Consider Google. The tech giant has several businesses in the long tail of computer services. They include e-mail, data storage, processing, office tools such as word processors and spreadsheets. Companies can sign up for paid plans (the "fat" part of the tail) and individuals can sign up for free or nominally free plans (the "long" part of the tail).

But notice that the plans for individuals (free e-mail and spreadsheets, for example) have nothing in the way of customer support. There is no help line to call. There is no support by e-mail. (There are web pages with documentation, and there is a web forum staffed by volunteers, which has some answers to some questions.)

Customer support is expensive, and the individual plans (either free or low-cost) generate such few profits for Google (on an individual basis) that a single 10-minute support call would wipe out years of profits.

Long-tail businesses don't offer real-person support because they cannot afford to.

But the headaches for the customers in long-tail products and services don't end there.

Google has, on more than one occasion, cancelled a person's account. The common explanation is that the person did something that violated the terms of service. What, exactly the person did is not specified, and there is no action listed to correct the problem.

I am picking on Google here, but this happens to users of other services, too.

What makes it bad for Google's customers (and Google, indirectly) is Google's wide variety of services. A violation of terms and conditions in one service can cause Google to suspend a person's account, which removes access to all of Google's services, including e-mail, spreadsheets, data storage, and more. Google provides no information to the customer, and the customer is effectively cut off from all services.

Google has discarded the customer. It seems a harsh resolution, but it is a low-cost one. Google does not spend the time discussing options with the customer; the cost of cutting off service is, essentially zero. Google loses the minimal profits from that one customer, but those profits don't cover the cost of investigations and discussions. It is cheaper to dispose of the customer than to retain them. There are lots more customers.

Long-tail businesses don't value customer retention.

These are two results of long-tail business models. I won't say that they are wrong. The economic conditions seem to require their existence.

And the market does offer alternatives. Microsoft, for example, offers support (limited, but more than Google) for its Microsoft 365 services. In doing so, they move the customer from the thin part of the tail to a thicker part.

The old adage "You get what you pay for" seems to apply here.

Excuse me, but your batch slip is showing

The larger, older companies have a problem. They computerized their systems a while ago, and now they have slow, customer-unfriendly systems. This is caused by technology: the early automated systems were (are) batch systems, and they exhibit certain patterns. Delays in output is one such pattern.

Here are some examples.

I submitted a stock trade order through the Chase web site on Sunday evening. I understood that the trade would occur during business hours in New York, so the earliest possible time of the trade would be 9:30 on Monday morning.

The confirmation e-mail of my trade arrived at 2:25 on Tuesday morning. I'm pretty sure that the trade was not completed in the wee hours of the morning. I'm guessing that the trade occurred shortly after the market opened on Monday, and probably no later that 10:00. Yet Chase needed more than 16 hours to send the confirmation e-mail.

I'm guessing that the person executing the trade had confirmation quite a bit sooner than 16 hours. Chase apparently thinks that customers can wait.

In another case, Chase sent me a "year end summary available" notice... on February 2. (At 2:28 in the morning. Apparently Chase sends all of its e-mails starting at 2:00 in the morning.) I can understand that Chase would want to wait a few days, to let merchants send transactions and get a complete picture of the year. But waiting a whole month seems a bit extreme. (I'm guessing that Chase waits until the end of the billing cycle in January, then waits a bit more, and then sends the notification.)

The culprit here is the batch processing model. With batch processing, the workload is divided. Front-end systems collect data and back-end systems run jobs at specific intervals. These back-end systems are responsible for updating amounts and sending e-mails. Certain operations occur "on-line", that is, immediately. These operations are considered expensive and are therefore limited to a selected set of data and performed for a selected set of users -- generally not customers. The result is that Chase defines customers as second-class citizens.

I am picking on Chase here, but other large companies that uses batch processing and have the same "second-class citizen" attitude towards their customers.

Large companies have relied on batch processing for decades. And for decades, batch processing has been good enough. But no more. A new kid in town has raised the bar, and customers are not going to be satisfied with being treated as second class.

That new kid is Facebook.

Facebook (and other social networking sites) have built systems that provide immediate feedback for results. When I post my status on Facebook, I receive responses from friends within minutes. (Not days, and not hours. Certainly not months!)

Banks and other companies do not have the excuse of size or transaction volume to use as excuses. Facebook has over 500 million users; I know of no banks with similar customer bases. Facebook processes more messages than all of the transactions processed by banks -- combined!

The new generation of customers has been raised on Facebook and its immediate response model. They will be unhappy with "business the way we've always done it" and "you're a customer and you will wait". The bank that provides immediate feedback will win lots of customers.

This is not a technology problem. This is a management problem. The management at Chase is satisfied with the performance of their systems. (That is, they are satisfied that their systems are offending customers, since a small enough number complain.)

At some point the customers will revolt, but it will happen unevenly: mostly the younger customers will take their business elsewhere. Since younger customer tend to have smaller account balances, the averages will show an increase in assets per customer. This will be perceived by Chase management as a good thing. ("Average assets per customer is up, boss!")

But customer demographics is a funny thing. Companies with few young customers tend to have short lives. Their older customers remain (until they pass into the next dimension), and without a new crop of young customers to replace them, the customer base eventually shrinks. In the end, the company collapses into a fit of bankruptcy and acquisition.

The strategy for survival is to improve customer communication to a level close to Facebook. When the stock trade is complete, let me know, by e-mail, text message, Twitter, Facebook, or other method of my choice. Send me a year-end statement on January 4. Let me configure my account and notifications they way I want them, not the way your archaic batch system allows.

Or not.