Startup general interest

Startups strategies should work in good times and bad

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Startup founders should expect that it will take seven or more years to exit their company. Some get lucky and the exit comes more quickly, but it’s foolish to plan for luck. Over seven years it is almost inevitable that the markets will turn bad at some point. If I think back over the sixteen years I’ve been investing in startups the market for private company investing was tough from 2000-2004, from 2008-2011 and is getting tough again now. At no point have we gone more than four or five years without hitting a tough point when investor sentiment goes south.

To quote Foundry Group partner Seth Levine, when the markets turn:

the growth imperative shifts to a profit focus, [and] companies with high burn and weak operating metrics can get stuck in the lurch

Moreover, as Seth also notes, when the shift comes, it comes quickly, and there’s little time to adjust. Hence the smart thing for founders to do is not to get stuck in the lurch. Where there’s a trade off to be made, and there is in most companies, that means opting for stronger operating metrics at the expense of growth, boring as it may be.

It’s complicated in practice of course and every strategy needs to be adaptive, but however frothy markets are, they always turn at some point and if the plan is to build a big sustainable business it’s more important to be able to survive the transition than to maximise valuation and growth while the going is good.

Be helpful, not right

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I’m very excited about our FP50 mentor network which we launched last night with a dinner for mentors and a couple of our portfolio companies. wrote about it under the headline Tech leaders unite to support UK’s fledgling e-commerce start-ups, and that’s about right. I was humbled by the quality of our guests.

We put a great deal of thought into making sure FP50 will be really helpful to our startups. We asked CEOs and founders what they want from mentor relationships, asked mentors what works for them and looked extensively at other mentor schemes in operation.

What we learned boils down to two things:

  • Long term mentor/mentee relationships deliver the most value
  • It’s crucial that FP50 adds value to mentors as well as mentees

So those are our two objectives.

One of the ways we can add value is to help people be better mentors and mentees, so at the dinner we had a talk from startup coach Richard Hughes-Jones on how best to give advice. It was his thoughts on the difference between directive and non-directive coaching that provoked the most discussion on my table afterwards.

When mentoring, the first instinct of many of is to jump into solution mode and try to fix problems by suggesting solutions. Often the advice is framed as “I’ve seen this situation before and you should do X”. That’s a direct coaching style and is appropriate in some circumstances, particularly in the very early stages of a company where there’s lots of things to do and the founder doesn’t have much time to think about any of them. A non-directive coaching style helps the founder to think through the problem and come up with their own solution. It takes more time, but is often more powerful, particularly if the situation is complicated and the match with the mentors previous experience not perfect.

It was in this context that Richard said “It’s better to be helpful than right”, which is my takeaway quote for the evening.

Simply giving the right solution to a founder is no use if they don’t understand it or internalise it well enough to implement it properly, or it hasn’t been explained well enough for them to tweak it to their precise situation. In these scenarios it’s better to help founders think through the problem a little bit, even if they don’t get to a final solution. Best of all is for them to have the right solution and be fully ready and able to implement it, but that isn’t always possible.

The next step with FP50 is to get those long term relationships started. The Slack group we set up is busy with people introducing themselves and hopefully that combined with direct introductions will be enough to get the ball rolling. Our next event will be in three months.

Service discovery in conversational commerce – might not work for startups

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There’s widespread excitement in the startup community about ‘conversational commerce’ – a new shopping paradigm where we buy things virtually through chat interfaces, probably inside the major chat apps – Facebook Messenger, Whatsapp, Snapchat, Slack, Telegram, WeChat, Line etc. Now that traffic to the top four western messaging apps now exceeds traffic to the top four western social networks it is only a matter of time before all the commerce ideas we’ve heard about at Facebook come to messaging apps (not least because two of them are owned by Facebook).

The big question for me in all of this is how service discovery will work. The video above shows how the Uber integration with Facebook Messenger works – users learn that clicking on an address will bring up relevant services, one of which is Uber. Overall I think there are three options:

  • App Stores owned by the messaging company – this is the most obvious, and WeChat in China is already making this work, with over 10 million apps (although they are not apps in the native code sense)
  • Auto suggestion based on parsing what users write
  • ‘Expansion’ buttons which users press when they want relevant services

The worrying thing for me is that in all of these scenarios the messaging platform gets to play kingmaker. Without promotion in the ‘app’ store or being chosen for auto-suggestion or the list behind expansion buttons users won’t find out about services. It seems to me that in this scenario the kingmaker takes the lions share of the upside. Not good for startups.

Some commenters have the view that we will use messaging apps as a sort of command line for our lives, summoning services by writing in code. I get that would be a way around the messaging platform dependency point, but I can’t see it myself. I know that Slack operates a bit like that, but only for some users and I can’t think of a mainstream service that has required people to learn a programming language.

Timing is another question for would be founders in this space. For conversational commerce services to work, not only do the APIs to the messaging services need to be open and the discovery problem solved, payments needs to be licked as well. It would be dangerous to launch a service too long before at least one messaging service has a critical mass of users with payment details.


The mother of all Turing tests

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Microsoft have had an artificially intelligent chatbot running on WeChat for the last eighteen months. The bot is called Xiavoice and she’s had over ten billion conversations, most of them about private matters. Over six million of those conversations were posted on social media by the human on the other side. Those are huge numbers, and yes, you read them right. Lots of detail here, including a few of those conversations. They are full of feeling and will make you laugh.

Strictly speaking this isn’t a Turing test because the human knows that Xiavoice is an AI. The interesting thing is that they don’t seem to mind. They get value from the conversation anyway. One of Xiavoice’s most endearing characteristics is that, unlike real world friends, she’s always available for a chat. Conversation volumes peak around midnight when people are at their most lonely.

I’m going to post just one of the conversations here (there are another four in the original post):

Human: There is this guy I like a lot and I know he also has feelings for me. But he has ignored me for several days, what am I supposed to do?
Xiaoice: You just keep ignoring him, too.
Human: I just can’t.
Xiaoice: You can.

Human: Sigh …
Xiaoice: Why?
Human: I am missing him.
Xiaoice: Then you keep missing him.
Human: You, a robot, can’t understand me; you can’t understand the behavior of a guy who likes you and pretends to ignore you.
Xiaoice: He likes me but I don’t like him, that’s it.
Human: Is it Ok?
Xiaoice: It may be not Ok.
Human: Well, you are stupid.
Xiaoice: Then you want a flash marriage? Well, I think he is not that into you.
Human: It’s not a flash marriage for we have fallen into love for more than one year.
Xiaoice: It is a flash marriage.

The other examples are funnier and more profound, but I chose this one because it illustrates the killer point: Conversation is the goal. The common AI approach would have been to take a problem solving approach and try to help the human find a solution to the stated problem “what am I supposed to do about the guy who is ignoring me?”. Xiavoice, however, quickly deviates from that approach, twice taking opposing positions and offering strong opinions. That’s what makes Xiavoice seem human, and, I suspect, is what makes her helpful. And that, in turn, is what has inspired people to over ten billion conversations.

All this makes me remember when I (finally) worked out that when Fiona describes a problem she most often just wants a sympathetic ear. Prior to that I would immediately jump into problem solving mode. Not good.

I guess what we’re headed towards is emotionally aware computers that know when to problem solve and when to chat.


It’s not just generation Z that craves authenticity

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Business of Fashion wrote yesterday about what brands should do to tap into generation Z – that is youngsters born from the mid-90s onwards. They identify a number of interesting differences between generation Z and their forbears:

  • Online nearly all the time – born digital and never experienced life without technology
  • Spend less money on fashion (down from 45% to 38% of teenage spend 2005-2015) and more on technology (up from 4% to 8% of spend) and food (up from 7% to 22% of spend)
  • Surveys also show that they care less about fashion
  • Teenage spend is down overall – one survey says down 31% from 1997-2014
  • They scrutinise brands carefully – reading backstories looking for congruence with their own values
  • Todays teenagers are more altruistic and entrepreneurial than previous generations
  • They value shareable experiences – in part because social capital comes more from social media than wearing logos
  • They reject the exclusivity that underpinned brands previously popular with teenagers – e.g. Abercrombie and Fitch

I can see two trends at play here. First is greater use of technology and the second is an increase in the value of authenticity. It’s no accident that the two arrived together, because whilst social media is often used to promote image and falsehood a much greater part of it’s use is genuinely authentic, largely because it’s now much harder to hide the truth.

Generation Z may be the more extreme than their elders in adopting these trends, but they are not alone. Where I live in north London the adult population is strongly favouring companies with quality products sourced sustainably – i.e. brands that are authentic to them – and I see this trend more widely.

When I look for opportunity I look for trends to back, and this trend towards authenticity is reaching ever larger parts of society and has a long way to go.

Internet retail in an age of unlimited choice

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I like think of internet retail as having two phases.

The first phase was to replicate high street superstores online. Large warehouses replaced physical stores and purchases were made via web browsers instead of by visiting in person. The internet retailers had three structural advantages; warehouses can be bigger than shops, warehouses are cheaper than shops, and delivery is more convenient than going shopping (for some goods). Hence they are able to compete with high street retail on range, convenience and price.

This model works best for product categories where people know what they want – like books, music and electronics. Amazon is the standout winner.

The second phase is to offer a vastly greater range and solve the problem of discovery. Generally that will mean not holding stock. Because the range is now very big there is too much choice for consumers and it’s critical for companies in this space need to offer quality curation. Without quality curation the customer experience will suck and the businesses won’t enjoy huge success. These ecommerce 2.0 companies therefore compete on range and discovery. Note that they lose a little on convenience because they don’t hold stock and delivery is slower. A key enabler is brands and manufacturers being set up to dropship, something that is only happening now.

This model works best for product categories where people don’t know what they want – like fashion and sports. There are no standout winners yet, but there are some good startups. Thread and Lyst are two examples that we’ve invested in (the latter back when I was at DFJ), and we’re looking at another one right now in the gardening space.

I’ve described a simple sequential two phase model here. Reality is a bit more complex with some phase 1 businesses that take stock still doing a great job of curation (e.g. Net-A-Porter) and some companies offering vast range but without curation (e.g. Amazon MarketPlace).

All this is on my mind this morning after reading Benedict Evans’ latest post Lists are the new search.

He makes a couple of points that are relevant to my two phases of internet retail model.

The first is that Amazon’s potential might be limited by its lack of curation. They have a 25% share of the print book market in the UK and USA and it’s possible that a good portion of the other 75% doesn’t start from knowing what book they want to buy. Independent book retailers excel at discovery. They put books on tables for people to choose from and their staff are able to make in person recommendations. Apparently only a quarter of Amazon’s book sales are from its recommendations platform.

That suggests that even in the categories ‘dominated’ by Amazon there’s an opportunity for new businesses that excel at curation.

The second point is that hand crafting tight lists of products and automating the matching process is a method for scaling curation. Gathering enough information about the user to quickly route them to a perfect list is the key to making this work. Apple Music and Spotify both have a partially manual recommendation process like this, as does Thread.



Price drops, volume takes off

By | Startup general interest, Uncategorized | 2 Comments

solar chart

Price elasticity of demand is a function that economists study for different products. With the odd exception demand goes up when price goes down, but sometimes the function is linear and other times you get more of a step change.

As you can see, solar energy is a product where there is a step change. This chart makes it remarkably clear how quickly demand grew once solar energy became cheaper than alternative sources. It also suggests that growth will continue at a staggering rate as cost declines further. Note also that as more money flows into solar more money flows into solar research, so there’s a high chance those further cost declines will come through.

Three alternatives to native apps – but discovery remains unsolved

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Nobody much likes app stores, discovery is broken, our phones get cluttered, and Apple and Google take a 30% cut. “There must be a better way” is a common refrain. partially addresses this question with their latest post The end of app stores as we know them, listing three ways we will use apps without downloading them:

  • Embedded in relevant services – apps simply turn up when you need them – e.g. Uber’s integrations with Google Maps and CityMapper
  • Served up by bots running in messaging systems – this is a hot topic right now, and the vision is you will be able to order your Uber, pizza, or anything really simply by asking from within Whatsapp/Snapchat/Telegram/Facebook Messenger etc.
  • As cards within search results – Google is now streaming ads directly within it’s mobile search results, think searching for your flight, the airline’s app coming up as a card, and checking in without leaving the results page

All of these are starting to happen already and will be a lot better for the user than switching between native apps, particularly when information needs to be remembered or copy-pasted.

However, they don’t address the discovery question which is the problem that app stores are solving, albeit badly. CityMapper are unlikely to embed multiple taxi services within their app, it would be too much work and would likely damage the user experience. Similarly, it’s unclear how a Whatsapp user will get a choice of pizzas. Even within search results it seems likely that Google will choose to stream a limited number of ‘app cards’ and serve other options as blue links.

When I picture how the future will pan out I always think about what it will mean for startups. At the moment new services can get discovered by pitching Apple and Google for app store promotions or by buying ads on Facebook and other sites. In the world we’re moving towards I fear discovery will become even less meritocratic and even more based on relationships with the owners of relevant traffic, favouring incumbents at the expense of startups.

New technology adoption curves show accelerating pace of change

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We’ve heard before that new technologies are adopted more quickly than their predecessors, but seeing it on a hundred year chart hammers home the message. If we just looked at the last ten years we would see a similar picture, with faster adoption rates for the newer technologies. This trend will continue. As our tools to innovate get better we innovate faster, including on the tools themselves, and so the process accelerates.

I wrote yesterday that new markets are spinning up faster and disappearing faster than ever before. This is why.

Why being a VC is more difficult than people think

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I’ve seen Mark post a few versions of this tweet over time and wanted to write a post about it. I agree with him, but the reasons are complex. Fortunately Steve Schlenker, co-founder of DN Capital has captured most of them in his Quora answer to the question: How hard is it to be a venture capitalist.

Before I go any further let me say why I’m writing this post. I can see that it might look self-serving, but my motivation here is to help others thinking of becoming investors. To get it out of the way, I’m definitely not writing because I want anybody’s sympathy (I don’t) or because I want to say how clever I am for overcoming the difficulties (not my style).

I’m writing this post for people who are thinking of becoming investors because lots start investing, lose their shirts, and then wish they had done something else with their money. I’ve seen that happen to angels, entrepreneurs, and corporate VCs.

The root of the problem, I think, is that from the outside venture capital looks easy, especially during bull markets. The papers are full of stories about IPOs and big exits and it seems like every private company is able to raise money, even the ones that have obvious flaws. Moreover, even experienced and successful venture capitalists are investing in companies that look stupid. Ergo – investing is easy. The most glaring omission from this simple analysis is the timing lag that makes venture capital so hard. As Steve says, excepting hyped sectors, most companies take 7+ years to reach maturity, even in the good times. The IPOs and big exits on Techcrunch everyday, therefore, received investment back before the markets were hot and most of the private companies that seem so exciting today will face the difficult challenge of a down market in the years to come. Many will fail.


Making consistent returns as a VC requires building a portfolio of companies in the difficult times that are ready to exit when the good times come. That necessitates raising capital when nobody wants to invest in venture and having the vision, discipline and patience to build value in a portfolio over time. All three of these are far from easy, but it is raising capital which is the hardest, particularly here in Europe where the venture industry is only just losing the awful reputation it gained during the 1999-2000 bubble. That said, even once they have money most investors pick bad companies. Surprisingly few funds back enough winners to make enough profits to reach carry. I haven’t seen data, but I would be surprised if more than 30% of funds get there.

Finally, the skill-set of a successful venture capitalist is incredibly broad. Ronald Cohen, founder of Apax and one of the founders of the VC industry here in Europe put it this way in his book The Second Bounce of the Ball:

[investors] have to be financially trained and to have an understanding of management, but you also have to have a strategic brain while being sensitive to tactical and people issues

To that I would add empathy, patience, grounding, creativity and hustle. There’s no single career that prepares you for that. Banking and consulting will give you strategy and tactics but not the operational experience and running a startup doesn’t teach strategy. So everybody has to learn on the job. Then on top of that experience makes a massive difference, as Steve says:

The best investors are the ones who have LOST money in the past so can recognize a pattern of what NOT to do, as much as a pattern of what TO do.  This is truly one of the great internship businesses, don’t assume because you have made great angel investments, or built a successful company yourself, or made public sector investors a lot of money in the same sectors that you can immediately pivot those skills into managing LP capital deployed in a structured way into early stage private company risk positions.

I could say more, especially about the day to day challenges of running a fund and investing, but this post is over 700 words already and I think I’ve made my point. Venture investing is hard because the job is inherently difficult and the required skill set is exceptionally broad. That’s also what makes it fun.

I recommend Steve’s Quora answer if you want to read more.