Success Story
Farro
Farro is a rapidly growing New Zealand artisan grocery retailer. Farro had huge amounts of data, but were struggling to access, visualize and analyze it quickly. Here's how 11Ants helped.
How 11Ants is Powering Data-Led Growth at Farro
VIDEO TRANSCRIPT
Introduction I’ll start by saying I just love the interaction with 11Ants. They have been a huge part of our solution over the last few years as we’ve matured as an urban farmers market grocery business here in New Zealand.
How has technology impacted you personally as a business leader? On a personal level, as with most people, the rise of AI has been a little bit daunting. We’ve all known we need to get into it and start exploring to ensure we’re keeping up with the industry. In that sense, the experience with 11Ants has been really rewarding. It has helped bridge the gap in our knowledge and understanding of how language models work and how AI can support a business.
Simplistically, it has changed how I start conversations. Historically, I used to begin with: "What report do I need? What numbers do I need to pull?" In a very short space of time, that has started moving toward: "What problems are we trying to solve? What are we trying to solve for our customers, our team, and the business?" I find that I move to those questions quite quickly now, and that’s evolving the business at a rapid rate. It has made me more confident and faster in my ability to review and comprehend data to reach solutions. Previously, I would have spent a fair amount of time working through spreadsheets, chasing numbers, or waiting for someone who knows where the data lives. Now, my ability to access information is so much faster. I’m spending more time thinking about the data and following up with actions, rather than just trying to understand or pull the information.
What has been the biggest surprise using the tool? Specifically regarding 11Ants, the biggest surprise has been the quality of the thinking. It hasn’t just been giving answers; it provides a lot more detail and context. For example, it will give you the likely drivers and a comparison of information. What’s really exciting is that it actually gives you options for what to do next. Of course, we have to temper that and discuss the detail as a business, but it’s driving our ability to ask harder questions. That is a significant step change—moving from data retrieval to overall decision support.
How is this changing the day-to-day operations at Farro? It’s shifting the organisation quite quickly to an evidence-led conversation. I find that in our trading meetings, the conversations have become a lot richer. We aren't having so many conversations around "I think this is the reason why" or "I think this was the outcome." It’s more evidence-based.
People are more willing to challenge the assumptions we may have made in the past because it’s easier to access and validate information. We don't have to wait a week to understand a question; we do it live in the session. That helps us make decisions for our customers much faster.
The other element is broadening access to data. Not everyone in a business is naturally data-inclined. Historically, we were reliant on a few subject matter experts or "super users." Now, everyone from marketing and operations to our category teams and assistants can self-serve. They come to discussions better prepared, which makes for a much richer quality of conversation.
How do you see this changing the future of grocery? Grocery is incredibly fast-paced. 11Ants is making us faster and smarter. We’re shifting from reporting on what happened to running the business in near real-time. Most of us don't have a shortage of information—there’s lots of it. The challenge is the ability to synthesise that information to make sense of it.
Working with a tool like 11Ants, you can do that faster, which means we can make customer-first decisions at scale. Instead of debating what we think shoppers want, we interrogate the behaviour. We can understand price sensitivity and real drivers at scale. We get richer information: who did a promotion bring in? What demographic? What did it replace when they made that purchase? And importantly, what margin did it generate?
We are still in our infancy in this space, but we are learning to ask better questions to maximise the opportunity. I’m particularly excited about taking steps toward predictive operations—improving our forecasting and scenario planning. Using historical data to inform the future has always been challenging, but these tools will help us understand things like how a price move affects volume and how to work with suppliers to better forecast margins. There is a lot to be excited about for the future of our teams and our customers.
