A large chunk of our company relocated to Raleigh, NC - so we also moved our HQ here.
They literally did a spreadsheet with different metrics they were looking for (business environment, they knew there were only some weather conditions they'd be willing to go for, looked into schools & safety for their young kids, taxes, house prices etc) graded and analyzed that data (we're an analytics consultancy so if you think about it, it makes sense :) ).
After narrowing down to 2 or 3 locations, they ended up with Raleigh. About 4 (including the first two co-founders) moved here initially, together with their families (wife & 4 kids each). Few months later others joined the team here as well, families included. We still have some collages working from Bay Area and we support them, but most of the team is here now.
Instead of focusing on what Machine Learning is, this tutorial shows you how to apply it to a specific issue, like what to do when your image is broken.
My colleagues built what we think is the first free Tableau Connector that integrates Adobe Analytics, AdWords, Facebook Ads, FB Pages, Bing Ads and Kochava data inside Tableau dashboards.
We're also getting ready to roll out a bunch of new features this week, including data blocks, preview, custom calendars, and a Youtube connector.
Would you mind giving us your thoughts and/or feedback on it?
Title edited back to show Forbe's title. But I think that it should have been more about how lean and design thinking can be applied to content and marketing.
Just to clarify: I changed the title because I thought there was much more to this story than what the author or publication chose as a title.
IMHO It's an interesting analysis of how lean & design thinking can be applied to efficient content & communication. I think it goes beyond a niche discussion between public relations professionals.
And from our experience with our startup, it's what a startup should look for when creating content or looking for efficient marketing solutions (whether in-house or outsourcing it).
Well, I didn't use the original title because my belief is that it is misleading. Employee satisfaction does matter, but it depends how you define it - that was my take from the story.
Imho quoting an actual fact resulting from their study was the objective solution compared to a debatable title meant to attract eyeballs.
Paddy explained how it is likely that future agencies would be run by mathematicians & statisticians. And how "for example, the next time you see an ad for Web Summit on Facebook, realise that that ad might only be shown to another 15-150 people out of Facebook's 1.5 billion users. And furthermore in some instances that ad might only be shown to you for a short period of time before that ad self-pollinates with something probabilistically even more creative or compelling, or is simply stopped. That's personalising not for the 1% but for the .000001% of users, without almost human intervention whatsoever."