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Take Rates – What are the most popular product choices?
I want to apply the discussion of entropy to the features of a configurable product. But first we have to introduce the important concept of a “take rate”. In different industries this is called an “attach rate”, or a “penetration rate”. The idea is very simple: the take rate of an option is the fraction of units sold that include that option.
The take rate of option x is the number of units sold with option x, divided by the total number of units sold. So if 70% of our cars are sold with cloth seats and 30% with leather seats, then cloth has a take rate of 0.7 and leather has a take rate of 0.3.
In the case of a feature with two options, like cloth and leather, this looks just like a coin toss with two options, tails and heads. Recall that coins may not be fair. If I send you a message about a customer’s choice of seat, the entropy of that message is the same as for the outcome of one toss of a suitably biased (.3 to .7) coin. So take rates can be interpreted as probabilities.
Some features have more than two options. For example a backhoe feature called Feet has four different options: none, Flip, Flip Guard, and Street Guard. Each of these options has a take rate, and as long as we include the “none” option, these take rates have to add up to 1.0. So perhaps 30% of customers do not order Feet, 40% order Flip, 20% order Flip Guard, and 10% order Street Guard. The take rates are 0.4, 0.3, 0.2, and 0.1, respectively, which add up to 1.0.
With four options we lose the connection to coin tosses. We could use a loaded die to talk about features with six options, but an all purpose metaphor is the roulette wheel. Think of a spinning roulette wheel, or a stationary wheel with a spinning arrow as in many children’s games.
The wheel represents a feature, and there is a pie-slice for each option. The size of the pie-slice is proportional to the take rate. An example is shown above for the Feet feature of our backhoe. We can simulate a customer’s choice by spinning this wheel (or spinning an arrow). With this metaphor we can have any number of options, with any take rates. The “none” choice must be included to get a full pie (or there may not be a “none” choice).
To summarize, a product is a collection of features. Each feature has some mutually exclusive options, each of which has a take rate. These take rates add to one.
Understand product choices to manage complexity
A product is a collection of features, and each feature has alternative options. Understanding features helps determine strategies such as late staging. Some features are tangible, material things about the product: which engine, how much memory, Bluetooth. Other features are abstract or soft, like geographic region or sales channel. Among tangible features, distinctions can be made on the basis of the degree of postponement possible.
Pin-on features can be added to the product at the last minute, after a specific order is received. The classic example is the power cord for a printer. Hewlett-Packard avoided having different printers for different countries by attaching different power cords to a common printer.
Reconfigurable features can be changed after a real customer order is received. There are literally hundreds of different kinds of tractor tires, depending on the work a tractor will be used for. A tractor has to be built with some kind of tire just so it can be driven off the assembly line, and it’s easy to change the tires to suit the customer.
Line features, by contrast, are so basic to the product that they can’t be changed, such as the chassis or transmission for a vehicle or the motherboard for a computer.
Abstract or soft features are really attributes of the order rather than of the product itself. But they may be very valuable in understanding customer demand. The pattern of choices for tangible features may vary considerably by geographic region, which is a soft feature. For example, engine block heaters are popular in North Dakota and convertibles are popular in Florida, but convertibles with engine block heaters are almost non-existent.
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Extending the product configuration to gain insight
One of the most important components in choice complexity is the product configuration itself, the mixture of product options that give a product its unique signature. Obviously the typical product orderable options are needed to analyze the complexity of a product, but other more abstract options can offer surprising insights into product and customer behaviors.
A typical car configuration has options such as sedan, V6 engine, automatic, blue, cloth, AM/FM/CD, sunroof. But more abstract items can be recorded along with these to offer more insight. Sales type can be recorded to analyze what types of product configurations sell better in promotional sales events as opposed to normal sales transactions. An attribute to record an extended factory warranty option may provide new ideas for packaging options together with additional warranty services that customers are moving towards.
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How many choice combinations does your product have? That depends.
Possible combinations
This is a question with several answers. The easiest answer is the least useful. The number of possible build combinations, or unique configurations, is easily computed by multiplying the number of options for each feature. For example, if your product has feature A with 3 options, feature B with 2 options and feature C with 4 options, then there are 24 (3 x 2 x 4) possible build combinations.
These numbers grow very rapidly. If you have 5 features, each with 4 options, there are about 1,000 build combinations (exactly 1,024). With 10 such features, the number of combinations is about 1 million (1,048,576), and with 15 features it is over 1 billion (1,073,741,824).
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