Introduction – the first-order problem The first-order problem for startups often is, they are not making something people want enough to pay for. As you can see from the CB Insights data, founders identify this as the most common reason for failure. Figure 1 Reasons for startups failure Notice the connection between 1 and 2: We can paraphrase that as…
Introduction This post is about startup thinking. In my dissertation about startup dilemmas [1], I argued that startups can exhibit what I call as ‘reference point bias’. My evidence was emerging from the failure narratives of startup founders, where they reported having experienced this condition. The reference point bias is a false analogy where the founder compares their startup with…
Johdanto Luin mielenkiintoisen artikkelin: http://miter.mit.edu/the-unexotic-underclass/ Teesinä on, että startupit keskittyvät yhteiskunnan kannalta “vääriin” ongelmiin. Ne keskittyvät joko eliitin ongelmiin (korkeasti koulutetut kosmopoliitit) tai eksoottisiin kolmannen maailman ongelmiin, joihin usein luovat lumeratkaisuja kestävien ratkaisujen sijaan. Sen sijaan alemman keskiluokan ongelmat jätetään huomiotta: esim. työttömyys, uudelleenkouluttautuminen, sotaveteraanit (USA). Tätä kohderyhmää kuvataan näkymättömäksi “alaluokaksi”, koska startupeille he eivät ole olemassa. Miksi näin on? Kirjoitin…
Introduction I ran an analysis with IBM Watson Personality Insights. It retrieved my tweets and analyzed their text content to describe me as a person. Doing so is easy – try it here: https://personality-insights-livedemo.mybluemix.net/ I’ll briefly discuss the accuracy of the findings in this post. TL;DR: The accuracy of IBM Watson is a split decision – some classifications seem to…
GOMCHA European Winners 2016 1. Introduction In the past couple of weeks, a few people have approached me asking for tips on how to do well in the Google Online Marketing Challenge. So, I thought I might as well gather some of my experiences in a blog post, and share them with everybody. A little bit of background: I’ve been…
Just a picture of a black sheep. Introduction. Hal Daumé III wrote an interesting blog post about language bias and the black sheep problem. In the post, he defines the problem as follows: The “black sheep problem” is that if you were to try to guess what color most sheep were by looking and language data, it would be very…
Introduction The ambiguity problem illustrated: User: “Siri, call me an ambulance!” Siri: “Okay, I will call you ‘an ambulance’.” You’ll never reach the hospital, and end up bleeding to death. Solutions Two potential solutions: A. machine builds general knowledge (“common sense”) B. machine identifies ambiguity & asks for clarification from humans The whole “common sense” problem can be solved by…
1. Introduction In rule-based bidding, you want to sometimes have step-backs where you first adjust your bid based on a given condition, and then adjust it back after the condition has passed. An example. An use case would be to decrease bids for weekend, and increase back to normal level for weekdays. However, defining the step-back rate is not done…
Johdanto Media on riippuvainen mainostuloista. On jatkuva kiistelyn aihe, miten paljon toimittajien tulisi kirjoittaa juttuja, jotka saavat klikkejä ja näyttöjä suhteessa juttuihin, joiden yhteiskunnallinen merkitys on korkea. Nämä kaksi kun eivät aina kulje käsi kädessä. Sosiaalisen median ja hakukoneiden merkitys toimittajan työssä Käytännössä toimittajat joutuvat työnsä puolesta huomioimaan juttujen kiinnostavuuden sosiaalisessa mediassa. Tämä on tärkeää vaikka haluaisi kirjoittaa vain yhteiskunnallisesti…
Introduction. Hm… I’ve figured out how to execute successful political marketing campaign on social media [1], but one link is missing still. Namely, applying affinity analysis (cf. market basket analysis). Discounting conversions. Now, you are supposed to measure “conversions” by some proxy – e.g., time spent on site, number of pages visited, email subscription. Determining which measurable action is the…
