How it is computed
Take the selling price of each retailed unit, subtract its cost including reconditioning and any pack the store carries, and add the results for the period. Divide by units retailed. Run new and used separately, always; a blended front gross hides more than it shows.
Why it matters
It is the first half of total gross per unit, and on the used side it is the half the store controls most directly through what it buys, what it spends in recon, and how it prices.
Front gross and velocity trade against each other. A store holding high front gross on slow turn is exercising discipline; a store giving the car away and still missing volume has a different problem entirely. The number means nothing until you know which store you are looking at.
How operators read it
- Read it with days to sale beside it. High front gross on a unit that sat a hundred days may have been eaten by the floorplan and the price drops before it ever hit the statement.
- Separate the new side from the used side. New front gross is often thin by design, with volume and the manufacturer's money behind it; used front gross is where the desk earns its keep.
- Look at the spread by salesperson and by manager before you look at the average. An average front gross is made of a few people holding it and a few people giving it away.
Questions people ask
Does front gross include the doc fee?
That depends on how the store books it, and the only wrong answer is an inconsistent one. Decide where it lives, keep it there, and compare like to like.
Is a low front gross always a problem?
No. A store built for velocity runs thinner front gross on purpose and makes it back in volume, F&I, and the service drive. The problem is low front gross without the volume to justify it.
How A.D.A.M. reads it
A.D.A.M. computes front gross per unit from the deal detail by salesperson, by manager, and by store, new and used apart, and reads it beside volume and aging rather than alone. He reads it beside the numbers it trades against, names what the gap is worth, and leaves the decision where it belongs. What an AI advisor should do, and refuse to do.