A Frequentist and a Bayesian Frequent a Bar

A Frequentist and a Bayesian have been going to this bar for the past five evenings. The bar is a special kind that offers only two kinds of beers – one is Amber and the other is Dark.

The first evening the Frequentist orders Amber and the Bayesian orders Dark.

The second evening the Frequentist orders Amber and the Bayesian orders Dark.

The third evening the Frequentist orders Amber and the Bayesian orders Dark.

The fourth evening the Frequentist orders Amber and the Bayesian orders Dark.

The fifth evening the Frequentist orders Amber and the Bayesian orders Dark.

This is sixth evening.

What are the chances the Frequentist will order Amber?

What are the chances the Bayesian will order Dark?

Your answer will tell you whether you are a Frequentist or Bayesian. A mindless dashboard driven manager or a hypothesis setting, data seeking, and dynamic decision maker.

Life is a series of probabilities – our job as decision makers is to seek relevant data to reduce the uncertainties.

For extra credit, what are the chances one of the two will be run over by bus or the bar shuts down due to numerous reasons? (Black Swan)

Recipe for Minimum Viable Versioning

jetblue-evenmoreProduct versioning is the simplest and fairest mean to price discriminate. While it may sound unpalatable to the idealistic minds, price discrimination is actually better for customers and businesses. That is when done right. Else it becomes operationally expensive, ineffective in market or worse turns off customers. That is where even established businesses fail. I provide a very simple and testable recipe to do product versioning.

First I want to expand on the benefits of price discrimination. Price discrimination is charging different customers different prices based on their willingness to pay. It is fair when customers willingly pay their prices over marketers enforcing it. It is clearly good for businesses because it helps maximize profits. It is good for customers for many reasons

  1. It allows them to experience a product they otherwise would not be able to afford- like a no frill discount airline that makes overseas travel possible for many.
  2. It allows customers to pay for only what they value and not pay for extras.
  3. It gives them the choice – sometimes they may want to splurge, while most times sticking to basics.
  4. it gives them the flexibility and convenience – like express line at amusement parks.

When done right, for businesses, the clear benefit is profit maximization. There are also other significant benefits

  1. Understand customer segmentation, purchase occasions and behavior.
  2. Optimize capacity – be it manufacturing capacity of breakfast cereal brand or web scale capacity of a cloud service.
  3. Refine (pivot) current product offerings to better tune to customer needs.
  4. Find the right price points for the products without tying down to a single wrong price.
  5. Clear separation of customers – like Nordstrom and Nordstrom Rack.
  6. Surface customers who have even higher willingness to pay.

So it is better to offer multiple versions of your product even if it in its MVP (Minimum Viable Product) stage. This may sound contradictory to the concept of MVP, after all an MVP is meant to test the demand and discover product-market fit with limited resources. How can a startup afford to invest in multiple product versions when it has only limited resources and is lean by definition?

Offering multiple versions of the same product does not mean investing in yet another product line and doubling your development cost. Especially it is not recommended for a startup that is trying to validate its MVP in the chosen customer segment. That leads us to a real simple and effective recipe for Minimum Viable Versioning.

The underlying economic principle is – customer value perceptions are different and if they perceive a value difference (real or not) they will gravitate towards the version that they believe offers them the most value.

Think about that for a minute. This means  you do not build three or four different products but make the customers think there are three or four products with different value offerings. That is you can build just one product and yet price discriminate if you can nudge your customers to believe there are multiple products.

Take for example the most quoted example of a printer  price discrimination where IBM added a chip to slow down print speed. While you could do such a product line change that does entail manufacturing costs and operational complexities.

What if IBM didn’t really add a delay chip but simply changed the specs to say slower speed?  A customer who values speed of printing is not going to be tempted by the lower priced “slower” version while the price sensitive customers are happy to buy the same.

Applying this recipe to the present day cloud services, you may offer a version that is limited in capacity but may not build any code to enforce that restriction. For example a 2GB capacity limit and 10GB capacity limit for two versions. Those who value more capacity will self select to higher priced larger capacity version and the price sensitive customers will stick to the lower capacity version.

Some of those who picked your 2GB limited version may end up using more than that. But so what? Most who believe they want more than 2GB self selected to your higher priced version and you gain better market adoption, better understanding of segment-version fit and better profit without changing the product one bit.

Remember the economic principle – it is not the real value difference as much as the perceived value difference. Value is in the minds of customers with their wallets out and ready to pay.

So go ahead and build one MVP. But offer three versions (Why three?) that CLEARLY and EXPLICITLY communicate to customers the value differences so they can self select. While measuring product market fit with MVP you now can measure price perception and segment-version fit. If you find exceptional demand for your “low-end” version, find a way to build it at lower cost so you get to keep more of the price as profit. Until then, they do not need to know it is the same product.

When you take risks based on data

Today is Super Bowl XLIX. One scoring play we are most likely to see today is the point after kick. Teams seldom miss it. It is a sure one point. They do have the option of going for two instead of taking the sure one point. Teams go for the two only when they are forced to. That is when they re in fourth quarter and a single point still puts then at a disadvantage or keeps the door open for the other team.

Successful two point conversion is not given. It is risky. But the time to take risk is when you have time and resources to recover if it does not pan out as expected. Not when when that is the only option. Armed with data it is easier to take risks than with just gut.

Why don’t they go for it every time? Should they go for it? Let us look at some data.

Today’s Super Bowl features defending champion Seattle Seahawks and three time champions New England Patriots. Here is how the team statistics look like (source)



In the past seven years Seahawks attempted five fewer than Patriots and have less than half the success rate of Patriots.
So it is likely Seahawks won’t go for two unless they are forced into it and are most likely to miss it.

Patriots have a 50% average success rate over the past seven years. That is an expected value of 1, same as assured point after kick. So they should go for two every time. There is only upside for them.

Price Discrimination At The Altar of God – Revisited

A while back I wrote about the single price model at a Hindu temple to bless cars, known among the community as “car puja”.  I then wrote about the value left on the table by not setting different prices,

The last time I walked past one such event at a East Bay Hindu Temple, I saw two cars parked side by side  waiting to be blessed. One was a BMW X series and the other a Toyota Corolla.  The price the temple charges for the ceremony? A standard fee of $25.

The value to customer is of emotional kind and not economical. The perceived value to the customer is of private kind and is different for each customer. For instance, the value of the ceremony to someone who bought Lexus is much more than the value to someone who bought a Corolla.

That said, the value of the blessing to a first time car buyer or someone who  bought the maximum they can afford (even if it were a Corolla) is high.

This screams out for practicing price discrimination.

Price discrimination is not about squeezing every bit of consumer surplus from every customer (in one model it is). It is about getting customers to willingly pay the price they can pay and still feel happy about it.

A regular reader of this blog sends an example of price discrimination at the altar of god done right. This comes to us all the way from Notre Dame cathedral in Paris. As one walks along the caverns of the cathedral one sees near every niche a bunch of votive candles lit. Next to the lit candles are stacks of new ones that you can pick up and light as offering.

The price? In reality it is €0.  But it is more nuanced than that. The set price is 0 but you are encouraged to leave donations. This is where the price discrimination done right comes in. A simple method would have been to offer just one type of candle and ask visitors to pay what what they want and expect them to pay their true value of lighting a votive candle. What the good folks at Notre Dame have done is a nicer and better form of pricing.

They offer the visitors not one candle type but three candles types – a very basic small sized version, a middle version and a highly decorative large version. The price? These are free remember? There are no prices but only suggestions, setting an anchor to donate and offering them three different options.


Price discrimination, despite its bad rap, is a good thing for all.

Too Many Cooks Spoil the Myth -Hidden Hypotheses Syndrome

You likely have heard many of the maxims like the one about cooks and broth – Too many cooks spoil the broth. And likely used it without realizing it and even though you and your colleagues are not cooks or when your work does not really involve making broths. But I can say with high certainty that you never asked,

“Do too many cooks really spoil the broth?”

Thankfully humorist Joe Queenan did. As he set out to question this and many other maxims, Mr. Queenan wonders why they are never true. He offers us some infinite wisdom like,

The English language abounds with hoary maxims—tidbits of putative wisdom that, upon closer examination, prove to be completely idiotic.

The list of time-honored, moronic maxims is by no means tiny.

Folk wisdom is equally cretinous.

The best part is his line of question on the maxim on cooks and broth.

Do too many cooks spoil the broth? Was there a control group with a smaller number of cooks and different broth?

What was likely a humorous take is actually asking relevant questions when rest of us have suspended disbelief and accept these as enunciated truth. Our suspension of disbelief and acceptance of inanities extend beyond broths and watched pots into business realm.

Take a closer look at his line of questioning. A simple question on evidence and the method of analysis that opens wide upon the veracity of the claim.  This simple question we fail to ask when we see, read, listen to Gurus and charlatans presenting their pet theories in bite sized chunks and colorful TED speeches.

Mr. Queenan’s simple question bring out the issues you and I need to worry about when we read, “women in board led to better share performance“. Or “women who play video games have more sex“. Or when a popular Guru sees a movie and writes up business lessons.

The issues are

  1. How was the hypotheses developed in the first place?
  2. How was it verified to be stated as a claim – the experimental design and data collection?
  3. What hidden hypotheses are at play? (As he asks, will the result be different with different broths?)

We seem to be longing for the the comfort of Gurus walking down the mountain with simple business maxims for us to Retweet (and follow). All it takes is one visit to a store or a cab ride for them to come up with sweeping prescriptions for all of us, regardless of the variations. One instance of a chaotic kitchen with cooks milling around and someone tipping over broth pot lets them declare universal theory about cooks and broths.

You cannot place all the blame on them. More than 70% of the blame should be on us – the willing audience that has suspended disbelief. And our failure to recognize the simple fact that it is not enough to know that data fits one hypothesis and we need to look for falsifying evidence.

Here is a simple message – No one can be trusted so verify and trust with reservations.


Bigger than Bigger Profits

A while back I wrote an article about brands finding a way effective product versioning to get customers to willingly spend more, happily part with more of their cash and consumer surplus and hence able to drive up their profit.

The principle is not new. The examples were there just to illustrate the power of effective pricing and versioning. None of those examples come close to the scale of what Apple was able to achieve with its iPhone 6 and iPhone 6 plus.

I wrote about long term profit potential of Apple’s iPhone 6 versioning. As customers lined up for hours and miles over the weekend to buy the new phones we have some early survey numbers that points to Bigger than Bigger profits.

In my last article I predicted increase in Average Selling Price just from not offering a 32GB version and making the cheapest version stay at 16GB. With that change and the introduction of iPhone 6 plus we did see a huge shift in product mix sold over the weekend. According to Wells Fargo analyst,

Most notable was shift to 64GB and 128GB models versus prior launch surveys and greater popularity of 6 Plus. Of those surveyed, 67 percent intended to buy the 6 Plus versus 33 percent the 6. Additionally, 33 percent planned to purchase the 128GB versus the last two launches for the highest-end model of 22 percent and 17 percent.

In the end what does the net new profit for Apple look like? Crunching the numbers with data from Wells Fargo analyst and treating COGS increase as negligible here it is.


That’s Bigger than Bigger indeed!