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What the advertising cost,and what it returned.

These are four accounts we run. Each figure covers only the period we managed the account, and each case ends with what its numbers do not prove.

Engine three, tickets

Two clubs, one season,2,123 seats at $1.97.

$4,182Spend
2,123Tickets sold
$1.97Cost per ticket
29.9xReturn

The situation

Two clubs on full season schedules, new to paid ads. A season is dozens of small sell-through problems, and the dates that need help never sell themselves.

What we ran

  • Weighted spend toward the soft midweek dates on the schedule
  • Worked the existing season ticket base separately from cold prospects, so the two were never bidding against each other
  • Wired ticketing platform tracking so a sale could be attributed back to the click that caused it
Tickets sold by month, both clubsMonth 3 is the end of the schedule, so spend and inventory both run down
Tickets sold by month, both clubs04008001,200599Month 11,244Month 2280Month 3
Show the numbers
Club AClub BCombined
Spend$2,361$1,821$4,182
Tickets sold1,3587652,123
Cost per ticket$1.74$2.38$1.97
Tracked revenue$83,738$41,077$124,815
Return35.5x22.6x29.9x
MonthSpendTicketsRevenue
Month 1$1,326599$36,325
Month 2$2,4491,244$72,651
Month 3$407280$15,840

What this does not prove

  • This is one season. It does not show the result repeating, and a second season is the real test for a ticketing account.
  • Both clubs sit in similar markets and ran the same months, so this is one set of conditions. It says little about live events in general.
  • A 29.9x return is unusually high and is a function of ticket price against a low cost per acquisition. Do not expect this shape in a category with a longer consideration cycle.

Engine one, lead generation

Thirteen months,1,373 leads at $14.

$19,217Spend
1,373Leads
$14.00Cost per lead
13Months live

The situation

A specialty retailer in a small market a long way from our home base. Search ads already worked. The question was whether paid social could add volume without wrecking the cost per lead.

What we ran

  • Started on a deliberately small monthly cap and did not raise it until the cost per lead held for a full quarter
  • Put a tracked number on every ad and landing page, so phone calls were attributed to the ad that produced them
  • Built the CRM pipeline through to quoted and sold, so a lead could be followed to the thing that pays
Cost per lead by month, twelve full monthsLower is better. Spend held through winter; over the run, spend per month rose 56% and cost per lead 11%.
Cost per lead by month, twelve full months0$5$10$15$20$25Deep winter$10.67$21.19Month 1Month 3Month 6Month 9Month 12
Show the numbers
Launch quarterLatest full quarterChange
Spend per month$1,098$1,718+56%
Leads per month92131+42%
Cost per lead$11.89$13.15+11%
QuarterSpendLeadsCost per lead
Launch$3,293277$11.89
Deep winter$4,570230$19.87
Spring$5,150364$14.15
Latest full$5,153392$13.15

What this does not prove

  • Cost per lead measures the input. This account tracks 36 attributed purchases worth $80,188, which is real but is only a fraction of what the business closed from these leads.
  • Search advertising was already running and working throughout. We did not run a holdout, so some share of this volume would likely have arrived anyway.
  • One account in one category. A thirteen month run shows seasonality, but it is too short to set a repeatable benchmark. Your market will not behave like this one.

Engine two, ecommerce

Spend tripled,and so did the return.

$6,824Spend
272Orders
4.85xReturn
4Months

The situation

A brand in a category the platforms restrict, where much creative never clears review. It had never been scaled, and pushing spend in a category like this usually collapses the return.

What we ran

  • Wrote every ad to pass review in a restricted category before it was submitted
  • Raised spend in steps, and held each level until the return held
  • Worked on average order value and acquisition cost together
Return on ad spend by monthMonthly spend rose 213% over the same four months, and average order value 37%.
Return on ad spend by month02x4x6x8x6.76xMonth 1Month 2Month 3Month 4
Show the numbers
MonthSpendOrdersCost per orderReturn
Month 1$73616$46.002.04x
Month 2$1,63257$28.634.17x
Month 3$2,15078$27.564.27x
Month 4$2,306121$19.066.76x
Across the four monthsStartEndChange
Monthly spend$736$2,306+213%
Cost per order$46.00$19.06-59%
Average order value$93.94$128.78+37%
Return2.04x6.76x+231%

What this does not prove

  • Four months is a ramp, too short to count as a track record. The hardest test in ecommerce is holding a return through a full year including the post-holiday trough, and this account has not seen one.
  • This ad account was later actioned at the platform level and the campaign was rebuilt on a new one. That is a standing risk in a restricted category and it is planned for, but it means the run above is not continuous to today.
  • Figures are platform attributed with server side conversions. The brand's own store reporting will not match exactly, and where the two disagree we treat the store as the truth.

Engine one, local service bookings

Four months on a small budget,$53,217 in bookings.

$1,917Spend
93Bookings
$20.62Cost per booking
27.8xReturn

The situation

A local experience business that sells premium bookings online. The budget was small and all of it went to ad spend. The owners ruled out discounts and prices in the ads. In late summer they moved the ads to someone else, so the same account now shows what happened without us.

What we ran

  • Kept all spend in one bookings campaign, so a small budget still gave the platform enough purchases to learn from
  • Sent each booking and its dollar value back to the platform, so it optimised for paid bookings
  • Sold at full price, with no discounts or prices in any ad
Bookings in equal 58 day windowsSame account, same tracking and similar spend: $860 with us, $907 after the owners moved the ads elsewhere
Bookings in equal 58 day windows0102030405041Last 58 days with us11First 58 days after
Show the numbers
MonthSpendBookingsCost per bookingReturn
Month 1$35415$23.6319.3x
Month 2$46221$22.0026.0x
Month 3$42621$20.3034.1x
Month 4$48519$25.5523.9x
Month 5, 13 days$18917$11.1343.5x
58 day windowsLast with usFirst afterChange
Spend$860$907+5%
Bookings4111-73%
Cost per booking$20.98$82.46+293%
Revenue$21,894$9,839-55%
Return25.5x10.8x-58%

What this does not prove

  • 78 of the 93 bookings were credited to a view: the person saw an ad, did not click and booked within a day. Counted on clicks alone it is 15 bookings and $8,933, a 4.66x return.
  • The handover comparison puts summer next to autumn. There is no earlier year to control for the season, so part of the drop may be seasonal.
  • The budget was small, so a few bookings swing the return hard. There was no holdout test, so we cannot say how many bookings would have come without the ads.