With last night possibly having been the hottest on record for the UK, I’m too tired & toasted to write a long post. Lucky readers I hear you cry 😉
Instead, here is a collection of blog posts I’ve found interesting today. Ones that should help customer insight leaders expand their own reading list.
Hope it helps, even if you don’t get to the beach to read today.
First, here is an interesting piece on principles of storytelling that marketers (or analysts) can learn from journalists. Nicely illustrated with a worked example by Yuval Maoz, applied to content marketing.
There’s one rule any journalist learns on the first day on the job. It is applicable for anyone who posts news online, whether you work for the New York Times or BuzzFeed. The rule is simple. Any news report must answer the 5 Ws: What happened? Where? When? Why? By Who?
If you’re looking to improve your use of research methods. Perhaps catching up on the use of mobile for surveys or even more sophisticated qualitative research, then this next post is a good place to start. Quirks magazine generally would make good reading for connected research leaders looking to do some work related beach reading. In this post, Chris St. Hilaire (founder of MFour mobile research agency), shares how mobile applications have developed to do just that.
History of Infographics
If your thoughts turn to presenting your insights or visualising your data, then this next blog post should be of interest. For those traditionalists (like me), who prefer a physical book to read on the beach, this article is also a book review of “Mapping the Nation”, which looks like a good addition to your reading list.
Deep Learning practical applications
To balance a reading list that is so far sounding more focussed on research & softer skills, here’s a useful AI article. If you’ve wondered about the potential relevance of machine learning to practical problems in your business, here is a great place to start. In this post on Deep Learning Patterns blog, they share a great collection of ‘deep learning’ applications. Each listing includes a short description and link to an article, video, or paper.
When we first are introduced to deep learning, we see it as a better machine learning classifier. Alternatively, we could subscribe to the hype that it is ‘brain-like’ neuro-computing. In the former instance, we grossly underestimate the kinds of applications we can build with this.
Take your time
Hope that helps you with your reading list for the beach this summer. Take time to reflect, as well as brush up on your technical knowledge. Now is a great time to set new goals for you & your team in H2.
Enjoy the sun!