There’s over 2 billion square meters of retail floor space in the world, or around 350,000 American football fields’ worth, being manned by tens of millions of people.
Walmart alone employs over 2 million people directly and has an annual staff turnover of 44%. The problem of staff turnover is not unique to Walmart, but rather endemic to the entire retail sector.
Every year, Walmart trains almost a million people for their first day on the job, and retailers report that staff training and retention is one of the most significant costs and pain points they face.
Spatial computing has the potential to radically reduce the cost of staff training and the time that staff spend on tasks. Precisely positioned information in space allows for better knowledge transfer and communication than anything previously possible, and at a fraction of the cost of other innovative retail technologies.
The cost of implementing spatial computing in your store may be comparable to the price of a single point-of-sale machine.
Every new retail employee carries a training cost of hundreds of dollars, and spatial computing is about to knock that down to a fraction. Across tens of millions of employees, and 2 billion square meters of retail space, the transformative potential is massive.
We are building retail operations tooling on the posemesh, a decentralized protocol for collaborative spatial computing. If we imagine the ownership of virtual real estate averaging out at the meager price of 0.10 cents per square meter, then the combined posemesh usage from retail operations tooling alone would dwarf the entire Ethereum network’s revenue.
When we factor in future use cases like AR shopper marketing, retailers may be paying much more for spatial computing, as it helps them reduce cost, drive basket size, and increase margins.
At the time of writing, the Ethereum network generates about 3.4 million USD worth of revenue every single day.
The retail sector alone might well be double that before the end of this decade.