Client story  /  Weather intelligence

Meteum

b2b.meteum.ai
Meteum
Who hired us
The Head of Business Development, Meteum
The offering
Hyper-local weather forecasting built on machine learning, fusing every available station and data source into a forecast for a specific plot of ground rather than a city.
The task
Sell forecast accuracy to the businesses whose money depends on it: farms, power producers, insurers and the engineers who build for them.
97
Meetings booked
84
Confirmed held
87%
Hold rate
93
Companies introduced
UAE, Saudi Arabia, Egypt, Morocco, Jordan
Markets
8 months from 2023
Engagement
Industries we sold into
AgricultureEnergy and industryInsuranceProfessional services

In 2023 we were hired to sell weather to people who already get it free.

Everyone has a weather app. That is the objection, and it arrives in the first minute of every call. The answer is not a better app. It is that free forecasts are computed for the nearest city and most agricultural and industrial sites are not near a city.

Our highest hold rate on the roster came out of this engagement: 87 per cent, 84 of 97 booked meetings confirmed held. When a product answers a question the buyer is already arguing about internally, people turn up.

What we did

Eight months across the Gulf, Egypt, Morocco and Jordan, in agriculture, renewable energy, insurance, engineering and environmental agencies. 97 meetings booked, 84 confirmed held, 93 companies introduced.

Al Dahra, Elite Agro, Magrabi Agriculture, Daltex, Dakahlia, SEKEM, ARASCO and Les Domaines Agricoles in Morocco. ACWA Power, AMEA Power and Aramco on the energy side. Environment Agency Abu Dhabi, EY, GHD, McDermott, RSK, Sarwa Insurance, Allianz Egypt and Transport for Cairo. Agri-tech platforms including ReNile, Zr3i and Mozare3, where the forecast becomes a feature inside somebody else's product.

The engagement started as meeting-booking and did not stay there. Our man moved from SDR work to running the deals themselves, and closed some.

Two sentences from a Saudi agronomist that became our qualifying question

The best explanation of this product we ever heard came from a prospect, not from the client.

He worked on agricultural feasibility studies in Saudi Arabia and told us exactly why public data failed him. The country's ground stations belong to the government and are spread across an enormous area, so the nearest one to a given site can be very far away. Worse, if the land sits at a different elevation to that station, the forecast is wrong in a way nobody notices until the crop is in.

After that call our reps stopped asking whether a prospect cared about weather. They asked how far the nearest station was from the site, and whether the land was higher than it. Two questions, answerable in ten seconds, that separate a company with a forecasting problem from one that merely has an opinion about the weather.

The same engagement produced the other kind of insight, the commercial kind. When an Egyptian smart-farming platform wanted the forecast inside its own app, the sensible structure was not a licence at all. It was a share of what the platform earned from it, which let a young company adopt the technology at a price that moved with its own revenue.

What it shows

When a product competes with something free, stop arguing about quality and find the condition under which the free version is simply wrong. Then turn that condition into a question a rep can ask on a first call. Our hold rate here was the highest we have recorded, and the reason is that we were only calling people for whom the free version was already failing.

Every figure counted from the activity tracker.
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