Heating-fuel distributors buy and staff a fleet for one day — the coldest of the year. dropt re-times the deliveries you already make so that day gets smaller, without ever letting a tank run dry.
A 1,030-tank distributor's 2016–17 winter (anonymized). Same total gallons, same operating days, drop sizes matched to their own history — dropt only changed when. Peak day: 15,637 gal → 7,761 gal (−50.4%). Zero tanks dry.
Tank ID, date, gallons — the export your fuel software already makes. No customer names, no addresses, no install.
Same gallons you delivered, same days you ran, drop sizes your trucks actually make, tanks modeled physically. Every truck visit counted.
Day one runs cautious. As the forecast proves itself on your data, the dial earns toward your measured ceiling. Every step reversible, every claim checkable against your own records.
Thirty minutes. One data export. You'll see your peak day, what it could have been, and exactly what it costs — nothing changes about how you operate until the numbers convince you.
Get your numberdropt is in its pilot phase. Figures above are measured results from replaying real distributors' historical delivery data under audited, volume-matched rules — not customer outcomes. Your result is measured on your data before anything is promised.