In this post: Data Driven Cultures in startups should be better at prospection than other cultures. Data Driven Cultures Carl Anderson, 2015 (Data Scientist at Warby Parker) defines a data driven culture as: Is continuously testing; Has a continuous improvement mindset; Is involved in predictive modeling and model improvement; Chooses among actions using a suite of weighted variables; Has a culture where decision makers take notice of key findings, trust them, and act upon them; Uses data to help inform and influence strategy. Prospection There is tremendous variation in how people think about the future. There’s a lot of variation in how people think about how people think about the future. If I were to use a very strong magnet[…]
Author: Christopher Berry
In this post: Data Driven Cultures in startups should discover product-solution-market fit more reliably than Ego Driven Cultures Data Driven Cultures Carl Anderson, 2015 (Data Scientist at Warby Parker) defines a data driven culture as: Is continuously testing; Has a continuous improvement mindset; Is involved in predictive modeling and model improvement; Chooses among actions using a suite of weighted variables; Has a culture where decision makers take notice of key findings, trust them, and act upon them; Uses data to help inform and influence strategy. Startups A startup is defined as an experiment looking for a problem-solution-market fit. The goal of a startup is to become a business. To do that, it must discover a market, a subset of people[…]
Consider the statement: The strategies generated by data driven cultures are likely to produce sustainable competitive advantages. Data Driven Cultures Carl Anderson, 2015 (Data Scientist at Warby Parker) defines a data driven culture: Is continuously testing; Has a continuous improvement mindset; Is involved in predictive modeling and model improvement; Chooses among actions using a suite of weighted variables; Has a culture where decision makers take notice of key findings, trust them, and act upon them; Uses data to help inform and influence strategy. Strategy For the purposes of brevity, I’ll define a strategy as: An artifact; That enunciates choices selected from acknowledged tradeoffs; Which is rooted in a paradigm; That is actionable; With the intent of causing a sustainable competitive advantage in[…]
What is a data driven culture? Data Driven Cultures Carl Anderson, 2015 (Data Scientist at Warby Parker) describes a data driven culture as on that: Is continuously testing; Has a continuous improvement mindset; Is involved in predictive modeling and model improvement; Chooses among actions using a suite of weighted variables; Has a culture where decision makers take notice of key findings, trust them, and act upon them; Uses data to help inform and influence strategy. This is a fine summary and worthy of unpacking. The Big Why Data driven cultures are likely to produce better, sustained, performance over time than the alternatives. It’s not even worth considering the alternatives to a data driven culture. How do you know if a[…]
Into the trough of disillusionment with the hyped technologies! The canary in the coal mine for me, with respect to BitCoin, is this post. Look, nobody has enjoyed more popcorn around BitCoin than I have. From Coinye to Dogecoin, crypto-currencies have delivered the lulz. Do I believe there’s a slope of enlightenment for crypto-currency? Absolutely. Do I believe that’s imminent? Nope. Banks are apex ruminants. The lessons from BitCoin have to be fully digested before something really good comes out of it. Machine learning. Huge potential and the best is yet to come. The first wave around machine learning gave us Netflix and Amazon. And then the bloom came off the rose a bit. And now there’s deep learning and we’re[…]
Some reports have adblocking penetration at anywhere between 10% and 40%. Some publishers are blocking content from the adblockers. Others are making the ads unskippable with ad block. Broken systems are interesting, aren’t they? The system of advertising is broken. Here’s the best that I can explain it from as many perspectives as I can rally. Advertising in the early days, radio, was incredibly lucrative. The development of a consumer economy in the roaring 20’s and consumerism in general was huge. A marketer could spend $1 on advertising and got $4 back. Paid media was crazy effective. The same went for television. And then there was a sort of grand bargain, a big deal, struck between creatives, those that create[…]
This WSJ piece “Has the world lost faith in Capitalism” had this infographic: And prompted Marc Andreessen @pmarca to remark on Twitter: “The inevitable result of 15 years of slow economic growth.” His tweet prompted me to think about the relationship between economic growth and the gini coefficient (a measure of income inequality). And there’s a lot to it. I don’t think it’s a straight line causal model between economic growth and inequality. (And I’m not suggesting that Marc thinks it is, it is, after all, Twitter). The core representation of a causal model is depicted below: In very short terms, when we decided in 80’s that we were going to go for a service based economy, the linkage between wage growth and productivity[…]
Let’s start with a story. Daan did a traditional fast follow. He calls it Netherflix. His story was: “It’s like Netflix…for The Netherlands!”. At first, he buys rights on the cheap, pays for digital subtitling, and has a successful kickoff. He gets through to 10% household penetration, or roughly 700,000 subscribers, with an annualized gross revenue of about 60 million Euros. The strength of the Euro lets him raid the Anglosphere and he can stock 10,000 hours of content reliably [1]. He gets through the struggle of getting his stack to deliver content and minimize churn. He’s able to host and deliver 10,000 hours reliably, in spite of supporting video players across 11 different front end platforms, and the costs associated with hosting,[…]
A score serves as an ultimate abstraction or summary. That’s especially true in sport. “Who won?” “The Blue Jays. 11 to 5.” The Blue Jays won because they moved men more often across one specific plate more often than the other team. This is all very American. A brief period of action. Collect statistics about that brief period. ???. Profit. And it’s easy. Baseball is nice for the 1 to 1 correspondence of points to a single event. American football and basketball are spicier. Cricket, with all due respect to my antipodean friends, is ridiculous. There’s so much more to the performance of The Blue Jays or the Australian National Cricket Team. But the score is the ultimate summary. There’s[…]
That title, ‘morphing the lean startup’, may be technical jargon. But it is literal. And brief. I have a few thoughts to share about them both. Morphing There’s a very small sliver of research in the Marketing Science on morphing. Two papers, ‘website morphing‘, and its adtech successor, ‘morphing banner advertising‘, stand out as giants. This technology makes snap changes to a digital user experience. The ultimate reason why you’re not hearing more about morphing in adtech is because paid agencies can’t figure out how to scale the creative necessary to drive it. I’m convinced that morphing is the ultimate promise I bought into back in the mid-nineties – the perfect intersection of recsys and experience. It requires an extreme[…]