16:9 Podcast – From ESLs to Avatars At NRF 2019
January 23, 2019 by Dave Haynes
This is a special edition of the podcast, which I am pretty much whacking together myself, in the wake of running around the NRF show last week in New York.
I had my handy little Tascam recorder with me, so I grabbed some quick interviews with several companies I bumped into, with the idea of stitching them together in a round-up. These are not the biggest companies. Not necessarily the hottest stuff on the show floor. But they caught my eye, or in the case of the first interview, reflect my thinking that I wanted to know more.
Normally I get interviews properly smoothed out by my sound engineer guy, but with four interviews and intro and so on, it was a big ask on short notice. So here I am, fiddling around with Audacity audio software. So this will be a bit rougher than normal, but the content is solid.
One of the things I noticed on the NRF show floor was how there were way more electronic shelf labels than I have seen in the past, which is why I stopped to chat with Rob Crane, the head of global sales for the ESL company Altierre.
I bumped into Tomer Mann, from 22 Miles, outside the Intel booth. He was doing stand-up demos of his company’s long-running wayfinding platform. That’s well established, but I was interested in what the company was doing in retail, using HTML.
Inside that Intel booth, I chatted with a Spanish company, called Kendu, that comes out of retail graphics and has introduced a hybrid print and signage solution that uses LED animations behind a lightbox frame of print graphics, and also uses gesture for interactivity.
Finally, I was wandering around the Innovation Lab – which is a lot of new companies, but also companies who can’t afford a full booth. I noticed people hanging around a floor display, and reacting to the screen. A company that’s partially Toronto, partially Berlin, has an avatar chatbot thing that uses AI to drive interactivity. Twenty Billion Neuron’s avatar seems a little gimmicky, but done well it would be useful in spaces where there’s a set of predictable questions.
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