Category: business

Posted on

Unlimited Freedom of Speech Fails on Platforms

On January 8, 2021 Twitter permanently suspended Donald Trump’s account, joining Facebook, Instagram, and Twitch in the censorship of the President. Many prominent voices stated this is a dangerous encroachment on freedom of speech, sometimes making comparisons to China’s government censoring the people. Having operated communities of millions of users, I believe Twitter’s biggest failure was not applying its rules consistently to all users, enabling abuses to increase in magnitude and eventually requiring the drastic response of a permanent suspension. Further, a social platform that does not censor, where complete freedom of speech is guaranteed, is an idealistic vision, but would have questionable viability and is likely unwanted in practice.

I’ll start with the basics, First Amendment rights to freedom of speech prohibits the government from limiting this speech, it does not require citizens or companies to provide the same freedom. When a person or company shuts down discussion from someone on their property or platform, that person or company is exercising their freedom of speech. For the most part, nobody has an obligation to let someone else use their property so that the other person can exercise freedom of speech.

But just because companies have the right to censor people, should they? This is a more complicated question. In theory, I want unlimited free speech, a world in which censorship doesn’t happen, because inevitably those in power, the censor, now controls access to ideas and information and will likely support their preferred narrative. In practice, I’ve learned that lack of moderation will likely destroy a platform, and moderation (a softer way to say “censorship”) is actually desired by communities, both online and in society in general.

Moderation is Necessary

Many platforms on the Internet start open and free and eventually become moderated, and a strong driver for that moderation is the abuse of the open platform destroys the value for others. Email started off great, with an inbox filled with relevant communications and eventually turned into a signal to noise ration of about 1:150, with fake Viagra and Nigerian princes rendering email nearly useless until filtering (moderation) eliminated SPAM. Message boards and social networks become unusable when SPAM and bots infiltrate, so in addition to community moderation, there is an ongoing, continually escalating battle to validate real users vs. bots. Even friendly actors can destroy a platform – when games were popular on Facebook and developers were heavily exploiting the feed for viral growth (hey, Zynga), the real social value declined as a majority of updates were about cows from your friend’s farm, and Facebook built tools to limit this game SPAM. There is always value in exploiting these open systems at the detriment of the other users, so abuse is the natural outcome.

This community desire for moderation, whether explicit or implicit, isn’t unique to online, we see it every day in society. No matter how much freedom we want for everyone, if somebody is singing in a theater during a movie, we want them to shut up or leave. We support one’s right to share their ideas, but if they are on a bullhorn outside of our house at 4:30 AM, we want them to go away. We set our own rules for private property and have laws for public property to support this moderation.

So when Twitter took action against Trump’s accounts, this was Twitter finally enforcing its policies on a user that had consistently abused the rules they established for their platform. They finally said, “like all other users, you can’t use the bullhorn at 4:30 AM either”. I am a strong supporter in our elected officials being held to the same rules that apply to regular citizens, especially since they are often the ones imposing these rules on the citizens (anyone that has been subject to a COVID shelter in place lockdown only to see their elected officials indoor dining or world traveling understands the rage-inducing hypocrisy). The editorial decision Twitter made was not the suspension of Trump’s account, it was years and years of allowing him to violate the terms they set for their platform, allowing a slow progression to eventually becoming a tool for organizing an attack on our government. It is impossible to know what would have happened if Twitter had enforced its policies consistently years ago, but generally problems are easier to manage when you address them early instead of letting them grow in magnitude and force.

Creating an Platform Without Censorship is Difficult

But won’t censoring just drive these users to build another, more powerful network, or to hidden communities where they can’t be reached? Maybe, but it isn’t that simple. A large, functional community requires the support of many companies that are effectively gatekeepers, and they have restrictions on abuses of their platforms. If you want mobile apps, you need Apple and Google’s platforms. If you decide to be web only, you still need hosting for your servers, a CDN (how content is cached and distributed at scale) and DDOS (distributed denial of service, when people kill your servers by flooding them with traffic) attack protection, companies like Microsoft, Google, Amazon, Akamai, and Cloudflare. Cloudflare is a great example of a company that has shown extreme and sometimes controversial support against censoring any site (even some pretty horrible ones), but eventually shut down protection for a site that was organizing and celebrating the massacre of people. Each of these platforms has the ability to greatly limit the viability of a service they believe is abusive, which is exactly what happened to Parler when Apple and Google determined their lack of moderation was unacceptable. There are other possible technology solutions like decentralized networks that might be able to reduce the dependency on these other platforms, but this isn’t just a technology problem.

Beyond technology requirements, what about the financial viability of a completely open platform? Monetization introduces another set of gate keepers, from payment processors, to advertisers, and legal compliance. While there will always be some level of advertiser willing to place ads anywhere (yes, dick pills for the most part), most major advertisers don’t want to be associated with content that is considered so abusive that no major platform wants the liability of supporting it. Depending on the activities on the site, banks can be prevented from providing services to the platform, and even with legal but edgy content (e.g. porn), there is a huge cut that goes to payment processors as they take a risk in providing money exchanges. Crypto can provide some options, but it is largely not understood by the average user and, depending on the content of the site, there can be legal requirements to KYC (know your customer), and liability for profiting on the utility of the site if the content is illegal. There are potential solutions for each of these, but it gets increasingly more difficult to achieve any scale.

Building on dark web is a possibility, although still vulnerable to many of the platform needs for scale. The dark web is also the worst dark alley of the Internet, difficult to discover and navigate, and the lack of moderation would mean many abuses, from honeypots (fake sites likely setup by law enforcement to have an easy way to track suspicious behavior) to scams and exploits preying on the average user that doesn’t understand the cave they’ve wandered into.

So while Trump certainly has a large base of followers and the financial resources (well, maybe) to have one of the best chances of being a catalyst for a new platform, there are many forces outside of that platform’s control that challenge its viability.

So, What’s Next?

If I had to guess, a few of the “alternative” networks will make a land grab for the users upset by the Presidential bans. The echo chamber of everyone having the same belief may not provide the dopamine response they get from a network with extreme conflict, so it may seem less interesting for the users. I also assume the environment is ripe for people to go after the next big thing, decentralized, not subject to oversight. Ultimately, societal norms will likely limit the scale and viability of these networks, and those limitations will likely be proportional to the lack of moderation.

So, all we have to do is ensure societal norms reinforce individual liberty while not enabling atrocities on humanity. It’s that simple. 😟

Update: in the 10 hours since I wrote this, AWS (Amazon’s web hosting) decided to remove Parler from their service, which will likely take the site offline for at least several days.

Update January 10, 2021: Dave Troy (@davetroy) published a Twitter thread with the challenges specific to Parler, with details about their lack of platform options.

Posted on

Empathy Driven Metrics

Social networks, online communities, and social media are services we use because of the promise they offer to strengthen relationships with other humans. However, these services frequently fall short of that promise, sometimes harming the relationships they were meant to support. In many companies, delivering a negative customer outcome results in business failure, but for many social companies, negative customer outcomes are producing positive business results for product teams because the business success metrics are not aligned with customer success.

Or, maybe the metrics are perfectly aligned with customer success, but unfortunately, end users are not the customer. The argument, “If you’re not paying for it, you’re not the customer; you’re the product being sold” explains the poor outcomes for end users resulting in positive business results from customers (typically advertisers). I believe a great number of employees in these companies do think of you, the end user, as their customer, but the systems in place to validate a successful outcome fail to reinforce the importance of the customer’s needs outside of the business objectives.

It is common to hear social companies talk about being “customer obsessed”, and I have met plenty of Product Managers that genuinely care about the end user as their customer. But how many companies translate this obsession into their performance metrics to deliver an outcome that is truly successful for the customer? How often do you see companies reporting objectively measured progress towards delivering customer well-being? Engagement metrics like daily active users, ads watched, shares, retention, number of posts, and time spent in app are all very common… but without consideration of customer well-being, what do engagement-driven metrics deliver in a social product that if fundamentally about human relationships?

Show me the incentive and I will show you the outcome.

Charlie Munger

Worse Human Interactions

Many of the negative customer outcomes so many people experience correlate with a positive result for the companies creating the product. Disagreement, anger, and outrage all drive activity and engagement… since last week your posts increased 23% and your time spent in app is up by 8%, but you’ve also unfriended uncle Ned because he keeps posting fake political stories about your favorite candidate, and you disinvited your extended family from Thanksgiving.

But even positive content combined with effectively scorekeeping popularity through shares and likes, can lead to worse outcomes and lower self esteem as people tend to post their best moments, creating the perception that everybody else’s life is amazing, while you do laundry, eat leftovers, and watch Netflix alone.

Worse Decisions

Humans have many cognitive biases, error patterns in the way we think, leading to irrational decisions. Online we are regularly influenced by an availability cascade, overwhelming our critical thinking by making obscure or even crazy ideas seem rational as they are repeated and seemingly reinforced as widely accepted when we witness more and more people supporting the idea.

You watch one video because you are amused that a guy thinks the Earth is flat, and then your recommended feed is showing more support for his argument. Based on what is being presented to you, there seems to be a lot of support for this flat Earth idea. What seems like an obscure initial video you watched thinking it’s ridiculous that this guy thinks the Earth is flat has led you down the rabbit-hole of conspiracy videos, and you’re starting to think there might really be two sides to consider in this whole chemtrail thing, but good news, you’re watching 13 more videos and 72 more minutes than you did last week!

The poor outcomes don’t stop with the individual, they are reflected in negative outcomes for society overall. Misinformation about vaccines continues leading to a reduction in vaccination rates and new outbreaks of mostly-eradicated diseases. Unfortunately, sensationalized false claims can go viral quickly, while corrections get a small percentage of the original article, so the fake information gains a substantially larger public mindshare.

Balancing Business Metrics with Customer Empathy

For many businesses, validating successful customer outcomes is relatively straightforward… reducing their cost per widget, increasing their leads, reducing time spent in a business process are all objective benefits. But for products that are fundamentally about human relationships, a successful customer outcome is more subjective, but by most definitions of healthy relationships, is not based on dependency, quantity of consumption, or other common assessments of engagement.

What metrics might a company consider if customer well-being were a consideration in the successful customer outcome? Factors like happiness, growth, confidence, personal enrichment, support, safety, and fulfillment seem like good candidates. In customer interviews, this would also mean understanding the real answer to the question, “How do you feel after using our product?“

Customer Well-Being is Measurable

The subjective nature of metrics like “customer happiness” presents a challenge. However, technology is reaching a point where it is becoming possible, at scale, to more objectively answer the question, “how does my customer feel?”. Sentiment analysis of text has matured considerably, and can be used understand customer. Similarly, emotion recognition of voice and visuals can provide insights into the immediate reactions. Technologies like these are being applied to problems predicting depression from written text and speech. Wearables with biometrics are becoming increasingly common and also provide an opportunity to assess the physical impact from online interactions.

Further reinforcing that measuring customer well-being is possible, in 2018 the New York Times piloted ad placements based on the emotions certain articles evoke. However, like many current applications of sentiment analysis, this use case emphasized the value created for the advertiser, focusing on targeting the customer with premium-priced ads when the customer is in an emotional state that is optimal for the advertiser. The examples cited targeted upbeat, inspired customers, but it is easy to imagine the same technology could be used to target customers that are upset, reactionary, and likely more susceptible to radical suggestions. In other words, perfect for divisive political targeting.

An encouraging example of prioritizing customer well-being comes from Dan Seider at Stigma, using input from webcam images, regularly processed by artificial intelligence to understand online consumption impact on happiness. If this type of customer data can be secured (likely requiring it to never leave the customer’s device), this technology could lead to solutions that help people understand how their online habits are benefitting or harming their well-being. While empowering individuals with these sort of tools is great, it represents third-parties trying to provide protections from social products, rather than social companies considering customer well-being as part of their product success.

Codify Better Social Outcomes

From a business results perspective, there is little need for the current social giants to change. A couple of times a years we see news surface where customers are outraged by being exploited, manipulated, or endangered, a CEO repeats a statement about fixing things, and the market value of these companies generally continues to increase in spite of these problems.

I believe many CEOs are sincere in their desire to eliminate the social problems manifested in their products (I mean, who wouldn’t want that to go away), but I don’t see this desire supported with how the company objectively assesses success, and I am skeptical we will actually see improvements until customer well being metrics are considered alongside of engagement metrics. A commitment to results requires measurement, and cultural integration into what is considered success, from product performance to employee incentives. If you don’t track it, you probably don’t really care about it.

For earlier stage social products and companies with a commitment to better customer outcomes, it is easy to assume that strong product leadership holding this commitment is enough to stay on that path. Codifying what a better social outcome means will help make the path clear when there are inevitable product tradeoffs between short-term gains vs. long-term enduring value for customers. As new employees join the company they will see values like “we love our customers” not just as words painted on the wall, but as a requirement for success.

Does your product team include customer well-being as a desired outcome? I’d like to hear more, especially how success is measured – please leave a reply below!

Credits
Kids in Field on Laptops image by Unknown, via Pxhere
Blockhead Toy image by Unknown, via Pxhere
Girl on Playground image by Unknown, via Pxhere
Computer Draining Man image by Unknown, via Pxhere
Excited Kids on Laptop image by Unknown, via Pxhere

Posted on

Rewards from Talking to Customers

Most people that build products or run companies have heard the mantra, “get out of the building – talk to customers.” It is easy to assume that talking to customers is only about building a better product. Talking to customers will help you build a better product, but more importantly, you may be rewarded by learning how your work changes people’s lives!

I recently had an experience that was so delightful I had to share it with my former employees, and they decided to share it with their millions of customers. Below is the excerpt from the IMVU blog:

You may remember a very familiar face in the photo featured in this story.  Brett Durrett is and always will be a friend of IMVU, even after his 11 years on staff and nearly 5 years as our CEO. Beyond his professional titles, or even his leadership as CEO, Brett was an active user that frequently went into chatrooms to join the conversation, answer questions, solve issues, or simply say hello. On Fridays at the HQ office, it was common to see Brett speaking from a microphone about the week’s accomplishments, and always finishing with words of inspiration, a story of encouragement, or a new product to be excited about.  Even if we didn’t hear your stories, Brett always told us your stories so that we could remember why we work at IMVU: we are here to spread the power of friendship, to help people find friends, to encourage them to express themselves, and to find an outlet for creative expression.Recently, our current Chief Operating Officer Kevin Henshaw, forwarded an email he received from Brett to the entire company about how IMVU continues to work its magic on and off our product. 

Brett’s email read like this:

On Monday I was wandering around New Orleans wearing my IMVU hoodie, as I am one to do. I went into a coffee shop and the woman at the counter asked me how I got my hoodie, to which I replied, “I used to work for IMVU”. Her eyes lit up as she proceeded to tell me how much IMVU meant to her as she was growing up.

Bea told me she used IMVU because it allowed her to connect with people without any stereotypes about who she was – she got to decide how she wanted to be seen. She also loved that it didn’t cost much to experience a fantasy lifestyle. She had a lot of friends on IMVU that felt the same. She really gushed about how important IMVU had been in her life. Her excitement went on for minutes. My traveling companion was taken aback, as I seemed to have rock star status. It was a chilly day in NOLA, but I gave Bea my IMVU hoodie (she had made me feel so warm inside that I really didn’t need it).

If you’ve talked to enough IMVU customers you know that Bea’s story isn’t unique… IMVU has helped people find their life partners, best friends, and caring families.

I thought I would use my chance encounter as an excuse to reach out to IMVU employees, say “hello”, and remind them that there are a lot of silly things than can happen on IMVU, but don’t lose sight of the really meaningful things as well! Bea’s story is a testament to what this is really about – helping people find new friends and creating something meaningful to benefit their lives. On behalf of Bea, myself, and millions of customers, keep up the great work!

Do you have a delightful customer story? I’d love to hear about it… please leave a reply!

Posted on

Q&A on Digital Transformation

In August I presented The Challenges of Executing Lean Startup at Scale, generously hosted by Rangle.io in Toronto, Canada. Rangle is the premier digital transformation consultancy, founded on Lean Startup principles and achieving impressive growth – a really great success story. I spent some time with Nick Van Weerdenburg, Rangle’s CEO, discussing Digital Transformation.

Some of the topics covered in the conversation include:

  • Solving customer problems is more important than rigorously following a process
  • The challenges of being on an agile team while working with or being part of a non-agile organization
  • Successful agile transformation requiring a culture change before a toolset change… most organizations get this backwards
  • How to choose metrics that are meaningful to your business

I hope you enjoy the video:

If you watch the video I would love your feedback! Please leave a comment below telling me what you think I got it right and what you think sounds crazy. 

 

Posted on

When Customers Benefit From Decisions They Hate

I’ve been looking at a lot of products recently, mostly for very early stage companies, where one typically builds a successful product by addressing a customer’s needs, and the customer is delighted. But some product decisions, while not well received by customers (or sometimes hated), end up being better for the customer in the long term.  As an example, with major version updates, customers can immediately hate re-learning a product they already knew how to use, even though the changes may result in a better experience and more customers.

A few years ago I was in the position where it was necessary to make such a product decision… I knew would be hated by my customers, it was unlikely the benefit could be communicated to them, and if the decision was wrong, it would be a disaster that could result in 100 people losing their jobs.

It was a change to the experience that powered 90% of IMVU’s revenue.

What is this IMVU Thing?

IMVU creates social products, connecting people using highly-expressive, animated avatars. A huge part of the value proposition is creativity and self expression, a lot of which comes from the customer’s choice of avatars and outfits. People are usually surprised to learn that the business generates well over $50 million annually. IMVU’s business model is based around monetizing that value proposition, as customers purchase avatar outfits and other customizations. However, IMVU doesn’t create this content, it is built by a subset of customers (“Creators”) for sale to other customers – IMVU provides the marketplace and facilitates the transactions. IMVU was the only entity that could create new tokens for the marketplace, so almost all of IMVU’s revenue was from customers purchasing tokens to buy virtual goods. This creates a true two-sided market, and one of the biggest challenges is balancing the needs of both sides of the market. Never was balancing these markets so risky as the decision to take control of the way Creators earned real-world currency through sales of their products.

But First, A Little History…

Today the idea of selling virtual goods for real money is common place, as is people getting paid for creating user generated content…. examples include YouTube, Roblox, and Twitch. When IMVU was pioneering this model, there were few examples, and a lot of uncertainty around the concept of virtual goods being converted to real currency, in particular if this process would classify the company as a bank, with all of the associated banking regulations. IMVU avoided this risk by not handling any conversion of tokens to real currency, and instead allowing third parties to engage in transactions independently.

Very quickly “Resellers” popped-up, offering customers tokens for prices below what IMVU charged, and frequently purchasing tokens, enabling successful Creators to obtain real currency (IMVU took a percentage of every transaction, so the overall supply of tokens always decreased and helped keep the economy strong). This structure created a robust marketplace, where customers loved a huge catalog of items, Creators benefitted from their success, and Resellers benefitted from arbitrage.

When there is a benefit to exploiting a system, people will try to exploit the system. Since the benefit in this system was real money, it didn’t take long for bad actors to surface. IMVU customers were being harmed by bad Resellers that would take their money and not provide tokens, or steal their accounts (and tokens). As a result, we locked-down the Reseller program to less than 20 trusted people and had requirements for them to maintain good practices to remain in the program. And things were good…

The World Changes

Fast forward to 2015 and the world has changed… selling virtual goods and making money from user-generated content are well established practices. And, perhaps related to these practices being more mainstream, financial institutions have established best practices and requirements for these types of businesses. Mobile apps were also well established, which included customer expectations for purchasing in-app content, and app store guidelines for selling virtual goods. These developments, along with recognizing opportunities to provide more purchasing reliability to customers, drove IMVU to restructure the fundamentals of the Reseller program.

The decision to go through this restructuring was highly disruptive to customers, generally unpleasant for all involved, and absolutely the right thing for both customers and the company.

The Heart Transplant

The fundamental change was eliminating Resellers altogether, with IMVU providing royalty payments directly to Creators for the sale of their virtual goods. The process of paying content creators directly is pretty straightforward if it is your starting point, but transitioning to it is painful.

The immediate pain comes from managing communication with a large, passionate community that benefits from the established system, doesn’t necessarily see the need for change, and doesn’t (and can’t) have the breadth of information necessary to understand why changes are necessary (and ultimately, beneficial). IMVU’s Community Manager made heroic efforts and did a great job with communication, but there were still massive forum threads, petitions, and doomsayers.

The next challenge is trying to do the best thing possible for the Resellers, knowing that ultimately the result is going to be eliminating their business, so all you can hope for is making the best of a crappy situation. At this point Resellers were a small oligopoly with strongly protected positions, giving them a huge advantage in both purchasing tokens from Creators and selling to customers, and many had many months of token supply in inventory. Making things even more complicated, many Creators were also uncertain about their future ability to sell tokens, and wanted a way to cash out.

The solution was to announce to the IMVU community a timeframe for the wind-down of the Reseller program, allowing Resellers a small window to purchase tokens from Creators, and a larger window to deplete their inventories. A few Resellers dumped their tokens immediately at fire sale prices, but the more savvy Resellers paced their sales, recognizing that prices would increase as supplies dwindled. A few Resellers maximized the opportunity to buy tokens from Creators at next-to-nothing prices and benefit by selling them an close-to-peak prices a few weeks later. Ultimately Resellers were able to deplete their inventories before the program end. During the two month transition, IMVU resisted discounting its own token sales as to not compete with Resellers – this choice, combined with the tokens flooding the market, had a very real impact on revenue, both in the immediate loss of token sales and in the months following, while many customers had stockpiled a large supply of discounted tokens and didn’t need to purchase from the company.

The remaining transitional work was relatively straightforward (I’d write, “simple”, but I saw several teams of people work their butts off to get everything in place and working in time). Creators needed to provide necessary documentation so they could receive payment, and IMVU needed the accounting systems and people to facilitate payments.

But it wasn’t smooth sailing yet… While IMVU was very good about tracking Reseller token supply as part of monitoring the economy, unknown was the fact that Creators had a pent-up demand to sell their tokens, and much of this demand was completely unmet by the oligopoly of Resellers. As a result, request for royalty payments were much higher than initially expected. The new process would lead to a better result for a larger number of customers, as Creators would reliably be able to receive royalties. However, this immediately meant substantially higher expenses for the company, which was already feeling the impact of lower revenue from the Reseller cash-out. No amount of spreadsheet magic could make the business results look good.

A Quick Note on Leading Through Uncertainty

I was CEO of IMVU during this transition, and I distinctly remember this period as one where I felt I may have made a catastrophic decision. Most bad decisions can be corrected if you’re responsive, and it is usually better to take action and correct if necessary vs. stagnate from analysis paralysis. However, given that the token economy was the business, getting this transition wrong was an existential problem for the company. Over a hundred employees could lose their jobs, and millions of customers could lose a product where they connect with friends.

I knew the potential impact before making the decision, and exercised a lot of diligence researching the economy and token ecosystem (to be more accurate, I had an amazing COO that did the heavy lifting and we were aligned on our understanding). There were few decisions I made where I felt as confident in the ultimate result it would produce, but the timing, and seeing the painful business results each week certainly tested my confidence internally and I would review my assumptions to see where I could have gotten it wrong. Externally I remained more confident, reassuring employees and board we would see an inflection point… soon… it’s coming… hang in there.

I’ve heard other CEOs share stories with a similar pattern… the role requires a balance of internal self-questioning while portraying confidence externally, and the CEO rarely has the ability to share that internal conflict with others.

Results!

In the third month following the changes, IMVU hit the inflection point – the transitional business pain stabilized and started producing positive results. Taking full control of the Creator and Reseller aspects of the economy meant customers could have a reliable experience, from purchasing tokens to receiving royalties for their content. As part of the better-regulated process, there were other bad actors, scams, and negative customer experiences that were eliminated. And since there were less variables in token supply and pricing, it was much easier to maintain stability in the value of the token, a huge win for Creators, the business, and customers that ultimately benefit from a vibrant Creator marketplace.

The change to a more tightly-controlled token economy, combined with other big initiatives that were engaging new customers, resulted in a significant wave of growth and record results for IMVU’s business.

Key Takeaways

  • Talking to customers is critically important! Deeply understand the core of their objectives and pain points, and make sure product changes solve for the customer’s needs.
  • Be mindful that customers won’t have the breadth or depth of information necessary to recognize the real benefit of some product decisions. Sometimes what seems to be an immediately unpopular product decision is necessary to deliver a better customer experience over the long-term.
  • Spend the time to get information necessary for confidence in decisions that can have significant impact, but also be humble, open to recognizing a mistake, and ready to adjust if the results aren’t there.
  • With a large enough customer base it becomes impossible to solve for everybody, as occasionally their needs will conflict. Be intentional in product decisions that make these tradeoffs, solving for the best long-term customer experience for the customers your business needs.
  • Unsupportive customers should be an exception… most of the time your decisions should delight your customers.

 

Do you have examples of product changes customers hated but ultimately produced a better experience for them? If so, I want to hear about them! Please leave a reply, below.

Posted on

Know Thyself – Startup or Small Business?

There are plenty of good businesses that fail because they are convinced they must be great businesses.

When an entrepreneur asks me for advice for their company, the two most common questions I end up asking are, “what do you want to get out of this?”, and some variation of “do you really want to run a Startup, or would you be happier running a Small Business?” It’s not uncommon for people to make the mistake of thinking these types of companies are basically the same.

What’s the Difference and Why Does it Matter?

When you look at all of the new companies being created, the majority of these are Small Businesses. There are a few reasons for starting these, from following your passion, to having a reliable income, to perhaps creating a family business that will provide work for future generations. These companies are generally funded with family savings, small business loans, or personal loans. In almost all cases, the goal of these businesses is to be cash-flow positive and, if there is company growth, it is usually constrained by actual cash coming into the company, not spending ahead of revenue. As such, a Small Business will have revenue very early after starting, quickly as months or weeks. Owners are typically rewarded by the longevity of the company, a share of the profits, and sometimes a sale of the company.

While you couldn’t tell from a survey of Silicon Valley, but only a very small percentage of new companies are Startups. These are companies that have a vision to discover some radical innovation, in a product, a process, or a service, that has the ability to win a huge market. Since this is an exercise in discovery, the path of a Startup is one of uncertainty and high risk, with 9 out of 10 of these companies failing. The uncertainly means Startups need risk capital (usually multiple infusions) and can take years before they have any revenue. The most common source of funding for these companies is Venture Capital. Proving a repeatable business model and massively scaling business is the goal of Startups. Owners (shareholders) are rewarded by a liquidity event where stock in the company is converted to cash, typically through an acquisition or by having an IPO, and trading stock on the public markets.

The differing goals, and the financing dynamics mean that Startups and Small Businesses operate almost opposite of each other. With cash being a critical resource in a Small Business, business decisions are typically risk adverse. In most cases the better decision will be one that keeps the business at break even rather than risk negative cash flow, even if that decision has a small chance of a huge positive change.

In contrast, since 9 out of 10 Startups fail, that last 1 has to not only deliver economic wins for itself, it has to carry the weight of the 9 others that didn’t (since investors actually want better than market returns over the several-year life of the fund, the real increase in value for a win needs to be closer to 30x). What kind of decisions lead to a 30x return on investment? Not the conservative, sane ones you want protecting the existing value of a Small Business. Investors need big returns and that means they need the company to take big risks.

Crossovers are Rare

Occasionally you will hear about company being run as a Small Business that is super successful has the outsized success of a Startup. More common is the Startup that has crossed-over to being a Small Business… in almost every case the crossover to Small Business represents a failure for investors, where the company established a sustainable business but not one that could generate liquidity. These companies are sometimes referred to as “zombies” by investors… won’t die, but the stock will never turn into cash. For Startups it is way more likely that they fail completely, burning through all cash in high-risk attempts before discovering an actual business. The lucky ones can become acquihires (where a company “acquires” the team as employees, but no real cash is spent). Acquires can be a decent outcome for some of the team, but it a failure for investors.

Know Thyself

And this gets back to my question to many entrepreneurs, “what do you want to get out of this?”

Too often an entrepreneur has shared his company with me and I’ve seen a good business – one that can pretty reliably grow at 10-15% per year, provide jobs for many grateful employees, have lots of happy customers, enable taking decent amounts of cash off the table as it grows, not require 60+ hour weeks to manage. That’s a pretty good outcome, but it is a Small Business, not a Startup.

A lot of entrepreneurs (especially in Silicon Valley), see Startup as the only option.

And, Startups are great, too! They change the world (usually with the intention of making it better), they risk death doing the crazy things that occasionally produce amazing results. And for those very few entrepreneurs that make it through the gauntlet, successfully deliver a revolutionary business, they are rewarded with substantial financial rewards and, occasionally, hero-like status. They’ve created a great business.

My advice to any entrepreneur starting the journey of building a company is understand what you want to get out of the company, from quality of life to financial reward, and understand if you want to build a Startup or a Small Business.

 

I would really like to have more great Small Business stories! If you are part of a Small Business or you know of a great Small Business, please leave a comment!

Posted on

Avoiding the Perils of A/B Split Testing

A/B testing is widely used in product development, popularized as a fundamental component of the Lean Startup  framework, and providing a scientific way of validating product and business improvements. The concept is simple… put some customers in the new experience, compare the results against customers that didn’t get the new experience, and better metrics validates the improvement. In reality, this process of validation is very complicated and there is no shortage of hazards leading you to poor outcomes.

Creating Information out of Data is Hard

IMVU had a culture of data-validated decisions from almost day one, and as a result we made it easy for anybody to create their own split test and validate the business results of their efforts. It took minutes to implement the split test and compare oh so many metrics between the cohorts. All employees had access to this system and we tested everything, all the time. A paper released in 2009,  Controlled experiments on the web: survey and practical guide, reinforced that split testing was the undisputed arbiter or truth. We were clearly on the right path. 

While the ability to self-assess progress created a very empowering culture, we were largely ill-equipped to understand the nuances of what the data actually meant. Years later we would start to better understand, we don’t know how much we don’t know.

First Know Why

The first opportunity to make a mistake with split testing is deciding to test in the first place. When creating a split test has a very low barrier, it is easy to err on the side of just testing everything so that you can have the data if you need it. But every test has a lot of hidden costs than come from false-positives, clarification of data, shiny-object distractions, inconsistent customer experiences, and additional opportunities for introducing bugs.

Recognizing that being a split test packrat has a real cost, there should be some requirement for incurring this cost. Are very least, answering the question, “What are the significant changes that will be made as a result of this test?” Additional pre-test work to specify what will be measured, and what results will determine success or failure can also go a long way towards ensuring time spent testing is valuable.

Test Implementation is a Project

IMVU had a great framework to make test implementation a seemingly simple task, with a few lines of code of creating a branch for the test experience, and leaving the current experience as the control. Again, this made creating tests seem deceptively easy, and left openings for measuring the wrong thing.

Often a split test is a cross-functional effort, with an engineer handling the implementation and the customer being any combination of a product manager, acquisition team, marketing representative, revenue officer, or generally interested party. In some cases, the interpretation of test data is done by another person altogether. Correctly understanding what the internal customer wants to know, capturing the right data, and converting that data into information ends up with many points of communication that must be accurate to deliver a valid test.

For example, the acquisition team wants to test a new landing page, simply reordering the registration fields because they think it will improve the registration completion rate. The engineer realizing this is a no-brainer takes the 15 minutes before lunch to create the quick test, two paths and the test is running. However, the registration page has both manual registration and sign in with a social network account, so the test is including a lot of users that are social logins, irrelevant to the registration fields. This subtle nuance means that the impact of the registration field changes will likely be lost as the irrelevant data acts as a damper. What the customer wanted to know isn’t what the test is answering, and it’s likely that nobody on the project knows there is an error.

The ease of creating a split test should not be conflated with delivering quality results from a test. Doing it right is a project and requires investment of resources consistent with any other project.

WTF Do These Results Actually Mean?

Assuming you were diligent in your experiment design, you captured all of the relevant data, and you avoided some of the common errors of A/B testing, you now need to make sense of the data. In the best cases, you’re looking at something like “the registration landing page increased conversions from 1.83% to 2.01%”, in the worst cases you find something like “customers are engaging with messaging feature 17% longer… but their lifetime value has dropped by 4%”, and now there is work to put together a narrative that explains the perplexing results.

In 2012 I read a paper, Trustworthy Online Controlled Experiments: Five Puzzling Outcomes Explained, and I had what I like to call an, “oh shit” moment. Highly controlled experiments, run by companies with world-class, dedicated analytics teams were getting perplexing results that required substantial research to understand what was actually happening. What chance did we have of getting this right when we are running 15+ experiments a week with training consisting of a one page internal wiki version of, “A/B Testing for Dummies”?

The tl;dr summary of the paper, without deep consideration for the “why” behind the change in metrics, positive results may be antithetical to what you are actually trying to achieve.

The up-front work to limit the scope of the experiment and how it will be measured / interpreted can help, assuming you have the self control to ignore the data outside of scope. Often these perplexing results require follow-up experiments to better isolate cause and effect. I also highly recommend talking to customers – often qualitative insights from hearing their experiences can often help make sense of what the quantitative results were hiding.

You’re Biased. No, Really, You Are

I’m sure there are a lot of great reasons we humans are wired to think the way we do, and this wiring probably served us very well in many situations. However, humans also come standard with cognitive biases, built-in tendencies to make irrational decisions. Unfortunately, putting a bunch of effort into building something and then getting a giant pile of metrics is a perfect enabler for a cognitive biases and craptastic decisions.

While numerous biases are working against you, with a buffet of metrics one of the most common is the Texas sharpshooter fallacy, in which the all of the test metrics that are improvements over the control metrics are used to demonstrate the success of the test. With a 95% confidence rate, 1 out of 20 metrics tracked are expected to show a false positive improvement, so even an A/A test (two separate cohorts with identical experiences) would likely show “improvements”. Before we eliminated the practice of metric-sniping at IMVU, it wasn’t uncommon to hear somebody say something like, “my pet project to streamline registration didn’t change registration, but it does deliver a 5% improvement in [the completely unrelated] customer lifetime value, so we should keep it.”

There are process controls that can help reduce the potential impact of various biases, in particular around defining and constraining each test. However, being aware of these biases and encouraging a culture consistent with the dialectical method can help make better product decisions, even beyond interpreting test results.

Talk to Your Customers!

One of the biggest risks that come from over-reliance on split testing is seeing it as a more convenient method of getting customer feedback. Why spend 30 minutes on the phone with one customer when you can simply measure the actual actions of thousands of customers?

Looking at data and sending surveys may seem like an efficient use of time, but that highly structured approach is unlikely to surface critical customer insights. Metrics and surveys will often answer the “what”, but almost always miss the “why”, the most critical driver of valuable insights. There is no substitute for talking to your customers.

In the words of Steve Blank, “Get Out of the Building.”

 

I’m interested in hearing other stories where split testing has made an impact, either positive or negative. Please share a comment if you have one!

Posted on

How to Respond After Leaking Your Customer’s Data

The most recent consumer-hostile disclosure of an account breach was Uber’s leaking of 57 million accounts almost a year ago. I’d like to say this is an extraordinary event, but much like a favorite character getting killed in Game of Thrones, companies leaking customer data is just another regular occurrence we’ve come to expect. What continues to surprise me is how badly so many companies screw-up their response to a breach. The one principle that should guide companies following a breach is, “make the decisions you would want a company to make if it was your account that was compromised.”

And sure, it’s easy to point fingers when it’s not you in the hot seat, so I’ll use the breach I managed as an example… The breach I was responsible for was in September 2015, when I was CEO of a company that had over 100 million registered accounts.

Initial Response

The breach was caught around 11:00 PM at night… within a couple of hours we had a fire-team of employees in the office. The priority was confirming that the breach was indeed fully contained, and then validating we understood the full extent of the breach. We wanted to communicate to customers as quickly as possible, and we wanted to be able to accurately convey the amount of exposure. Every other project was de-prioritized and employees were working 24/7 on projects related to the breach.

Thanks to some security precautions we had in place, we were able to detect the breach in real-time, limit the data that was accessed, and understand exactly what data was exposed. Also, due to the nature of the data that was accessed, the actual customer exposure was minimal (e.g. no credit cards, social security, addresses)… assuming the attacker had planned to use the data for malicious purposes, the actual value of that data was extremely low.

As we reached morning, we contacted law enforcement and legal counsel, both of which informed us that the data exposed was insignificant in terms of risk. We were also told that, because of the type of data accessed, there was no requirement to disclose the breach.

While we had a pretty solid understanding of what happened as part of the breach, we didn’t want to be overly confident, so we continued the process of going through hundreds of servers and employee computers to look for anything that might have been missed, a process that took a little over two full days.

The Ransom

Within 24 hours of the breach I started receiving emails that threatened to release the customer data and publicly announce the breach if we didn’t pay a sum of money. My response to the blackmail was letting them know I would consider their proposal, but ultimately the damage they would do is to customers that didn’t deserve to be exploited, and to employees, good people that already feel a ton of weight from the responsibility. They gave me a few days to make a decision.

Talking to Our Customers

After we had confidence that we had contained the breach, removed any attack vectors, and fully understood the data accessed, we were ready to talk to our customers. Less than 72 hours had passed, but it felt like an eternity getting to this moment.

We posted to our forums and messaged our customers individually with the details of the breach, specific data accessed, how that data can be used, and what steps to take (on our service and others) to protect against any further attack. We also disclosed that the hacker had tried to extort money in exchange for silence.

While I can’t say that any customer was pleased that the exploit occurred, many responded very positively to our handling of it. Earlier that year credit card and health care breaches of highly-sensitive data took many months to be announced, so many of our customers appreciated how quickly we moved to keep them informed.

Evidently the hacker didn’t read our forum post, as the next day they gave me the final warning that they were about to announce the breach to our customers and the media. I informed the hacker that we would not be paying the ransom, reminded them that the people they will hurt don’t deserve it, and pointed them to the forum posting fully disclosing the breach, accessible to all of our customers and the media.

Post Breach

Through a process of many, many postmortems and follow-up action items, the company continued to improve security in several areas, projects that extended many months. We understood exactly how the breach occurred, and the human component that enabled the breach. What we explicitly didn’t do is punish or threaten anybody – throughout the whole process we made all employees feel safe, which enabled people to be fully transparent and quickly disclose their mistakes, a critical aspect of quickly understanding how the breach occurred.

The moment that sticks out in my mind the most was an email I received from an employee in response to a detailed summary of the events I sent to the company. That employee expressed that they had never been so proud to be at a company, in the integrity we demonstrated to our customers, and the unwavering support for the employees. It was one of those emails that CEOs move to their “save forever” folder. 

Key Takeaways

While there are a lot of opportunities for companies to make customer data more secure, the unfortunate reality is even the companies with the best security practices experience breaches – this is going to happen. However, a few steps can provide better outcomes for all parties:

  1. Treat your customers as you would want to be treated.
  2. Make your employees feel safe. Fearful employees will conceal critical information that is necessary to fully understand the problem.
  3. Don’t negotiate with criminals. It’s bad for your customers, there is no way to enforce the criminal’s end of the agreement, and the deception is likely to be revealed at some point. Perhaps one acceptable variation on this takeaway is, if you do negotiate with criminals in the interest of your customers (e.g. to get details about how the leak occurred), still be transparent with your customers and disclose that a transaction occurred.
  4. Do the follow-up work. After an exhausting amount of effort getting past the initial breach it’s easy to feel like your work is done… make sure all of the known exploit vectors are eliminated.

 

Have you been impacted by a company’s data breach? I’d like to hear about your experience – please leave a comment!

Posted on

Your Agency is Hurting Your Chance of VC Funding

Early-stage venture capital firms have high deal flow and very little time to assess each company, so understanding key assessment criteria will help you get your deck from the “no” bucket to the partner discussion. A common reason many companies fail to get past “no” is they are agencies.

Is Your Company an Agency?

In an agency, value created by the company is unique to each customer. As a result, the company revenue reflects more of a work for hire relationship. The problem with this model is, while an agency can still be a very good (or even great) business, it is hard to scale and typically doesn’t improve margins when it does scale.

When asked, entrepreneurs don’t always recognize that their business model is an agency… they may see the unique customer work provided as building support in the underlying platform, or a way to help onboard early customers. While all possible, it’s unlikely, and VCs that have looked under the hood of hundreds of companies will understand the signals indicating this is an agency:

  • A majority of revenue comes from additional work provided, not from the product / service
  • Work performed is applicable to a specific customer (e.g. content creation, integration, customization)
  • Customers largely came from relationships, not from a repeatable sales process
  • The company is pivoting from a consulting business

What if My Company is an Agency?

So, what do you do if your business looks like an agency? Well, it depends on what you want for your company. If you’re happy with a potentially good (or even great) business that may grow at a reasonable rate, be a source of employment for a bunch of people, and maybe never have an exit, skip the VC and run your business (of course, you have to run cash positive or get loans to get you there). And, the lack of an exit doesn’t preclude a payout… I’ve met several owners of “lifestyle businesses” that, on top of a good salary, pull substantial amounts of money out of their company.

If you do want to go the VC route and have a VC-sized exit, you’re going to either prove your business is the exception (unlikely), or make some fundamental changes to your business to achieve some combination of the following:

  • A consistent shift in revenue away from unique customer work and towards your product or service
  • A convincing process showing the unique work for each customer is scalable (i.e. not limited on the supply side)
  • Margins improving with growth   

Pivoting to a new business model is usually easier written than done. And, if your agency model is working for you, a pivot away from a working business model can be risky. The again, if you’re the type of entrepreneur that is excited by building VC-backed businesses, you probably eat risk for breakfast.

 

 

Posted on

Less Minimal, More Viable – Creating Better MVPs

I had the exceptional luck to work with Eric Ries at both the company that was his inspiration for The Lean Startup, as well as the company that was his catalyst for the change needed to build companies differently (and I hope someday I can convince Eric to release his insightful yet unpublished manuscript “The Bloated Startup” – maybe your tweets can help #EricPleasePublishTheBloatedStartup).

One of the fundamental ideas from The Lean Startup embraced by startups is the Minimum Viable Product (MVP), a product strategy that minimizes investment while maximizing learning and market validation. And while MVP is a great and seemingly simple concept, many startups fail to execute it successfully.

There was a time not too long ago when startups regularly burned many millions of dollars in years of stealth mode, building massive projects anticipating the use cases for all of their future customers, and the concept of releasing anything that wasn’t robust being heresy. A combination of those companies spectacularly imploding, investor expectations that companies achieve validation faster,  and the embrace of accepting failure while chanting the mantra “fail fast”, made the pendulum swing the other way.

The most common criticism of MVP is too often it is actually Mvp, where minimal is emphasized and viable is highly subjective, but leans towards not viable. It’s not that MVP is a bad concept, it’s simply difficult in practice. As a result, others have looked to redefine MVP – Jason Cohen proposed the SLC (Simple, Lovable and Complete), and Laurence McCahill proposed the MLP (Minimum Loveable Product), both emphasizing the importance of delighting customers to being “viable”, and reducing the opportunity to simply ship a broken experience to customers using “learning” as an excuse.

Rather that create another TLA, I’m offering guidance to make the implementation of MVPs more effective:

  1. The MVP Delivers Your Value Proposition
  2. The MVP is a Functional Product
  3. The MVP Provides Validation or Valuable, Intentional Learning

Let’s dig into each of these a little more..

The MVP Delivers Your Value Proposition

The MVP must deliver the customer value proposition for a subset of customers that will be early adopters. Delivering on your value proposition may seem obvious, but in the interest of trying to achieve the minimum investment, it can be overlooked.

Core to IMVU’s value proposition was connecting people through expressive avatars, which was initially delivered via a 3D client on the PC. IMVU had an early mobile product that connected customers by enabling messaging from their phone, and while we called it a mobile MVP, it wasn’t. Specifically, the messaging was text-based, so it didn’t deliver on avatars or expressive communication. Since it didn’t include avatars, it also didn’t test the business model, which involved selling items to stylize an avatar. Many existing customers liked the functionality provided, enabling them to perform some basic functions while not at a PC, but nobody would become a new customer on this product – is was simply a helpful add-on.

Later IMVU built a real mobile MVP, starting with the very basic set of functionality that enabled expression via your avatar, and the ability to purchase items for customization (also important to expression). Knowing the PC offering, the mobile MVP felt pretty bare bones, didn’t include 3D (something we knew customers wanted), but the customized avatar was present, enabling self expression. We gained new customers that only knew of IMVU as a mobile experience, and we validated that the business model worked. Eventually full 3D was added with a lot of other features that did an even better job at reinforcing the value proposition, but it was a pretty humble beginning.

The MVP is a Functional Product

The need to be minimal yet completely functional is where great product design comes in, recognizing that the best products are fully functional without being complex – simplicity delights customers.

The test I’m proposing is, without adding additional functionality, does your MVP continue to deliver value to your early adopters? Asking another way, can you imagine walking away from the MVP and seeing your early adopters still using it in 24 months?

When it comes to applying MVP to new product functionality for an established product, this simple but complete requirement is even more critical. I witnessed many MVP projects that shipped in half-done limbo as some customers liked it sort of, but it was broken, but not valuable enough to finish… the result is many rough edges and missed opportunities to delight customers.

The MVP Provides Validation or Valuable, Intentional Learning

One of the most disappointing results to hear from a failed MVP is, “we learned it didn’t work”. Aside from the obvious desire for projects to be successful and delight customers, this result represents a failure to intentionally learn. A great indicator this is happening is a product manager presenting data harvested after the fact, hand picking metrics that were not identified before the product was built, creating learning theater.

The MVP should reduce uncertainty, either by validating previous decisions or providing information necessary to make specific future decisions.

When building the MVP, there should be a clear hypothesis, identification of the metrics that will be used to gauge progress, the ability to capture those metrics, and an understanding of the critical decisions that will be influenced by the results. In addition to creating a discipline around honest assessment of progress, these requirements guide the team’s product development decisions.

 

Have you learned something valuable from building a MVP? I’d love to hear your story! Please leave a reply in the comment section.