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This presentation is from my talk at the 2017 SaaStr Annual Conference in San Francisco. It offers an overview of a simple model to understand a SaaS business and the key levers a CEO can pull to get the most impact. The presentation covers: Optimizing the SaaS Funnel: - Get inside your customer’s head - Break down the funnel into microsteps - Identify bottlenecks - Use funnel math to make improvements 12 key levers within the funnel: 1) Product/Market fit 2) Top of the funnel flow 3) Conversion rate 4) CAC (customer acquisition cost) 5) Number of sales people 6) PPR (productivity per rep) 7) Getting enough leads 8) Pricing 9) Customer retention rate 10) Dollar retention rate 11) Months to recover CAC 12) Recruiting, onboarding & management

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We’ve shared a lot of data about whether and why ‘this time is different’. But beyond that, why is the tech market opportunity larger than any time in history (no, really!)? One word: mobile. In this update of his past presentation on Mobile Eating the World — delivered this month at Andreessen Horowitz’ annual investor meeting — a16z’s Benedict Evans shares just how and why mobile changes everything. Because tech is outgrowing the tech industry.

Mobile Is Eating the World (2015)

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+ Updated version for NEXT Conference Hamburg + https://nextconf.eu/event/how-deep-learning-is-changing-the-design-process/ Deep learning is a new and exciting subfield of machine learning which attempts to sidestep the whole feature design process. This session explains how it derives from AI, why it quietly became a part of user experience and how it also changes the actual design workflow. The talk highlights a range of use cases and doesn’t forget to illustrate why user experience design for artificial intelligence matters the other way around.

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Isn't AI going to be dominated by the big companies like Google and Amazon and Microsoft and Baidu? What can startups do to thrive in this ecosystem? What are investors looking for when they meet AI-powered startups? Should startups with AI inside think about their go-to-market process any differently from other startups? Frank Chen from Andreessen Horowitz will tackle these and other AI startup questions in this session.

Frank Chen at AI Frontiers: Startups and AI

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Network effects. It’s one of the most important concepts for business in general and especially for tech businesses, as it’s the key dynamic behind many successful software-based companies. Understanding network effects not only helps build better products, but it helps build moats and protect software companies against competitors’ eating away at their margins. Yet what IS a network effect? How do we untangle the nuances of 'network effects' with 'marketplaces' and 'platforms'? What’s the difference between network effects, virality, supply-side economies of scale? And how do we know a company has network effects? Most importantly, what questions can entrepreneurs and product managers ask to counter the wishful thinking and sometimes faulty assumption behind the belief that “if we build it, they will come” … and instead go about more deterministically creating network effects in their business? Because it's not a winner-take-all market by accident.

Network Effects

Looking to scale something up? Depending on how you're going after your market/ acquiring users, you may need to build a sales organization that's optimized for a top-down or bottom-up sales process (or perhaps both). Watch the video overview at http://a16z.com/2015/03/06/go-to-market-bootcamp/ and then check out this slide deck, which shares some concrete tips and tools for accelerating time to market -- from the go-to-market experts at a16z, led by 'sales savant' Mark Cranney. Because selling to enterprises is a lot like getting a bill passed through Congress: it can get stuck. And getting stuck -- or going down the wrong path -- can mean death to startups in a competitive market. Here's how to avoid that.

Go-to-Market Best Practices for Startups

What you'll get from this deck 1. The M&A race for AI: by the numbers 2. Watch out! hype ahead: definitions & disclaimers 3. Machine Learning drivers: why is Machine Learning a ‘thing’ now (vs before) 4. Venture Capital: forming an industry, the AI/ML landscape 5. The One Hundred (+13) AI startups to watch in the Enterprise 6. The great Enterprise pivot: applying Machine Learning at scale 7. - where to go next -

Solve for X with AI: a VC view of the Machine Learning & AI landscape

Ed Fernandez

In this update of his past presentations on Mobile Eating the World -- delivered most recently at The Guardian's Changing Media Summit -- a16z’s Benedict Evans takes us through how technology is universal through mobile. How mobile is not a subset of the internet anymore. And how mobile (and accompanying trends of cloud and AI) is also driving new productivity tools. In fact, mobile -- which encompasses everything from drones to cars -- is everything.

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From KTVL News10: Oregon is currently one of two states that does not allow customers to pump their gas. A law passed by the Legislature in May and signed into law by Gov. Kate Brown in June will allow Oregon counties with 40,000 residents or less to deviate from that. Gas stations in two central Oregon counties will continue to pump gas for customers despite a new law allowing self-serve gasoline in rural counties that takes effect in a few days.

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