# Tampa Ford Dealer: $739,215 in Sales from One 12,655-Piece Mailer

> An active-shopper direct mail campaign at a Tampa, FL Ford dealer sold 23 vehicles in 40 days at a $32,139 average ticket, drove 643 service ROs, and accounted for 11% of the store's total sales. The truck-buyer math and why a 2-week read would have killed it early.

**Author:** DirectMail.io Editorial  
**Published:** 2026-05-19
**Category:** Case Studies  
**Reading time:** ~7 min
**Tags:** Case study, Automotive, Dealer marketing, Active shopper data, Direct mail attribution

Canonical URL: https://directmail.io/blog/veterans-ford-tampa-case-study/

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A Ford dealership on West Linebaugh Avenue in Tampa, Florida ran one direct mail drop in January 2019. The list was 12,655 households flagged as in-market for a vehicle. The response window ran six weeks. By the end of it, the dealership had matched 23 vehicle sales back to the file, totaling **$739,215.11 in retail revenue** at a **$32,139.79 average ticket**, plus **643 service repair orders** tied to the same households. The campaign accounted for **11% of the store's total sales** for the period — and **39% of the store's total service ROs**.

Same vendor, same data product, same mail mechanic as the [Polk County Honda case study](/blog/polk-county-honda-case-study). Different store, different brand, different vehicle mix. The Honda dealer averaged $19K per sale across a balanced new/used file with a heavy lease tail. This one averaged $32K with zero leases and a truck-heavy book. The platform math comes out differently when the ticket size shifts that hard — and the response curve does too.

Here's what the campaign produced and where the leverage sat.

## The campaign in one paragraph

One mailer, one list source, one in-market segment. The file — 12,655 households inside the dealership's Tampa Bay trade area — was sourced from active-shopper data: people whose digital and offline signals indicated they were within 60 days of buying or replacing a vehicle. The piece dropped on January 10, 2019. The attribution window ran through February 18. No second touch, no email overlay, no retargeting layer. One mail piece against one in-market list.

## What the dealership sold

Of the 23 attributed vehicles:

- **11 new** units — $474,851.92 in revenue, **$43,168 average**
- **12 used** units — $264,363.19 in revenue, **$22,030 average**
- **23 financed/cash purchases, 0 leases**

Truck and full-size SUV inventory dominated the new mix: F-150s, F-250s, an F-350, Explorers, and a Mustang at $51K. The single largest ticket was a 2019 F-250 at $62,911. The lowest was a used 2016 Focus at $11,666. Six of the 23 transactions cleared $45K.

The zero-lease line matters. Ford F-series buyers in this market finance or pay cash — they do not lease light trucks the way Honda Civic and Accord buyers lease compact cars. That's a structural difference in the vertical, and it shows up cleanly in any mail file pulled against truck-heavy inventory.

## Revenue-per-piece — the number that decides whether mail pencils out

$739,215 ÷ 12,655 pieces mailed = **$58.41 in attributed revenue for every piece dropped**. At a typical fully-loaded 6×9 oversize cost of $0.55–$0.85 per piece (data + print + postage), the gross margin sits in the 70×–100× range on revenue, and roughly 9×–14× on gross profit after a conservative per-unit dealer margin assumption.

Revenue-per-piece climbed about 13% over the Honda case study at the same list size and same attribution mechanic — almost entirely a function of the higher average ticket. The mail performance per impression was comparable. The vertical mix did the rest of the work.

## The week-by-week curve — front-loaded, with a long tail

| Week | Window | Vehicles | Revenue |
|------|--------|----------|---------|
| 1 | Jan 10–16 | 7 | $216,009 |
| 2 | Jan 17–23 | 7 | $218,238 |
| 3 | Jan 24–30 | 2 | $60,863 |
| 4 | Jan 31–Feb 6 | 2 | $60,461 |
| 5 | Feb 7–13 | 3 | $85,241 |
| 6 | Feb 14–20 | 2 | $98,404 |

Fourteen of the 23 sales — **61% of total units** — landed inside the first 14 days. That's a different curve than the Honda store, which spread evenly across all six weeks.

The shape isn't random. Truck buyers shop in a tighter window than compact sedan buyers. A truck shopper who's been pricing F-150s for three weeks before the mailer hits is closer to a decision when the piece shows up; a Civic shopper triangulating between Civic, Corolla, Mazda 3, and used Camry takes longer to land. So the head of the curve runs hotter on truck-heavy mail.

But the tail still mattered. Weeks 3 through 6 produced **9 sales and $305,000 in revenue** — 41% of the campaign's total. A dealer GM pulling the report at the 14-day mark would have seen a strong start and assumed the campaign was already done. Killing it there would have left $300K on the floor. The 40-day window is the difference between "great campaign" and "great campaign, properly counted."

## The service-bay number nobody counts

From the same 12,655-household list, **643 service repair orders** showed up at the dealership's service bay during the response window. That's **39% of the store's total ROs** for the period — almost four times the share that attributed vehicle sales pulled.

Service ROs don't carry the ticket size of a vehicle sale, but at a $250–$400 typical RO gross, 643 of them add roughly **$161K–$257K of additional revenue** to the same mail spend, attributed to the same list, in the same window. With service included, the campaign's effective revenue-per-piece climbs into the **$71–$78 range**.

The pattern is the same one the Honda store showed: the people on an in-market file who don't buy a car often still come in for service. The mailer reactivated the relationship. The DMS match shows it. Most automotive direct mail vendors don't pull the service match because their stack doesn't connect to the service writeups. This one did, and the second-order revenue showed up cleanly.

## What made the attribution credible

Three things separated this report from the average dealer "we think mail worked" recap. They're the same three from the Polk County writeup — and they're worth repeating because dealer ad reps still skip them:

1. **Match type was disclosed and conservative.** Every attributed sale shows the match basis — Full Name/Address, Last Name/Address, Address only, or Trade VIN. Nothing matched on zip code or city. One match in this campaign came in on Trade VIN alone — a buyer who'd traded in a vehicle the dealer had previously sold, with the trade-in's VIN landing the attribution. That's the kind of granular signal a DMS-integrated stack can pull and a generic mail vendor cannot.
2. **Sales were pulled from the dealer's DMS**, not a survey. The list of 23 buyers came out of the actual sold log, then matched back to the mail file — not the other way around.
3. **The campaign and dealer totals were both reported.** 23 attributed sales against a dealership total of 214 sold units. 643 attributed ROs against a dealership total of 1,633. The 11% and 39% campaign shares are grounded in real numerators and real denominators, not against an imagined baseline.

If a vendor can't show match type, DMS source, and dealer-total context, assume the ROI report is decorative.

## Why this campaign's numbers diverged from the Honda one

The two campaigns ran the same playbook a few months apart, at similar list sizes, against similar in-market files. They produced two different shapes:

- **Honda store:** $586,601 / 11,385 pieces / 31 units / $18,923 average / sustained 6-week curve / 8 leases / 23.4% service share
- **Ford store:** $739,215 / 12,655 pieces / 23 units / $32,140 average / front-loaded 2-week curve / 0 leases / 39% service share

The Ford store sold fewer units but pulled more revenue. The Honda store moved more inventory but worked a tighter average. Neither outcome is "better" in isolation — they're two different vertical signatures inside the same direct mail mechanic. A dealer principal reading these numbers should expect their own results to land closer to whichever brand/inventory mix their store actually runs. F-150-heavy lots will look like the Tampa report. Civic-heavy lots will look like Polk County.

The platform math, in both cases, was profitable by 60×–100× on revenue and 8×–14× on gross profit.

## What's repeatable

Five components carried the campaign. All five are platform features, not creative tricks.

1. **Active-shopper list source, not generic conquest.** The 12,655 households were filtered for in-market signals before the file was cut. A saturation drop against the same trade area would not produce the same math.
2. **A tight geographic radius with truck-buyer skew.** Most matched buyers lived within 15 miles of the dealership. Buyers as far as 30+ miles out were typically F-series and F-250/F-350 commercial shoppers — a smaller buyer count but high revenue per match.
3. **A 40-day attribution window — not 14.** Pulling the report at the 2-week mark would have shown 14 sales and $434K. The other 9 sales and $305K came in weeks 3 through 6. The window length is the difference between "keep running it" and "kill it."
4. **DMS-level match on both vehicle sales and service ROs.** Counting only the cars sold and ignoring the 643 service ROs leaves $160K–$257K of campaign revenue out of the analysis.
5. **A single-touch test, kept simple.** No email overlay, no retargeting attribution muddle, no second drop. One mailer, one window, one match. The attribution is clean because the campaign architecture was clean.

## Running this on DirectMail.io

The platform side is what compounds. Active-shopper data, suppression against the dealer's existing customer file, the postal stack, and the DMS match-back are all native to DirectMail.io — you don't stitch them across four vendors and lose attribution in the seams. For dealers, the [automotive solution page](/solutions/brands) covers the workflow end to end. The [features overview](/features) walks the address-hygiene, list-source, and tracking pieces individually.

For agencies running campaigns on behalf of dealer clients, the same stack is white-label-able under sub-accounts — see [Agencies](/solutions/agencies).

## The honest summary

An 11% lift on dealership-total sales and a 39% lift on service ROs from a single mailer is a strong number. But the more durable lesson sitting in this report is what *good attribution* looks like in automotive direct mail when the vertical signature shifts. Front-loaded curves don't mean shorter campaigns. Higher average tickets don't mean weaker volume. Zero leases don't mean a broken file. They mean the math has to be read against the inventory mix it's running against — and the window has to be held open long enough to count the tail.

For the broader vertical context — which offer types deliver this kind of math and which don't — see [Automotive Dealer Direct Mail: 9 Offer Types Ranked](/blog/automotive-dealer-direct-mail-playbook). For the attribution architecture that produced this report, see [the best direct mail tracking & attribution tools](/blog/best-direct-mail-tracking-attribution-tools). For the comparable Honda store running the same playbook, see [Polk County Honda Dealer: $586,601 in Sales from One 11,385-Piece Mailer](/blog/polk-county-honda-case-study).