What can we learn about sales from this grandma?

She is 68 year old grandma, a former teacher and she is one of the most prolific sales people in the world. From her humble beginnings  30 years ago she now leads a sales army of 300,000 sales people and hauls in $8M in sales commission.

Her sales secret?

Lead With Emotions:

The most powerful weapon is to move somebody emotionally. So if you send out a signal as love, you will receive the same signal back.

Tell Stories: When she talks she uses stories filled with emotion, like about her mother.   She favors simple stories, from Christopher Columbus to pyramids to Ronald Reagan,

It’s up to us to elevate ourselves to be givers

Believe: When everyone else worries about the playing field and system that does not favor them she strongly believes

“the system is designed only for me to succeed”

Always Be Connecting: When most struggle with reaching their customers she turns even her everyday action turn into a sales lead. She made her first customer by asking for restaurant recommendation on the street

“that is how we made friends. And then we told him about the business.”

Don’t Keep Score: When most try to focus on how much they make she does not keep score.

“I don’t even know how much I make”

Make Deeper Connections: When sales people are known for superficial connections she believes in making stronger connections,

“You have to know the inside of people, rather than the outside of people. You’ve got to know their hearts.”

In fact her success largely depends on delighting her customers so much and turning them into her sales people.

And the result speak for itself doesn’t it?

But wait there is more. If you have not figured out yet, this is meant to be dripping with irony. Did I mention she is an Amway, a multilevel network, distributor? Can you see how she is simply one of those lucky few among the millions who happened to consistently get heads in each toss of coin and ended up at the top of the pyramid?

What can you learn from this sales machine grandma? Survivorship bias of course.

Next time you read stories asking you to learn about sales, business, marketing etc. based on anecdotes beware of this.

Story link here.

Fail fast because successful companies failed before they succeeded

There are several versions of this statement, one way or another they glorify failures and in the name of exhorting startup founders these inspirational statements lead one to believe

1. After a few failures success is inevitable
2. You must fail first to succeed
3. Fail fast so you can succeed
4. Failures signal impending success
5. “Failure can be a true blessing in that it educates you and prepares you for success” (from here)
6. “Remember that most successful entrepreneurs fail good and hard before they finally make it” (same source)

All these assertions are happy to point out popular examples. The problem is the assertions are derived from the very examples they are using as evidence.

First let us make something very clear. Success and Failure are the only two possible outcomes for any venture you undertake. But the fact that there are just two outcomes does not mean they are equally probable. It is not the case of tossing a fair coin and calculating the odds of heads or tails.The chances of success and failure can be and are very different. If you take the base rate (looking at the success rate of thousands of ventures and small businesses) the success rate is 3 to 5%.

Second  even if we assume that Success and Failure are equally likely, a series of failures does not mean inevitable success. Take the coin example. The probability of getting 10 Tails in a row is same as the probability of getting 9 Tails in a row followed by a Head.

Lastly the fact that those who succeeded had failed in the past is irrelevant. Those who make such an argument pick only the success stories that are popular, recent and available to them. When you only look at those who succeeded and are still in business you are leaving all those who did finally succeed and gave up or still trying without success. Even in these cited success stories success is mostly random rather than a result of their failures. The fact that those who succeeded had “failed hard” does not mean when you fail you will succeed.

Granted they learned from their mistakes but you do not have to learn from your own mistakes.  You do not have to fail to learn. Failure is not the true blessing. Insane success with hundreds of billions of valuation even when your venture has no real product or clear value add is true blessing.

Those who advise you to fail are not being intellectually honest. Their advices are no different from those advising a gambler to bet on a slot machine that had been coming up empty for the past few hours.

 

Let us get street education, who needs formal education …

There is considerable noise  being made to discourage kids from going to college, to be  “pirate”, to skip college education to start something or to follow their passion. The argument goes, “because people who started something big, Bill Gates, Steve Jobs and Mark Zuckerberg did not need college degree”.

Reporters like Sarah Lacy, instead of taking a critical look at such discussions are joining in.

@wadhwa i'd support anything my kid wanted to do. two of my brothers dropped out and my parents–TEACHERS– supported them.

— Sarah Lacy (@sarahcuda) April 14, 2011

I believe most are aware of the meaningful counter argument made by Vivek Wadhwa and others. Instead of repeating that I will quote what Rev. Al Sharpton said in an interview with Stephen Colbert.

May be the reporters and the likes will see the cognitive biases in their case for asking kids to drop out of college.

The interview video link is here and it is unrelated to this noise about education bubble:

Colbert: You don’t have higher education. You got your education on the streets my friend, education in the church. Why can’t we give that to children and forget about the books?
Isn’t there sir, a tyranny in this country that everything gotta be out in a book? Why can’t we let these kids fly, be free?

Sharpton: (pointing at Colbert) See this is Exhibit A why we need education.
I know. I dropped out of college. I know myself everyday the regrets I have in not pursuing my degree.

Colbert: But you have done very well sir.

Sharpton: How many people that came out of the same neighborhood that I did, that had the same background I did was able to make without an education. Most of my friends ended up in jail or dead. I want to make sure that dosn’t happen to the next generation.

Rev. Al Sharpton gets selection bias and survivorship bias.

Do Peter Thiel and Sarah Lacy get  P(A|B) is not same as P(B|A)?

Do they know if tens of thousands of kids listen to them and skip college, how many will have a future like Gates, Jobs or Zuckerberg?

The Real Limitations of Evidence Based Marketing

This is not a reply to Seth Godin’s post. While his post triggered this, the usage of the term Marketing is different between the two articles. To me, Mr. Godin’s article’s use of marketing reads more about marketing communication and messaging. I cannot agree more on the need to present the message in more interesting and acceptable format than just gobs of facts and data. We cannot hope that the rational automatons will figure it out, years of behavioral economics research has shown that we are anything but rational.

Marketing, to me,  means strategic marketing – activities that come way before we get to messaging. Like choosing the segment to target, the product versions to deliver, the pricing strategy and how to reach these customers.  This article is about that definition of marketing. However, Mr. Godin’s use of the phrase “Evidence Based Marketing” for a messaging tactic will create confusion in the minds of many. Using data and facts in messaging is a tactic, it is not Evidence Based Management.
Read on.

Evidence based marketing is flawed, it is rife with multiple errors. The common error types are

Inherent Data Errors: Data is noisy and incomplete. Sometimes the readings can be just plain wrong due to probabilistic nature of data source.
Environmental Errors: Context and environment collude to further muddy the water by tricking our eyes, minds and tools. Due to no fault of our own we see mountains when there aren’t any (like John Ross’ Croker Mountains).
Observer Effect: Call it Heisenberg uncertainty principle or Hawthorne Effect. The very act of reading the data can taint it.
Methodological Errors: Call it sampling error or survey error, our methods of data collection are inadequate. They introduce their own errors that are sometimes unquantifiable.
Data Collection Errors: We do not know what or how to measure. We ask the wrong survey question or add the wrong stimulus  but treat the received data as answer to the question we had in mind.
Analysis Errors: Test for statistical significance is flawed and misused. Not just Type-I and II errors, the very method of hypothesis testing is flawed. We collect data conditioned on the hypothesis being true and declare, “since data fit the hypothesis we conditioned to be true, the hypothesis is true”. We take comfort, wrongly, in using lower p-values. When data fit the hypothesis we stop, ignoring the fact that data can fit any number of hypotheses.
More Analysis Errors: We take comfort in adopting more rigorous and computationally intensive analytical methods. We treat correlation as causation and even regression as causation, look to the past to guide the future. We ignore lurking variables that could explain common causation.

Yet, Evidence Based Marketing is preferable to the alternative – based on guts, fads, Guru’s revelation, opinion of the person with highest title, and just plain observations.

The alternative is rife with errors that are not easy to see or measure – Cognitive errors. We suffer from multiple cognitive biases like Recency Effect, Availability Bias, Selection Bias and Survivorship Bias.Worse, the alternative rely on Commitment Bias and Agreement Bias (peer pressure) to push through a version of truth. Here the truths are unfalsifiable and it is forbidden to look for falsifiable evidence. Anyone stepping outside the accepted norm is labeled and shamed into compliance.

Evidence Based Marketing is flawed but it is clear and explicit about the flaws and lets the decision maker be the judge. The good practitioners know its flaws and bad ones cannot overlook it for too long.

Evidence Based Marketing eliminates the need for a charismatic leader and survives across leadership changes. The Alternative relies on the words and presence of the leader and the methods change when leadership changes. One myth is replaced by another.Both Evidence Based Marketing and its Alternative will take us to Madagascar but will try to tell us it is actually San Diego. Evidence Based Marketing would do that with data selection error, Alternative will just tell with authority.

When  uncovering new data shows otherwise, Evidence Based Marketing will reduce its certainty and state the likelihood that its prediction is correct.

Evidence Based Marketing is about forming a repeatable and falsifiable theory. The practitioners know that their is theory is true only because there isn’t data to prove it otherwise.

Which pill is it going to be for you?

Biases in Making a Case for Freemium

[tweetmeme source=”pricingright”]Reasoning and decision making biases are not new – they have been extensively studied and reported.  Committing the same biases are not new either – for academics and new media specialists alike. It should come as no surprise to see the same mistakes committed by very smart  thought leaders like Mr. Anderson and Mr. Om Malik when they write about how Freemium  would help startups and other businesses alike.  I have written previously about biases committed by Anderson in his book Free, now let me discuss Mr. Om Malik’s case for freemium.

To be clear, Mr. Malik’s post is titled  How Freemium Can Work for Your Startup , in which he discusses three startups, EverNote, RememberTheMilk and DropBox and on their ability to generate revenue with a freemium model. Based on these an on a NYTimes article on EverNote Mr. Malik offers 10 commandments of a successful freemium app. Let us look at the biases and flaws in the overall case for freemium and flaws in one  specific “commandment”. His rest of the commandments are actually quite good and applies to any business model a startup chooses.

1. Survivorship Bias: – Mr. Malik looks only at those that “succeeded” (by his definition I understand, generating some revenue, not necessarily profit). What about all other startups that failed despite those? Did he closely look at all those that failed to say that these did not have the same characteristics as the three he declares to be successful? This is not new, we have seen this flaw before in the business best seller Good to Great by Jim Collins (who later followed through with Why the Mighty Fall).
2. Availability Bias: Mr. Malik’s post came after his query to his readers for services that they find indispensable.  So we can hypothesize that his argument is based on information that is available to him and vivid in his memory.
3. Omitted Variable Bias: This is ignoring other reasons that might have caused the success and incorrectly drawing causation conclusion from correlation.
4. Ignoring Other Options: EverNote may be making $79,000 per month from a fraction of the free users who upgrade to paid service,  but could they have generated equal or more revenue  through other marketing options available to them including offering only paid versions? I do not have data to say either way, neither does Mr. Malik offer any to support that Freemium was the best of the available options to EverNote. After evaluating all options if freemium still offers the best chance to succeed, then by all means do it but not without exploring other options.
5. Can the business wait? In a follow up post, Mr. Malik writes,
   

   I used Evernote as an example of a freemium application that’s successfully converting its free users to paid ones. Indeed, the more people use an application like Evernote, the more likely they’ll be to pay for a premium version of it.

   Mr. Malik recomends patience as a virtue, waiting for customers to fall in love and find the service indispensable not to mention switching a hassle. Customers, enamored by the free service will try it and start using it and this may take a long time before they upgrade to the paid version. Can businesses know or model this conversation rate? Without this, it is incorrect to assume that this conversion will happen and will do so before your startup runs out of cash. Customers can stay on free version longer than your startup can stay solvent (hat tip to Keynes).

6. Free is Free marketing? One of the 10 commandments is
   

   Free is free marketing. Instead of advertising, the service should sell itself.

   How true is this statement? Where is the data? Does free sell better than marketing/advertising? I have some data,  a paper published in Marketing Science Aug 2009 studied the impact of marketing actions like exhibits, print ads, PR. Of these marketing actions, all but PR and Exhibits yielded better long run sales than free as the marketing action.  Another problem is when there are many similar free services available to the customers – what will be your share of mind and wallet?

To recap: New kinds of products do ot need new kinds of marketing.  If after evaluating all options  freemium still offers the best chance to succeed and maximize your profit, then by all means do it but this is not a generic solution as it is touted to be. Do not accept, without challenging, statements like “freemium works” or “it worked for 3 and hence it will for every startup”.

“For example is not proof”

Survivorship Bias and Other Flaws in Anderson’s FREE

[tweetmeme source=”pricingright”] In his new book, FREE: The Future of a radical Price, Mr. Chris Anderson supports his arguments with many examples of businesses that used razor-razor blade model, advertising model, and free + premium model. The last few pages of his books are just a list of examples of businesses that are successfully implementing, according to him, what he calls the “freemium” model. Are examples enough to state absolutes like “the future of a radical price”?

Even if that is enough, Mr. Anderson lists only those businesses that seem to have made it, at least for now, and does not include those businesses that tried many of the free models and failed. That is the classic survivorship bias. If we restrict just to the new media businesses that Mr. Anderson focuses on, there are many instances of ventured that went under. Even the small subset one can find in TechCrunch’s  “DeadPool” is a daunting number.

Even among those businesses selected,  the time horizon is too short to say they are successful or will deliver long term profit growth. Mr. Anderson uses  a different metric, “uptake among customers” rather than profit to measure their success. His careful choice of metric is not by accident, it is about cleverly framing the argument and directing his readers and listeners to focus on a metric that is irrelevant but supports his argument.

The next problem is confusing correlation with causation. Among the blockbuster success stories he quotes like YouTube, he attributes the customer uptake to the free model. He uses  Prof. Dan Ariely’s  Hershey’s experiment to substantiate this claim on causation. You can see Prof. Ariely’s comments on people using his experiment in his blog. In his Hershey’s  experiments, the claims were based on experiments that used control groups and treatment groups. But Mr. Anderson makes his claim based on YouTube being free.

Businesses, before jumping on Mr. Anderson’s far-reaching conclusions, should ask about his decision making process and analyze their own business based on hard data. As professors Pfeffer and Sutton point out in their book Hard Facts, the difference between an academic (who is much maligned by the new media Gurus) and a self proclaimed Guru is  that an academic gives you an open system of decision making where as a Guru gives you a closed system that talks in absolutes, ignores evidence, focuses just on benefits and minimizing the drawbacks of their recommendation.