Agriculture
Marketing intelligence built for the harvest calendar.
Standard analytics were built for 30-day cycles. Ag runs on seasons.
An equipment dealer runs digital campaigns in February. A farmer researches in March, visits the lot in May, and signs the purchase agreement in June — after the planting window clarifies their yield projections. Standard analytics credit the last click and miss the six months of brand-building that made the sale possible. Quantli extends the attribution model to match how agricultural buyers actually make decisions.
Harvest Calendar Attribution
Configure attribution windows aligned to planting and harvest cycles — not arbitrary 30-day windows. Understand which pre-season campaigns drive post-season equipment purchases.
Commodity Price Correlation
When corn prices rise, equipment buyers gain confidence. Quantli correlates commodity market signals with your ad performance data to identify optimal campaign windows.
Equipment vs. Input Analytics
Separate the economics of equipment sales from input purchases. Each category has different margins, cycle lengths, and buyer behaviors — your analytics should reflect that.
"Our pre-season brand campaigns were getting cut every year because the sales team couldn't see the connection. Quantli made it visible. Those campaigns are now protected budget."
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Agriculture — no commitment required.