I worked for a retail analytics company that would do things like track WiFi/Bluetooth devices, faces, and general shopper traffic.
It had been a few years since I've worked there but the real problem was that all of this didn't work. All these promises to our clients that's you would get data equivalent of online shoppers, in store, but it simply wouldn't work. Guess people age, gender, previously seem face, tracking where they walked. All horribly inaccurate.
Though apparently it's an industry wide thing as "imputing" was common practice. Don't have the data? Make it up!
I don't know about retail but if you are ever in Las Vegas or Reno, go into a casino and walk past every slot machine to the reservation desk and ask for a room. Availability and prices will be far worse than booking after gambling or even phoning from the parking lot.
Isn't this just price segmentation by contact method? If im already at your hotel asking about rooms I'm likely less price sensitive than someone calling in advance. But If i give you my players card likely get some kind of paltry discount.
Yeah, well -- LV is the original source of much of what we know today about data mining. So, it makes sense that they would still be decades ahead of the rest of the field.
Yea you just “stitch” the data together to get your perfect customer data profile.
Actually you end up with about 5% of your customer base properly tracked, and those people are already buying the most stuff anyway. I would bet that nailing the supply chain and focusing on your margin would be a better investment in most cases.
True. Most of it is marketing BS. Overpromise is the norm. But if you read the comments here, you see that even technical people are buying that. And possibly it will work later, so we can worry now.
But there's no reason that this couldn't work well with improvements in sensors and implementations. If you don't think this is possible in a highly reliable way, you are wrong.
Technology is ever advancing and improving and I’m sure eventually we will get there. Or we’re already there, like I said, I’m out of the loop for past few years so maybe some amazing improvements have happened.
Another inhibitor of this technology is how cheap/behind retail companies tend to be.
We want advanced analytics.
Ok, we can set up these cameras and the like which will send everything to our servers for computation.
We only have dsl at the store.
Ok, then we need to set up a server(s) at the store.
We only want to spend 2k max per store, and use sub-sub-sub contractors to actually set up this equipment.
All of this pain and trouble scared me away from working with retail focused companies for past few years.
This. I am a lead developer in a leading FR company, and this comment right here hits the nail on the head. Every one of your points is an active issue with retail. It's a pain in the asshole.
With optical cameras, wifi and Bluetooth signatures, location data, 3rd party databases, and ML, there is more than enough data to get an ID enough shoppers to care. None of that tech is prohibitively expensive. It just requires someone to build out a cost-effective implementation with off the shelf parts.
There's a lot more "just" to deploying anything of the sort to a 1,000+ physical store footprint.
At minimum, what's the local network situation? Where are you storing and processing the take? Are you installing edge compute or transferring it out? If the later, what are your latency requirements?
I try and take a healthy dose of "maybe it's a harder problem than I thought" whenever something is valuable, looks easy, yet no one is doing it.
This plan all falls apart when the retail CEO has "his nephew manage the project, 'cause he's good with computers". Then a 20 year old more concerned with girls and video games appears. He has zero technical experience beyond video games, and attitude that you're his flunky. Seen it. Multiple times.
It had been a few years since I've worked there but the real problem was that all of this didn't work. All these promises to our clients that's you would get data equivalent of online shoppers, in store, but it simply wouldn't work. Guess people age, gender, previously seem face, tracking where they walked. All horribly inaccurate.
Though apparently it's an industry wide thing as "imputing" was common practice. Don't have the data? Make it up!