When you consider different ways of getting information, you might think of going on Google or reading a book

But how to do this in an environment with no libraries, computers, let alone internet access?

Farmers in the field have limited means to get information and We Farm are looking to help by providing a Peer to Peer platform for farmers to send SMS questions and answers to each other.

Kenny, the CEO, and I discuss the process – of pairing these questions and answers, why he thinks people are altruistically contributing to the platform and the most common question that they get asked by farmers…

At times the audio is a little bit iffy, but we’ve done our best to edit things to what is hopefully an acceptable level, if you want some more information head to samfloy.com / podcast for the show notes.

For now though, hope I you enjoy this episode with Kenny from We Farm

Here are some of the key quotes:


“We Farm is a crowdsourcing app…”

For people without the internet. Primarily people are connected via SMS.

“Farmers interact with We Farm”

They send in a question of something which they would like to know. Typically about how to deal crop pests or when the rains are coming.

“Machine learning”

The We Farm algorithms process the messages sent through and match the question to other farmers who can answer

“The 150,000th farmer”

Is soon to be onboarded onto We Farm. We’ve just had our second birthday

“There aren’t other tools for farmers”

If you’re using an old school feature phone there are limited services for you. What we do even more so is empower the community.

“A lot of farmers have never been asked their opinion”

This is how We Farm is looking to challenge the “top down” approach of assuming that poor people need to be told what to do.

“Offline marketing in a digital age”

One of the challenges we have is to sign up farmers. This is typically through radio and partnerships along the supply chain.

“We are for profit”

But have a social mission at our heart. Our model is similar to a social network, like Facebook and Twitter, which become profitable at scale.

“Data for multi-nationals”

One of the big amounts of value that We Farm generates is through tracking droughts and diseases as they develop, providing this hard-to-get information to commercial entities.

“Building algorithms”

We’re looking at taking plain text SMSes and categorising them into whether this could be, say, Foot and Mouth disease. Our tech is built out of London.

“60% of questions answered in 24 hours”

This is pretty similar to online services like Quora. In the data we can see things like when people are charging the phone.

“A core human need to contribute”

Which is often the primary reason why farmers answer questions. We’re tapping into the same motive as why people write on Wikipedia.

“Non-financial rewards”

Are overwhelmingly preferred by farmers, rather than cash incentives. People like to be recognised on the radio.

“Young to old”

Younger people seem to be asking more questions, and older people answering them. This is an interesting East Africa cultural dynamic.

“Detecting existing answers”

This is something we’re looking at doing to provide a quality service for our farmers – using our existing bank of answers to answer common questions

“There is some filtering of answers”

Though ultimately it’s based on how the community responds to the questions sent. It’s difficult to block derogatory words because, for example, the Swahili word for “coconut” is “nazi”

“Branding for both”

One of the challenges has been having We Farm make sense to both VCs in London and farmers in East Africa.

“Channel agnostic”

We want farmers to get their information from We Farm, whether it’s SMS or Twitter or whatever over the next few years.


Social Media Follows etc.

Twitter:  WeFarm
Website:  WeFarm
Facebook : WeFarm