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Awhile back I blogged about Ashwin, one of my ex-students who wanted to raise a seed round to build Unmanned Aerial Vehicles (drones) with a hyper-spectral camera and fly it over farm fields collecting hyper-spectral images. These images, when processed with his company’s proprietary algorithms, would be able to tell farmers how healthy their plants were, whether they were having trouble with diseases or bugs, and whether they had enough fertilizer and enough water.

(When computers, GPS and measurement meet farming, the category is called “precision agriculture.” I see at least one or two startup teams a year in this space.)

At the time, I pointed out to Ashwin that his minimum viable product was the actionable data he’d be able to supply to farmers, not the drone. I suggested that to validate his minimum viable product, it would be much cheaper to rent a camera and plane or helicopter and fly over the farmer’s field, hand-process the data, and see if the information he collected was something farmers would pay for. That was something he and his team could do in a day or two, for a tenth of the money they were looking for.

Fast forward a few months and Ashwin and I had coffee to go over what his company, Ceres Imaging, had learned. I wondered if he was still in the drone business, and if not, what had become of the minimum viable product.

It was one of those great meetings where all I could do was smile: 1) Ashwin and the Ceres team had learned something that was impossible to know from inside their building, 2) they got much smarter than me.

Crop Dusters

Even though the Ceres Imaging founders initially wanted to build drones, talking to potential customers convinced them that, as I predicted, the farmers couldn’t care less how the company acquired the data. But the farmers told them something that neither they nor I had even considered – crop dusters (the fancy word for them is “aerial applicators”) fly over farm fields all the time (to spray pesticides.)

They found that there are ~1,400 of these aerial applicator businesses in the U.S. with ~2,800 planes covering farms in 44 states. Ashwin said the team’s big “aha moment” was when they realized that they could mount their hyper-spectral cameras on these crop dusting planes. This is a big idea. They didn’t need drones at all.


They could hire existing planes and simply attach their hyper-spectral camera to any crop dusting plane. This meant that Ceres didn’t need to build an aerial infrastructure – it already existed. All of sudden, what was an additional engineering and development effort now became a small, variable cost. As a bonus it meant the 1,400 aerial applicator companies could be potential distribution channel partners.

The Ceres Imaging minimum viable product was now an imaging system on a crop dusting plane generating data for high value tree crops. The team’s proprietary value proposition wasn’t the plane or camera, but the specialized algorithms to accurately monitor water and fertilizer. Brilliant.

I asked Ashwin how they figured all this out. His reply, “You taught us that there were no facts inside our building. So we’ve learned to live with our customers. We’re now piloting our application with tree farmers in California and working with crop specialists at U.C. Davis. We think we have a real business.”

It was a fun coffee.

Lessons Learned

  • Build continuous customer discovery into your company DNA
  • An MVP eliminates parts of your business model that create complexity
  • Focus on what provides immediate value for Earlyvangelists
  • Add complexity (and additional value) later

This story originally appeared on Steve Blank. Copyright 2014

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