WeFarm

Kenny Ewen spent seven years in Peru running an international NGO that worked with indigenous communities. That experience shaped the problem WeFarm set out to solve: hundreds of millions of farmers who have no internet access and little way to learn from one another. The company's own framing is that roughly 500 million farmers without internet supply about 70% of the world's food. WeFarm was developed by Ewen and his team before launching as a startup in 2015.

WeFarm's first version was deliberately simple for the user. A farmer in rural Kenya with no internet can send a free SMS question, such as asking why a cow isn't giving milk. The platform's machine learning algorithms analyze the message's content, theme, keywords, and location, then pick out 10 to 15 people in the network who have relevant knowledge. Those people receive the question by SMS, and the company generally expects two to three answers. Ewen said people answer because they love farming, not because they are paid. The company is not incentivizing answers financially or through gamification yet. The product was described as an MVP that had 'done extremely well,' with the next step being stronger machine learning and natural language processing.

The company started as a grant project. It won funding from Google through the World Google Impact Challenge, which provided the initial capital. Ewen said that grant was 500,000 pounds. WeFarm later raised a seed round, which Ewen described as about $1.7 million in total raised, and the team grew to about 20 people across London, Nairobi, Klaipeda, and Peru.

WeFarm found its users through channels that Ewen said were a re-examination of old-fashioned marketing. Radio was the biggest. The company partnered with radio stations and invited farmers onto air, which sometimes brought 4,000 to 5,000 sign-ups in an hour. The second channel was partnering with businesses that buy from farmers and with NGOs that work with them. WeFarm gave those partners information and data in exchange for access to their networks.

By the time of the interview, the platform had about 140,000 farmers. Ewen said about 35% of users contributed information every month, and about 85 to 90% were still using the platform three months after signing up. He also said most people who churn leave within the first 24 hours, and those who stay for that period rarely leave.

What worked was the combination of a low-friction interface and high early engagement. Farmers needed only a phone and an SMS number, and the company claimed strong monthly contribution and retention rates. Radio partnerships were especially effective at acquisition. Ewen also noted that the company had validated revenue sources, including commercial contracts with a major UK high street retailer.

The model is not yet profitable, and revenue is small. Ewen said investors had encouraged the company to focus on growing the network rather than on near-term revenue. Ewen projected revenue of around $50,000 for 2017 from early commercial sources. He also said the company is pre-profit, not pre-revenue.

As of the interview, WeFarm was focused on growing the network toward a million users, improving its machine learning and natural language processing, and building future monetization around aggregated, non-personal supply chain data and small transaction commissions when farmers buy products through the platform. Ewen described the company as an information service first, with monetization expected to come later.