ChatGPT Test: A Short Post About Wordle and Probabilities

WordleBot’s analysis of my picks a few days ago.

Today in Curious About Marketing I wrote about the Wordle and probabilities. As an experiment I put “A short post about wordle and probabilities” into chat.openai.com and this is what I got back:

By ChatGPT:  Wordle is a popular word game and online toy that allows users to create word clouds from any text they provide. The game displays a cloud of words, with the size of each word indicating its frequency in the provided text. This can be used to understand the probability of each word appearing in a given text. In addition, Wordle can be used in educational settings as a tool for teaching concepts related to probability, such as relative frequency and probability distributions. The game can also be used to analyze a large amount of text, such as a book or article, to identify the most frequently used words and their probability of appearing in the text. Overall, Wordle provides a fun and interactive way to learn about probability and text analysis.

Day 1 of my newsletter: Curious About Marketing

Don’t give me too much crap about trying to be trendy after the trend has peaked…. but today I am launching my newsletter: Curious About Marketing on Substack. I plan to write about marketing strategies and will try to measure how well they are working. Marketing executives don’t seem to talk about their strategies that often. Well, not in advance anyway. Career advancement in marketing often comes when someone takes credit for a great strategy after the fact! This is much easier than creating a hypothesis and setting out to put it in motion and rigorously testing it. Many, even most, marketing strategies fail, and all need adjustments.

So I hope to decipher the strategies and measure them. I would love to have you join me in the dialog.

You can get to the newsletter on Substack here: Curious About Marketing

Or just add your email to the list here:

Genie and the Salesforce GTM Playbook

Salesforce presentation at Dreamforce22. A Genie or a Rabbit… where is the hat?

Salesforce introduced Genie at Dreamforce ’22.  Bret Taylor, Co-CEO of Salesforce, calls Genie the most significant shift to the Salesforce platform in 20 years. This development illuminates Salesforce’s aspirations in the modern data ecosystem.

The present conditions are remarkably like the early CRM days when Salesforce got its start.

Before Salesforce, there was a large CRM industry.  Microsoft, Oracle, Siebel and just about any consulting company or system integrator would build a CRM solution from their kit of tools and templates.  These were custom solutions and very expensive.  Most of them failed.  Many failed spectacularly after years of effort and millions of dollars invested.  It is staggering to think of the waste in the wake of those projects.  Not only did they require money and people, they also sucked up time like it was the last water in the desert. Time that competitors used to pillage market share.

So, it was no wonder that conditions were favorable when Salesforce made its entrance.  Salesforce’s cloud based CRM was cheap by comparison and ready to use right away.  Salesforce had one message:  you can have CRM now for a fraction of what you have in your budget.  The situation was so bleak that customers didn’t even care if Salesforce worked.  Their alternative was not working and cost a fortune and was a huge distraction.  Salesforce saved the day.

Fast forward twenty years to the modern data warehouse automation sector. For the past three years, I have been watching and pattern matching. The big, specialized vendors like Informatica, Talend, Tibco along with the generalized vendors like Microsoft, Oracle, IBM and the consulting shops like Accenture, Deloitte, Tata, and McKinsey will gladly build you a data warehouse. It will be expensive, take forever, and in the end, probably fail .If it takes a long time to build it will be a failure merely because what was needed last year is not what is needed today.

Just Google “data projects fail” and see what you get. Thousands of articles quantifying the depth and the breadth of the waste. Just like the old days in CRM!

Salesforce is now positioning Genie to: “…bring together ALL your customer data into a single source of truth”.  And by ALL Salesforce is talking about ALL data sources in a company.  And they say their average customer has 976 data sources.  So, Salesforce is going to connect to ALL data sources and then do this:

Presentation about Genie at Dreamforce 22.

This sure looks like the data flow diagram every data platform vendor from Matillion to Microsoft uses to describe their data stack.  Put it all together and Salesforce is running their old CRM playbook in the data sector.

Detractors will say that no serious data scientist is going to use Salesforce Genie in their serious data project. What about DevOps? (inside joke). I say, let’s just watch what Salesforce does with Genie. It could be CRM all over again.

Other links about Genie:

What is Salesforce Genie

Genie Product Innovations

The Roadmap to a Free Trial and Frictionless Growth

There are two kinds of B2B SaaS companies, those with a “Free Trial” and those without.  Some would argue there is also a third kind of company where the “Free Trial” button leads to a form where the customer must apply for a free trial instead of a truly self-service free trial.  This is just another flavor of not having a free trial.  The free trial strategy only works if it is completely frictionless for the customer and the company.  When you log in each morning, you want to be able to see that hey, 110 free trials kicked off last night! 

Within the free trail group, there are two variants.  Applications with a network effect, and those without.  Both types can effectively use the free trial strategy, but the companies seeking a network effect may choose gaining more users over ever getting paid.  This model is sometimes called “freemium”.  Where users sign up for free, and can continue for free, or can upgrade to paid.

The free trial strategy where the company wants to get paid by every customer is the panacea for B2B SaaS.  Some people call this “Product Led Growth”.  It can be the key to your frictionless growth.

So, there are two types of B2B SaaS companies, those with a free trial and those that wish they had one.  And within the free trial group, there are those that want to get paid by every customer and those that may have customers that don’t ever pay.

If you are a B2B SaaS company with a free trial and the desire to get paid by every customer, here are three things to put on your roadmap:

1. Be relentless in evaluating the usability of your application.  Make absolutely sure it really does work for the users you want.  Test and QA until you are certain you have a 100% self service new customer onboarding.  If you are not sure, have a beta trial or some other track that only finds adventurous potential customers that will help you work out the free trial bugs.

2. Promote your pricing in advance of the free trial.  Since you want every customer to pay at the end of the trial, there is no point hiding the cost or making it difficult for potential customers to calculate what the cost will be.  No customer you want for the long run is going to take the time to learn your application while just hoping it will fit in their budget.

3. Understand your customer’s path to your free trial button.  Make a list of every path you can imagine your ideal customer following to your free trial button and start testing them one by one.  This exercise probably starts with a search for something like: “how to load SAP into data warehouse”.  When I run this search, I get 4 ads and 82 million results.  The success of this path for you requires that you get to the top of that list.

From this discussion, which just starts to map out the journey, we see there is a lot behind every one of those free trial buttons on B2B SaaS websites. Done correctly, the free trial strategy can absolutely fuel your frictionless growth.

We Can’t Keep Winning if We Don’t Really Know The Why

Lack of curiosity killed the sales process cat.  It is fun to celebrate a record quarter or even a new closed deal. The bigger the number, the more fun it is at the celebration.  After the fun, and probably after the ibuprofen kicks in, it is worth the effort to go back through each step of the sales process and capture as much learning as possible. 

While doing so, it is essential to be aware of preconceived ideas (or pet theories) and actively work to understand the why behind the win – and not just look for evidence that supports existing thinking.

Here are my five mile markers in the sales process and related questions to help guide the learning for either one big deal, or a record quarter:

Mile Marker 0, the Beginning

Often referred to as the awareness stage, and it can be quite a bit earlier than we thought – making the sales cycle longer than we may have previously calculated.

·       When did the prospect(s) first interact with us?

·       What exposure did the prospect(s) have to us before the inquiry?

·       What were their initial motivations for the inquiry?

Mile Marker 1, the Connection

People buy things from people they like.  How are the relationships built between our prospects and our company?

·       What relationships were built and in what order?

·       What activities drove the relationship building?

·       How did the motivation of the different parties vary?

Mile Marker 2, the Alternatives

There is always competition.  Sometimes the alternative is buying nothing.  Quantifying the alternatives is essential to understanding the process and building a winning predictable machine.

·       What were the prospect(s) picking between?

·       What are our strongest arguments (the prospect’s perspective)?

·       Weakest arguments?

·       What drives the timeline?

Mile Marker 3, the Details

It is easy to get caught up in our perspective and fail to clearly understand the customer’s motivation.

·       How do the prospect(s) think about risk?

·       How do they calculate the value of our product?

·       What problem are we solving for them?

 Mile Marker 4, the Win

The win is just the beginning of the relationship and customer happiness is not assured!

·       What is the first measurable mile marker after the win?

·       What pivotal actions need to be taken and when?

·       How do we calculate ongoing customer happiness?

There is often a good deal of hand waving in sales, and even more in marketing.  It is fun to call out the good numbers, and celebrate wins with the team.  At the same time, let’s not miss the opportunity to learn. Great teams are willing to dig into the details and really think openly about the why.

Extra Credit: It may seem strange that I started the list with Mile Marker 0. If you have ever been to Key West, you will know why!

Winners and Losers

We don’t need the Superbowl to know that people are very interested in winners and losers. The headline of any news item makes it clear. If you want clicks, you better be talking about winners or losers or both. The pandemic has both reorganized and reinforced our winner and loser lists. Some politicians have lost their jobs because they handled public health poorly. Unsurprisingly, some already strong ecommerce companies got stronger. And some surprises came out of nowhere. Tupperware for example, is trading at $32 today, up from $1.15 earlier in the year.

Stories about those that come out on the top or the bottom are rarely as straightforward as they seem. Some winners deserve the spoils of winning because of virtue or hard work, others just got lucky. Some truly lovely people come out on the short end. Life is certainly not fair and even less so in pandemic times.

While some of the winners were using their added advantage to pound more nails in their competitors’ coffins, other winners where using serendipitous winnings for good. In addition to the many stories of much needed food banks and offers of shelter and healthcare, the story of Brooks Sports is worth retelling.

Brooks Sports is no stranger to winning or losing. It has seen both multiple times since its founding in 1914. It has made everything from ballet slippers before the great war, to the #1 rated running shoe in 1975. Brooks has built a solid business and currently commands about 25% of the running shoe market. Since 2011 Brooks has been a subsidiary of Warren Buffet’s Berkshire Hathaway. Buffet has famously said, “Never invest in a business you cannot understand”. People like to run, runners need shoes, shoes wear out…good business. Straight forward enough, but who would have guessed that Brooks’ revenues would jump 22% in the time of the coronavirus? People work out, gyms close, people like to run…and spend their gym membership budget on shoes.

Now the good guys win part of the story. It turns out that frontline healthcare workers who spend all day on their feet, also like the lightweight and comfortable shoes Brooks makes. Knowing their customers, and knowing their healthcare customers were facing great challenges, Brooks took their winnings and contributed 45,000 pairs of shoes to frontline healthcare workers. You can read more about their “Our Heroes Wear Scrubs” campaign here.

We Need a Zillow of Public Health

The US needs an automated data store for all things healthcare.  It needs a Zillow of Public Health. The Gates Foundation is uniquely positioned to bring this about.  Many people will say this is impossible. Here are some of the objections they will lob at the idea:

Objection 1:  It is the CDC’s job / the CDC is doing it already / the CDC will do it now

• The CDC has not done it in the past

• The CDC is not doing it now

• The CDC exists in a world where doing it will be very difficult

• Homeland security has had nearly 20 years to do something similar on the security front and has not succeeded (consider their inability to track children crossing the border)

Objection 2:  There are many regulations that make it impossible for a private foundation to collect and manage health data

• The current crisis offers a temporary reprieve from many regulations

• The current crisis provides the motivation to get it done now

• The Gates Foundation’s contribution towards addressing the current crisis affords it a unique exemption from regulatory pushback

• The Gates Foundation is best positioned to persuade the government, the community, and the public on the benefits

Objection 3:  It is too hard, and will never be ready in time to make a difference

• Yes it is hard and a few years ago it might have been impossible, but new tools and techniques will enable us to see the initial results in just weeks

• It is the 3,142 counties and over 8,000 hospitals, each with different governance, systems and capabilities that drives this need for an automated central data store

• Even after the initial wave has passed, efficiently collected and trusted healthcare data will be essential for bringing the economy back and managing future waves without resorting to closing down large portions of the country. 

Objection 4:  The health insurance lobby will kill it (many, many reasons they would find it threatening)

• They could be persuaded that equal access across the health insurance industry to high quality health data would be better than their current situation

• They might prefer to support a neutral 3rd party with the reputation of benevolence instead of being subject to data poorly managed by the government, or worse yet, intentionally mismanaged by the government.

Benefits of This Approach

A Zillow user can use a simple map to access information about any house in the United States.  The last actual sale price is listed along with other specific facts about that house. As a result, not only could Zillow tell you exactly how many houses sold last month, but it could give you a complete list of them.  Zillow does this by aggregating the property records from every single county in the country. For the purpose of this discussion, let’s call this approach of capturing every single record the complete data approach.  

The healthcare industry has never adopted the complete data approach.  In healthcare, data is sampled and statistical methods are applied and results are calculated.  This is why the CDC’s best guess as to the number of flu deaths per year range from 12,000 to 61,000.  The CDC is not tracking each case, it is sampling some data and analyzing it.  If there was a complete data system for healthcare, a Zillow for healthcare, you could know exactly how many death certificates issued by county coroners listed flu/pneumonia as the cause of death.  In addition, you would know the age, gender, race, and location of each case. The necessity of this is obvious in the current pandemic environment. Contact tracing at scale is not possible without a complete data approach.

Great Efforts Being Made by the States

State governments maintain systems tracking disease in their jurisdictions.  Washington State is no exception and is using its system to track the coronavirus.  You can see the results here.  This is not an attempt to malign the good people working for the State of Washington.  I have no doubt they are working around the clock to assemble the data. To their credit, they may be adopting a complete data approach, tracking each case of covid19 in our state.  There are several signs that the systems they are using are not up to the task. The note that the last 4-7 days may be under-reported illuminates the struggle the state is facing to get the data into the system.  The note that 15% of the cases are not associated with a county is also a red flag. It also may be true that new cases are 40% less likely to start on weekends, but it does not seem likely, and ultimately, it does not seem likely that the state will be able to sustain the current manual data management process.

Next Up at the Gates Foundation

First let me say, I have no knowledge of what is going on inside the Gates Foundation.  I know they are an organization that uses data to drive decision making, and they attract the best talent in data science.  I would love to know if the Gates Foundation has the appetite to become the trusted center of a complete data approach in US Healthcare.  Because we need a Zillow of Public Health.

Other Recent and Relevant Articles

IHME Covid 19 Updates

Gates Foundation Annual Letter 2020

HBR Vaccine Distribution Article (4/2/2020)

Bill Gates’ Washington Post OpEd (3/31/2020)

Modern Data Management and the COVID 19 Pandemic

For a timely example of modern data management, take a look at the Johns Hopkins visualization of the COVID 19 pandemic. For an example of NOT modern data management, take a look at the CDC reporting on the flu. The contrast is stunning. The COVID 19 visualization updates every 15 minutes and shows its source data and methods. The CDC flu page has not been updated since week 8, February 22.

Modern Data Management
(updated every 15 mins, exposes source data and methods)

Johns Hopkins Visualization of COVID 19 Data - lists its sources, updates every 15 minutes

With 100,000 cases and 3,400 deaths we can easily calculate the death rate of 3.4%. We know that many of the governments are not reporting the data accurately — particularly when it comes to cases. So the death rate may be significantly less because the number of cases could be much higher.

It would be interesting to compare the COVID 19 model to the CDC flu model, but so far I have not found a good side by side where the data is presented in similar formats.  It appears that the CDC takes some time to compile its estimates of the impact of the flu. In this report, the 2017-2018 and 2018-2019 seasons are still listed as preliminary and subject to future revision. The elevated attention on COVID 19 and the hour by hour real time reporting is a significantly different method from compiling estimates based on death certificates. It is not hard to imagine a scenario where a COVID 19 death goes unreported.

NOT Modern Data Management

(Update interval unknown - weeks or more; source data and methods unknown)

CDC Flu Report Weekly — 3 week lagtime.

The CDC reporting presents deaths as a percent of all deaths in the US and cases as n per 100,000 — making it theoretically possible to calculate the death rate. In the text the CDC estimates there have been at least 32 million cases, 310,000 hospitalizations, and 18,000 deaths from the flu this season. A death rate of .0005. (one 20th of one percent).

There is no question that the COVID 19 dashboard also has shortcomings. Most notably, it can only present the data we have available and as has been widely reported in the news, the US government has barely been testing anyone. So the number of cases in the US is not accurate and everyone knows it.

For those interested in pathogen tracing, check out Nextstrain.

Nextstrain, an open-source project tracking pathogen genome data, does a better job of tracking how the virus travels, but does not do as well in presenting the number of cases, their current status, and fatalities.

NextStrain tracking of the evolution of the virus

I am sure this is interesting to epidemiologists. I am not sure what it telling us though.

For those that think we should give our governments or the CDC a pass because data work is hard. Check out this website put up by a high school student in Mercer Island, WA (by Seattle).