Greg forwarded an interesting site to me today:
An Analysis of Netflix’s DVD Allocation System
Netflix’s approach dynamically adjusts the quality of their service for different classes of customers. As a new Netflix customer, it’s important that I have a good experience, so they’ll give me better access to new releases. As a long-time but high-margin customer, I’ll get a similar treatment. Since they have a subscription model, infrequent users are high-margin users. But if my habits are eating too far into their profits, the availability of items in my movie queue will fall off dramatically. They’re actively adjusting my behavior (with respect to their service) so they can make more cash. Once I’ve entered Netflix limbo, I may end up going to Blockbuster to get that new release I want, which is fine with Netflix— I’m paying them monthly, not per rental. This model, properly tuned, will only eat into customer satisfaction for the kinds of customers they don’t want anyway.
Another example of this can be found in credit card customer service centers. Some credit card companies are reportedly sticking their worst customers (the ones with excellent credit, who always pay their bills on time) on hold for longer, and immediately answering calls from their best customers (the ones who pay the minimum each month, etc).
I call this the “fire your customers” model of achieving higher margins and selective customer satisfaction with the limited resources of any profit-driven company.
Lets look at another approach— the approach of Easy Everything, the company behind Easy Internet Café, Easy Cinema, Easy Jet, and others. They are all about dynamic pricing, so rather than firing or otherwise inconveniencing the customers they don’t like, they simply charge more. Easy Internet Cafés make you pay by the minute for access, and their per-minute price is dynamically tied to the utilization of the cafe. You pay a lot more during peak hours. Easy Cinema prices their movie tickets dynamically, depending on a combination of how far in advance you book (want to see Gigli for 90 pents? Book 2 weeks ahead) and how popular the showing is (based on past utilization or on current bookings made so far).
I call this the price tweaking approach, and it seems very much in vogue right now. Of course, airlines have done it for years. It’s typically combined with lots of value-added things that cost extra. At the Internet Cafe I can buy drinks, print things out for $x per page, etc.
I don’t mind paying more at peak times and for extra services; it makes sense to me that I should, and while I do feel I’m getting a good deal if I play the game right, I’ll always wonder what the person sitting next to me paid. Also, as opposed to the “fire you customers” model, my experience will not be worse at times when I pay less (in fact it might be better— I’d rather sit in a quiet, mostly empty Internet cafe anyway). But the dynamic pricing model is annoyingly opaque when compared to Netflix or the simple “Matinee vs. prime-time” movie pricing that most theaters use. But by requiring you to put the movie tickets onto your credit card, they make the dynamic pricing pill easier to swallow.
Anyway, I think both of these models are really just getting off the ground. They rely heavily on computer-based analysis, trends, etc.
Other things to think about:
- As an outsider, what can you glean simply from the dynamic pricing? If you know what goes into the pricing, and how it’s weighted, you might be able to extrapolate backwards and get some really nice information about usage patterns, etc.
- What other traditional businesses set prices dynamically?
- Cell phone companies, roughly based on network utilization
- “Filenes Basement” discount clothing store, based on how long it’s been sitting around.
- Music? Listen to it the first time for cheap. Each time thereafter, the song gets more expensive, until it eventually is free. Nice concept, wouldn’t work in the real world.
- You tell me!

Comments
Dec 5 02003 4.54p
phredx #
So apparently Amazon got into quite a bit of trouble for one aspect of their now famous multivariable testing wherein they began offering different customers different prices for the same goods.
The reason this becomes problematic is because it could become a discriminatory process, intentional or no. For instance, if Amazon were somehow able to divine one’s race, they could begin upcharing minorities. That’s a pretty extreme example, but imagine if it were applied to partisanship. E.g., Fox News could charge registered Democrats more via the cable company.
Now, in the freedom of the marketplace, in theory, such biases would trend toward whatever were most effective.
Regardless, I’ll be curious to see how these “dynamic” systems are forced to walk any particular regulatory line as they evolve.