As a non-technical founder of a startup, you may think you’re at a disadvantage. You’re acutely aware that, in the disparaging words of YC’s Paul Graham, you’re “just some business person.”

But don’t overlook the value of what you possess: insight into a market opportunity that is closed to outsiders as well as direct access to the initial buyers.

For tech-enabled founders such as yourself, mobilising an effective product and engineering team in the early stages of your startup journey is a crucial enabler. And solving this challenge requires more than just a capital partner, it requires a digital partner too.

Part 1: The Founder’s Dilemma

Picture the scene: you’re a highly skilled professional; let’s say a doctor or a lawyer. You’ve been working in your sector for at least a decade and your career prospects are bright.

But something at the back of your mind is bothering you.

You’ve had an idea for a new software product that, if it existed, would make you and your colleagues faster, more efficient and more informed; better versions of your professional selves.

The more you think about it, the greater your desire to see it happen.

But, you’re not technical. You have little commercial experience and enjoy a good standard of living which will be hard to forego.

A few years ago, you wouldn’t have seriously entertained the notion. After all, you’ve never considered yourself an entrepreneur. But now everyone seems to be starting a ‘tech’ company despite knowing next to nothing about developing software.

Maybe you could be a ‘startup founder’ after all?

Having made up your mind, your instinct is to move quickly. Your immediate priority is to to build the first version of your product idea and test it in the market. To do this, you’ll need money. Partly for yourself, but mainly to acquire the additional expertise you need.

You’re not sure how much it will cost but doubt your limited savings will be sufficient. You assess your options and conclude there are three routes forward:

1. Learn to code and build the initial version of the software yourself.
2. Hire a ‘technical co-founder’, give them the role of CTO and rely on them to build a team.
3. Find a ‘dev shop’ or agency and pay them to build your product.

You quickly discount the idea of learning to code as too inefficient and time consuming. As Daniel DeLaCruz from Dualboot Partners observed,

“Non-technical leaders should not learn to code. However, they should become acutely familiar with the process of building software.”

You take this to heart and read everything you can with the words Agile, Lean or Product Management in the title. They seem to make sense. More sense than that Udemy course on Javascript, at least.

Hiring a CTO to build an engineering team now seems like the most appealing option. Part rock-star, part comfort-blanket, the notion of having someone on your team who ‘knows about tech’ is compelling.

But, thanks to the explosion of startup activity (not to mention aggressive recruitment by companies like Google, Amazon and Facebook) engineering expertise isn’t always easy to come by.

As a non-technical founder, it’s unlikely your niche idea will appeal to an industry veteran. You also worry about how to evaluate possible candidates and how much this unicorn-shaped figure may cost. It’s likely they’ll expect a high salary and a lot of equity in return for their involvement.

You’ve heard stories about non-technical founders being bamboozled by their CTOs who promised much but delivered little. After a few months, the CTOs often left for more exciting jobs at DeepMind (or somewhere similar) taking half the firm’s equity and leaving a half-finished product behind.

You consider Option #3.

Cash for services providers — or ‘dev shops’ — remove the problem of hiring and retention but bring different concerns. You’ve met founders who distrust their technical suppliers. The most common complaint seems to be a lack of responsiveness and commitment.

However, the root cause of this mistrust seems to arise from an absence of aligned incentives and shared outcomes. It’s in a dev shop’s interest to maximise the time they spend working on your product. But it’s in your interest to extract maximum efficiency from them.

The lack of strategic guidance also concerns you. When your team are charging purely for time, long-term plans usually fall by the wayside in favour of short-term fixes.

And how do you know you can trust what you’re being told? As a non-technical founder, you’re at risk from the Dunning-Kruger effect. Buoyed by enthusiastic false confidence, you (literally) don’t know what you don’t know so can’t spot your mistakes or errors of judgement.

What you really need is a genuine venture partner. One who can provide both technical expertise and capital…

Part 2: Founder/Market Fit

Venture investing has been compared to building a stool with three legs. The legs are: people, markets, and innovative products.

Different investors emphasise different legs of the stool. Thanks to the tremendous influence of Andy Rachleff, most emphasise the overarching value of product/market fit.

However, in the B2B world, it’s easy to overlook the value of founder-market fit. In contrast to the self-doubt they instinctively feel, professional founders are in a privileged position despite their lack of technical knowledge.

Firstly, a professional founder has secrets: unique insights into market opportunities that are hidden to outsiders.

Being problem-lead protects them from the principal reason for startup failure; known at Y Combinator as SISP, a Solution in Search of a Problem. The problem they seek to solve is not theoretical, it’s something they’ve encountered and wrestled with personally, often for many years.

Second, their network means they can immediately (and credibly) connect with the initial users of their product. This again is an ‘unfair advantage’; professional credentials bring an authenticity not easily replicated by outsiders.

Finally, one should never underestimate the extent of the cultural divide between engineering-lead startups and corporations, mainly to the discredit of the former. Corporate Heads of Innovation are frequently exasperated by the behaviour of the startups with whom they engage and advocate for internally.

Common complaints include a disdain for information security concerns, dogmatic adherence to Amazon Web Services and an expectation that users should adapt their working practices to accommodate new software, rather than the other way round.

I’m not sure which guidebook recommends treating prospects with arrogance and discourtesy, but it’s been well distributed in some spheres.

A founder who understands how to conduct themselves inside a large organisation, who shows deference to rank and an empathy for the cultural challenge faced by Innovation Leads has a far greater advantage than they realise.

Part 3: Capital and Code

Despite their privileged perspective, non-technical founders still face execution-risk related to software development in the earliest stages of their startup. Unique market insights can be easily derailed by an inability to deliver a solution.

When you’re ‘pre-product, pre-revenue’ the challenges you face are formidable. But when you’ve proved there’s a market for your idea (ie. when you’re ‘post-product, post-revenue’) your prospects are transformed. At that point, you’ll attract as much capital and talent as you need.

Those looking for the most efficient way to reach that point should consider Venture Services; a small but growing category within the juggernaut that is the venture capital industry.

Venture Services means the exchange of software services for equity in a startup, as opposed to one purely of cash.

As Derrin Hill, of Venture Services firm RevRoad, observes,

“Systems solve problems more than people do.”

Venture Services firms acknowledge the execution and hiring risks faced by non-technical founders and address them by providing software engineering and product management resources to founders. They are ‘operator angels’ at scale.

Although it’s fashionable for venture capitalists to extol a gameplan of ‘finding the smartest possible founders and backing them to the hilt’, non-technical founders need both capital and code in the early stages to succeed.

The TLDR

There are tech businesses and there are tech-enabled businesses and it’s important to differentiate the two.

The first wave of startups were lead by computer science dropouts and fresh-faced software engineers who built (then dominated) new markets in consumer technology.

But, in the new wave of enterprise technology, most founders will be experienced professionals. Domain, rather than technical, experts. They’ll possess unique market insight but lack the technical expertise necessary to realise their business vision.

For these founders, Venture Services could be the best way forward.

“Venture services focuses on solving a specific sub-section of founder needs: the need for quality software and the need for capital to pay for it.”

This post is the second part in a series on venture and venturing. Part One examined the ‘what’ and the ‘why’ of venture, primarily from the perspective of the providers.

This second part deep dives into ‘how’ venturing actually works in the context of venture services, the corner of the venture ecosystem I occupy as a partner of London-based Pivot Venture Services.

My first experience of venture was via PreHype, a pioneer of the corporate venture model. PreHype facilitate a number of innovation programmes globally and, in collaboration with NewsCorp, helped birth Newsmart, for whom I was Product Director in 2015.

My first real break in venture came as MD for Castle (aka ‘Castle Digital Partners’), a venture services firm based in Charlotte, NC. I set up Castle’s London Studio and inked their first European venture deals.

Venture, in all its forms, is the professionalisation of angel investing.

Angel investment has a bad reputation. One that is characterised by chaos, amateurism and exceptionally high levels of risk.

I once attended an investment seminar where a seasoned angel presented his view that one shouldn’t expect to make any money from angel investing and that it was more about having fun.

This seemed counter-intuitive. But when your company is you, a big idea and a slidedeck, it’s hard to convince others to back you (especially if you’ve never started a company before.) Given the obstacles, it’s a miracle first-time founders ever make it out the gate.

Super-early startups are a ‘dead-zone’ analytically. Valuations, forecasts, market sizes and business plans are like Shrodinger’s Cat; simultaneously worth zero and one million.

Institutional investors don’t engage until much later on. They are scaleup, as opposed to startup, investors. They enjoy the comparative luxury of a working product, market traction, even revenue from the companies in which they invest.

What is Venture Services?

Venture services firms serve two sets of interests, those of early-stage founders and those of early-stage (‘angel’) investors. They facilitate transactions that align the interests of both towards the rapid creation of equity value.

Jeff Bezos is well known for advising founders to ‘bet on the things that don’t change’ if they want to build a durable business. He bet on customers’ desire for low prices and fast delivery not changing and both seem to have paid off well.

For venture services firms, the bets are as follows:

1. We are betting that startup founders will continue to need capital and great quality software.
2. We are betting that wealthy individuals will increasingly want to invest in startups whilst reducing the risk of losing their investment. (In the UK in particular, they will continue to take advantage of the UK Government’s generous tax relief schemes, such as SEIS and EIS, for as long as they are available. More on this later…)

Bet #1: Founders

Proptech. Lawtech. Connected Enterprise. Smart Cities. IoT. The tech-sector is diversifying rapidly. And so is the archetypal startup founder.

Outside of Silicon Valley, it’s increasingly rare for first time founders to be hackers or coders. Instead, most are domain experts who have identified an opportunity to disrupt or transform the status quo with software. They are, in the words of Paul Graham, “just some business person.”*

[*Important note: Mr Graham uses this term in a somewhat derogatory manner. We most definitely do not.]

And for “just some business person” with a vision but no technical experience, the challenge of building an initial product and finding sufficient capital to pay for it can be insurmountable. It’s a much greater obstacle to startup progress than is commonly acknowledged.

Historically, non-technical founders looking to start a company have had two options to choose from.

Either they find a technical co-founder / CTO and rely on them to build a product in exchange for a healthy slice of equity.

Or they reach further outwards to one of the many providers of software services (aka ‘dev shops’), typically located on the eastern edge of the European Union (think Poland, Czechia, Belarus, Ukraine, Russia), or in India and pay them in cash.

Each route has its pros and cons, both of which have been well documented here and here.

Venture services firms offer a third option to founders, one that sits between an invested employee and a detached supplier. And one which, ideally, offers the benefits of both.

These firms don’t create companies or lay claim to their ideation. They partner with mission-driven founders to solve a specific subsection of their needs: the need for working software and the need for capital to pay for it.

For startup founders, finding a partner willing to remove the two biggest obstacles to early-stage progress can be compelling. It’s common to hear founders talk of their desire for value-added capital. Done correctly, venture services should feel like an accelerator on steroids.

By trading in equity, venture services firms attain goal congruence with founders that suppliers are unable to achieve. This creates a partnership culture of trust and shared outcomes.

What’s most appealing to investors, however, is that venture services significantly reduces risk. This includes team risk, technical risk and (above all) execution risk at pre-product stage.

The percentage of startups who burn through their initial capital but fail to deliver an actual product remains surprisingly high. This usually occurs when CEOs unexpectedly part company with their CTO and find themselves with half a product that has little or no value.

Experienced angels will have witnessed this on multiple occasions. Having confidence that a product will be delivered, on time and on budget, is rare and appealing.

Bet #2: Investors

Investment decisions don’t exist in a vacuum. They occur within a complex macro-economic environment of financial incentives and opportunities, notably tax relief and grant-funding.

All governments seek economic growth. As startups are high-growth vehicles by definition, governments are increasingly trying to incentivise early-stage investment. Widespread awareness of the generosity of these schemes, combined with the explosion of interest in startups, has created a perfect storm of capital searching for a home.

By way of example, let’s examine the UK government’s Seed Enterprise Investment Scheme, better known as SEIS. For early-stage startups, SEIS is the financial equivalent of methamphetamine.

In the words of CrowdCube,

“To say that the Seed Enterprise Investment Scheme, or SEIS, is incredibly generous is somewhat of an understatement. Of course we all hope our investments do well, but if you pay tax at 45% and make an investment of £10,000 that fails completely, you only lose £2,750 due to the tax relief.”

Wealthy individuals with high income tax bills have stampeded to find startups that will allow them to take advantage of the tax relief offered by SEIS. But few have direct access to qualifying companies or the time to find them.

Whilst the relief is an end in itself, investors also want to protect their investment and minimise downside potential. They’re not just looking for startups that qualify for SEIS tax-relief. They’re looking for the best startups that qualify for SEIS tax-relief.

Via access to select early-stage startups, venture firms are well positioned to broker these trades.

How Venture Services works

In Part One, I observed that the economic details of venture deals are rarely disclosed. It’s hard to quantify how much equity (and cash) really changes hands between founders and venture firms. The spectrum is very broad.

As a first stab at demystification, below is a breakdown of how a successful venture engagement works at Pivot. It’s a happy path, one in which all the boxes are checked.

The very short summary is that venture services means building software in exchange for equity, syndicating part of the equity to cover costs, and retaining the remainder as margin. This aligns the firm’s incentives and upside with those of the founder(s) with whom they partner.

The slightly longer version is as follows:

1. The firm meets a startup founder and makes an investment decision based on the market opportunity and the extent to which quality software will create momentum and initial traction.
2. Working closely with the founder(s), the firm scopes and estimates the cost of the software development required to help the startup reach its agreed goals.
3. The firm’s Investment Manager determines if additional cash is necessary and calculates the equity premium the firm will add as margin.
4. The firm agrees a pre-money valuation with the founder(s) and makes a proposal to develop their software in exchange for a % of the equity in the company.
5. If both parties agree to terms of the venture proposal, the founder(s) transfer the agreed equity to the firm, typically via an option or an Advanced Subscription Agreement (ASA).
6. The venture firm designs, develops and deploys the agreed software for the startup and maintains/iterates upon it for an agreed period of time. The software engineering team are paid directly by the venture firm from their fund capital or by syndicating a % of the equity to investors in exchange for cash.

Why Venture Services is Hard

Compared to other forms of venture capital, venture services remains niche.

This is primarily due to the complexity of the business model. There are more moving parts, and more factors to align, in a successful venture deal than a conventional investment. Most investors prefer to avoid the additional overheads and responsibilities of being a venture partner.

Additional reasons I have observed are as follows:

#1: Cashflow

In Part One, we explored why venturing can’t be funded by profits from a services business; at least not long-term.

Services businesses generate revenue in the form of cash. Venturing is investing, which is deferred revenue. What makes the two irreconcilable is usually the cost base.

As software companies are asset-light, the lion’s share of their cost base is payroll. If you have a lot of salaries to pay at the end of each month then you need the cash to pay them. And, if all of your profits are funding ventures, then you are dangerously exposed in a downturn.

I have experienced services companies with large workforces all but go bankrupt trying to move into venture. The consequences were drastic and unfortunate, mainly for the employees.

So, how can venture firms build software without the overhead of large team of developers and designers? We solve for this at Pivot by mobilising teams on a deal-by-deal basis and working within a tightly managed, fixed cost environment.

We generally employ a mixed model, with CPO and CTO working ‘onshore’ (in our case, in London) and UX, design and engineering working ‘near shore’, typically in Eastern Europe. We always seek to build long term partnerships by working with the same individuals across a number of ventures. This creates bonds of familiarity and trust that generate real team effectiveness over time.

The costs for the team are rolled into the overall capital raised by the venture firm and then exchanged for equity in the company.

#2: Market-size

Finding startups that are good investments is hard. Finding startups that are pre-product, pre-revenue and a good investment is a treasure hunt of mythical proportions.

It’s hard to accurately size the market for venture services. It could be very small based on the ratio of deals we have done versus the opportunities we have passed on.

The downside of working at the highest risk end of the investment spectrum is that it’s, well, risky. Most investors prefer to see proof of market traction. It’s a giant leap of faith to invest in a market for something that doesn’t yet exist.

Pivot endeavours to de-risk this by backing founders who sell back into their primary network, at least in the first instance.

Ex-lawyers are well positioned to sell lawtech solutions to other lawyers. Ex-marketers selling marketing platforms to their former (marketing) colleagues is a reasonable bet. Unlike hackers, “just some business person” often has the edge when it comes to sales. And sales is the bigger challenge long-term.

#3: Culture

Venture services firms combine expertise (and application) in two distinct fields: early-stage investment and software product development. Folks from these respective fields come from different places, have different mindsets and speak different languages.

Service providers are instinctively inclined to work with whoever wants to work with them. Investors are instinctively sceptical. Service providers are default ‘yes.’ Investors are default ‘no’.

I speak from experience when I say that the two are also treated very differently by founders and the startup community in general.

Investors are top of the food chain and get treated accordingly. They enjoy high response rates to their emails and meeting requests. They don’t sell or hustle as a rule.

Life is different for providers of software services. Much of their time is taken up writing estimates and proposals that go unacknowledged. Their communications are ignored. They have to hustle constantly.

Part of the achievement of a venture services firm is finding a common ground for these very different individuals to interact within. This alone is a barrier to entry.

TL:DR

That’s pretty much all I have to share, so far. As you can probably tell, I’m bullish about the potential of venture (and venture services) as an emerging category within venture capital as a whole.

Any other players (or aspiring players) within the space, I’d love to hear from you.

Here’s the TL:DR:

1. Venture is still a niche space, primarily due to the complexity of its business model.
2. All equity deals (ie. where startups pay no cash) are the most compelling, differentiated, and potentially lucrative form of venture. Smart founders value the opportunity to onboard an experienced product team at speed and are prepared to trade their equity accordingly.
3. It’s impossible to succeed in venture without access to a pool of capital, typically a fund or syndicate of investors.
4. Keeping overheads as low as possible is key to success.
5. Whilst the value proposition is compelling and the problem large and frequent, the size of the addressable market remains hard to quantify (and may be very small.)

This post is part one of two about venture and venturing. Part One examines the ‘what’ and the ‘why’ of venture, primarily from the perspective of the providers.

Part Two delves into ‘how’ venturing actually works in the context of ‘venture services’, the corner of the venture ecosystem I occupy as a partner of London-based Pivot Venture Services.

This series is also about early-stage startups: what it means to work in and around them and why venture is an investment option worthy of consideration by startup founders.

The header image of this article is from William Hogarth’s series of paintings on fortunes made and lost during the birth of modern capitalism in London. Anyone who works in the startup space today will recognise the cast of hustlers, fantasists and rogues, not to mention the world of opportunity and (above all) risk in which they operate.

What is Venture?

Venture means risk. ‘To venture’ as a verb implies sharing risk in an activity for which the outcome is uncertain. Venturing requires an appetite for risk and chaos. Despite the urge to reduce risk in the context of investment, there is no avoiding the risk profile of venture which remains high when set against other investment options.

When they hear the word ‘venture’, most people think of venture capital. Venture capital firms are integral to the sector we loosely call ‘technology’ and the growth story of almost every ‘tech company’ we can name (and countless others that we can’t).

Despite achieving what feels like mainstream status, venture capital still describes the allocation of funds to very high-risk investments that could potentially offer higher returns. These investments are called startups. Venture capital firms give funding to startups in exchange for equity.

‘Venture’ in this article means the exchange of services for equity in a startup, as opposed to an investment of cash. This form of exchange has commonly been known as ‘sweat equity’ (sometimes simplified to just ‘sweat’) to imply a trade of labour (‘sweat’) rather than capital. Venture is not a separate asset class, but a form of venture capital.

‘Sweat equity’ in software has existed since time immemorial. However, it has usually meant the time invested by the founding team of a startup (for no fee) rather than an arrangement with another company.

Sweat equity agreements have occurred between startups and software services firms, but they have tended to be pro-bono side hustles (“We really like you but you don’t have any money so we’ll do some work for equity”) rather than the strategic focus of the services provider. In the last few years, these relationships have begun to proliferate and evolve.

Venturing, as a theme or business category, has recently received a lot of exposure. Much of this can be attributed to former ustwo owner, and FKTRY founder, Jules Ehrhardt who delivered a ringing endorsement of its future in his widely read article ‘State of the Digital Nation 2020’, subtitled ‘Venture Road’.

‘State 2020’ provides an exceptionally thorough account of the global venture landscape. It reveals a fragmented ecosystem and a diverse range of players. Even the names vary widely. There are startup studios, product studios, venture development firms, venture studios, venture services firms and venture builders. To this list, Jules adds his own twist, the creative capital studio.*

Most venture firms tend to focus on the product and ideation capabilities of the team; hence the frequency of terms like ‘factory’ and ‘studio’ in the names. These reflect the background of the founding team who, as a rule, tend to come from digital strategy, design or engineering backgrounds.

But venture is a two-sided business, services and investment. And, in my experience, the investment challenge is the harder part to get right.

There are many capable services companies from across the agency and development shop spectrum who can deliver good quality software products to agreed schedules. There are very few investment firms that can consistently generate high returns at seed stage.

From what I can see, the underlying economics of venture are rarely disclosed by any of the players. As a result, it’s hard to know exactly how they structure their venture deals, or their historic rates of return. It’s easy to make the case for venture as an exciting business to enter. But a profitable one? Not so much.

Many venture firms work for both cash and equity. This is because they are discounting their services and do not have a fund of capital to draw on. This arrangement skews towards the ‘services’ end of the spectrum in terms of its value-proposition and the nature of the relationship it engenders.

Those that are funded tend to focus on the potential upside (rather than the short-term benefit of cash) of the deal, so work for equity only. These firms tend to be viewed (and treated) more like investors.

To complicate things further, the spectrum of equity different venture firms expect is also very broad.

For startup studios the amount is typically more than 50% and sometimes upwards of 80%, making CEOs employees rather than founder-owners. For venture services firms, the amount is typically in the 20% ballpark for startups who are pre-product and need an MVP. For startups who have an MVP and some traction, it can be as little as 10%.

Why Venture?

In my experience, people choose to venture for 3 reasons.

The first is that everyone wants to work with startups and build the next cool product.

Unfortunately, startups tend to be closed to outsiders. They don’t engage much with service companies or consultants. They are cash strapped by definition and self sufficient as a result.

The curious only really have to two routes in: found one or join one founded by someone else. Of course, you could invest also in one. But investors don’t ‘work with/in’ their investees and rarely get a glimpse of real life behind the curtain; just the rosy reality founders want to convey.

The second reason is a contributing factor to the first and was well articulated recently by Y Combinator’s Jessica Livingston.

In her article, ‘Think about Equity’, Jessica points out that no one gets (really) rich from earning a salary,

“There’s another way to make money besides salary. You can get it by starting a startup or by going to work for one. And deciding which startup to work for is not like deciding what big company to work for, where you go for the big names, because the equity with the most upside is that of startups so small that most people have never heard of them”.

Most of us have been brought up to associate material progress with salary increase. But, in the last decade, we have observed many young (mainly) men generate incredible wealth for themselves and their colleagues in relatively short periods of time. None of them did so by working for a salary at a large company.

Real wealth is achieved through owning, not earning. The economic landscape in the West is changing and the expectations of the workforce are changing too. People realise that equity is the real source of wealth. And they want in.

Finally, there is economic necessity.

As the subtitle suggests, one of the key themes of State 2020 is that the future of the ‘cash for services’ model employed by digital agencies is bleak. Commoditisation is destroying profit margins and will continue to do so unless they reinvent how they charge for the value they create. The only way forward, according to Jules, is through venturing.

Why is Venture still niche?

If the appeal (and potential upside) of working with startups is so great, why isn’t venturing more widespread? The reason is that successfully combining services with investment is far more challenging than many realise.

To quote Jules (again),

“the economics of risk-based, deferred revenue, venture work is fundamentally irreconcilable with paid for time consultancy work.”

Services companies are cash generative. The cash they receive for their services allows them to pay their only real costs (their staff) and net a healthy profit. Venturing, on the other hand, is investing, which means deferring cash for equity. Equity in private companies is illiquid. As a result, cash flow becomes a problem very quickly for services companies moving into venture.

Funding venture activity from the profits of a services business is unsustainable long term. I have experienced firms all but go bankrupt attempting the transition. Be warned.

Jules is correct in his observation that, without access to a pool of capital (which he refers to as a ‘sidecar fund’), it’s near enough impossible to stay afloat.

How can these two very different business models be reconciled? We will explore this in Part Two.

TL:DR

1. Venture means trading services for equity in startups and is a form of venture capital.
2. Despite an upsurge of interest in the business model, the venture space is currently diverse and fragmented, with no dominant players.
3. Venture remains niche due to the complexity of its business model.
4. No comprehensive data exists on the profitability or rate of return across the industry.

*Despite this article’s focus on venturing with startups, it’s important to acknowledge that many of the elite consultancies, notably McKinsey and Boston Consulting Group, have been venturing in the enterprise for some time via their BCG Digital Ventures and McKinsey New Ventures arms.

McKinsey labels this endeavour ‘asset-based consulting’ and, after years in stealth mode, has gradually begun publishing details of its solutions. Not surprisingly, the financial arrangements that underpin the venture deals with their clients remain undisclosed.

“Companies fail all the time. And product strategy is the best defence you have against this.” — Des Traynor, Intercom

[This article is adapted from various presentations given in London in 2017, including Products that Count and the London Product Strategy Meetup. If you prefer listening to reading, you may want to check out the video of one of those events (with slides) here>> & at the end of the article]

For anybody who works in a small company, especially a startup, discussion of ‘product strategy’ is seldom top of the list. In fact, it rarely makes the list at all. The prevailing viewpoint is that it’s ‘just theory’ that has little value in the real world.

In environments where resources (eg time + money) are limited, there’s an overwhelming preference for execution over discussion, for ‘doing’ over ‘talking’. As a result, a lot of product teams end up coding and shipping (and coding and shipping…) without a clear sense of where they’re headed. And, as the Cheshire Cat observed, “If you don’t know where you’re going, any road will take you there.”

Companies fail all the time, that’s startup economics. But, in today’s hyper-competitive landscape, not knowing where you’re headed is the fastest route to failure.

Product strategy is, for me, the art and science of knowing where you’re trying to get to before you set off. It means transcending the notion that a product is about screens and features. It’s about starting with your user’s desired outcomes and working backwards to the technology. This is not new thinking. Steve Jobs was fond of saying this decades ago. But it seems every generation needs to relearn this, as every generation is susceptible to the assumption that technology is the answer.

A partner from a London-based venture capital firm recently drew a chart for me that encapsulated how his firm evaluate the hundreds of startups, grow-ups and scale-ups they encounter every week. He labelled the y axis ‘Unique market insight’, the x axis ‘Differentiated technology’ and drew a cluster of dots in the bottom right of the chart and two dots in the centre.

98% of the companies his firm encounters are in the bottom right cluster, he said. They all have ‘deep tech’ expertise, are at the leading edge AI or VR for instance, but they lack genuine insight about who will actually use the technology they are developing. They are answers looking for questions.

The only companies worth investing in, he continued, are the ones able to combine the two. Unique market insight, he emphasised, is always more valuable than leading edge technology.

Rarely observed, and much less documented, over the last few years is the emergence of a number of individuals who have developed their own school of thinking (or their own ‘lens’) on product strategy. None of them are household names to the extent that Marc Andreessen or Sam Altman have become, but all have established their own ‘school’ of thinking. Each has their own group of disciples, all of whom co-exist in splendid isolation.

This article provides an overview of those different product strategy ‘lenses’ which, collectively, constitute a new toolset for product managers and product-focussed founders of software startups.

These lenses can be applied to any product by any team and can clarify its purpose, value proposition and the desired outcome of its user. They require no training, little preparation and deliver more or less immediate results.

Product Strategy #1: The Big Idea

Let’s start with the biggest idea right now in product strategy. It’s the brainchild of someone who is still comparatively unknown, although many will have encountered him indirectly. His name is Ben Thompson and he’s the founder and author of Stratechery, the best source of insight on strategy in the technology sector by some margin.

Much of the analysis of the tech world originates from Ben Thompson. His weekly analyses get picked up and disseminated by most of the leading news publications. Many of the articles that you read in The Wall Street Journal, Forbes or the New York Times about events in tech quote him directly.

From what I can work out, he never sleeps. He lives in Taiwan, reads everything imaginable before anyone in the West is awake, and produces long-form analysis of every notable event in technology 3+ times per week. He’s one of those people that’s more talked about than actually read. And that’s mainly because the sheer volume of content he publishes each week is beyond what most people can absorb.

Ben Thompson’s Big Idea is ‘Aggregation Theory’. It’s about three years old and he’s evolved it over time. Aggregation Theory is like Einstein’s General Theory of Relativity. It’s the foundational paradigm that makes sense of everything else.

Aggregation Theory has two tenets. The first is that owning the direct relationship with the user is the most powerful thing in the market.

The second tenet is that the cost of adding users and distributing digital goods is now zero.

Once upon a time, the business of distributing information or content (like magazines or music) came with huge barriers to entry as production and transport cost a lot of money. Now, thanks to Amazon (via its virtualised hosting service, AWS), it costs almost nothing at all.

In Ben’s parlance, the marginal cost of adding an extra user is now zero. This means it costs as much to serve a billion people as it does to serve one person. Economically, this is transformative and has made much of what we call ‘disruption’ possible.

Although ALL aggregators own the relationship with their customers, there are three distinct ‘types’ according to Ben.

The first are companies that aggregate supply via acquisition. Netflix is the best example. By methodically aggregating access to supply, Netflix aims to become the best place to see any film. It achieves this by licensing content from established studios and investing heavily in original content.

Netflix’ ‘power’ derives from its position as the #1 place where people connect to films.The more films it can offer, the more users it acquires. As this cycle repeats, its position becomes stronger and stronger.

The second type aggregate supply indirectly, ie. they don’t ‘own’ the supply side. They do incur some cost acquiring suppliers (known as supply transaction costs) but their power extends from an ability to connect the biggest group of suppliers with the biggest group of customers. The best example of a ‘type 2’ aggregator is Uber.

The final aggregator are those that connect users to content although they neither own the supply nor do they incur acquisition costs. Type three is best exemplified by Google. Newspapers used to own access to content but Google has blown this channel wide open.

There’s a final category of aggregator, known as a super aggregator. This type is best exemplified by Facebook. Super Aggregators don’t just connect consumers with suppliers at scale. They own both sides of the equation. They’ve got the most users, the most content and a self-serve advertising model that allows them to reap massive profits simply by enabling those interactions.

To appreciate how powerful (and profitable) the super aggregators have become, look no further than the recent US Senate hearings into possible Russian interference during the last presidential election. Despite the General Counsels for Twitter, Facebook and Google getting hauled over the coals, the hearings mainly served to reveal just how painfully clueless most of the political establishment is about how the super aggregators make money. And how profitable they really are.

The self-serve nature of the super aggregators’ business means that they don’t know who is advertising on their platform. They just sit in the middle and pocket the profits. This is why they’ve become powerful (and valuable). It could also be their undoing. What has, until now, been the most amazing profit machine is now creating serious regulatory problems.

Product Strategy #2: The Job

The next lens is our old friend The Job to be Done, recently renamed the Customer Job by Alan Klement, author of When Coffee and Kale compete.

Jobs to be Done (JTBD) is the oldest ‘new’ idea in product and has enjoyed a tremendous ground swell of interest amongst Product Managers in 2017.

Understanding the concept of Customer Jobs requires an understanding of progress and the extent to which your product helps users become better versions of themselves. Almost everyone is familiar with JTBD’s central tenet that, “Customers don’t want your product. They rent your product to make progress in their lives.” The thing that everybody forgets is that the products themselves don’t have jobs.

Users (ie. people) have jobs, struggles and aspirations. And it’s users who hire products to enable them to achieve those desired outcomes.

If you find yourself talking about what job your product does (which is surprisingly easy to fall into) then you’ve got the meaning twisted. It’s people that have the jobs. A product is a solution for a job.

Alan Klement is fond of using the analogy of Fireball Mario. As a product team, it’s a great question to constantly stay focussed on, “How are we making our user awesome? How can we help them become Fireball Mario?”

To answer this question, you need to know what awesome means for your user. You need to know the outcome they’re trying to achieve or the progress they want to make in their life. It’s unwise to discuss any other aspect of your product until you can confidently answer this.

When I run strategy workshops, we start with Customer Jobs then explore how to enable them with product. The best tools for facilitating this are the canvases developed by Strategyzer, the innovation consultancy co-founded by Alex Osterwalder.

Strategyzer’s Value Proposition Canvas is a great method of deconstructing the pains and gains that constitute specific Customer Jobs and identifying how they can be enabled within a product or service.

Once this exercise has been completed, usually for a variety of customer segments, I recommend using the Lean Product Canvas that Ash Maurya adapted from Alex Osterwalder’s Business Model Canvas.

Ash’s version is more product-focussed, cannily focussing the discussion on how product and market fit together. It obliges teams to start with customer segments and their problems (not features and screens), then identify solutions, channels to market and the unique value proposition. It’s a great exercise that even the most sceptical can embrace and apply without fanfare.

[Incidentally, I’m well aware there are fearsome academic disagreements within the JTBD community. I don’t want to get into them here, but if you want to understand the counterview, here’s a good place to start>>]

Product Strategy #3: The Switch

One of the most popular quotes I’ve ever used in my presentations is from Whale’s Justin Kan. He once observed that start-ups mostly don’t compete against each other, they compete against no one giving a shit. This neatly encapsulates the overwhelming choice of products, services and content that app stores and the web now present to consumers.

Startups are often so focussed on building their product, they forget just how unlikely it is that anyone is ever going to care less about it.

The app store offers millions of new options every day. The harsh reality is that we’re full. Our minds are full. Our devices are full. Our lives are full. We have more information and more content than we need.

Our attention has coalesced around a very small core. 80% of people’s time is spent in just three apps. The top eight mobile apps are owned by Google and Facebook and 50 per cent of people, at least in the US, download zero new apps per month. Product adoption is a far bigger challenge than most founders realise.

It’s interesting to explore the evolution of thinking in respect to new product adoption. Initial orthodoxy originated from a guy called Everett Rogers. It was Mr Rogers who coined the term ‘early adopter’ and ‘late majority’ in the context of a curve he called the Innovation Adoption Cycle. Everett’s curve paved the way for Geoffrey Moore’s chasm. But Everett himself has been largely forgotten.

Everett’s explanation of new product adoption was refreshingly simple. It was basically this: the best product wins.

Consumers evaluate each new product qualitatively against existing options and switch to ones they judge to be better. Very logical and rational. This was accepted wisdom for about 30 years.

Then, sometime in the 1980s, along comes Daniel Kahneman, who most of us now know from his 2012 book Thinking Fast and Slow. He turned Everett’s thinking completely on its head and proved that new product adoption is highly irrational and entirely constituted within our sense of loss and gain.

This is now known as Prospect Theory and Kahneman won the Nobel Prize in economics for his groundbreaking ideas.

The three tenets of prospect theory are:

1. Outcomes are judged in terms of gains and losses.

2. Judgements are relative to our individual situation. (A big reduction in the price of petrol in France would still be viewed as expensive to someone in the US.)

3. We hate losing stuff far more than we like gaining something new. (This is known as Loss Aversion.)

When we switch products, we feel the pain of what we are losing much more than the pleasure of the gain. Time is a factor in this as losses are experienced immediately but the gains aren’t felt until much later.

Our innate tendency to overvalue the status quo is called the Endowment Effect. This helps to create what John Gourville dubbed ‘the 9x problem’ of new product development.

If you multiply the degree to which the average consumer over-values their existing products (3x) by the degree to which innovators over-value their new products (3x), you get a 9x differential. This, claims Gourville, explains why so many new products fail despite offering demonstrable advantage. They are better, but not by enough.

Alongside Clay Christensen, Bob Moesta has been described as ‘one of the key architects’ of Jobs to be Done theory. He’s extended the initial theory in multiple directions, one of which is his Switch workshop, which he delivers under the banner of the Re-Wired Group.

Moesta and his team believe strongly that consumers don’t simply adopt a product, they switch from something else. Each time you ‘hire’ a product, you ‘fire’ the incumbent. And, during this period of change, there are four forces that act upon you which influence your decision.

Two forces incline you towards making a change and two incline you against doing so.

First is the push. This starts with frustration with your current situation, a sense that the ‘as-is’ is sub-optimal, or even downright broken. This triggers the action of looking for something else.

Then, there’s the pull. When you hear about something else that’s better, you want to check it out. I’m old enough to remember when Google’s search engine was first released. The word of mouth was incredible. People would just tell you ‘This is so much better than anything else’ and you only needed to try it once to jump onboard.

There are also two forces that preserve the status quo.

The first is habit, which is a huge thing to overcome. As a new product developer, ‘Good enough’ is your biggest enemy. Many Product Managers still use Excel to manage their backlogs because it’s good enough. There isn’t enough of a push to cause them to switch to Trello, Jira etc.

Next is the anxiety which accompanies loss aversion, the innate fear of the new.

An analysis of the 4x ‘Progress Making Forces’ that consumers experience as they consider your product is another activity I would encourage all product teams to undertake. If you don’t understand the switch moment for your product, you won’t understand how to market it effectively or iterate upon it over time.

Switch analysis can also transform your understanding of the competition. This is best exemplified by Reed Hastings’ quote about Netflix competing with a bottle of wine.

I believe Reed has since observed that his new competitor is sleep. Either way, his comments illustrate the diversity of the actual competitive landscape. Brands like Netflix, Facebook, Snapchat etc are now locked in an epic battle to monopolise your time. All other activity undertaken during the day now competes with them directly.

Product Strategy #4: The Pyramid

Here’s a tip: if you want to appear knowledgeable, it never hurts to talk about your product’s ‘unit of value.’ Value has been a popular trope in product for some time. And Eric Almquist, has done more than most to develop our understanding of this concept.

Eric is a partner at Bain and Company and has spent 25 years consulting to large corporations in various sectors. During that period, he’s conducted a huge amount of research about how product value is constituted and understood by management. His conclusion was that value is complicated, amorphous and hard to quantify. Everyone is an expert on price, but no-one’s an expert on value.

As a result, managers tend to focus on cost reduction and supply-side efficiencies rather than the demand side which remains poorly understood.

To progress our understanding of product value (and communicate what they learnt from their research), Eric and his team produced a ‘Pyramid of Value’ that visually identifies 30 separate value units which products and services can deliver to consumers. Using a recognisable framework ‘borrowed’ from Maslow’s Hierarchy of Needs, the pyramid stacks the units in four layers: functional, emotional, life changing and social impact.

Base heavy, like any pyramid, most units congregate further down the stack while a single unit (self-transcendence) resides at the peak.

Most products (in fact, most startups) tend to compete solely within the functional layer. They save time, money or inconvenience for their users. Not that there’s anything wrong with that. It’s worked well as a strategy for Amazon and Uber, but it’s extremely competitive as most companies operate in this layer.

Eric believes there are bluer oceans, better opportunities and wider profit margins, to be found by setting ones sights further up the pyramid. Take Apple as an example. They rarely compete on features or functionality, the iPhone is almost always behind the curve in this regard. Instead, they compete on an emotional level, on less tangible brand qualities. And their margins are eye watering compared to everyone else. Despite recent decline, they still capture about 79% of global smartphone profits.

The Pyramid of Value represents a great opportunity for all product teams to assess what units of value they compete upon. Eric is keen to point out that trying to compete on all elements would be prohibitively expensive, even for the most affluent. Success, he concludes, is the result of carefully defining on which elements of value your product should compete. Then ignoring the rest.

Even elite companies (think Amazon and Apple again) only over-index on about 10 units. On the remainder, they’re no different from every other company. The challenge is knowing exactly where you compete and to focus accordingly.

Product Strategy #5: The Journey

Chamath Palihipatiya is one of the most quotable people in tech. And 2017 has been no exception. He was part of the top team that can claim credit for helping Facebook achieve the extraordinary scale it now enjoys. Chamath once observed that product development is about state change. About moving people from never having heard of your product, to thinking about it, to actually using it.

The next product strategy lens means understanding the journey users undertake as they move between states.

At first, the user doesn’t even know who you are. Then, they’re considering you and trying you out. Next, they understand you and use you regularly. Then, once they’re locked in, they want to customise you around their own specific needs. Every user moves through this journey in the same sequence.

The journey itself can be viewed from a variety of angles, or lenses. One is the value lens. Initially, your product has to communicate its value promise. Then, it must demonstrate this value. Next comes value delivery; every time someone uses the product the value is delivered consistently. Finally, you extend the value for each individual user and, eventually, into other products.

What does this mean in practice for the product team?

Getting the first stage right requires close interaction with the acquisition or growth team, ensuring you communicate exactly what the product does in the most succinct manner.

Next comes onboarding, very much part of the product, when you need to convince interested trialists of the product’s value as quickly as possible.

Next is core task completion, when your product has established a role in someone’s life and you need to embed that position further.

The final stage is administration, so users can customise and change the product to suit their needs.

Each stage requires coherent planning and feature development, to ensure each user need state is catered for. Most products start with core task completion but overlook the other states that need supporting.

In terms of measurement, the this lens maps neatly against the Pirate Metrics established by Dave McClure.

The first stage are the acquisition metrics, next is activation, the third stage is retention and revenue and the final one is referral.

(Like Hollywood, Silicon Valley has been confronting its sexual predators and Dave McClure has been one of the casualties. Unlike Harvey Weinstein, he confessed pro-actively. I guess it’s too early to know how long he’ll remain on the blacklist.)

It’s worth pointing out that, if your product is B2B, there are two different journeys to consider. Buyers and users of software are typically different individuals within organisations. Their needs and desired outcomes are different, so the acquisition, onboarding, task completion etc. must differ for each accordingly.

Priorities also vary greatly. Buyers typically place much more value on administration capabilities, something that’s easily overlooked by the product team in the early days.

If you’re buying a product for 15,000 or 20,000 users at your company, the most important thing is to understand who is using it and how often. Next, you need reporting tools in place so you can demonstrate to the CFO (or the Finance team) how you’re getting a return on this investment.

It’s too easy to focus on the users (and their needs) and to overlook the buyer who, at the end of the day, is the actual customer who is writing the cheque.

A critical element of the onboarding stage is that it is the location of the now-legendary event known as the ‘Aha! Moment’. This occurs when the user suddenly understands your value proposition and realises how it can help them achieve progress (or desired outcomes) in their life.

The ‘Aha! Moment’ is generally accepted as a tangible reality in technology companies; certainly Facebook and Twitter take it very seriously. Chamath has been vocal in describing how the Growth Team at Facebook measured ‘time to Aha!’ in fractions of a second and were hyper-focused on reducing that time further.

For Chamath, growth starts with an understanding of product value and is about moving new users to the ‘Aha! Moment’ as quickly as possible.

A great exercise in product strategy is to ask, “What’s the ‘Aha! Moment’ for our product?” and, more importantly, “How long does it take for our ideal user to reach it?” How many interactions or sessions should it be? then, “How can we shorten it further?”

Few can expect to measure it in seconds, as Facebook does. If you manage a B2B SaaS product, time to Aha! could take months. For most products it’s probably somewhere in between the two.

Product Strategy #6: The Story

Still on the margins, but gaining ground, is the notion of ‘Product as Story’. This lens has been pioneered recently by Donna Lichaw in her book ‘The User’s Journey: Storymapping Products that People Love.’

Donna was a scriptwriter in Hollywood before making a career pivot into user experience design. By comparing what she learnt across the two disciplines, she observed that the narrative arc (how a typical screenplay is structured) can be used to document a user’s ‘story’ with a new product.

The narrative arc aligns neatly with how the JTBD school describe the Customer Job. Just as there is scene-setting and an incident in the narrative arc, there’s a ‘current state’ and a ‘trigger’ in the Job Story espoused by Bob Moesta and Alan Klement.

To compare the two more directly, a standard narrative arc would include the following steps:

1. Exposition

2. Inciting problem (or trigger)

3. Rising Action

4. Crisis

5. Climax or Resolution

6. Falling Action (or ‘denouement’)

7. End

In Donna’s methodology, the user’s story follows a similar trajectory.

1. User problem

2. Trigger / Call to action

3. Flow

4. Impediments / Obstacles to success

5. Problem Solved

6. Value delivered

7. Finish Flow

8. Goal Met

Donna calls the application of this technique ‘storymaking’ rather than storytelling.

It’s been commonplace for sometime for companies to write their ‘brand story’. Instead of placing your company at the centre of the narrative, Donna advocates making the user the hero instead. She encourages every product team, especially those developing a new product, to write 3 stories : the concept story, the origin story and the usage story. And she’s kindly made templates for these available for free.

To avoid falling into the trap of building technology without any market insight to justify its existence, it’s important to start with a human story. A story in which your user is the hero.

Product Strategy #7: The Hook

Nir Eyal has made as much contribution (and impact) as anyone to our understanding of product strategy in the last few years, via his lectures, essays and book, Hooked: How to build Habit Forming Products.

Like any great artist, he steals liberally from other pioneers and absorbs their thinking into his own.

In Nir’s case, the kernel of his thought originates from Dr. BJ Fogg, his former tutor, who directs research and design at the Persuasive Tech Lab at Stanford. The lab itself is proving to be well ahead of its time, pre-empting key debates in tech that are only now emerging.

Fogg’s research focuses on the impact that computers have on our habits and behaviour, the intersection of psychology and technology, and the ethics that arise as a result. One of his many insights is a formula for influencing behaviour, which he calls a ‘Behaviour Model for User Design’, also known as the FBM (Fogg Behaviour Model).

The FBM states that human behaviour is constituted by three factors, motivation, ability and triggers. By considering (and harnessing) these elements in product design, it’s possible to effect long-term behavioural change in the user.

Nir extended Fogg’s model, added insights from his own observations of products like Facebook and Linkedin, and established a new design formula he christened ‘The Hook’.

The Hook explains how product developers can create habit-forming behaviour in users by cycling them through a loop of interactions consisting of a trigger, an action, a variable reward, then continued investment.

The trigger is what interrupts your train of thought and brings your attention back to the product. The trigger most familiar to us currently is a notification, either on your phone or in your browser. The trigger compels you to interact with the product, and that interaction brings some form of reward.

This series of interactions generates increasing investment of self into the overall product experience. Over time, you may add details and customise your profile which serves to deepen your relationship with the product long term.

Nir’s thesis is that the most successful tech companies (Facebook, Google, Linkedin) have consciously designed their products to perpetuate behavioural change (and serious habits)amongst their user base via careful application of the Hook Model.

Critical to the efficacy of the model is the fact that the rewards are variable. This means not only that they are unpredictable but ultimately unsatisfying too. In Nir’s words, “they scratch the itch but leave you wanting more.” This is why notifications are frustratingly obtuse. “Did you see what 7 people said about Jay’s post?”

This is product design powered by FOMO. And the extent of the dopamine release in our brains from responding to these triggers has been shown to be equivalent to crack cocaine.

The tactics used to achieve this are simple, yet effective. A good example is autoplaying videos, allowing you to keep watching content (and adverts) indefinitely. This is the natural evolution of pages that infinitely scroll, a tactic that has been used by publishers and social media for some time.

Nir’s thesis received a huge fillip in 2017 from our old friend Chamath (again!) and a number of his ex-colleagues who seem to be experiencing a collective phenomenon known as ‘Facebook guilt.’

Chamath, as candid as ever, explicitly warned users of tech and social media products that “you are being programmed”, going on to conclude that Facebook (and other products) are “tools that are ripping apart the social fabric of how society works.”

Justin Rosenstein, a former Facebook engineer who birthed the ubiquitous ‘Like’ button, concurs. He alleges that “our minds are being hijacked” with the result being that “All of us are distracted, all of the time.”

It looks like Tristan Harris, who pioneered the debate about the ethics of behavioral design and the ‘Attention Economy’ as part of his ‘Time Well Spent’ initiative is set go mainstream in 2018.

Ethical concerns aside, it remains a valuable exercise for any product team to consider the Hook Loop and the Fogg Behaviour Model in the context of their own product. Do you know the internal and external triggers that precede engagement? Do you know which motivation (6 types, according to Fogg) you are acting upon?

Product Strategy — Summary

So, there you have it, a new Product Strategy Tool Set for the digital era. Seven lenses that can be instantly applied by any Product Team (or founding team) to clarify their true purpose. If nothing else, each should ensure the team moves beyond thinking of the product as simply a set of screens and features. It’s about a journey, a story, a switch. It’s about delivering value and above all, it’s about making your user awesome; helping them make progress in their lives.

Getting Product Strategy right

Companies fail all the time. And your product strategy is the best defence you have against it, says Intercom’s Des Traynor.

In Summary: In a short talk, packed with insights, Des Traynor explains why, in the early stages, nailing product strategy is even more important than perfecting sales and marketing.

Deep-diving into the problem your product solves, its defensible ‘moat’, the relationship between product and brand and the importance of being technology agnostic, this is a timeless masterclass for founders and product leaders everywhere.

The Product Strategy Toolbox

My presentation to the London Product Strategy Meetup in November.

In Summary: An overview of the product strategy landscape in 2017. This covers everything from Ben Thompson’s ‘Aggregation Theory’ to Anju Sharma’s ‘Stack Fallacy’ via Jobs to be Done, Switch Analysis, the Value Pyramid and the Story Arc.

Your Strategy is a Hypothesis!

In today’s uncertain environment, it makes sense to view strategy as a hypothesis instead of a plan, says Amy Edmondson and Paul Verdin in the Harvard Business Review.

In Summary: Most companies view strategy as analytically sound and regard all failure (such as missed sales targets) as flawed execution. Cheating and cover-ups are natural byproducts of this, as management refuse to accept ‘No’ or ‘It can’t be done’ for an answer. Just ask VW and Wells Fargo.

Closing the gap between strategy and execution may not be about better execution, but about more dialogue between strategy and operations. And more experimentation.

The key indicator of ‘strategy-as-hypothesis’ lies in how managers interpret early signs of gaps between the plan and the actual results. Does it mean teams are underperforming or that initial assumptions are flawed?

What the f$%* is Product Strategy?!?

As the Cheshire Cat observed, if you don’t know where you’re going, any road will take you there, says Yoav Yechiam.

In Summary: Startup CEOs tend to be so obsessed with output and ‘progress’ that they forget to check their course.

Startups fail because they aren’t able to achieve product/market fit fast enough. They run out of time and money too soon. They neglect their product strategy and focus on tactics, tricks, and easy fixes instead.

If you’re trying to move onboarding conversion from 30–60% while your user acquisition cost is 10x lifetime value then your real problem isn’t your product manager, it’s your product strategy.

What it means to ‘Invest in Product’

In Summary: The decision to invest in software is no different from any other investment decision. It should start with a business case and be linked to the primary value drivers of your company

Over-investment in product at an early stage is a common problem. It’s adviseable to build your initial product with web technologies that are accessible by anyone. Native apps are powerful vehicles for delivering customer value, but wrong for early stage experiments.

Don’t expect to ‘discover’ new monetisation models as (chances are) they don’t exist. Focus on ones that are already established (charging for downloads, software as a service, advertising). If you can’t foresee a path to profit, then question the value of making the investment.

Nine out of 10 product ideas aren’t worth building.

The ‘Mobile App’ business is dying

The dream of building a mobile product that launches a business and nets $billions is looking less likely every day, says Fast Company.

In Summary: Comscore’s recently published Mobile App Report sheds more light on the dominance of the app space by a handful of Tech Unicorns. Three of the Top 10 most used apps are owned by Facebook, four are owned by Google, and the other two are Snapchat and Pandora. Every single app on the list is owned by a publicly traded company.

The fastest-growing new apps are ones that have been gaining momentum for years, the products of marketplaces or services that benefit from powerful ‘network effects.’ Think Uber, Venmo and Music.ly.

What will Product Management look like in 2028?

When it comes to product management, we’re still in the MS-DOS phase, messing around with floppy disks, says Alpha’s Thor Ernstsson.

In Summary: Product Management is all about making data-informed decisions to deliver value to customers. Much of that involves equipping those doing the design, engineering and marketing with the tools and data to do their jobs effectively.

Aside from certain product leadership roles, product management processes in the future will be integrated into other roles and functions across the organisation.

By 2028, every business will be customer-first. No consumer or business user will have patience for a frustrating product, especially when they can quickly turn to a competitor. Users always opt for frictionless experiences, often without realising they’re making a switch.

Product Quote of the Month

“Product-market fit is not revenue growth, it’s not growth in users, it’s not being #1 in the App Store. Product-market fit is retention that allows for sustained growth.”

Great piece on the real Metrics That Matter, by Pinterest’s Casey Winters.

And finally…

Thank you (and Goodbye)

This is the last edition of Pivot Product Hits. I’d like to thank everyone who has taken the trouble to subscribe, read, and share our mutual interest in Product Strategy.

I hope it’s been as rewarding to read as it has been to edit and publish.

So long.

Paul J | Pivot

Originally published at Pivot Product Hits.

Pivot Product Hits | The Final Cut was originally published in HackerNoon.com on Medium, where people are continuing the conversation by highlighting and responding to this story.

The Product Strategy Toolset

A canvas masterclass, from Alex Osterwalder.

In Summary: Selling colleagues on the value of product strategy can be challenging in startups and tech companies where the prevailing culture is one of coding rather than talking. To succeed, Product Managers need to deploy tools and methods that deliver maximum value in the shortest possible time.

In my experience, the most effective combination is Alex Osterwalder’s Value Proposition Canvas and Value Map combined with Ash Maurya’s Lean Product Canvas. These can be completed by a group, are easy to use and swiftly achieve closure around the target customer, the Job to be Done, the value proposition and the channels to market.

In this excellent short, Alex Osterwalder uses the Value Proposition Canvas to demonstrate how Tesla serves a variety of its target customers’ needs.

What (exactly) is the Product Customisation Curve?

In product development, there’s no single thing you can build that will make all users happy, says YC’s Aaron Harris.

In Summary: If you’re a startup, any angry customer can feel like the end of the world. This often leads product teams to create unsustainable product customisations. The biggest danger is committing to large costs that are hard to remove. Doing this can force your company down a path to failure or an extreme pivot.

The harder thing to do is figure out which customisations to make, weighted by the increase in happiness of the users you actually want.

As a guiding rule, customisations that are software features are easier to build than customisations involving people processes. If you have to build a people process, build one that can be replaced with software later.

Don’t invest in Products, invest in Customers

It’s not a feature problem, says Vonjour’s Dan Tawfik.

In Summary: Product is the foundation of a startup. The first iteration of a product delivers the kernel of value that the company delivers for years to come. But small iterations in the product just deliver marginal returns. If you don’t acquire users in a meaningful way, you’re not giving your business the chance to survive.

When building Vonjour, Dan’s team rapidly developed new features thinking each one would be an inflection point. (‘Ticketing will be a game changer’…) But, not one moved the needle when it came to growth.

Eventually, they stopped building features and invested the remainder of their capital in marketing, rather than product. In doing so, they discovered that the imperfections they noticed weren’t an issue for users. The majority were perfectly satisfied with the product as it was.

Designing Products with AI

Designing with AI is just like designing anything else. Focus on people problems, test your assumptions, and provide affordances for when things go wrong, says Facebook’s Erica Virtue.

In Summary: The allure of AI is that it can make your product ‘magically’ work.

But good product design uses AI in a way that enhances the experience, rather than defines it. Whilst working on Facebook Recommendations, Erica’s team didn’t try to invent a completely new behaviour. Instead, they found an existing one and made it far better.

Even if your AI works most of the time, there are going to be moments when it fails. So, usability testing with real people remains important. By watching people go through experiences early, Erica’s team uncovered a lot of issues with their AI they wouldn’t have noticed otherwise.

Feature / Product / Company?

In Summary: Most companies begin life somewhere between a feature and a product. And that’s where most companies end, as a collection of features that feel like a product but are really somewhere in between.

Features provide specific point value to users. Products stitch together related features into bundles that solve problems that are universal. The bigger the opportunity and the more ubiquitous the solution, the more focus can pay off.

Instagram built a series of relatively simple features into a product. But the opportunity was so large they were able to turn that product into a company by stitching together its users into something larger.

The features were ubiquitous across the user base. They solved a problem that many people had the need for in a way that worked for everyone.

How to make Product Decisions without Doubt

When you doubt your product decision, step back and ask yourself: what do I believe about the world, and does this push us in that direction? asks Slack’s Paul Rosania.

In Summary: From introducing the algorithmic timeline to Twitter, to turning on Do Not Disturb for all Slack’s users by default, Paul Rosania has presided over some of the most hi-profile (and hi-risk) product decisions in tech.

Product decisions of this nature can be paralysing acts of faith. But, rather than avoid critics, Paul’s advice to Product Managers is dive headfirst into their doubts.

Start by getting the debates off email and offer direct, human contact to solicit feedback. This process will help return you to your product’s purpose, your company’s worldview and (critically) your instinct.

How WhatsApp and Facebook design Products at scale

When building a product, having a clear problem to solve can be half the battle, says WhatsApp’s Charlie Deets.

In Summary: Whereas Facebook uses a high level mission to drive company decisions, WhatsApp uses design principles to focus product conversations so the majority of their thinking goes into the minutiae of the execution.

Also unlike FB, WhatsApp prefers not to alert people to new features in the product. They assume that, if they build features that are obviously useful, people will find them and engagement will naturally follow.

If WhatsApp had a product motto, it would be “Move Slow and Deliberate.” When designers hand off to engineers, they try to deliver as much of a finished spec as possible.

Product Quote of the Month

“Keep it short. Respect users’ time. Get to the point and get out of the way.”

Great primer on designing voice products, from Clearleft.

Originally published at Pivot Product Hits.

Pivot Product Hits | November Edition was originally published in HackerNoon.com on Medium, where people are continuing the conversation by highlighting and responding to this story.

Aggregation Theory | The Big Idea in Product

Ben Thompson (via his Stratechery brand) is unquestionably the most influential commentator on Product Strategy right now and Aggregation Theory is his Relativity. It’s ‘The Big Idea’ that makes sense of everything.

In Summary: Aggregation Theory describes how certain platforms companies (eg. Facebook, Google, Uber) have been able to dominate their industries in such a systematic way. It also explains why their valuations are so stratospheric. In the eyes of investors, they are playing a zero sum game.

According to Ben, Aggregators have the following characteristics:

• they have a direct relationship with their users
• the goods they ‘sell’ are digital and thus have zero marginal costs
• the goods they ‘sell’ are delivered via the Internet, meaning zero distribution costs
• their transactions are handled automatically via credit cards or PayPal etc

Aggregators enjoy winner-take-all effects. As the value of an aggregator to its users is continually increasing, it gets harder and harder for competitors to take away users or win new ones.

There are different types of aggregators (Netflix is different from Uber which is different Facebook) and there are even Super Aggregators. But their potential is the same: as customer acquisition costs decrease over time, marginal customers are attracted to the platform by virtue of the increasing number of suppliers.

How will AI impact Product Strategy? A thought experiment

As advances in AI make prediction cheaper, Amazon’s strategy could change from shopping-then-shipping to shipping-then-shopping, says HBR’s Ajay Agrawal.

In Summary: AI is fundamentally a prediction technology. So, what happens to a company like Amazon as their data scientists, engineers, and machine learning experts dial up the accuracy on the prediction machine? The answer is that prediction becomes so accurate that it’s more profitable for them to ship you goods it predicts you will want rather than wait for you to order them.

If implemented today, the cost of collecting and handling returned items would outweigh the increase in revenue. But, better predictions will attract more shoppers, who will generate more data to train the AI, which lead to even better predictions creating a virtuous circle of increased revenue and lower returns.

Competitive Analysis for Product Managers

Competitive analysis is a waste of time if you don’t understand how it impacts your strategy, says Philosophie’s Chris Butler.

In Summary: Competitive analysis is essentially how your strategy works in comparison to your competitor’s strategy. There are real benefits to understanding how your competitors perceive the world and how your (potential) customers feel about them.

Competitive analysis can help frame your own product context, discover other problems your customers have and even bond the team together against a common foe.

But making too many choices because of your competitors, rather than for the outcomes your customers need, will put you at their mercy. No matter what customers think of your current product, you’re fighting against their perception of your competition, not their product’s features.

Thinking of building ‘Uber for X?’

The deeper the skillset required to perform a service, the less likely the traditional Uber model will work, says PocketSuite’s Sam Madden.

In Summary: Before you start building the next ‘Uber for X’ product, think through some basic variables.

On the consumer side, think through what type of service industry you are trying to disrupt and where that industry falls on the skill vs. urgency graph. This will help maximise client convenience. On the pro side, think through customer conversion vs. retention needs, and optimise for the highest and most economical utilisation rates.

Your product will need to take into account customisation services or projects needed, an understanding of whether the pro is right for the job and the flexibility of communicating the request.

Maximising value means providing maximum convenience for the client and maximum utilisation rates for the pro.

Is AI in Product just Hype?

Anyone who watched Jian Yang’s app label all food as either ‘Hotdog’ or ‘Not Hotdog’ in Silicon Valley may not realise how accurate this scene really is, says James Somers for MIT.

It’s the new normal for every startup and tech company to talk casually about how they’re ‘using AI’ to accelerate their product’s value. In most cases, these claims overlook 2 fundamental realities. The first is the sheer size of the data sets necessary for machine learning to be applicable, the second is how limited the technology still is.

To get a person to recognise a hot dog, you show her a hot dog. To get a deep-learning system to recognise a hot dog, you might have to feed it 40 million pictures of hot dogs.

Building Products for Emerging Markets

Local challenges for Product Managers can be very different from those in developed countries, says Google’s Alyssa Maharani

In Summary: For much of the world’s population, the Internet is still slow and unstable. Ensuring your product requires minimal data to operate is key to ensure adoption. It’s also essential to incorporate some form of ‘offline mode’ to ensure that customers can continue using your product when there is no Internet coverage at all.

English continues to be the language of social status so products can still be designed in English. But Product Managers should consider adding symbols and icons to help those with less understanding of the language.

Many people buy secondhand phones in emerging markets so products must be optimised for older makes, slower processors, and lower memory space. To test a new release, go to known ‘blindspots’ in the country, buy some secondhand phones and continuously gather feedback.

Featured Product Event

Product Talks | Product Strategy Meetup — 17th October

Product Strategy geeks who happen to be in London on Tuesday 17th October may want to check out Krishna Panicker’s talk at Rainmaking Loft entitled ‘Know thy Competition.’

A former Product Manager at Microsoft, Skype and Blink, Krish has some great insights into the link between disruption and strategy and why Product Management isn’t about making a great product but about making the user awesome.

Originally published at Pivot Product Hits.

Pivot Product Hits — October Edition was originally published in HackerNoon.com on Medium, where people are continuing the conversation by highlighting and responding to this story.

How can Machine Learning lead to better Product Design?

Quora’s CEO wades in (on Quora, obviously…)

In Summary: Machine learning can help curate a better product over time. Predicting user behavior helps shape your UX around how people will use your product.

Machine learning helps reduce the need for the user to make choices. If you have a search engine, the searches people perform (and the sites they go to) can predict what they’ll want to search for next.

Almost all B2C products these days have interfaces that are driven by machine learning recommendations. These includes Quora, Netflix and Spotify. Netflix, one the one hand, gives users very little control over what it will recommend. Twitter, on the other hand, largely constrains your timeline to tweets from people you follow.

Are voice-controlled Products just hype?

The full potential of voice UIs is still to be realized. For now, they remain little more than voice-controlled smartphones, says FastCo’s Katherine Schwab.

In Summary: A recent study by Microsoft revealed that most people still don’t have a mental model of how VUIs are supposed to work. The biggest challenge is one of the simplest: it’s hard to understand what they can and can’t do.

Only 14.3% of respondents used their smart home device to shop. The reasons given were the lack of a screen and not knowing how to use the device to shop.

In the main, people use their voice devices to do relatively simple tasks they could also do using their smartphones. The most popular use cases are asking the device to play a song, control smart lights and set a timer. And asking the weather.

This indicates that voice is an auxiliary technology, not a primary one, undeserving of the hype it’s received so far.

Want to build the next great Product?

To spot the next great product opportunity, focus on what doesn’t change, says David Mattin.

In Summary: Consumer trends are made from two fundamental things: change and basic human needs. Most of the products we use today serve some basic human need. Security, value, distraction, convenience and fun are a fundamental part of our nature. They’re never going away.

Truly new ways to serve a basic human need are rare. The best way to spot new trends is simply to look at the new products entering the market and ask: does this serve a basic human need in a new way?

AI is a tech trend. The really powerful trends, that tell you something meaningful about the future, are trends in human behaviour and expectation.

How Products hook users

Like it or not, habit-forming technology is already here, says Nir Eyal.

In Summary: As infinite distractions compete for our attention, companies are mastering new tactics to stay relevant in users’ minds and lives. We’re faced with a future where everything will become more addictive.

Companies increasingly find that their economic value is a function of the strength of the habits they create. Following the lead of tech giants like Facebook and Google, product teams everywhere are mastering the mechanics of habit formation to increase engagement with their products.

Habit-forming technology creates associations with ‘internal triggers’ which bring users back without the need for marketing or stimuli.

As a result, consumers need to understand how habit-forming technology works to prevent unwanted manipulation.

What is your Product really selling?

In a marketplace of distraction, products that save you time are going to win, says Gary Vaynerhchuk.

In Summary: Too many people focus on shipping a technical iteration or adding features to a product that only complicates the experience.

No one wants complexity layered upon their daily life. No one cares about specifications and numbers anymore. People literally want cars to drive themselves! They want freedom and simplicity and speed.

AI is an important technology because it saves you time. It can learn and automate processes which would have taken much longer. Virtual assistants save you time. Google Now and Siri save you time. Uber saves you time. It’s why they’ve won.

The main thing product teams should ask themselves is: how does my product expedite a market experience that used to be tedious and tiresome for all?

The Process vs. The Product

Customers only care about how our products feel in their hands, nothing else, says Tinder’s Jeff Morris Jr.

In Summary: We work in an industry that glorifies the process of everything we build. We’re obsessed with roadmaps, methodologies, acronyms, and productivity tools. But we need to remember that customers don’t care about how we build our products, or our process.

We spend our days writing specs, filing Jira tickets, and editing roadmaps. This is Process.

Our job is to delight customers through the projects we build. Process is important, but do not forget that customers judge us on one thing. This is the Product.

Why Product Engagement is your most powerful salesperson

It’s well known that ‘helping is the new selling.’ Which is why delivering product value, measured by user engagement, is the most powerful sales tool you have.

In Summary: Some time ago, SaaS companies discovered they had created a new channel for lead generation. The new channel was the product itself and the new leads it produced became known as Product Qualified Leads, or PQLs. PQLs are users who reach pre-defined triggers that signify strong likelihood to become a paying customer.

The definition of a PQL will differ from product to product. What stays constant is that engagement strongly correlates to purchase propensity. So sales teams can efficiently invest time and energy communicating only with those that tip the scales.

Today, every high-performing SaaS company aligns their product, engineering, customer success and growth teams around a central goal (happy, engaged users) underpinned by robust data that provides measurable outcomes.

Your customers hate MVPs! (And you should too…)

No one wants to use an unfinished product its creators are embarrassed by, says WP Engine’s Jason Cohen.

In Summary: Product teams have been following the MVP dogma for years without re-evaluating whether it’s the right way to maximize learning while pleasing the customer. Customers want great products they can use now.

Products that do less, but are loved, are more successful than products which have more features, but that people dislike. Google Docs had just 3% of the features of Microsoft Word when it launched. It succeeded because it did a great job at what it was primarily designed for: simplicity and real-time collaboration.

Not every product has to become complex. Some products can (and should) remain simple, lovable and complete.

Product Quote of the Month

“Simplicity and quality of design has become a moat, especially when coupled with Product features that encourage adoption or new layers of value for incremental users.”

Applause for Greylock’s Sara Guo — an excellent summary of the product strategy landscape.

Originally published at pivotservices.curated.co.

Pivot Product Hits | September Edition was originally published in HackerNoon.com on Medium, where people are continuing the conversation by highlighting and responding to this story.

“In a freemium world, there’s far less sales involvement. The product does the majority of the selling.” — Jess Iandiorio (Drift)

It was some time ago that SaaS companies discovered that, by aligning engineering, marketing and data teams they had created a new channel for lead generation. Better yet, the channel was usually more effective than the established sales and marketing practices they had previously relied upon in terms of conversion.

The new channel was the product itself and the new leads it produced became known as Product Qualified Leads, or PQLs.

As Tomaz Tunguz observed at the time,

“PQLs are potential customers who have used a product and reached pre-defined triggers that signify a strong likelihood to become a paying customer.”

These qualified leads could be passed to the sales team, where they typically converted at 25–30%.

“The potential to leverage the a SaaS product’s freemium tier or trial period to identify high quality leads has never been greater.”

Fast forward to 2017 and the potential to leverage the a SaaS product’s freemium tier or trial period to identify high quality leads has never been greater, thanks to improved understanding data science and a suite of analytics and instrumentation packages that have shifted the needle definitively from build to buy.

As a product manager, it’s easy to get lost in vanity metrics and data points. But it’s clear to any product team working in B2B SaaS that the real ‘metric that matters’ for qualifying propensity to purchase AND propensity to churn is product adoption.

As Josh Elman recently reaffirmed, the only thing product teams really need to think about are:

• Are people using your product?
• Are they using it how you expect?
• Are they performing at the frequency you expect?

You want to understand which users are more likely to come back than others. Those that are highly likely to come back are your core users. You want to have most of your new users converting to core in the first month

Once you can predict which users are core, you can start figuring out what things they did to increase the likelihood of being a core user. The best starting point is to calculate how likely someone is to return to your product in Month 2 based on how many days they visit in Month 1.

In fact, this ethos now forms the central axis of any high-performing SaaS outfit, aligning Product, Engineering, Customer Success and Growth teams around a central goal (happy, engaged users) underpinned by robust data that provides measurable outcomes.

Long standing principles of marketing, like the concept of ‘The Funnel’, have been irrevocably challenged by social media channels that make it easy for people to become advocates for a brand (like Instagram followers) without ever becoming a customer. Consumer engagement is no longer linear so new touch points have emerged to measure the path to purchase; almost all within the product itself.

“Each company will have its own unique set of product engagement metrics which means the definition of a PQL will differ from product to product.”

Each company will have its own unique set of product engagement metrics which means the definition of a PQL will differ from product to product. What doesn’t change between them is that engagement strongly correlates to purchase propensity so sales teams can efficiently invest their time and energy communicating only with those that tip the scales in this regard.

In the B2B space in particular, there’s another vector that the product team can leverage to positively impact sales; one that precedes AND impacts engagement. Product design itself.

Amongst Sam Altman’s extraordinary trove of quotes and anecdotes is one that has become part of the Y Combinator creed:

“Until you’ve built a great product, almost nothing else matters.”

Simplicity, usability and elegance are not terms typically associated with enterprise software. But, as the sales environment evolves, so must the product.

Slack is the poster child for adopting consumer-grade design as its secret weapon for winning in B2B. Instead of focussing on selling their product, they focus on delivering value by obsessing over every interaction and ‘micro-moment’ of the product experience.

It’s well known that ‘helping is the new selling.’ Which is why delivering value, measured by product engagement, is the most powerful sales tool in SaaS.

Originally published at www.notioncapital.com on August 24, 2017.

Why Product Engagement is the most powerful salesperson in SaaS was originally published in HackerNoon.com on Medium, where people are continuing the conversation by highlighting and responding to this story.

What (exactly) is an Anti-Active Usage Product?

Engagement is a lagging indicator, says Plainflow’s Leonardo Federico.

In Summary: Most Products Managers monitor user engagement as a key ‘metric that matters’ for their product. But user time is finite and the impact on our lives of multiple products demanding our attention is constant distraction (from notifications) and context-switching.

‘Anti-active usage’ products up end this logic. With anti-active usage products, the user doesn’t need to do anything. The product works in complete autonomy, yet still delivers outcomes.

By saving their users’ most precious resource (time), anti-active usage products challenge our preconceptions about retention and product engagement and set a new standard for value delivery.

Are people really (really) using your Product?

As a counter to Leonardo’s post above, here’s Greylock’s Josh Elman on why usage is still the most important signal for most.

In Summary: As a Product Manager, it’s easy to get lost in vanity metrics and data points. However, the only thing Product Managers really need to think about is:

• Are people using your product?
• Are they using it how you expect?
• Are they performing at the frequency you expect?

You want to understand which users are more likely to come back than others. Those that are highly likely to come back are your core users. You want to have most of your new users converting to core in the first month.

Once you can predict which users are core, you can start figuring out what things they did to increase the likelihood of being a core user. Start by calculating how likely someone is to return to your product in Month 2 based on how many days they visit in Month 1.

Feature Creep isn’t the real problem!

Feature creep disguises an inability to execute on the core value of your product, says Hiten Shah.

In Summary: If you’re struggling with feature creep, you’re really experiencing the manifestation of a few root problems.

It may be because you don’t know what your market demands. As you grow, you gain new customer segments with different needs. It’s all too easy to build features for each segment that aren’t relevant to your overarching product vision.

It’s a Product Manager’s job to ensure everyone internally has the same understanding of what you’re building. You’re doing more harm than good by letting everyone have their say.

You won’t win by obsessing over feature creep, you’ll win by addressing the real underlying problems. To avoid feature creep, be clear on what your product is and how to best deliver it to each customer segment.

People need my Product!

But do they want it? asks Justin Jackson.

In Summary: The only way to successfully market a product is to make something people want. Identifying a ‘need’ isn’t enough. It’s difficult for people to do things they know are good for them. The benefit is too far in the future. People need to lose weight for their long-term health, but most don’t.

But, there are products that help people lose weight and switch away from fossil fuels. So, what’s their secret? They package their products in a format that people want.

To help reduce hydrocarbon emissions, Elon Musk started with something people wanted: a fast, luxurious vehicle (the Model S).

Customers buy emotionally and then rationalize their purchase with logic. To succeed, build something that gives users a quick win, and then continues to provide value over time.

Don’t just build Products for power users!

Beware the vocal minority, says Amplitude’s Mark Dondanville.

In Summary: Power users use your product regularly and know it inside out. Unlike average users, they give you feedback and leave comments and in-app reviews.

But power users only make up a small percentage of your total base. As a Product Manager, your goal is to attract new users, turn them into average users, then to power users.

Listening to your customers keeps you in tune with their needs. But the issues power users have often apply only to them, not the wider user base.

Make sure you listen to all of your users, not just the most vocal, and that the Product Team is focussed on converting new users into power users as rapidly as possible.

Are subscription Products bad actors?

I’m fine with the old version, says Guise Bele.

In Summary: Do you remember when you could buy Word, Excel and Windows on a perpetual license which barely ever changed? All of them are now available on subscription. Why? Because renting software forever clearly costs you more money than buying it!

Despite the current popularity of SaaS, subscription models are bad for customers when introduced purely to relieve Product Teams of having to continuously innovate and deliver value.

Should Product Managers employ Radical Candor?

Radical Candor was a spirited attempt to bridge the divide between ruinous empathy and obnoxious aggression. Thanks to Kim Scott’s book of the same name, it’s become a ‘hot’ business topic in the last 2 years.

In essence, it’s a communication framework that allows practitioners to walk the fine line between genuine empathy, critical feedback and tough decisions. However, it’s been associated with questionable practices, such as ‘front stabbing’, and used as an excuse for workplace hostility.

Most Product Managers are well intentioned in their communication but it’s all too easy to drift back to old habits. Some people are naturally inclined towards ‘people pleasing’, whereas others are less empathetic. Understanding the concept of Radical Candor makes us more aware of our own natural inclination.

Featured Product Event

Strategies to make anyone use your Product

Thanks to everyone that came down to my talk at Products that Count in London last month. For those that weren’t able to make it, here are the slides from the session.

Sadly, most of the audio was lost from the footage so the actual presentation isn’t available. But thanks to SC and Gunita for having me, I can definitely recommend their monthly sessions.

Product Quote of the Month

Common misunderstandings about building software products.

From a great list by John Cutler.

Originally published at Pivot Product Hits.

Pivot Product Hits — August edition was originally published in HackerNoon.com on Medium, where people are continuing the conversation by highlighting and responding to this story.