The Rule Of 40: Which Side Are You On?

In the early days, a company with solid product/market fit and a great team will grow extremely fast. Revenue growth can be 1,000+%. But as a company becomes established, things come back to earth. Tripling revenue when you have $50k in revenue is a lot easier than tripling revenue when you have $50MM in revenue. Over time, the company will eat up all the low hanging fruit. Competitors will enter the space and apply pricing pressure and reduce win rates. Scaling becomes even more difficult. Things just start to slow down.

This flattening of growth is nothing to be ashamed of. It's a natural curve for any product or company — even the iPhone's growth has flattened.

 
Apple iPhone worldwide unit sales from 2007 to 2018 (in millions)

Apple iPhone worldwide unit sales from 2007 to 2018 (in millions)

 

The way to break out of this natural flattening is to innovate. As Jeff Jordan says, “to add layers to the cake.” But eventually, even the greatest companies will see their growth rates begin to level off.

To maintain a high valuation despite slowing growth rates, companies will often point their energy towards becoming profitable or increasing profitability. One of the biggest challenges of a maturing company is this: should we step on the gas and continue to grow like crazy, or should we shift our focus to profitability?

The Rule of 40 provides an excellent framework for how to think about this question. The Rule of 40 states that a company's growth rate + profit margin (EBITDA) should exceed 40%. Companies that can stay above 40 will continue to be on the high end of valuations — 10x, 20x, 30x revenue multiples. According to a study done by Bain, software companies that are above 40 have valuations that are double those that fall below the line.

So as growth slows, it's useful for executives to ask, what side of the Rule of 40 do we want to be on? That is, are we going to continue to achieve the 40% via revenue growth or do we need to begin focusing on profitability.

The Rule is just a framework; it shouldn’t be taken as gospel. But it provides an extremely useful framing for how to think about one of the most challenging questions high growth companies face.

Transforming Value Chains

This piece by Ben Thompson titled, Email Addresses and Razor Blades, might be the best thing I’ve ever read on modern-day business strategy.

I strongly encourage you to read the post and/or listen to the associated podcast if you’re interested in this sort of thing.

The piece highlights Harry’s Razors and their efforts to disrupt the razor blade industry with an online direct-to-consumer (DTC) model.

By selling online directly to the consumer, Harry’s was able to disrupt the razor blade value chain created by giants like Proctor & Gamble and cut out retailers that leveraged their shelf space to take a ~40% margin. By selling online and leveraging highly efficient, targeted advertisements via Google and Facebook, Harry’s could pass a lot of that 40% back to the consumer, dramatically undercutting the incumbents and scooping up lots of market share.

Thompson points out that this margin quickly disappeared via Facebook and Google ad auctions. As DTC companies flooded to these ad channels, the prices went up and up and up, erasing the 40% margin, and bringing the razor blade market back to equilibrium. Now, Harry’s and other DTC companies are pivoting into brick-and-mortar and the FTC is raising anti-competition flags. Nobody wants to compete with P&G, but that might be a lot better than competing with Facebook...

The broader lesson here is that is it so crucial for companies to deeply understand the value chain associated with the product they’re delivering and how that value chain is changing over time. The macro conditions that allow new entrants to earn a seat in the value chain can be the same conditions that take that seat away.

Business Models & Tech

This somewhat dated (2015) but still highly relevant essay by Alex Danco offers an insightful overview of the state of software in healthcare. If you care about this sort of thing, I highly recommend reading it.

The most interesting aspect of the piece for me is the reminder that when tech impacts or “disrupts” an industry, the tech isn’t necessarily the interesting part. The interesting part is the business models that change or emerge as a result of the tech.

Here are a few examples of what I mean:

Spotify leveraged technology to change the business model of music from $10 per album to 40 million songs for $10 a month.

AirBnB leveraged technology to change the hospitality business model, listing 6 million rooms and homes while owning zero properties. 

Uber leveraged technology to change the taxi business model, doing 4 million rides per day, while owning zero vehicles or taxi medallions.

As we consider how much software has impacted (or not impacted) healthcare, we shouldn’t be looking for the flashy, healthcare-specific, transformational technologies. We should consider the new and emerging business models that are enabled or enhanced by technologies. Those aren’t hard to find.

Things That Don't Scale

I recently started using Superhuman, the popular $30 per month email application, that's getting lots of buzz. It's a wonderful product. It solved my email overload problem.

I would've started using it sooner, but before they would grant me access, I had to complete a thirty-minute consultation with one of their staff members to configure my email and learn how to use the product most effectively. That seemed unnecessary to me, so I passed.

I eventually got desperate and agreed to the consultation. I now see why they force this — they go deep on how you use email, do some real-time customizations, and make sure you know how to use the product. All of this makes users much less likely to churn.

That said, it's surprising that Superhuman, an application with thousands and thousands of users, would make this kind of investment in onboarding new users. For a $30 per month consumer email application, this seems like the definition of something that won't scale.

I recently came across an interview with Superhuman's co-founder, Rahul Vohra, where he talked about the importance of these consultations and was asked if he thinks they can scale. He responded by saying that organizations need to identify the things they do that won't scale and decide which of them they should keep on doing. These are things that, from the outside, may seem small and wasteful but are actually core differentiators consistent with the heart of the organization's strategy and competitive advantage.

I've been thinking about this a lot lately. As an organization scales, the things that aren't scaling start to become really obvious. And smart companies find ways to outsource, automate or completely stop doing them.

The hard part of all of this is identifying those things that, on the surface, seem like they obviously won't scale but actually drive big value.

At the Ritz-Carlton, every single employee (even the maintenance folks) has a budget of $2,000 per guest to make things right. On the spot, without asking.

Zocdoc, the medical appointment booking service, sends a $10 Amazon gift card to users every time a doctor reschedules an appointment.

Zappos maintains a 24/7 call center, posts their phone number on every page of their website, and doesn’t have a phone tree.

In the early days, most startups will tend to overinvest in high-touch and high-cost activities. They have to do this because they're forcing their way into a market. They can't cut corners and scale isn't an issue.

One-on-one product training. High-touch recruiting and employee onboarding. Ultra-fast customer service response times. Even small things like sending hand-written holiday cards to every customer. These are obvious and easy to do in the early days. But many of them won't scale and there’ll be pressure to stop doing them over time.

The easy part is dropping things that don’t scale. The hard part is continuing to do them.

Some Thoughts On Enterprise Software: Increasing Consumerization, A SaaS Bubble & Cross-Company Network Effects

Here are some thoughts related to enterprise software that have been rolling around in my head for the last few weeks.

Consumerization’ Of Enterprise Is Accelerating

Aaron Levie (founder of Box) tweeted this the other day following the Zoom IPO:

I’m not sure we’re fully there yet, but the tectonic shift Aaron refers to is absolutely happening faster than I had thought.

Back in 2011, Chris Dixon wrote a blog post discussing why consumer tech is so much better than enterprise tech. I posted this comment:

In a [B2B] transaction, one good salesperson (the “seller”) only has to sell one person (the “buyer”) on the value of the technology. Once the product is sold, the buyer forces their 50,000 employees to use that technology whether they like it or not. A good salesperson with a good deck can do this fairly reliably.

And a good account manager can typically retain the client for a while; employees usually get used to the product and rarely complain enough for the buyer to cancel the contract and force the seller to improve the product. As a result, an enterprise product can suck and still flourish.

With a B2C product, this is much, much more difficult. The seller has to sell 50,000 individual “users”, one by one, on the value of the product without the luxury of a face to face meeting or 18 holes on the golf course. The B2C model forces the seller’s product to “sell itself”. As a result, a consumer product can’t suck if it wants to flourish. It has be good. Much better than the enterprise product needs to be.

In light of the Slack and Box IPOs, things are looking a lot different than they did back in 2011. There are a few trends causing enterprise software to look more like consumer software.

1/ Bottoms-up enterprise distribution is expanding. This is where an employee within an organization signs up for a service and tells a few colleagues. Soon, when enough employees are using the product, a sales call is triggered and the salesperson tries to sell the product into the organization top-down. Unlike the old days, this strategy only works if the product is really solid.

2/ Micro use cases are increasing the number of buyers inside an organization. The purchase of a CRM or ERP system will likely always be a complicated, top-down decision. But because of the emergence of SaaS products with narrow use cases that require relatively small budgets, the purchase of a SaaS product that, say, improves the efficiency of making sales commission payments to salespeople, will lie with a middle manager in the sales operations or finance function. When buying responsibilities are spread more widely and the decision maker is closer to the user (or is the user), the quality of the product has to improve.

3/ Buyers are getting smarter and products are getting more transparent. The internet has enabled thousands of micro trade groups and private communities to form, allowing professionals to share insights and best practices and advocate for one another. I recently joined a collective of revenue leaders from all over the world. We have a Slack account that we use to share information, ask one another questions, etc. There’s a #techstack channel where we discuss different SaaS products focused on sales and marketing organizations and our experiences with them — Outreach, Gong, Troops, Docusign, etc. I’ll never buy another sales-oriented SaaS product without consulting this Slack channel. At some point, nearly every buyer within a company will be a member of one of these groups (if they aren’t already). This only accelerates the transparency of information for buyers and makes product quality and delivery equally important — and in many cases, more important — than distribution.

There are still a lot of old school industries where top-down purchasing is a requirement because of outdated buying practices, the need for legacy system integration, security concerns, etc. But in the coming months and years enterprise software will continue to look a lot more like consumer software.

A SaaS Bubble?

I’ve heard many people refer to the explosion of SaaS as “the unbundling of Microsoft Excel”. That is, Excel used to do everything for us but now a bunch of companies have peeled off use cases and have built SaaS products around those use cases. This is really true in many ways. Fifteen years ago the companies I worked with did just fine without many of the SaaS applications we have today. We just did all of it in Excel. Sales pipelines, expense reports, commission payments, time tracking for consultants, project management, OKR management, etc. Now all of these things are managed by products like Salesforce, Expensify, Exactly, Harvest, SmartSheet and 7Geese. Companies today use so many SaaS products that Parker Conrad, the founder of Zenefits, raised $60MM to start Rippling, a new SaaS company that helps organizations set up and manage access to all of these applications. Largely due to bottoms-up distribution, the number of applications being used inside today’s companies has gotten way ahead of many system administrators.

Related to all of this, we’re due for an economic slowdown. Recessions seem to come around every ten years; we had the oil price shock recession that started in 1990, the tech bubble recession that started in 2000 and the mortgage crisis recession of 2008. We’re just about due for another one as we head towards 2020. When economic growth slows, it’ll be interesting to see the impact on many of these SaaS products. Many of them seem like ‘nice to haves’ rather than ‘must haves’. If that’s true, you have to wonder how many CFOs will cut back on some of these products and force their teams to go back to using tools like Excel. ‘Bubble’ is a strong word. And those that are bullish on SaaS will tell you that the market share of enterprise software that sits on the cloud is still a small fraction of total enterprise software spend. But it does seem logical that the boom is SaaS is supported by the bull market we’ve been in.

Enterprise Network Effects

Perhaps the most exciting thing happening in SaaS these days is network effects across companies. Network effects happen when you have a product that gets more valuable to each user as more users use it. Facebook is a classic example — the more friends you have on Facebook the better your experience is on Facebook. But now we’re seeing cross-company network effects all over the place. Box.com allows companies to share files with their customers. Companies can invite their customers to Slack channels. My company, PatientPing, is a classic example of how this happening in healthcare. It will be interesting to see how far this goes. Competitive and privacy concerns cause companies to be hesitant to share and open up their data troves to competitors and even vendors in many cases. If a company like Salesforce could find a way to get their customers to open up their data it would change the world of enterprise software. The use cases would be infinite. A fun trend to watch in the coming years.

It used to be that employees would sit around the water cooler chatting about systems and processes that don’t work as well as they could or complaining that they’re spending too much time doing low-value work that could be automated with software. This is still true. But now that it’s so easy and inexpensive to launch a software company, many of those same employees are realizing that other companies have the same set of problems and they’re building companies around solutions to those problems. As we’ve seen with Slack, Zoom, and others, some of these solutions can be multi-billion dollar companies.

Enterprise software used to be considered the boring part of tech. It doesn’t seem so boring anymore.

How Silicon Valley Became Silicon Valley (And Why Boston Came In Second)

When I was a kid growing up in central Massachusetts, I remember that a bunch of my friends' parents worked for super high growth tech companies like Digital Equipment Corporation (DEC), Data General, and Prime. While some people reading this may not have heard these names, these companies were behemoths. In the late eighties DEC alone was one of the largest companies in the world and employed more than 120,000 people. These companies were booming at the time in an area known as the “Route 128 Corridor”. Route 128 is a highway that runs south to north about 10 miles to the west of Boston. The area was a hub for technology companies — mostly focused on semiconductors, microprocessors, and minicomputers. It seemed like almost all my friends' parents worked at one of these companies or a company that provided support to these companies.

I also remember the bust that came in the early nineties when many of these companies downsized and thousands of people lost their jobs. It was a rough time for many people in the area.

What I didn't know at the time was that there were a set of competitors based in Santa Clara County, California, in the area now known as Silicon Valley, viciously competing with the Route 128 companies. Companies like Hewlett Packard, Intel, and Apple.

Most people now know that the Silicon Valley companies came out on top and that the tech scene in the area outpaced eastern Massachusetts significantly. Massachusetts remains one of the top 3 tech hubs in the U.S., dominates biotechnology, and is well on its way to becoming the country’s Digital tech hub. But outside of healthcare, the Silicon Valley area is far ahead and sees about 3x the number of startups and venture funding than the entire state of Massachusetts.

That said, back in the mid-1980s, you would've had no idea which region was going to come out on top. It could’ve gone either way.

AnnaLee Saxenian wrote a phenomenal book about all of this titled, Regional Advantage: Culture and Competition in Silicon Valley and Route 128 that examines the differences between the two regions.

Having lived in and worked in both areas, here are some of the key differences between the regions that I think allowed Silicon Valley to outperform. Certainly some of the takeaways are isolated to these regions at that point in time. But as lots of cities across the country try to increase the number of tech startups launched in their communities, many of the lessons from the battle between Silicon Valley and Route 128 can be applied by policymakers and tech leaders today.

Cultural differences

Massachusetts had a much more traditional, risk-averse approach compared to the Valley. A big reason for this comes from the parochial and puritanical cultural history of Massachusetts. But, more practically, it also comes from the fact that most people that worked in Silicon Valley weren’t from California. They were from the east coast or the midwest. You can’t underestimate the impact this has on a region. People aren’t spending time with their high school friends or church friends or summer camp friends. They’re spending time with the people they work with. And what do they talk and think about during that social time? Work. They’re bound together by their work. And they're much less worried about trying something new and failing at it because their friends and family back home may not even know about it. An executive that worked on both coasts described it this way in the book:

“On the East Coast, everybody’s family goes back generations. Roots and stability are far more important out here. If you fail in Silicon Valley, your family won’t know and your neighbors won’t care. Out here, everybody would be worried. It’s hard to face your grandparents after you’ve failed.” —William Foster, Stratus Computer

This meant that people in the Valley were much more willing to take risks, start companies and jump from job to job. As they jumped from job to job and made friends with people at work, they created networks centered around their work across several companies in the region. It was common for an engineer to quit their job on a Thursday and show up at another startup on Monday. These new experiences led to more friendships and led to a ton of collaboration between companies and an openness to sharing with one another for the greater good. It was common for Silicon Valley competitors to call one another for help with technical problems. This kind of collaboration created a rising tide for everyone in the area. The power of this kind of environment is enormous.

By contrast, in Massachusetts, most of the people working in tech were from New England. From the book:

”The social world of most New England engineers, by contrast, centered on the extended family, the church, local schools, tennis clubs, and other civic and neighborhood institutions. Their experiences did little to cultivate the strong regional or industry-based loyalties that unified the members of Silicon Valley’s technical community. Most were from New England, many had attended local educational institutions, and their identities were already defined by familial and ethnic ties.”

There was a separation between work and social life for Route 128 workers. For workers in the Valley, it was much more of a grey area. Workers in Route 128 tech often went right home after work and immersed themselves in their local towns, where they had ties that went back generations. Workers in the Valley didn’t have these ties. Instead of driving several miles back to their town, they were more likely to go out to dinner or to a bar in the area to talk about technologies and markets.

Job hopping

As mentioned above, workers in the Valley would jump from job to job growing their network and gaining new experiences. Route 128 had a much different culture where loyalty was highly valued and if you left you could never come back. Workers often stayed at their jobs for 10+ years. This was unheard of in the Valley. Workers felt that they were working for the Valley — the community — rather than for an individual firm. If they decided they wanted to come back they were often welcomed with open arms. As I've written in the past, this impact is felt today as California has banned the use of employee non-compete agreements while Massachusetts has allowed them to persist.

Collaboration with universities

Stanford actively promoted startups by offering professors up to help with product development and created several funding mechanisms for new ideas. MIT took a far more conservative approach and was very reluctant to invest dollars or time into things that were too risky. This created artificial walls between the best tech companies and the best technical research. Many of the east coast companies claimed they had better working relationships with Stanford and Berkeley than they did with MIT and Harvard.

Dependence on government contracts

Because of its proximity to Washington, Route 128 companies had lots of reliance on government contracts that had long term obligations that restricted innovation. It also (appropriately) led to a secretive culture that stalled collaboration with associations, competitors, partners, and other organizations in the local ecosystem. By contrast, by the early seventies, Silicon Valley companies were receiving far more financing from venture capital investors than they were from government contracts. The east coast's dependence on government contracts made widespread collaboration nearly impossible.

Geography

Silicon Valley companies started around Stanford and expanded to cities like Mountain View and Santa Clara but couldn’t go too far as they were locked in by the Santa Cruz mountains to the west and the San Francisco Bay to the east. This led to a very dense community of tech companies. By contrast, the Route 128 companies were spread far and wide. DEC, the largest of the companies in the eighties, was based in Maynard, with more than 20 miles of forest separating them from the hub of Route 128.

Organizational structure

Related to the dependency on defense contracts and its proximity to established political and financial institutions, Massachusetts companies were more formal and created organizational structures that had a strong resemblance to the military. This kind of organizational design can slow innovation as the lower rungs of the ladder are less reluctant to offer new ideas and there's far less cross-functional learning. Executives had their own parking spaces and executive dining rooms. Stock options were only offered to those at the highest levels of the organization. This even applied to work attire — the uniform for 128 companies was a jacket and a tie, in the Valley it was jeans and a t-shirt.

Today, something like 75% of all venture capital funding goes to three states -- Massachusetts, California and New York. As governments and entrepreneurs across the country try to expand the number of tech companies that emerge and grow in their communities, it’s important to remember that ecosystems create a lot more jobs than companies. The key is less about funding and micro-incentives and more about creating the complicated environment that allows an entire ecosystem to thrive.

Going All In On Content

Several weeks ago I spoke to a partner at Andreessen Horowitz (also known as a16z), the prominent, Silicon Valley venture capital firm.

He explained to me that his firm takes more of a "marketing" as opposed to a "sales" approach in attracting entrepreneurs to their funds. For people that know the firm, this may seem obvious.

When I started working in tech, the best venture capital firms did not take this approach. Their investments were driven by rooms full of young associates cold calling entrepreneurs to find the best companies. a16z has taken a different approach and has focused on getting entrepreneurs to come to them.

The way that they’ve accomplished this is through the production of great content — blogs, social media, podcasts, videos, etc.

The quality of their content is phenomenal. The a16z podcast has been a favorite of mine for years. One of their founders, Ben Horowitz, has written a best selling book, The Hard Thing About Hard Things, that has become an indispensable guide for people starting a company. They’ve also recruited partners that were great at producing content long before they joined the firm. Chris Dixon, now a partner at the firm, was a major inspiration for me to start writing this blog. He no longer blogs independently but you can find his archives here. I also followed Benedict Evans closely long before he joined the firm back when he was a mobile analyst in Europe and writing great stuff about tech. Now he's a partner at a16z. He’s arguably become the new Mary Meeker of tech with his annual State Of Innovation Talk.

a16z made a brilliant move by recruiting these two guys. I'm sure they're great investors in their own right, but I know for a fact that they're incredible content producers.

Case in point: when my company started talking to a16z about taking an investment from them I was very excited; not because I knew the firm well, but because I had an extremely high opinion of them that was driven by their content before ever actually meeting or speaking with anyone from the firm. That is the definition of great content marketing. High quality content that doesn’t ask the consumer for anything, but passively improves the perception of the company or product.

I just started reading Seth Godin’s new book, This is Marketing, and in it he reminds us of the right way to do marketing:

The other kind of marketing, the effective kind, is about understanding our customers’ worldview and desires so we can connect with them. It’s focused on being missed when you’re gone, on bringing more than people expect to those who trust us. It seeks volunteers, not victims.

Seth has been saying this in one way or another for almost 20 years (at least since writing the Purple Cow) and it’s a great way to think about content production. If a16z’s content went away, a lot of people would miss it. That’s a great standard.

Most marketers are producing some form of content these days. But very few are going all in. At last check, a16z sees about 2,000 qualified inbound pitches per year, only to make 20-40 investments. So going all in is clearly working for them.

Marketers don’t necessarily need to hire the top thought leaders in their space to create content. But it’s worth thinking about what going all in would mean for your brand and asking yourself if anyone would miss you if you were gone.

The Issue Of The Day

I’ve found that one of the most important things an executive can do is to regularly identify the “issue of the day” for their company or their team or their group and to address it with urgency.

Peter Drucker refers to this as identifying “what needs to be done?” Ideally, it's one thing, but definitely not more than two.

The discipline to continuously have this in mind and to have the emotional intelligence to be able to accurately identify the issue of the day is difficult and something that separates great leaders from the rest.

The issue of the day could be a number of things: some are opportunities, some are problems, some are strategic, some are tactical, some are elated to business problems, some are related to people problems. An example could be launching a product that will create a large growth opportunity or retain a specific set of customers; onboarding new managers and making them into productive leaders or something as small as fixing a commission policy or plan that is frustrating for top salespeople. The key is the ability to recognize the issue and measure its importance and urgency in comparison to the hundreds of other burning issues that could be addressed.

One of the most difficult things about determining the issue of the day is that different people will often have different perspectives on what the issue of the day actually is. The board, the CEO, the executive team, the line managers will often have different opinions. Getting alignment here is crucial. And, just as important, if alignment can’t be gained across all relevant stakeholders, the executive must make the call on what's most important now and focus on that thing more than any other.

Silo And Un-Silo

Back when I was working at Next Jump, an e-commerce company that enabled big brands to offer their products and services at a discount to large employers and customers of large consumer marketers, our primary objective was to drive spend through our website.

My specific job was to drive user acquisition. I was focused on acquiring more companies to buy the product for their employees and then to get employees (users) to register an account and keep coming back. My colleague, I'll call her Jane, was in charge of site merchandising and had the job of converting those users into buyers once they came to our site. So my job was to get people to our site, and her job was to get people to buy once they arrived.

Every week our teams would meet to review results. We’d start by focusing on the total spend on our site during the previous week. Some weeks the numbers would be up and some weeks they'd be down. In the weekly meeting, our leadership would look at Jane and ask what happened during the previous week. Frequently, Jane would look at me and say, “we didn’t have a lot of spend on the site because we didn’t have a lot of traffic.” Other weeks I would look at Jane and say, "we had plenty of traffic but that traffic didn’t convert into spend."

This was obviously unproductive. We were pointing fingers at one another and defending our impact on the overall number which meant that nobody was responsible for the overall number.  

Our solution to this problem might seem counterintuitive: we created silos.

We came up with something we called “the box.” My team had the job of getting people into the box (get people to the site) and Jane's team had the job of making good things happen once they were in the box (get people to buy things once they were on the site). My primary metric was weekly unique users and Jane’s primary metric was conversion of those users (spend per unique user).

This changed everything. We set up specific metrics for each team where neither one of us could ever blame the other. My team wasn’t measured on overall spend (something we couldn’t control alone) and Jane’s team wasn’t measured on overall spend (something her team couldn’t control alone). We were measured on our slice of the spend metric (users and conversions) and if we both did our job we had a great week. This change created crystal clear ownership and accountability which led to lots of creativity and powerful initiatives to drive each teams' numbers. Our overall spend numbers started heading up and to the right.

Over time, though, things started to break down. Because we were so silo’ed my team wasn’t focused on the overall company goal, we were focused on our team goal. So my team would do whatever we could to drive users to the site regardless of the impact on spend. We would repeatedly promote offers from Target and Best Buy (brands that had 'mass appeal’ and would drive traffic but had relatively low value discounts with low conversion rates). This would drive a ton of traffic to the site, but the traffic didn't convert. Similarly, Jane was focused on conversion so she would promote the best offers on the site (30% off Juicy Couture, as an example). Users would come to the site expecting to see an offer from Best Buy and would see a great offer from a brand they had no interest in and a not so great offer from Best Buy. This led to a low-quality experience, lower spend, and user churn. Overall growth in spend began to slow down.

In response, we quickly setup processes to begin working more closely together. We had to fix the disconnect. We had to collaborate.

We built a monthly merchandising calendar that every team member could access in real-time. We set up several 10-minute check-ins so that the acquisition team knew exactly what the site merchandising team was promoting each day and which offers were converting at the highest rates. The acquisition team would send all marketing emails to the merchandising team prior to sending to users to get their sign off. We used data from the acquisition team to convince the mass appeal brands to offer deeper discounts. 

At first, these efforts forced collaboration. But over time the collaboration became much more organic. The teams became inclined to be collaborative. After a few weeks, the numbers started to head back up. That said, we definitely didn’t abandon the silo’ed metrics for each team. Hitting those metrics was still the primary job of each team. What changed was the approach we took to hitting each of our metrics. It was about transparency and collaboration and a broader focus on what was best for the company as a whole.

The point here is simple: not having silo’ed metrics is a bad thing and being too silo'ed is a bad thing.

As an example, sales teams need to have silo’ed sales metrics that they’re accountable for to force ownership and creativity and high performance. But if the sales team is only focused on one top line metric and nothing else, over time they’ll be motivated to close deals that may be bad for the company and will lead to high churn rates. They have to have a silo’ed metric but also be forced to consider what’s best for the company as a whole.

Companies get in trouble when they lean too far towards one side. Telling groups to just work together to drive an overall number leads to a lack of accountability and creativity. And too much separation leads to a lack of collaboration and focus on the broader goal.

Well run companies find a balance and learn to silo and un-silo.

Bottom-Up Enterprise Software Is Now Mainstream

Back in 2012 I wrote about the 'bottom-up' approach to enterprise software distribution. Bottom-up happens when a product is initially procured by an individual employee or group of employees and then, once a critical mass is reached, a seller upsells the product across the organization with additional features, bulk pricing, etc. This has now become a mainstream approach to enterprise software distribution. I recently attended a Go-to market conference held by a prominent venture capital firm and they advised everyone that the first question an enterprise startup should ask before designing a go-to market strategy is: are you bottom-up or top-down?

With successes like Atlassian and Slack and others the bottom-up model has come a long, long way in recent years. 

However, bottom-up doesn't work for every industry -- at least right now. Take healthcare as an example. To sell a product into a large healthcare organization you must get IT approval, work with compliance, promote workflow changes, train staff, potentially integrate into an EHR, address HIPPA concerns and do lots of other stuff before the first user can log-in. The top-down model can be a requirement.

That said, I believe we’ll start to see this change. The bottom-up model will only become more mainstream and will take market share from vendors that don’t adapt. Traditional enterprise vendors should take note and start to evolve.

Some specific implications:

Software vendors need to prioritize the user of their product over the buyer of their product (they're quickly becoming the same person). Engagement and user satisfaction metrics should be equally important as sales metrics. Employees are increasingly demanding that the software they use at work function at an equivalent level to the apps they use on their phone. And switching from vendor to vendor continues to get easier. If a product isn't adored by its users its ripe for disruption.

This change also means that product must play a much larger role in distribution. The product must be remarkable so people will talk to their colleagues about it and it must be easy to spread the word about and nearly effortless to access. If you look at the fastest growing enterprise startups (see below) the one thing you’ll find is that nearly all of them make it extremely easy for a new user to sign up.

Finally, this trend will bring big changes to sales and marketing teams. Marketing (messaging from one to many) will play a larger role in the selling process as it'll be responsible for acquiring the product's early users. This changes messaging and use of channels in a big way. When any employee within a company is a potential buyer your marketing starts to look a lot more like Apple's than Oracle's. And salespeople will need to increase their selling competence to represent both the user (human factor data insights, workflow changes, usability) as well as the enterprise buyer (product context, integration, ROI).

The line between enterprise software and consumer software is continuing to blur. And while there are industries where top-down will continue to thrive, the processes and systems and beliefs that have enabled this approach are beginning to crumble.

In the end, the real threat that bottom-up startups present to top-down vendors isn't just that they may have a more effective way of getting a product into market, it's that their approach requires them to build something that's very unique in enterprise software: a product that people love.

Enterprise User Acquisition & Consumer User Retention

In thinking about a product's user acquisition, the nice thing about enterprise products is that when you get one customer you get a lot of users. You just need to sell one CIO on your product and you’ll quickly pick up thousands of users.

The not so nice thing about enterprise is that you’re going to lose about 20% of those users every year due to employee turnover. Your entire user base is going to turn over every five years. Acquisition scales in enterprise. Retention does not.

The not so nice about consumer products is that, unlike enterprise, you have to acquire users one by one. You don’t have the scalable distribution channel that you have with enterprise. In consumer, user acquisition is expensive and really difficult.

But the nice about consumer products is that once you get users you can keep them forever (you don’t have the turnover problem).

It’s interesting to note that some companies have figured out how to take the good from enterprise and the good from consumer.

One example is eShares, an enterprise product that digitizes paper stock certificates and options and warrants and rolls them up into an easy to use cap table to help startups and startup employees manage their equity. Employees generally sign up for the service just before their start date when they receive an option grant from their new company (to sign the option grant employees need an eShares account). If the employee leaves the company they keep their account open to manage their equity and they can add subsequent option grants from subsequent companies to keep all their documents in one place.

eShares is brilliant in that they have morphed an enterprise product into a consumer product and have reaped the benefits of both models. This is a super powerful way to quickly build a huge set of engaged users and is a great way to get ahead and build a platform rather than just a useful app. I’m sure eShares investors are taking note.