One of the most difficult part of a product manager’s job is pricing. Too low and you don’t make enough money (or leave money on the table), too high, and the product fails to take off. Getting it just right is part alchemy, part luck, and often just a bit of a guess.
There are dozens (hundreds?) of books on pricing, there are guidelines and frameworks, there are blogs and consultants all poised to help you wade your way through the process.
However, this post isn’t about product management analyzing the inputs and determining pricing. Instead, it will document a few real cases where engineering, sales or senior executives set the prices based on their proclivities.
So, let’s dive in:
Sales setting pricing
If this sounds like the fox guarding the hen house, that is because it is. Sales, being closest to the customer will have a specific empathy with the customer. So they will take their cue from the customer as to what the price should be.
Of course, customers are always looking for a good deal so they will want a low price.
Hence, when sales gets the task of setting price, they will often collaborate with the target customer (or a few target customers), and then set a price accordingly.
Of course, if the BMW dealer asked you what they should price the M3 at, you would say that you would spend about $30K for it (when the list price is a hair less than $63K). Of course, sales will justify this price by saying that they will sell the hell out of it, and move a lot of volume. That customers were committed to buying shedloads of units. Yada yada yada.
So sales sets the price, and assures management that the volume will enable R&D and production to reduce production costs to get to an acceptable margin via a learning curve, and continuous cost reduction efforts.
But this never comes to pass, and often the price that sales sets is well below what is an acceptable profit, and of course the volume predictions never happen, and the cost reductions are not enough to staunch the bleeding.
And we lose money. Lots of money.
coda: if sales also is responsible for defining the initial product specs, this is a double dose of disaster. It essentially means that you are outsourcing all of your product management responsibilities to the end customer. Yes, I have seen this in action, and yes, it is ugly.
Engineering setting pricing
Being engineers, and living in a black and white world, engineers take the gross margin desired, and the costs of the system (cost of goods sold) and calculates the price to ensure the margin.
Simple, and crystal clear. You want 65% GM, divide the cost by (1 – GM) and you get your selling price.
But this fails for a couple reasons. First, there is always some discounting, so the engineer just fudges the margin to account for the average discount. Second, and probably more serious, is that the cost is not strongly correlated to the “value” of the product. Engineers notoriously are suspicious of this concept of value. To to their judgment, that is close to “bullshit“, or “fuzzy marketing bullshit“, and no sir, they don’t like it. Not one bit.
Senior Management setting pricing
One would be excused for thinking that senior management has a grasp of the fine art of pricing, and how to identify value, and set a price that maximizes the bottom line.
But one would be wrong. Sadly, senior management often thinks that they have gut instincts. They feel they know the market, and they know what the product is worth (nb: that isn’t the same as value)
So, you get a binary distribution. Too high and too low. With a wide (and I mean WIDE) gap between the two values. Unfortunately, as a product manager, you will often find yourself arguing against the gut-instincts, and no amount of evidence, analysis, and rationalization will sway the argument.
All three groups will set the wrong price. Sales is too close to the customer, and not in your court. Engineers are far too pragmatic. Senior Management truly believes their own gut.
My advice? Analyze the hell out of it, and get to the pricing before these other groups try to weigh in. Do the analysis early, and keep your fingers on the pulse of the markets.
Then try to prevent too much variance.