Tinus le Roux knows fans via Fancam he knows when they attend and how often they attend. On this podcast Sean & Tinus discuss the differences of computer vision and facial recognition and why it is important to sports business.
On this podcast you'll learn about:
- Tinus le Roux on how Fancam started and what it offers
- How Fancam got into the US sports market
- What computer vision does and why is it important
- How Fancam differs in capturing data to measure fan engagement
- How Fancam help sports teams close sponsorship deals
- Where they see Fancam going in the next 18 months
Listen to Tinus le Roux on Sports Geek
Sports Geek hosted by Sean Callanan
Tinus le Roux - Fancam
Tinus le Roux quote
Every time we take one of these pictures, people go look at it and they spend a lot of time there and then learn more about sports and sponsorship. Then we realize that's actually a sponsorship asset.
Tinus le Roux
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Resources from the podcast
- Connect with Tinus le Rouxe on Twitter @tinusleroux and LinkedIn
- Follow Fancam on Twitter @Fan_Cam, Facebook and LinkedIn
- Some related articles you might want to read more about Fancam:
- Some Sports Geek episodes you might be interested in:
- Tinus Le Roux on digital activations and developing campaigns, way back on episode 15
- Yinzcam story with Priya Narasimhan
Highlights from podcast with Tinus le Roux
4:30 Tinus le Roux chats about Fancam and how it started
7:03 Working on 360 imaging and VR before Fancam started
19:24 Expanding Fancam installation in different stadiums
20:20 How they are analysing data
20:59 The importance of computer vision in fan engagement
25:14 Why Fan Cam is not doing facial recognition
27:48 Tinus’ insights on managing database for ticketing
31:22 Tinus on their plans for Fancam in the next 12-18 months
32:48 How they work on the pitch for their clients
34:00 How Fan Cam can help you benefit in sponsorship deals
41:31 Sports Geek Closing Five
49:40 Digital to Dollars – Go to DigitaltoDollars.com
51:45 Subscribe to Sports Geek News. Go to SportsGeekHQ.com/sgn
Some tweets/posts you may have missed
Nice work with the Mets Fancam
Know anyone who went to the Mets game yesterday?
Never been to Citi Field?
Zoom in to explore…
https://t.co/Ix1PyyD7hV— FANCAM (@Fan_Cam) August 5, 2018
Good to see how it all started
7 years ago.
Man with a broken back capturing our first Fancam.@BobSkinstad @jamestaylorsurf pic.twitter.com/InS3RGNukM— Tinus le Roux (@tinusleroux) May 23, 2017
Follow Tinus on his birding expeditions
Very lucky to get this shot of a Yellow-streaked Greenbul.
Limited distribution and another forest bird that usually keeps itself well hidden. pic.twitter.com/8V9QPMQF7D— Tinus le Roux (@tinusleroux) July 6, 2018
Sean meeting podcast listeners in NYC including Tinus.
It's ok I've been joined by fellow #stevesmithing participants for a #sportsbiz Meetup with people from
pic.twitter.com/0WrZaeJxqB
— Sean Callanan (@seancallanan) August 3, 2018
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More from Tinus le Roux
So for those having listened or planning to listen to my chat with @seancallanan , I thought to add to it by providing a few more practical use cases of computer vision in sports – and specifically how we're using it at @Fan_Cam .
Hope it helps… https://t.co/FE4zfITmpK— Tinus le Roux (@tinusleroux) August 20, 2018
Let's start by cutting out he buzzwords to get to the core opportunity for #SportsBiz people:
"If you could have a computer look at your crowd, what would you ask that computer?"
Here are some of the questions we're getting (and answering) at present:
— Tinus le Roux (@tinusleroux) August 20, 2018
Average Age..
– how old is my crowd?
– how does it change from one game to the next?
– why?
– how does this compare to league averages?
– how fast is my crowd growing older/younger?
– let me know when you guys see a spike, so we can act quickly to address it pic.twitter.com/aFKhQvAKEH— Tinus le Roux (@tinusleroux) August 20, 2018
Age distribution..
– how many millennials are coming to our games?
– we changed ticket brokers, can you pick up a change in demographics – we're concerned they're not reaching our target demo
– what's the crowd composition that delivers highest merch revenue? pic.twitter.com/9v1fv3oUNH— Tinus le Roux (@tinusleroux) August 20, 2018
Gender distribution
– what's the male/female split per age group?
– what's the effect of the weather/pricing on female attendance?
– how can we use these trends to predict distribution and plan our game day activations and merch stock accordingly? pic.twitter.com/pPM6ZXvGZR— Tinus le Roux (@tinusleroux) August 20, 2018
Combined data
– Please have a look at our season ticket seats. Are the same people sitting in them every game and if not (because that's the answer) how many games do they typically attend?
– show me which seats are always empty.— Tinus le Roux (@tinusleroux) August 20, 2018
– combine game data with 'bums in seats' data and help us predict how Gen X males react to a blowout. when do they leave?
– look at our seat packages sold on the secondary market, how many families bought those tickets?
– what's the optimum price point that draws most families?— Tinus le Roux (@tinusleroux) August 20, 2018
– how many people are paying attention to the jumbotron ads?
– which ad played best for Gen X females?
– how many people are looking at their phones?
– how does the differ from one generation to the next?— Tinus le Roux (@tinusleroux) August 20, 2018
There are obviously a 1000 more questions 'we can ask the computer', but these are some of the ones we're seeing in the industry today and I thought those who listened to the podcast would find it helpful to further their thoughts on the topic.
— Tinus le Roux (@tinusleroux) August 20, 2018
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