The Edge.Email — 1st Edition
Welcome to the weekly newsletter from The Edge Group. For each edition, we pull together our favorite content on all things media, marketing, innovation, analytics and of course, email.
If you’d like to learn more about the work we do, or discuss anything related to newsletters, content and data, please get in touch here.
While the quote below from this NY Times piece might border on cringeworthy, our team self-consciously observed that we proudly wear non-fashion consumer (and even b2b) brand logos on our clothing. It’s worth reading this and taking a serious look at “the strategy of using emotion and ‘shared values’ to build relationships with consumers — and to sell them more stuff.”
Translation: every company is now a lifestyle brand.
In this HBR piece, Salesforce Chief Scientist Richard Socher breaks down three areas of natural language processing we need to improve in order to help computers “understand” human language better.
One of these areas is Sentiment Analysis (SA) — you may have have heard of SA being used to measure the “mood” of the economy by analyzing thousands of current finance articles. SA can also interpret primary emotions from a plethora of customer reviews — very useful for brands. Socher suggests how SA can be improved:
The Big Mac Index from The Economist is one of the longest-running examples of using creativity to make data accessible (it was launched in 1986). By using the price of Big Macs around the world, they’re able to easily relay the concept of Purchasing-Power Parity to those who never took Econ 101.
This Digiday piece covers how how The Economist’s 12-person data journalism team did all the right things in launching a redesign. Rather than diving headlong into shiny, new objects, they surveyed over 1,000 readers to understand how people were experiencing the site.
(Note: the Big Mac version has inspired some other fun indices, like the Cafe Con Leche Index from Bloomberg that tracks Venezuelan hyperinflation.)
Instagram video below:
In 2016, McKinsey launched “The Real Innovation Awards” with the London Business School. In this piece, they give us a serious case of #DatasetEnvy, as they realized the award application forms contained valuable textual insights into what makes for a good “innovation story”.
From over 1,000 nominations, they crafted a number of archetypal stories like “best beats first”, “master of reinvention”, “perspiration”, “underdog”, and more. This piece is an Edge dream, as it both highlighted the importance of storytelling in business, as well as using existing, ‘unexpected” datasets to draw knowledge from.
This idea has it all: leveraging open APIs, personalized recommendations using seemingly uncorrelated datasets, and hanging with the cool kids (music & fashion).
Using your Spotify data in an arena like fashion recommendation is exactly one of those unexpected, but incredibly logical data connections we anticipate will become more frequently used across industries.
6. A NEWSLETTER
We spend hundreds of collective hours reading, studying and creating newsletters. To see a gallery of our favorites, and what makes them so good, go to GreatB2Bemails.com. Each week we’ll recommend one of our favorites.
If you’re looking to stay up-to-date on geopolitics and macroeconomic risk, we highly recommend signing up for EG Signal, a newsletter from Ian Bremmer’s Gzero Media.
They break down complex issues that most of us who are not working at a policy think tank gain minor exposure to (What exactly is happening in Pakistani politics? Did the EU really give into Trump on trade?). The newsletter also hits every element that we believe makes for a great product (conversational, digestible, smart, well-designed).
7. B2B FUNNIES
We are on LinkedIn for hours on end. We help clients strategize for LinkedIn. We understand the endless potential of value from LinkedIn. But this piece from The Outline, How to Beat LinkedIn: The Game, is simply perfect:
8. YOUR WEEKLY EDGE PARABLE
Last week, we fell for the gambler’s fallacy fallacy while poring over newsletter stats.
The gambler’s fallacy is when you believe the more a single event happens, the more it’s “due for a change”. Like thinking the roulette pill will land on red because it landed black five times in a row. The odds are the same, every time.
Our internal probability calculator isn’t broken. Recent information is useful for most things outside a casino, which can’t be practically measured. So it’s really a gambler’s fallacy fallacy when we think stats follow strict laws unaffected by the external world.
We learned our lesson while studying a client’s historical newsletter data: no matter which way we turned our heads, we couldn’t explain certain fluctuations. After digging in, we found a number of probable, real-world factors — holidays, client-related events, etc. — that could have affected those spikes.
Weekly Edge Parable: Don’t rely on pure statistics when studying historical marketing data — consider the changing world of events that may have influenced those stats.