Marketing-driven forecast of agricultural production
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Summary of the challenge:
The main goal is the development of a predictive service that, from the estimated degree of success of a digital marketing campaign, predicts how its impact will become into real purchase orders to the producers.
Description:
The profitability and impact of digital marketing campaigns strongly depend on the quality of the selected keywords. However, when generating a new keyword list that will form the campaign structure, there is no information about their quality in terms of their potential impact, measured as the probability of impression and click-through rate (clicks over impressions).
The prediction of the success of a digital marketing campaign is a hard problem by itself, but in this challenge, we want to go one step further and try to estimate its cross-sectorial impact: we want to explore whether having an estimate of the campaign’s impact can be used as a predictor to help producers of the advertised products to forecast and optimize their production needs.
In particular, the challenge focuses on the agriculture sector where many products are fresh and perishable, and good planning can help reduce waste.
Data:
REACH Data Provider
- AN GROUP: databases with historical orders of agricultural products (quantity, product, price, sales, company)
- JOT Internet Media: Keyword lists and statistics for mobile and laptop campaigns
- External Data Provider: Provided by applicants
- Open source:
Expected outcomes:
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