# The concept

When comparing trends in large chunks of data, it’s easy to arrive at the wrong conclusions when you don’t understand the underlying data in full context. When a segment makes up a bigger piece of the pie in one group vs. another, that segment can over-influence the aggregate results. If you are unaware of this over-influence, you could make the wrong decision for your business.

# The example

Let’s say you are deciding on two types of advertising for a nationwide promotion coming up. To aid in your decision, you run each ad in test city and monitor performance for 5 days.

After the 5 days are over, you put together a basic data table by day and by city, to compare conversion rates:

Day City A visits City A conversion City B visits City B conversion City A vs City B
1 50 10.00% 60 9.50% +5.3%
2 75 10.00% 90 9.50% +5.3%
3 (holiday) 200 5.00% 150 4.75% +5.3%
4 75 10.00% 90 9.50% +5.3%
5 75 10.00% 90 9.50% +5.3%
————– —————— ——————– —————— ——————– ———————
Totals 475 7.89 % 90 8.02% -1.5%

You notice that when you compare the totals for each city, that city A has a 1.5% lower conversion rate than city B, but when you review the performance by day, city A wins by 5.3% every single day. So which city had the better results and which ad should you choose?

# The math

If you look at the visits by day, you can see that on day 3, city A had 200 visits, which represents 42% of the total visits for city A in the 5 days. City B had 150 visits on that day, which represents 31% of the total visits. So even though both cities had much lower conversion than normal on day 3, and city A had a 5.3% higher conversion that city B, the impact of that bad day on city A’s totals was much higher than on city B’s totals because the bad day was over-represented in city A relative to city B.

If you had chosen the ad that ran in city B because of the overall better performance, you potentially would have given up the 5.3% additional orders you would have gained had you chosen city A.

# Conclusion

Make sure to dig a bit deeper and review your data across a few different (and relevant) segments, to ensure there aren’t inherent biases in the data driven by differences in mix. It can make a substantial difference in your outcomes and prevent big surprises down the line.

# The concept

The payback interval is the amount of time it takes to break even on a given marketing investment. When managing cash in a startup or other early-stage business, the time value of money plays an especially important role, given the level of operating risk under which most young businesses operate. This can be especially true with regards to paid marketing. The faster that the money you spend turns into new customers and new orders, the faster you can redeploy that money into more marketing and thus more growth. Marketing spend that takes less time to pay back the initial investment can have a significant positive effect on the business, even though the total return may be lower per investment.

# The example

Let’s say it’s January, and you are deciding between spending \$1000 on search advertising or social network advertising, for a business with 50% profit margin per order. After running some experiments, you are able to product the below table:

Month Search Revenue Cumulative Search Revenue Cumulative Search Profit Social Revenue Cumulative Social Revenue Cumulative Social Profit
Jan 1000 1000 500 100 100 50
Feb 600 1600 800 100 200 100
Mar 400 2000 1000 200 400 200
Apr 200 2200 1100 200 600 300
May 200 2400 1200 400 1000 500
Jun 200 2600 1300 400 1400 700
Jul 100 2700 1350 800 2200 1100
Aug 100 2800 1400 1000 3200 1600
Sep 100 2900 1450 600 3800 1900
Oct 100 3000 1500 200 4000 2000
Nov 100 3100 1550 100 4100 2050
Dec 100 3200 1600 100 4200 2100

As you can see, you got \$2100 back in Social (\$1100 net of \$1000 investment) after a year and only \$1600 (\$600 net) in Search, a difference of 31% (83%). But you achieved profitability in Search by March and in Social by July, less than half the time.

# The math

Let’s put together a table of cumulative profit for each ad type, net of the \$1000 initial investment. Let’s also add some columns for reinvested \$1000 investments, that you can only make when you get your initial \$1000 back from the prior investment.

Here is the cumulative profit table for Search:

Month 1st investment 2nd investment 3rd investment 4th investment 5th investment 6th investment
Jan (\$500)
Feb (\$200)
Mar \$0 (\$500)
Apr \$100 (\$200)
May \$200 \$0 (\$500)
Jun \$300 \$100 (\$200)
Jul \$350 \$200 \$0 (\$500)
Aug \$400 \$300 \$100 (\$200)
Sep \$450 \$350 \$200 \$0 (\$500)
Oct \$500 \$400 \$300 \$100 (\$200)
Nov \$550 \$450 \$350 \$200 \$0 (\$500)
Dec \$600 \$500 \$400 \$300 \$100 (\$200)

Here is the cumulative profit table for Social:

Month 1st investment 2nd investment
Jan (\$950)
Feb (\$900)
Mar (\$800)
Apr (\$700)
May (\$500)
Jun (\$300)
Jul \$100 (\$950)
Aug \$600 (\$900)
Sep \$900 (\$800)
Oct \$1,000 (\$700)
Nov \$1,050 (\$500)
Dec \$1,100 (\$300)

As you can see, because the payback interval for Search is so much faster than the interval for Social, you are able to reinvest so many more times (6 vs. 2 over the course of a year). As a result, the cumulative return by December for Search is more than double that of Social (\$1700 vs. \$800), despite Social’s superior cumulative return per investment (\$1100 vs. \$600).

# Conclusion

Shorter payback intervals allow you to grow your business at an accelerated rate relative to longer intervals. The earlier the business is in its life cycle, the more impactful the acceleration. For mature businesses with cash reserves, there is some benefit to diversifying into greater returns, but for most young businesses, payback is key.

# Product management

How A/B Testing at LinkedIn, Wealthfront and eBay Made Me a Better Manager interview with Elliot Shmukler
// A good synopsis of why testing of low-consequence decisions (Type 2) has a great cultural impact through enablement of learning and encouragement of diverse approaches to product management.

The brilliant mechanics of Pokémon Go by Matthew Lynley
// Very sticky and viral product driven by a great combination of variable rewards system, requirements to keep the game open, and unique gameplay driven by ever-changing environments produced by the users themselves.

Complexion Reduction: A New Trend In Mobile Design by Michael Horton
// Mobile design continues to simplify over time. This may be driven by the highly functional and specific usage of apps on mobile relative to desktop.

# Business and Strategy

DOLLAR SHAVE CLUB AND THE DISRUPTION OF EVERYTHING by Ben Thompson
// Gillette’s multiplicative advantage of innovation X awareness X distribution eroded as innovation yielded increasingly diminishing marginal returns and as the costs of awareness and distribution declined enough to allow smaller businesses like DSC to compete. As far as the acquisition price is concerned, ‘but \$1 billion for a 16% unit share of a market dominated by a brand that cost \$57 billion is startlingly small’.

Dollar Shave Club: How Michael Dubin Created A Massively Successful Company and Re-Defined CPG by David Pakman
// The winning formula = (Price X Convenience)^Brand. Also interesting is Venrock’s thesis to ‘choose categories where incumbents only sell through retailers and have no direct relationship with their actual customers’

Medium lands biggest website yet by Tom Kludt
// Medium’s approach to publishing is a significant departure from that of Facebook, Google, and Amazon in that the company has positioned itself as a network for publishers rather than a publishing platform. This is reflected in Medium’s intent to enable publishers to derive value from allowing content to be hosted on the site.

# Perspectives

The hedgehog and the fox
// The latest era of the hedgehog may be waning given the sheer number of technologies that have matured in recent times

Were There Aliens Before Us?
// As we gain greater certainty around more variables in the Drake equation, it becomes increasingly likely (almost guaranteed) that an advanced civilization has existed in the universe at some point in the universe’s history.

# The concept

When a key metric changes, there’s often a clear driver that impacted all users or customers. Your checkout process is broken, you launched a special sale, you kicked off a loyalty program, and so on. But sometimes there isn’t an obvious reason, and and a deeper understanding of underlying marketing channels (or other user segments) is required. This allows you to determine whether the cause is missed performance in a given segment, or a change in size of a segment relative to other segments. The latter example is mix shift, and it can meaningfully impact if it persists.

# The example

Let’s say your conversion rate in the latest week dropped from 5.05% the week before to 4.90%, and you want to know what caused the drop. You decide to start looking at the behavior of traffic coming through each of your 3 marketing channels.

So you put together a basic data table with traffic and conversion by each channel, and the totals:

Channel Last week visits Last week’s conversion This week visits This week’s conversion
Search 30 2.00% 50 1.90%
Email 100 6.00% 110 6.20%
Direct 70 5.00% 75 5.00%
All channels 200 5.05% 235 4.90%

# The math

First things first, let’s break do some quick math to make the data more usable:

Channel Last week share This week share Change in share Change in conversion Last week conversion diff from avg.
(channel / all channels) (channel / all channels) (This week share - Last week share) (This week conversion - last week conversion) (channel - all channels)
Search 15% 21% 6.3% -0.10% -3.05%
Email 50% 47% -3.2% 0.20% 0.95%
Direct 35% 32% -3.1% 0.00% -0.05%
All channels 100% 100% 0.0% -0.15%

The formulas used to calculate each field are right below each column header in the table above. Here are the steps we went through:

• Translate ‘visits’ to ‘share’, in order to make traffic apples-to-apples from one week to the next
• Calculate ‘change in share’ to understand how each channel changed in size relative to other channels
• Calculate the ‘Last week conversion diff from avg.’ to understand whether a channel improves or hurts conversion when its share increases

Now, to understand the different effects:

Channel Intra-channel Mix shift Interaction All effects
(Last week share) X (Change in conversion) (Last week conversion diff vs avg) X (Change in share) (Change in share) X (Change in conversion)
Search -0.02% -0.19% -0.01% -0.21%
Email 0.10% -0.03% -0.01% 0.06%
Direct 0.00% 0.00% 0.00% 0.00%
All channels 0.09% -0.22% -0.01% -0.15%
• Intra-channel represents the portion of the change in conversion due to changes within a channel. In this case, Email generated a positive effect of 0.1% because its conversion increased from 6% to 6.2%
• Mix shift represents the portion of the change due to changes in the relative size of a channel. In this case, Search generated a negative effect of -0.19% because its share increased from 15% to 21% of the total traffic.
• Interaction represents a second order effect caused by a combination of mix and intra-channel. It’s the least actionable effect, but it’s also usually much smaller than the other effects

As you can see, there are many effects taking place that impacted the drop in conversion 0.15 percentage points down to 4.90%, but the Search channel Mix effect stands out as the largest. Search, which has a much lower conversion than other channels, increased meaningfully from 15% to 21%. If this channel remains elevated, you’ll need to ensure that the underlying assumptions and economics account for this change lest it hurts overall profitability.

# Conclusion

Depending on how you look at it, mix shift can explain the large majority of changes in key metrics. Even special sales and loyalty programs represents segments that change the overall numbers when increasing or decreasing in size. Locating the mix shift and understanding why it happened is key to ensuring that your numbers don’t run askew and that your business stays healthy in the long run.

# Diseconomies of paid marketing

Digital marketing generally will create more sales, especially given the distribution capabilities of today’s leading ad platforms, but marketing spend is rarely frictionless. The cost to acquire more of a given population increases faster than sales because the quality of the additional traffic tends to decline, but this doesn’t necessarily mean you should stop spending.

# Simple example

Say that you run a company that sells widgets, with a product margin of \$10 per widget. You have recently been spending money on an ad platform called Poople, obtaining new widget orders at a cost of \$5 per order. You are acquiring about 1000 orders per month through Poople, and now have the opportunity to increase your spend to acquire 1100 orders per month. To do this, you have calculated that your cost will now come out to \$6 per order. Do you spend the money and increase sales at the increased cost?

# Framing the problem

It helps to think of this decision in terms of marginal costs and profit. As far as you know, every additional widget sold will earn you \$10, so your marginal profit is flat. You’ve now calculated that your additional cost per acquired order on Poople will increase from \$5 to \$6. So the question is whether the additional cost of the additional orders is lower than the additional margins from those additional orders (which you already know is \$10).

# The math

Once you’ve framed the problem, the math is fairly straightforward:

Marginal product margin = \$10 / widget order
Marginal cost from marketing spend increase
= (\$6 x 1100 - \$5 x 1000)/(1100-1000)
= (\$6600-\$5000)/(1100-1000)
= (\$1600)/(100)
= \$16 / widget order

In this case, the marginal cost is higher than the marginal product margin. So each additional order is actually unprofitable, and it’s not worth the growth unless you are getting \$6 worth of additional value from those orders outside of what the customers are paying.

Let’s say you would have been able to achieve 1200 orders after the added spend instead of 1100. In this case the marginal cost ends up being \$8, meaning you’d continue making money on the additional widgets. At \$8, the profit is less per widget than you make on the baseline 1000 orders, but it’s still a positive return, which makes the growth worth it.

# Conclusion

Make sure to understand and pay attention to marginal costs (and marginal gains) when deciding whether to increase marketing spend. Also, different ad platforms have different pricing models (CPC, CPM, etc.), so make sure to have the data to effectively translate that pricing into marginal costs.

# CAC defined

Customer acquisition cost represents how many marketing dollars it costs to get customers to buy your product for the first time. The basic CAC calculation is [Total Marketing Spend]/[Total New Customers].

# Why is it useful?

The lower your CAC is relative to the total amount a customer spends with you over their lifetime (LTV), the better. It means you can potentially increase marketing spend in order to grow and scale your business. If your CAC is relatively high, it likely means you need more optimization around your marketing or that your business needs to depend more heavily on organic marketing (word of mouth, social, SEO)

# Diving deeper

Given that CAC is a cost, it’s especially important to understand it in more detail. It’s easy to waste marketing dollars, especially in digital marketing, where more spend almost always seems to mean more customers.
Some additional analysis worth knowing:

• CAC by marketing channel
• Components comprising CAC (cost of traffic, conversion rate, new customer %)
• CAC of the marginal or incremental customer if you increase marketing spend
• Impact of the sales cycle on CAC (it can go down over time with long sales cycles)
• Percentage of marketing spend that is driving repeat customers

# Conclusion

For any company that expands through paid marketing channels, it’s imperative to understand CAC and how it evolves as those channels mature over the business’ lifecycle.

If you are planning on raising capital for your business, make sure to know it across all meaningful dimensions. Most investors will assume some portion of the raised funds (especially mid-to-late stages) will be dedicated to marketing. They’ll want to know the funds will be deployed prudently, and knowing CAC is a basic requirement for that.

# AOV defined

Average order value is intended to represent the dollar amount of your average customer’s payment. At its simplest, AOV is represented as [Total Sales] / [Total Orders]. So if you made \$1000 in total sales in a month on 100 orders, your AOV would be \$10 for that month.

# Why is it useful?

AOV can be useful for a variety of reasons, a few of which are:

• Understanding what your typical customer expects to spend with your business, which informs:
• Insight into whether your pricing is appropriates
• Understand how customers from different channels differ in their spending habits
• Calculate the profit you make per order, which in turn informs:
• How much you should be willing to pay to acquire an order through marketing
• How much you can offer in discounts without being unprofitable

# Diving deeper

After getting comfortable with the basics, there is a ton of additional analysis that you can perform on AOV in order to better understand your customers and your business.

• Different components of AOV (product price and quantity, shipping costs, taxes)
• Changes in AOV (effects of seasonality, product mix, pricing, loyalty programs)
• Relationship between AOV and conversion rates (usually caused by pricing, but not exclusivelys)
• Behavioral differences between high-AOV customers and low-AOV customers
• Comparing AOV to Median Order Value, to understand how much AOV is skewed by high (or low) spending customers

# Conclusion

AOV is a fairly important metric, especially in early-stage ecommerce businesses. Investors will almost always ask for it given both its applications and implications. When high-level sales or usage metrics change, it’s often a key element in helping teams find the root cause.

# Outsource startup stock option plans

## Productivity vs. dilution

In theory, startup options can make sense for employees given the risk / reward tradeoffs, but the choice is much less simple when accounting for structural elements in option grant fine print. For example, employees typically have 90 or less days to exercise vested shares when they leave the company. This can represent a huge cost for most employees in exchange for no immediate cash gain (unless the startup happens to be in the process of completing a liquidity event).

Some companies have begun to opt into providing significantly longer post-termination exercise periods, but this has implications as well for employees who chose not to leave the company (and future employees), in the form of a gradually increasing dilution of the equity pool.

In an environment where more companies are opting to forego exiting (given ease of raising private money, being profitable but unwilling to deal with public markets, or a host of other reasons), decisions around the structure of an option plan can have big implications. Either unengaged / unqualified employees choose to stick around for a long time if the plan is too strict, or they create a massive dilutive liability if the plan is too lax.

## Focus vs. Education

Most startups won’t be profitable at the time an option plan is devised, meaning the founders / executives have bigger fish to fry than to build a complex customizabe option plan that works for every employee. Building a business, hiring, finding a market, and creating a great product represent work that already takes a great deal of time and sacrifice, so even with the best intentions in mind, founders are unlikely to focus on this problem.

Many startup employees don’t know enough about equity compensation (especially stock options) to ask for the provisions which would best fit their individual situation, or to prepare for a given outcome (such as how to pay for vested shares when exiting the company). Perversely, there is a disincentive for founders to help educate employees, as this could reduce the company’s future optionality in the form of fundraising, future hires, the founders’ own compensation, etc. Even if employees were educated on these things, it’s unlikely that the company would customize the offer for any but the most senior employees.

So there isn’t time to build the perfectly complex plan, and there isn’t enough education to ensure employees make the best decisions for themselves.

## Outsourced management

With a few inputs from a startup’s management, would it be possible for an outsourced manager to create more custom plans for employees?

From the employer:

• Share of equity pool allocated to ESOP
• General comp bands by position
• Value of current common shares
• Known cash risks for the business
• Liquidity event likelihood
• Employee base and hiring rate

From the employee:

• Known and expected personal liquidity risks
• Financial risk tolerance
• Employment lifestage and flight risk
• Business’ performance expectations

Over time could the outsourced manager scalably educate employees and manage custom option plans, from offer through to exercise (including during employee termination)?

Could more commodity management and financial products be offered to employees over time as the outsourced manager scaled?

Ego is a mofo…

# ‘What Really Goes On’

One of my favorite Phife Dog rhymes is “Ego/I’m on my own jock skill/Cuz if I don’t say I’m the best/Tell me who the hell will”.

Founding teams are filled with egos. You probably already know that. Because you’re fucking awesome and know everything about everything. We all do. Ego is why an entrepreneur thinks their idea is a winner. Ego is why an entrepreneur runs through walls when others give up. Ego is why an entrepreneur risks it for the biscuit.

(You already know where I’m going with this)

Ego is also a huge source of conflict. Building anything requires communication and compromise. Ego prevents both.

If I’m right and you say the same thing as me, but you get the credit, what’s my reaction? Ego says “f- that guy!”. Ego strength, on the other hand, says “I’m happy someone I respect agrees. I must be on the right path.”

If I have an idea of how to reach a goal, and you have a different idea of how to reach a goal, what’s my reaction? Ego says “f- that guy!”. Ego strength says “I respect your process, and since you’re leading the effort, I trust you.”

# ‘Keep It Movin’

Our product leads are hyper talented. They know the subject matter, they know the technology, and they have a clear vision of where we need to be. I trust them explicitly to get us where we need to be. That’s why they own product.

Last week, ego and ego strength collided. During a discussion about our product with the product team, I wasn’t happy with the speed with which we were progressing. As a CSPO and terrible amateur product manager, I had envisioned a very specific process. This was not the process the product team was using in this specific conversation, and I didn’t think that was right.

Ego reared its infinitely ugly head, and I lashed out. I wanted them to follow my process, the scrum product owner process, moving forward. “We will not build our product on a shitty foundation. How the hell are we going to attract the engineering talent we need without properly written epics? It’s critical that we use my process, the approved process, the common process, the correct process from the beginning.”

Instead of reacting to my idiocy, one of our product leads stopped my rant and explained what he was actually doing. He walked me through his approach, and assured me that the deliverables would be what I expected. By simply acknowledging my concerns and explaining his approach, he mitigated my anxiety and reinforced his competency.

Ego strength won.

Matt

Post-script:

1. I swear no more Tribe references (for now).
2. Company and product will be revealed soon. Patience is a virtue.

# Product management

THE FIRST RULE OF PRIORITIZATION: NO SNACKING by Des Traynor
// The ability to find and prioritize low-effort-high-impact work diminishes as organizations mature. Many organizations tend to shift into prioritizing low-effort-low-impact work as a result, which rarely creates long-term value. Focus on high-effort-high-impact work, since this is where the value lies.

Why Amazon’s Echo is better to talk to than Siri by Chris Smith
// The Echo team is completely focused on building a great voice-only in-home assistant, allowing them not to have to worry about or prioritize mobility, UI, or a slew of other things that the Apple / Siri team has to consider. As a result, they’ve produced a great always-on, high responsive product with a great user experience.

# Data and Tech

How bot-to-bot could soon replace APIs by Niko Nelissen
// Interesting hypothesis that bots (bot-to-bot and bot-to-bot-to-consumer), could be the next evolution from APIs. This would be heavily dependent on the advancement of technologies that this evolution would rely on of course (NLP, ML, AI, etc.)

Facebook’s DeepText has “near-human” understanding of people’s posts by Tim Peterson
// Accelerating the evolution of NLP by eschewing traditional methods in favor of a character-based method, which uses massive swaths of available data to learn from observed relationships between characters, context, and sentiment.

# Business and Strategy

The inside story of Facebook’s biggest setback by Rahul Bhatia
// Many things went wrong here. One big lesson is to spend effort learning about your customers and their problems rather than imposing your solution on your perception of their problems.

Spotify’s Financial Results Reinforce Just How Broken the Music Business Is by Mathew Ingram
// Despite rampant growth and engagement, Spotify’s costs-to-serve may be too high for the company to reach profitability into the future. ‘Of every dollar that Spotify brings in the door in revenues, about 85 cents goes right back out the door again in the form of payments to the music industry.’

The Curse of Culture by Ben Thompson
// Couple notable quotes:
‘As with most such things, culture is one of a company’s most powerful assets right until it isn’t: the same underlying assumptions that permit an organization to scale massively constrain the ability of that same organization to change direction. More distressingly, culture prevents organizations from even knowing they need to do so.’ ‘Leadership is now the ability to step outside the culture that created the leader and to start evolutionary change processes that are more adaptive. This ability to perceive the limitations of one’s own culture and to evolve the culture adaptively is the essence and ultimate challenge of leadership.’

# Hard to Earn

#### by Matt Johnson

SO, I’m founding a start-up. Well, technically I’m founding a start-up with a team of talented contributors. We’re going to conquer the world by using [technology] to deliver [adjective] outcomes for [customer segment] in [industry]. It’s going to be amazing!

# ‘Intro (The First Step)’

You know what’s awesome about start-ups? Everyone genuinely wants to get involved with your company in some way, and everyone has an opinion on how to build it. “Focus on these customers.” “Don’t forget to do X,Y,Z.” “Beware of these pitfalls.” Etc. etc. etc.

Here’s the thing, though: All of that guidance and opinions and parables and bullshit out there starts once you’ve actually founded the company. You can find resources on product development, finding customers, raising money, blah, blah, blah. Very few people talk about how to get to the starting line. The “holy shit, we’re going to start a real company with real responsibilities!” starting line.

Where are the mentors who want to help you incorporate? Who want to help you pick your founders? Who want to help you build your board, without requiring a seat? Who love employer ID numbers, and taxes, and choosing the correct fucking insurance? No one eagerly steps up to help with the hard, boring, unsexy, soul-crushing, yet absolutely critical, decisions required to get started. Unless they want a piece of the company.

How many companies fail at this stage? Is this the plight of the COO? What challenges are next? Does any of it really matter?

# ‘ALONGWAYTOGO’

Bitching aside, our technology can win (I’ve been told start-up rule #2 is ‘Always believe’). I really, truly, believe that (see previous sentence). Can our team win? Let’s find out…

Matt

Post-script:

1. I hope to post with some regular cadence, but no guarantees. Sorry.
2. I know how to use Google. Please do not send me anything from the first 2 pages of search results to ‘help out’. I respect your effort, so save those links for a more appropriate time when I’m ready to digest your guidance fully. I promise you’ll have that opportunity.
3. I’ll reveal our product soon.
4. I know founders and start-up blogs are played out like your mom’s haircut. Or two-tone down goose. Also, you couldn’t converse if you had fucking React Juice (R.I.P. Diggy, s/o Grandmama).
5. I know I can be a know-it-all. It’s on my self-improvement list.
6. Yes, those are rap-nerd easter eggs.

# Anonymous content platform

## Whistleblower content

Currently, whistleblowers can rely on platforms which use anonymising networks to allow submission of sensitive information (the leaked content cannot easily be traced back to the content provider). In order to use the network, the whistleblower needs to download software (i.e. browser) and access services, so some basic technical skill is required, and UX is not well-evolved.

UX issues aside, once the information has been submitted, it needs to be distributed. For whistleblowers, platforms exist which allow for distribution of anonymously leaked content.

## Gawker-type content

Gawker is a highly publicized and well-read gossip publication currently being sued by multiple plaintiffs, related to published articles associated with the plaintiffs. A recent lawsuit in particular, by Hulk Hogan, has gained notoriety due to Hogan’s financial backing by Peter Thiel and Thiel’s potential motive for revenge. The costs of defending the suit may put Gawker at risk of insolvency.

## Anonymous platform?

Although there are options for whistleblowers, do similar widely-used options exist for anonymous submission and distribution of ‘less serious’ content? For example an anonymous content platform for news, rumors, anonymous memoirs, etc.?

Since these ‘less serious’ users may intend to produce content with the purpose of receiving payment, could payment mechanisms be created such that these users could be paid immediately and near-anonymously based on pre-existing terms (i.e. number of views, clicks, etc.)?

Could a better user experience be created for the providers, which allows for management of submission, distribution, and incoming payments?

Would a front-end need to exist, or could existing distribution platforms be leveraged once the content had been anonymously ingested?

## Technologies

Tor – Tor / Onion Services allows for the near-anonymous submission of content, such that the content provider has limited vulnerability with regards to being identified

Ethereum – Ethereum is a blockchain platform that enables execution of smart contracts using ether, a cryptocurrency.

# Data and Tech

Ethereum is the Forefront of Digital Currency by Fred Ehrsam
// Bitcoin proved the concepts behind blockchain and decentralized transactional networks, but Ethereum may be a better path forward.

Accelerated Mobile Pages Project
// One of the ways Google aims to circumvent Facebook and Apple’s app ecosystem. Mobile-optimized, for high speed and exploration.

# Strategy and business

Google’s Go-To Market Gap by Ben Thompson
// Hypothesis is that Google is the rare company that succeeded (immensely) almost purely from having superior technology, rather than business development, operational execution, marketing, product strategy, etc. Moving forward, this may present challenges to the company’s ability to compete with superior businesses, in spite of better tech.

A clever tweak to how apples are sold is making everyone eat more of them by Roberto A Ferdman
// Selling apples pre-sliced had a massive impact on fresh apple consumption. By pre-slicing, children were much more willing to eat apples for lunch, as this reduced seemingly miniscule challenges to eating apples.

The Leading Predictor Of Series A Valuation For SaaS Companies by Tomasz Tunguz
// ‘The data underscores why building a great product is the first order of business for a startup and why developing great customer success should be the second order of business. Many founders do this instinctively, and develop a cadre of reference customers.’

# Perspectives

This cartoon explains how the rich got rich and the poor got poor by Alvin Chang
// Strong hypothesis that wealth inequality is influenced by source of income (investment for upper classes, paychecks for lower classes), and regulatory impacts (i.e. tax policy) on those income sources.

Are You Successful? If So, You’ve Already Won the Lottery by Robert H Frank
// Grit, effort, and ingenuity are rarely undervalued when assigning credit for success, but humans tend to grossly underestimate the impact of luck. Reflecting on one’s good fortune tends to generate a greater willingness to contribute to others’ success.

The Evolution of Anxiety: Why We Worry and What to Do About It by James Clear
// Although humans have evolved for a Immediate Return Environment, most of us must operate within a Delayed Return Environment, which in turn generates anxiety. Converting anxiety-induxing long-term issues into measurable (and smaller) tasks can significantly alleviate anxiety.

Mongol hordes gave up on conquering Europe due to wet weather by Conor Gearin
// Mongol hordes, which innovated upon war through the integration of cavalry, may have retreated from central Europe primarily because of a swamp-like environment in Hungary in the mid 1200s. Because the army was unable to provide pasture for horses in Hungary, much of the disruptive advantage they had come to rely upon disappeared. Not dissimilar to Napoleon’s army in wintertime Russia.

# Strategy and business

What is Product Management by Mokriya
// Some perspectives on the function and its future.

# Data and Tech

What 671 million push notifications say about how people spend their day by Andrew Chen
// Lots of interesting takeaways here. Amazing how tight the spread between sends and opens are. And although not surprising, it’s also cool to see how much greater work-time usage exists for mobile apps vs. other media.

The Sumo Matchup Centuries In The Making by Benjamin Morris
// Amazing how much data has been collected on sumo matches over centuries…

With Instant Apps, Google Aims to Make the Web and Apps One by Cade Metz
// Google has clear incentive to work around the existing app (and app marketplace) model by blurring the line between web and apps, through either greatly improving the mobile web experience, or making apps more like the web.

Soon We Won’t Program Computers. We’ll Train Them Like Dogs by Jason Tanz
// Machine learning makes it significantly more difficult to understand the EXACT mechanics behind how computers produce output and make decisions.

# Perspectives

The Real Problem With Facebook and the News – Stratechery by Ben Thompson
// Shared facts and different perspectives could be an improvement over self-curated echo chambers.

The New 10-Year Vesting Schedule by Zach Holman
// Startup employees are finding it increasingly difficult to unlock compensation (in the form of stock options) generated by their by their contributions.

The numbers are staggering: US is ‘world leader’ in child poverty by Paul Buchheit
// The share of kids on foods stamps in the US has increased by over 60% in the last decade.

The Secret Shame of Middle-Class Americans by Neal Gabler
// A lot more people are struggling financially than it would seem, possibly driven by the democratization of revolving credit in the 80s and 90s, as well as income stagnation across many industries.

# Crowdsuing platform

## Class action / challenges

Litigation may be fairly easy in modern times (especially for people with the funds to sue), but there are still meaningful challenges for individuals suing large organizations, especially in cases where these individuals are dependent on said large organizations (for examples, employees of large and influential businesses).

Class action lawsuits tend to make it significantly easier for people to sue businesses for similar or shared greivances. Upfront costs are reduced, plaintiffs can be represented without being directly involved in the suit, and legal representation can be consolidated across plaintiffs. That being said, there are still challenges in these types of suits. They need to be certified by a judge, the suits require named plaintiffs to step up and start the suit, it’s difficult to select the best legal representation, lawyers are incentivized to settle, and so on.

## Certification required

(1) the class is so numerous that joinder of all members is impracticable;

(2) there are questions of law or fact common to the class;

(3) the claims or defenses of the representative parties are typical of the claims or defenses of the class;

(4) the representative parties will fairly and adequately protect the interests of the class.

## Crowdsuing platform?

Can a platform enable and ensure certification for class action suits?

Can a lawsuit be de-risked by enabling better selection (competition) of legal representation and coordination by named plaintiffs?

Can potential named plaintiffs gain confidence through knowledge of additional willing named plaintiffs?

# Employee ESO Insurance

## Employees and risk

Early stage employees (usually among 1st 40 hires, or joined before the company is unit positive) tend to take on significant time and salary risk when joining startups.

Some of this risk is compensated for by the opportunity to grow and generate impact at rates that these employees wouldn’t have been able to achieve in more mature businesses. Some of it is through the building of strong relationships forged through fire drills, all-nighters, and solving impossible problems. And lastly, some of it is compensated by vested equity.

Much of the value from the first couple of aforementioned trade-offs are dependent on the employees’ own effort and focus. For the third, the equity, a lot is out of the their control, especially when it comes to fundraising.

## Impact of raising capital

When companies choose to take on funding, they do so for a variety of reasons (staying afloat, working capital, new opportunities, fundraising climate, etc.), but they rarely consult or involve employees other than executives.

Yet the impacts of raising more money can have significant impact on one of the major reasons that employee give up time, salary, and oftentimes mental well-being to work at the company.

General dilution, preference, protection, increased cash burn, etc. are all ways that an employee’s equity stake can be significantly impacted. Aside from dilution, employees tend to be very inexperienced with most of the other ways that raising money can impact their common equity value.

## Stock option insurance?

Is there a way to allow early employees to protect themselves by purchasing some form of insurance on the value of their vested shares?

Could the insurance provider price the offering well enough to both mimize counterparty risk and benefit employees?

Is it possible that breakage (from unclaimed insurance or canceled policies) could effectively stand in for a counterparty?

# Weekly reads, week of January 25 2016

Misused mobile UX patterns by Zoltan Kollin

• ‘Experiments show, however, that exposing menu options in a more visible way increases engagement, user satisfaction and even revenue’
• ‘Basic functionality can be effectively represented by icons but for complex features, text labels should be used. (And if you use icons, always have them usability tested.)’
• Onboarding: Promotes progressive onboarding over overlays, because users tend to skip intros and tutorials. Empty state / blank slate needs to be simple and intuitive. Potentially have less options than once the page starts populating
• More companies are moving towards combining intuitive text with icons for the mobile experience → http://thomasbyttebier.be/blog/the-best-icon-is-a-text-label

The First 15 Seconds by Scott Belsky

• ‘An effective hook appeals to short term interests (one’s laziness, vanity, and self-interests) that are connected to a long term promise.’
• ‘As you build your product or service, bifurcate your approach […] initially, your prospective customers are lazy, vain, and selfish.Optimize for the first 15 seconds as a compartmentalized project. And then, for the customers that survive the first 15 seconds and actually come through the door, build a meaningful experience and relationship that lasts a lifetime’

The Sunk Cost Fallacy by David McRaney

• ‘Your decisions are tainted by the emotional investments you accumulate, and the more you invest in something the harder it becomes to abandon it’
• ‘When offered a chance to accept or reject a gamble, most people refuse to make take a bet unless the possible payoff is around double the potential loss’
• ‘This is the powerful force behind Farmville. Playing Farmville is a commitment to a virtual life form. Your neglect has consequences. If you don’t return, your investments die and you will feel like you wasted your time, money and effort. You must return, sometimes days later, to reap the reward of the time and virtual money you are spending now. If you don’t, not only do you not get rewarded, you lose your investments’

How Facebook Squashed Twitter by Ben Thompson
The idea of a “smartphone” that could connect to the Internet and run applications was around long before 2007; Apple…stratechery.com

• ‘as of 2009, not only was it easier to get started with Facebook, but it was also more likely that the service had enough interesting content to ensure most users had no desire to look for something better’
• ‘When it comes to “the empty spaces” most people don’t want to do work, but work is exactly what Twitter required. You had to know what you were interested in, know who to follow based on those interests, and then, to top it all off, you had to pick out the parts that you were interested in from a stream of unfiltered tweets; Facebook, in contrast, did the work for you’

Before Growth by Sam Altman

• ‘“do any users love our product so much they spontaneously tell other people to use it?”’

What’s your startup’s superpower? by Satya Patel

• ‘Google is best in the world at search. Facebook is best in the world at building a social network. Apple is best in the world at building integrated software and hardware for consumers. All of those markets are or were incredibly crowded’
• ‘Google knew that to be best in search in needed the best data infrastructure. Facebook knew that if it wanted the largest social network it needed a competency around growth of that network. And Apple knew that if it wanted to build devices for the average consumer, it needed simple and beautiful design’
• ‘Once you answer that question, you can focus on the development of that superpower rather than on things that make you temporarily different or different in a way that is easy to replicate’
• ‘They talk about reducing “cognitive overhead” and “friction” that discourages readers from signing up for e-mail newsletters. Bezos calls ideas that could upset Post subscribers, like jamming too many ads on a Web page, “reader hostile.”’
• ‘Bezos requires Post executives to write lengthy memos outlining their projects instead of using PowerPoint presentations, believing that narrative writing forces people to think more deeply’
• ‘Inside the new newsroom in Washington […] a large screen displays real-time traffic statistics of stories on its website. […] Bezos suggested measuring whether readers prefer the Post to its rivals. So engineers created a program that takes articles from [competitors], strips out their branding, then surveys readers on which articles they’d rather read’

Stack fallacy — Common cause of big companies missing out by Anshu Sharma

The fault in our startups by Haresh Chawla

# Weekly reads, week of January 18 2016

The FANG Playbook by Ben Thompson

• Each of the FANG companies was technically innovative in their own way […] but each of them […]depended to an incredible degree on products and infrastructure that already existed
• ‘By owning the consumer entry point — the primary choke point — […] the FANG companies have been able to modularize and commoditize their suppliers’
• ‘they are “aggregators” who start with the best customers and don’t really compete with incumbent companies, at least in the beginning. In fact, incumbents nearly universally benefit from the presence of aggregators, at least at first’

Nobody Wants To Use Your Product by Goran Peuc

• ‘People are not really into using products. Any time spent by a user operating an interface, twisting knobs, pulling levers or tapping buttons is time wasted. Rather, people are more interested in the end result and in obtaining that result in the quickest, least intrusive and most efficient manner possible’
• ‘When you think about it, do you really want to work on heating up your food, or do you just want your food to be hot? This is why microwave ovens can be found in basically every modern kitchen; it removes as much work as possible from the process of heating food. Of course, quite a lot of manufacturers still do not realize this and make their microwave ovens overly complicated with too many buttons and settings.’
• ‘This difference in approach — building for features versus building for result — can be seen in numerous products today, both digital and physical. The main reason why some products are great is that they take the load off of users and assist them in making decisions.’
• Lots of great examples: Nest, Dropbox, Google search, Gov.uk, Amazon Dash, Apple updates vs. Adobe Flash updates, etc.

The Power Of Focus by Greg Satell

• IBM’s modern-day roots began as a function of refocusing. This cultural trait served IBM well when facing more innovative competition, by relying on superior execution. 100 years later today, IBM is a longtime regular on S&P 500, in an age where the avg S&P lifespan is 10 years.
• Mission drives strategy - ‘The truth is that your mission needs to drive your strategy, not the other way around. Genuine excellence requires passion, commitment and consistency. You can’t create that in a boardroom meeting or a strategy session. It takes focus over an extended period of time.’
• ‘To be a great performer — in any field — you simply have to do things better. That takes work. You need continually up your game over a period of years — or even decades — in order to get it right. That takes focus.’
• ‘Amazon makes the customer its top priority, aiming to create an experience so magical “… it disappears into our customer’s every day as their new normal.”’
• Article stated takeaways: ‘Treat the customer as an individual, not a segment. Invest in earning trust, and never take it for granted. Think about making magic, more than making money.’
• ‘We always work backwards from the experience we believe an individual customer might appreciate, before we develop anything.’
• ‘I don’t formally “lead” the customer experience efforts, except in the same way as everyone in the company leads customer experience — it’s part of everyone’s job, every day.’

The Secret to Successful Customer Onboarding by Lincoln Murphy

• Onboarded should be defined by the customer, not the business.
• Know when the first value has been delivered, and drive the next level of engagement from that point.
• Talk to users to understand both of the above

Mobile Web vs. Native Apps or Why You Want Both by Luke Wroblewski

• Important to effectively utilize both mobile web and mobile app
• App has significantly better usage (retention), but web has significantly better reach (acquisition)

# Weekly reads, week of January 11 2016

The Story Behind How Pocket Hit 20M Users with 20 People via First Round

• This one is worth reading multiple times.
• Small, understaffed companies have the opportunity to ruthlessly prioritize ‘the most important thing’. Don’t waste this opportunity.
• All companies face the challenge of losing focus. When the entire company is working on fewer things, synergy effects result in big productivity gains.
• Leaders at every level over-index on their influence on the company’s culture. If it’s not working the way you want, look inward.
• Make your product dead simple. The easier it is to learn, the easier it is to engage. The easier it is to engage, the easier it is to find value.
• Power users are a great collective PM. Utilize them.

The Rise and Fall of Everest (the App) via Katherine Krug

Reflecting upon the demise of a promising goal-accomplishment platform.

Positives = great design, sales pitch, and investors

Not so positive =

• Too many features outside of the core offering
• Site speed and tech debt matter…to a degree. Blaming the cofounder is a bit disingenuous, but what follows makes sense. Don’t overbet on big features that you haven’t tested for user interest (and that may be outside your core offering). Also, unit testing is really important (as is, one could argue, dogfooding).
• Didn’t pick and effectively track core metrics
• Cash burn
• Didn’t build a strong user feedback mechanism. Comments around not cracking motivation, etc, belie a lack of obsessive customer focus. Great comments later on regarding making it easy first, then fast, and then pretty.

How to Swallow \$200 Million Accidentally by Blake Ross

• “Judge a company’s priorities by it’s pixels” can also be pointed inwards. Judge your own company’s priorities by its pixels. Make your company’s pixels reflect it’s priorities.
• “Professional assassins don’t introduce themselves” — It makes sense to test and iterate on relatively small % of your population, so well-positioned competitors don’t jump into the fray before you’ve worked through the kinks. Easier to do for a small startup than a Facebook of course.

Building a design-driven culture by Jennifer Kilian, Hugo Sarrazin, and Hyo Yeon

• User empathy and UX focus produce compound returns over time. Many companies state that they focus on these things, but metrics and budgets state otherwise.
• Understanding the ‘why’ behind customer activity is meaningfully more important than the ‘what’
• Move fast and iterate. “Consider Instagram, which launched by rolling out a product, learning which features were most popular (image sharing, commenting, and liking), and then relaunching a stripped-down version.”
• Retail product sales were weak over the holiday season; however air travel and restaurant sales were relatively strong. Hypothesis is that this represents a millenial-driven mix shift in preferences towards experiences over materials.
• Physical retailers are experimenting with incorporating more engaging interactions into the shopping experience. Nordstrom allows users to design their own shoes. Lululemon enabling exercise. Urban Outfitters and Pizza?

More reads 146 Startup Failure Post-Mortems via CB Insights

• Lots of good lessons in here, but the biggest takeaway is that there are a lot of ways that things can go wrong, and a lot of luck involved.
• Until product-market fit is achieved (and long after), maintaining speed and discipline creates the greatest odds of success.

How Many Funnels Does Your Startup’s Product Have? by Tomasz Tunguz

• Fairly straightforward read → map / know / understand your funnels