Making Agricultural Services Easier to Find for Smallholder Farmers

For a smallholder farmer, finding the right agricultural service can be just as important as having access to land, inputs, finance, or information.

A farmer may need an agrodealer, veterinary service, farm machinery, animal feed, seed, fertilizer, crop protection products, mechanization, or another specialised agricultural service. But knowing where those services are, what they provide, and which ones are close enough to be useful is not always easy.

In many farming communities, discovery still depends heavily on word of mouth, existing relationships, local knowledge, or simply knowing where to look.

Digital agriculture is beginning to change this. Across Kenya and elsewhere in Africa, digital platforms are increasingly being used to connect farmers with information, markets, inputs, financial services and agricultural support. Kenya has already invested heavily in digital agricultural infrastructure, including platforms that combine farmer information with geospatial and agro-meteorological data. World Bank

But there is another opportunity that deserves attention: making the agricultural businesses and services around a farmer easier to discover.

From Knowing a Provider Exists to Finding One Nearby

Imagine a farmer who needs veterinary assistance for livestock.

They may know that veterinary services exist somewhere in the county. But that does not necessarily answer the question that matters most at that moment:

Who can help me, and how far away are they?

The same question applies when a farmer needs seed, fertilizer, animal feed, machinery, irrigation equipment, crop protection products, or other agricultural services.

This is the problem we are exploring through a location-based agricultural service built around discovery.

The idea is simple: instead of treating agricultural businesses as entries in a static directory, make it possible to discover them in relation to where the farmer is.

A farmer should be able to see relevant providers around them, understand what those providers offer, and decide which ones are worth contacting.

Why Location Changes the Experience

Location is more than a point on a map.

For agricultural services, location provides context.

A list may tell a farmer that 100 agrodealers exist. A map can begin to answer a much more useful question: which of those agrodealers are actually accessible from where I am?

We use geospatial data to understand where agricultural businesses and service providers are located and how they relate to the areas and communities around them.

This makes it possible to build experiences around proximity and relevance rather than simply presenting a long list of names.

For example, a location-aware service can help answer:

• Which agricultural service providers are near me?
• How far away are they?
• What types of services are available in my area?
• Which providers are within a practical distance?
• Where are gaps in agricultural service availability?

That last question is particularly important.

Once agricultural businesses are represented geographically, the data can become useful not only to farmers, but also to people and organisations trying to understand how agricultural services are distributed.

The Agricultural Service Ecosystem Is Bigger Than Agrodealers

When people think about agricultural businesses, agrodealers are often one of the first categories that come to mind.

But farmers interact with a much wider ecosystem.

Depending on their needs, they may require:

• Agrodealers and agricultural input suppliers
• Seed suppliers
• Fertilizer and crop protection suppliers
• Veterinary and animal health services
• Animal feed suppliers
• Agricultural machinery and mechanization providers
• Irrigation and water-management services
• Farm equipment providers
• Livestock-related services
• Other specialised agricultural service providers

Each of these providers forms part of the infrastructure that supports farmers.

The opportunity is to make this ecosystem more visible.

Turning Business Data Into Something Farmers Can Understand

Finding a business is only the first step.

A map marker or business name does not necessarily tell a farmer whether that provider is relevant to their needs.

This is where business information becomes important.

A useful provider profile can bring together information such as the business name, location, services, contact details, category and other relevant information.

But even structured information can be difficult to interpret when it is incomplete, inconsistent, or presented simply as raw data.

We are therefore also exploring the use of artificial intelligence to analyse and describe business information.

AI can help turn available business data into clearer, more useful descriptions of what a provider does and the services they may offer.

The objective is not to replace the underlying business information. It is to make that information easier to understand.

That creates an important transition:

From seeing a business on a map to understanding whether that business can help.

Geospatial Data + Business Data + AI

The real opportunity comes from bringing these pieces together.

Geospatial data helps us understand where agricultural services are.

Business data helps us understand what those providers offer.

Artificial intelligence can help make that information easier to understand.

Individually, each component has value.

Together, they can create a much more useful discovery experience.

This approach is consistent with the broader direction of digital agriculture. Kenya's agricultural digital ecosystem already demonstrates the value of combining agricultural data with geospatial information to deliver more localised services and information to farmers. Read the World Bank's work on digital agriculture in Kenya.

Why Discovery Matters for Smallholder Farmers

Smallholder farmers do not operate in isolation.

They depend on networks of businesses, service providers, extension actors, markets and other organisations around them.

Yet the existence of a service does not automatically mean that a farmer can easily find or use it.

Research on digital agricultural services in Kenya continues to highlight both the potential of digital tools and the barriers that remain, including connectivity, affordability and digital literacy. Read the research record on FAO AGRIS.

That means digital agricultural services need to be designed around real-world access rather than simply assuming that every farmer has unlimited connectivity or sophisticated digital skills.

Our focus is therefore not simply on putting businesses on a map.

It is about reducing one of the smaller but important frictions in the agricultural journey: finding the people and businesses that can provide the service a farmer needs.

The Nearest Provider Is Not Always the Best Provider

Proximity is useful, but it should not be the only factor.

The closest business may not provide the required service. Another provider slightly farther away may have the right equipment, expertise, product, or availability.

That is why the goal is not simply to show the nearest business.

The goal is to help farmers discover relevant providers.

Distance, service category, provider information and other available business details can work together to give farmers more context when making a choice.

The map becomes the starting point, rather than the entire experience.

From a Directory to a Discovery Layer

Traditional business directories answer a relatively simple question:

What businesses exist?

A location-aware agricultural service can go further:

• What businesses exist?
• Where are they?
• What do they provide?
• Which ones are near me?
• Which ones may be relevant to what I need?

This changes the role of the directory.

Instead of being a database that farmers have to search through, it becomes a discovery layer connecting farmers with the agricultural service ecosystem around them.

There Is Also a Bigger Data Opportunity

Once agricultural service providers are mapped and structured, the value of the data extends beyond individual searches.

It can help reveal patterns in the agricultural service ecosystem.

Where are agricultural businesses concentrated?

Which areas have limited access to particular services?

Where are veterinary services available?

Where are mechanization providers located?

Which communities have access to input suppliers?

These questions can provide a different perspective on agricultural service availability.

Geospatial agricultural data is already being used in Kenya and elsewhere to support more targeted agricultural decision-making. World Bank

Our focus is narrower and practical: make the agricultural businesses and services themselves easier to discover.

Building Around the Farmer, Not the Database

It is easy to build a system around the data.

It is harder to build around the person who needs the data.

A database may contain thousands of businesses, categories, locations and attributes. But a farmer does not want to navigate a database.

They want an answer.

They want to know where they can find the service they need.

They want to understand what a provider does.

They want to know how far away it is.

And ultimately, they want an easy way to connect.

That is the experience we are trying to build.

Technology Should Reduce Friction

Digital agriculture does not become valuable simply because it uses maps, artificial intelligence, or large amounts of data.

The technology matters when it removes friction.

For a farmer, that friction might be spending an afternoon trying to locate a supplier.

It might be calling several people before finding someone who provides a particular service.

It might be travelling to a business only to discover that it does not provide what was needed.

Small improvements in discovery can therefore have practical value.

The broader digital agriculture experience in Kenya shows that mobile and data-driven platforms can support last-mile delivery of agricultural services, inputs, information and market connections. World Bank

The opportunity is to keep pushing that idea further.

From Data to Discovery

The vision is straightforward:

Make agricultural services easier to discover, easier to understand, and easier to access.

Geospatial data helps us understand where services are.

Business data helps us understand what providers offer.

AI helps us make that information easier to understand.

And a farmer-centred experience brings those pieces together in a way that can help people move from information to action.

This is not about replacing the relationships farmers already have.

A farmer who already knows and trusts their agrodealer should continue using them.

It is about making more options visible.

If a farmer needs a new veterinary service, a mechanization provider, an input supplier, animal feed, equipment, or another agricultural service, discovering what is available nearby should not have to be difficult.

The Map Is Only the Beginning

A map can show where businesses are.

AI can help explain what those businesses do.

Geospatial data can provide the context.

But the real objective is much simpler.

Help a farmer find the right service when they need it.

As digital agriculture continues to evolve, there is an opportunity to move beyond simply digitising agricultural information and start building services that connect people with the resources around them.

For us, that starts with discovery.

Because sometimes the difference between having access to a service and not having access to it is simply knowing where to find it. 
This is coming soon, stay tuned!