We all know the old enterprise software joke that “no one ever got fired for buying a Microsoft product”. But one of the important points in Auren Hoffman’s post on how Zoom is beating much larger competitors like Google Hangouts and Slack is that larger companies are not that unpleasantly predictable any more:

One of the biggest trends that is driving Zoom’s success is that companies are forgoing the full stack and buying the best-of-breed. The number of vendors the average company is buying from has increased almost 10x in the last 12 years. Companies are happy to buy from many different places. They are even happy to buy from new start-ups. […]

In fact, it has never been easier to sell to large companies. Large companies are open for business. They want to be sold to. They are sick of having a third-rate solution. They want to use the best product. If you can show them your product is superior, they are excited to buy.

This is an exciting development for product managers, especially if you’re building something in the B2B space at a smaller company. With a really good product it’s becoming so much easier to sell to larger companies without the need for the bureaucratic checklists that used to be an impossible barrier to break through (“Are you ISO 9001 certified?”).

That said, in most cases it’s important not to start there. As Box CEO Aaron Levie points out in this article about Slack’s move into the enterprise:

[Slack] have had a methodical process of continuing to drive strategy up market. They started with individuals and small teams, and then departments and bigger teams, and now broader enterprises. It’s been a very thoughtful strategy.

There are many reasons to start your product growth with smaller teams. One is that it will help you make incremental improvements very quickly. But it’s also really dangerous to end up in a situation where most of your revenue comes from a few large customers. So start small, get better, move into larger markets, and then just keep going…

My friend and colleague Garrett Dimon wrote about his experiences building and selling a product in his post Hindsight. He gives some advice based on what he learned. You might not agree with everything, but I think his perspective is really interesting and worth checking out. For example, on the balance between building product and doing marketing:

I don’t want to build an operational system to grow a business and then spend no time on the product. I want to design a company to build the product and serve customers. That’s not to say that there shouldn’t be some type of marketing that will need to be done, but I’d rather find ways where marketing is a by-product of the software rather than a separate activity. Checking analytics and numbers eventually becomes relevant for a business, but it’s a spectrum. I want to check the numbers to make sure the business is healthy, but I don’t want to be in a situation where I’m spending days analyzing or optimizing.

This interview with former Google and Flipkart product leader Punit Soni covers a lot of ground and is interesting all the way through. His thoughts on the importance of a go-to-market strategy is so important, and a trap many product managers fall into:

When an idea is finally in sight, it may be tempting to jump feet first into product building. According to Soni, founders need to resist the impulse to obsess over product to the exclusion of everything else at the very beginning. “It’s tempting to slip into a ‘build it and they will come’ mentality, especially if you’re convinced of your own product prowess. Now I’m a product manager through and through, but I’ll be the first to tell you that product usually isn’t the issue,” he says.

Instead, tackle go-to-market, working through who’s going to buy, why and what they would pay. “Product is more binary in that, either the tech will allow you to do it or it’s not possible. Making sure that you can build a sustainable business model around that product is a far tougher task,” Soni says. “Figure all of that out before you start a company, not as you go along. Once you check that box, then you can become a product-focused company.”

There are some great product tips in Scott Belsky’s How to Shape Remarkable Products in the Messy Middle of Building Startups, but this part about onboarding particularly stood out for me:

You can’t expect new customers to endure explanation. You can’t even expect customers to patiently watch as you show them how to use your product. Your best chance at engaging them is to do it for them — at least at first. Only after your customers feel successful will they engage deeply enough to tap the full potential of your offering.

One of the hardest things to figure out with onboarding is the right balance of selecting defaults (“doing it for them”) and having users learn by doing things themselves.

For example, within Postmark’s onboarding a continuing debate is whether or not we should auto-create a user’s first “server” for them, or help them understand the concept better by making them do it themselves. Finding the appropriate amount of friction to introduce is an ongoing and important challenge for any product’s onboarding.

Eugene Wei’s Invisible asymptotes is a long, excellent article about the importance of not just thinking about product-market fit, but also product-market unfit:

For so many startups and even larger tech incumbents, the point at which they hit the shoulder in the S-curve is a mystery, and I suspect the failure to see it occurs much earlier. The good thing is that identifying the enemy sooner allows you to address it. We focus so much on product-market fit, but once companies have achieved some semblance of it, most should spend much more time on the problem of product-market unfit.

For me, in strategic planning, the question in building my forecast was to flush out what I call the invisible asymptote: a ceiling that our growth curve would bump its head against if we continued down our current path. It’s an important concept to understand for many people in a company, whether a CEO, a product person, or, as I was back then, a planner in finance.

He goes on to discuss those asymptotes for different companies (for example, shipping fees for Amazon). Another interesting bit:

We speak often of the economics concept of the demand curve, but in product there is another form of demand curve, and that is the contour of the customers’ demands of your product or service. How comforting it would be if it were flat, but as Bezos noted in his annual letter to shareholders, the arc of customer demands is long, but it bends ever upwards. It’s the job of each company, especially its product team, to continue to be in tune with the topology of this “demand curve.”

I see many companies spend time analyzing funnels and seeing who emerges out the bottom. As a company grows, though, and from the start, it’s just as important to look at those who never make it through the funnel, or who jump out of it at the very top. The product market fit gradient likely differs for each of your current and potential customer segments, and understanding how and why is a never-ending job.

Figuring out what your product’s invisible asymptotes are sounds like a really good thought process to me. At the beginning of the article Eugene mentions one way Amazon tried (and succeeded) in answering this question:

For people who did shop with us, we had, for some time, a pop-up survey that would appear right after you’d placed your order, at the end of the shopping cart process. It was a single question, asking why you didn’t purchase more often from Amazon.

Another technique he mentions:

One approach I’ve taken when talking to companies who are trying to achieve initial or new product-market fit is to ask them why every person in the world doesn’t use their product or service. If you ask yourself that, you’ll come up with all sorts of clear answers, and if you keep walking that road you’ll find the borders of your TAM taking on greater and greater definition.

A good way to frame this could be to ask yourself something like this:

If we didn’t change anything about [product name], at what point would we hit a growth ceiling, and what are the factors that would cause that?

If you can have a reasonably confident answer to where the S-curve inflection point will be, you can start planning on avoiding it early. That’s a worthy effort, and definitely something I intend to think through for our products.

This is a fairly old post, but I only recently came across Dan McKinley’s Choose Boring Technology. It is so good.

What counts as boring? That’s a little tricky. “Boring” should not be conflated with “bad.” There is technology out there that is both boring and bad. You should not use any of that. But there are many choices of technology that are boring and good, or at least good enough. MySQL is boring. Postgres is boring. PHP is boring. Python is boring. Memcached is boring. Squid is boring. Cron is boring.

The nice thing about boringness (so constrained) is that the capabilities of these things are well understood. But more importantly, their failure modes are well understood.

He goes on to explain the process you should go through before you try out a new technology.

Spotify has been in the news quite a bit recently, especially since their IPO announcement. The best article I’ve read so far about Spotify’s business model (and challenges) is Ben Thompson’s Lessons from Spotify:

Spotify’s margins are completely at the mercy of the record labels, and even after the [lower royalties] rate change, the company is not just unprofitable, its losses are growing, at least in absolute euro terms.

Ben goes further to explain how difficult it would be for Spotify to cut out record labels completely:

Notice how little power Spotify and Apple Music have; neither has a sufficient user base to attract suppliers (artists) based on pure economics, in part because they don’t have access to back catalogs. Unlike newspapers, music labels built an integration that transcends distribution.

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Profitability aside, it’s fascinating and kind of scary to get a sense of the oversized role that Spotify plays in deciding what becomes a hit song. Austin Powell digs into the details in his article Inside the booming black market for Spotify playlists:

The biggest of those playlists can essentially manufacture hits. A single add to Spotify’s influential RapCaviar, which boasts more than 8 million followers, can result in hundreds of thousands of streams, depending on where it’s placed and how long it stays there. RapCaviar has been credited, for example, with making Smokepurpp’s “Audi” go gold, with 68 million streams and counting.

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But wait, there’s more (as the say). Some of Spotify’s biggest playlists are owned by none other than the record labels themselves. From Liz Pelly’s The Secret Lives of Playlists:

On other playlists, you’ll occasionally notice different logos: the thick cursive word Filtr, the all-caps logo for Topsify, or simple rounded text reading Digster. These are the playlisting brands owned by the major labels: Filtr by Sony, Topsify by Warner, and Digster by Universal.

What does this mean?

Outside of the Spotify staff-curated playlists, those curated by Filtr, Digster and Topsify have more visibility on the Browse pages than any other playlisting brands, individuals or labels. With these playlists, employees of Filtr, Digster and Topsify can simply log in and add tracks.

“Things like Topsify, Digster and Filtr remain good resources, especially for [major label] developing artists,” says Jeff. “I know that I can plug in such-and-such track to five [of our] playlists and start to rack up some plays, some revenue for that artist, get it in front of some new listeners, and you also get some algorithmic stuff going. Like Release Radar and Discover Weekly.” By using Filtr, Topsify and Digster playlists to generate activity on their own material, the majors effectively use these playlists to pump their artists into Spotify-owned algorithmic playlists.

The musical world belongs to the “curators” and algorithms. We’re just listening in it. And the company that has the most control over it all is not even close to being profitable.

In Airbnb and the Unintended Consequences of ‘Disruption’ Derek Thompson uses Airbnb as an example to explain how it’s not as easy to call tech innovation a good or a bad thing. It’s complicated…

Airbnb lowered prices for tourists, supplemented the income of renters, and simply made travel to major cities more fun. But upon inspection, it shares some things in common with more-controversial companies—albeit with less grave implications. Facebook and Twitter design for attention, but incidentally encourage mendacious outrage and trolling. eBay and Amazon design for open marketplaces, but incidentally encourage the frenzied resale of bulk-ordered toys around Christmas. Airbnb was supposed to challenge hotels by letting tourists pay renters. But its platform is unwittingly producing a subsidy of tourists, paid for by nonparticipating urban dwellers, who bear the cost of higher rental prices.

Jia Tolentino’s takedown of the gig economy for The New Yorker is so good. From The Gig Economy Celebrates Working Yourself to Death:

At the root of this is the American obsession with self-reliance, which makes it more acceptable to applaud an individual for working himself to death than to argue that an individual working himself to death is evidence of a flawed economic system. The contrast between the gig economy’s rhetoric (everyone is always connecting, having fun, and killing it!) and the conditions that allow it to exist (a lack of dependable employment that pays a living wage) makes this kink in our thinking especially clear.