Reforming Retail

Is This How Restaurant Concepts Will Grow in The Future?

Y Combinator (YC) is a pedigreed “startup” accelerator in Silicon Valley whose acceptance rate is tighter than that of Harvard. YC primarily takes three kinds of companies:

  • Companies with super networked founders
  • Companies with zero risk that YC likes to convince are “startups”
  • Companies that meet some PC, feel-good quota

But usually these companies have a tech-heavy component. Which is why when we saw YC announce a restaurant company in its latest class, we had to dig deeper.

On the surface Mac’d seems like a delightfully simple and delicious concept. In exchange for the 12-page Cheesecake Factory menu, Mac’d focuses on variations of macaroni and cheese. This eliminates menu complexity and streamlines operations. It also helps that Mac’d went with a fast casual concept – really the only segment of the industry that’s growing.

But most intriguing is how Mac’d started.

Taking advantage of social media platforms (i.e. free marketing), Mac’d ran pop-up stores in San Francisco. This helped the founders hone their menu, pricing, and even location. Once the pop-up store generated enough data (and revenue) to be convincing, the founders built their first brick and mortar location.

Scaling from there was further honed by data.

Using something called grey or ghost kitchens, Mac’d would share space in commissary kitchens and avoid costs associated with the front of house. They would focus on food prep – keeping costs low – and use third party services to reach customers. With little capital invested they could tell if a location made sense before laying a brick. If so, they’d build a store. If not, try the same approach in a different market and measure the results.

All of this makes us wonder if this is not the future of restaurants. According to any technologist the answer would be a resounding yes. If you want to read about how we data folks think about capital and product, there’s a famous book by Eric Ries called The Lean Startup. In a nut shell: do things fast and cheap, and use data to measure everything.

A/B testing is not something confined to just techies, so it’s good to see someone applying science to retail. There’s far too little of it if you ask us. Unless your name is Amazon, and who would want to emulate that story?


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