Media BuyingOld Account

Data as of Aug 20, 5:45 AM
Aug 14Aug 20, 2026vsAug 7Aug 13, 2026

Revenue

Total revenue
$1,177.46
↓14.8%vs prior 7d
Lead sale revenue
$61.19
↓13.1%vs prior 7d
Click feed revenue
$1,116.27
↓14.9%vs prior 7d
Call revenue
$0.00
Not yet reconciled — Ringba revenue exists but has no call_payout events.
Spend
$4,756.03
↓4.4%vs prior 7d

Funnel

Clicks
1,337
↓20.4%vs prior 7d
Leads
235
↑4.4%vs prior 7d
Conversion rate
17.6%
↑31.2%vs prior 7d
Leads sold
29
↑31.8%vs prior 7d
Sold rate
12.3%
↑26.2%vs prior 7d

Efficiency

CPL
$20.24
↓8.5%vs prior 7d
Avg RPL
$2.11
↓34.1%vs prior 7d
Avg click feed rev
$5.22
↓24.9%vs prior 7d
Blended ROAS
0.25×
↓10.9%vs prior 7d
Margin
-$3,579
no changevs prior 7d
CurrentPrior period
$0.00$74.42$148.84$223.26$297.68Aug 14Aug 15Aug 16Aug 17Aug 18Aug 19Aug 20

Campaigns

Account / Campaign / AdSpendClicksLeadsSoldCPLRPLRevenueROAS
$4,756.0394523529$20.24$2.11$1,177.460.25×
$2,421.8350812420$19.53$1.97$631.000.26×
$1,164.56283789$14.93$2.42$419.560.36×
$823.36000$0.000.00×
$229.27154330$6.95$126.900.55×
$117.01000$0.000.00×

Worth checking2 campaigns spent $940.37 with no revenue AND no resolving clicks at all.

Zero clicks is the signature of a broken tracking template, not dead traffic. Load the click URL and confirm the sub-IDs populate before pausing — untracked spend looks identical to wasted spend here.

How to act on this

Find out whether the traffic is bad or merely invisible.

  1. Not an Ads Manager fix first — open the ad's destination URL yourself and watch the redirect. If the sub-IDs are empty in the landing URL, the spend is untracked rather than wasted, and pausing would be acting on missing data.
  2. Then Ad level → Tracking → URL parameters. Every value should be a dynamic macro; a hardcoded one looks correct in the interface and attributes nothing.
  3. Check the same ad on mobile. Redirect chains that work on desktop break under in-app browsers more often than anything else in this stack.

Watch out: Fixing the template does not backfill history — the campaign will look brand new when it starts reporting again. Note the date you fixed it or you will read the recovery as a performance change.

Worth checkingThe best campaign at scale still loses money: 0.55× on $229.27 — CID767_FB_GB_AUTIN_Leads_JP_260723 – Purchase – ABO.

The weakest at this spend level returns 0.00×. Shifting budget between them is the cheapest available move, though it reduces the loss rather than reversing it.

How to act on this

Consolidate spend into what is working before building anything new.

  1. Shift budget between existing campaigns first — the spread you already have is free information, and a new campaign starts from zero learning in an account that cannot use saved audiences to shortcut setup.
  2. Increase in ~20% steps. Larger changes re-enter learning and you lose the performance you were consolidating.
  3. If everything is below 1.0×, reallocation reduces losses rather than reversing them. The answer is upstream — lead quality, buyer mix, or price per lead — and no amount of budget shuffling fixes it.

This account runs under Meta’s Financial products and services special ad category — its own description covers “insurance services” — so the guidance above is written to work inside these limits rather than around them:

  • Age is fixed at 18–65+ and cannot be narrowed. (Financial-services advertisers in Europe are the one exception; US accounts are not.)
  • Gender is fixed to all genders.
  • Some detailed targeting options — demographics, behaviours and interests — are unavailable.
  • No ZIP or postal-code targeting. Any city, address or pin must include everything within a 15-mile radius.
  • Lookalike audiences are unavailable.
  • Saved audiences cannot be used or created, so every ad set is built by hand — which is why duplicating beats rebuilding.
  • Custom audiences DO still work, provided the selection is not discriminatory. They are the one audience tool you keep, and the basis of converter exclusions and retargeting.
  • Copy naming a guaranteed rate or a specific saving gets rejected, and repeated rejections restrict the account.

Accounts, campaigns and ads with no activity in the period are omitted entirely. Totals here are lower than the cards above: only clicks that resolve to an ad can be attributed to a campaign. feeds and lead buyers open the demand side of any row — account, campaign or ad. Feeds show which feed at which tier bought the clicks; lead buyers show who bought the leads. They are separate controls because they are separate businesses: one pays per click into an auction, the other per lead accepted, and a row only offers the sides it actually earned from. Each side ends in its own subtotal, and the two together always sum to that row’s revenue, at every level. Clicks there counts only the clicks a feed paid for, a fraction of the clicks the ad produced; Sold counts sales that produced a payout, so it can sit a lead or two below the parent, which counts leads marked sold whether or not the payout has landed; and RPL is revenue per unit of that row — per paid click for a feed, per lead sold for a buyer.

Click feedsOld Account only

Feed / TierAvg bidBidsClicksRevenueRPU
$2.59
↓15.5%
1,016
↑5.3%
159
↑19.5%
$770.18
↓17.8%
$4.84
↓31.3%
$2.35
↑134.4%
784
↑1.0%
39
↑387.5%
$213.10
↑277.3%
$5.46
↓22.6%
$3.48
↓12.1%
416
↓45.6%
27
↓53.4%
$101.02
↓68.0%
$3.74
↓31.3%
$2.18
↓3.9%
619
no change
7
↑250.0%
$31.97
↑1172.6%
$4.57
↑263.6%

Needs attentionQuoteWizard pays $4.84 per click, down 31%, while volume is up 20%.

Revenue can be rising the whole time this happens, so it is invisible in the total. Either the traffic mix changed or their bids fell — the avg bid column separates those.

How to act on this

Work out whether you sent worse traffic or the feed simply started paying less.

  1. Compare the avg bid column against RPU. Bids falling means the feed repriced; bids flat with RPU falling means your traffic mix changed and the cause is on the Meta side.
  2. If the mix changed, look at which ad sets scaled during the period — the newest volume is usually the cause, and scaling a winner is the most common way to dilute it.
  3. Expand the feed to campaign and ad level above. If one ad is dragging the average, that is a creative decision, not a pricing one.

Watch out: Revenue can rise the whole time this happens. Judging the relationship on revenue alone hides it completely, which is exactly why these tables show RPU separately.

Needs attentionArity pays $5.46 per click, down 23%, while volume is up 388%.

Revenue can be rising the whole time this happens, so it is invisible in the total. Either the traffic mix changed or their bids fell — the avg bid column separates those.

How to act on this

Work out whether you sent worse traffic or the feed simply started paying less.

  1. Compare the avg bid column against RPU. Bids falling means the feed repriced; bids flat with RPU falling means your traffic mix changed and the cause is on the Meta side.
  2. If the mix changed, look at which ad sets scaled during the period — the newest volume is usually the cause, and scaling a winner is the most common way to dilute it.
  3. Expand the feed to campaign and ad level above. If one ad is dragging the average, that is a creative decision, not a pricing one.

Watch out: Revenue can rise the whole time this happens. Judging the relationship on revenue alone hides it completely, which is exactly why these tables show RPU separately.

Worth checkingQuoteWizard is 69% of click feed revenue.

Not a problem while it performs, but a single counterparty changing its bids moves the whole line. The other feeds are the hedge.

How to act on this

Reduce the damage one counterparty can do by changing its bids.

  1. Not an Ads Manager fix — a relationship and routing question.
  2. Send a small fixed share to the second-place feed continuously, even at slightly worse economics. It keeps their pricing honest and gives you somewhere to go the week the leader repricess.
  3. Track the concentration figure here over periods rather than at a point. A share that keeps climbing is the signal; the level on its own is not.

This account runs under Meta’s Financial products and services special ad category — its own description covers “insurance services” — so the guidance above is written to work inside these limits rather than around them:

  • Age is fixed at 18–65+ and cannot be narrowed. (Financial-services advertisers in Europe are the one exception; US accounts are not.)
  • Gender is fixed to all genders.
  • Some detailed targeting options — demographics, behaviours and interests — are unavailable.
  • No ZIP or postal-code targeting. Any city, address or pin must include everything within a 15-mile radius.
  • Lookalike audiences are unavailable.
  • Saved audiences cannot be used or created, so every ad set is built by hand — which is why duplicating beats rebuilding.
  • Custom audiences DO still work, provided the selection is not discriminatory. They are the one audience tool you keep, and the basis of converter exclusions and retargeting.
  • Copy naming a guaranteed rate or a specific saving gets rejected, and repeated rejections restrict the account.

Each figure shows its change against the same figure last period, so a feed paying less per click reads differently from one being sent fewer clicks — revenue alone moves the same either way. Avg bid averages every bid into the feed, winning or not: market context, not earnings. RPU is what a click actually paid. Expanding a feed shows its own tiers — QuoteWizard’s Platinum and Diamond, SwitchBoard’s Email and SEM, numeric ids for Arity and QuinStreet. Those come straight from the payout and so, unlike the campaign view, need no attribution and add up exactly; bids are not tiered and stay blank there. Tier names are each feed’s own and are not comparable between feeds. For which campaigns and ads earned this, open sources on a campaign in the Campaigns section. A blank change means no activity at all last period, which is not the same as a fall from zero.

Lead buyersOld Account only

Buyer / Campaign / AdAvg bidBidsSentSoldAcceptRevenueRPU
$3.23
↑17.8%
217
↑3.3%
143
↓4.7%
10
↓16.7%
7.0%
↓12.6%
$20.60
↓43.1%
$2.06
↓31.8%
$3.84
↓12.2%
217
↑3.8%
46
↓24.6%
4
no change
8.7%
↑32.6%
$16.19
↓44.1%
$4.05
↓44.1%
$1.00
no change
217
↑3.3%
74
↑19.4%
7
↑133.3%
9.5%
↑95.5%
$7.00
↑133.3%
$1.00
no change
$0.70
↑8.0%
217
↑4.3%
58
↑13.7%
4
↑100.0%
6.9%
↑75.9%
$6.03
↑170.4%
$1.51
↑35.2%
$0.25
↑8.8%
208
no change
23
↑21.1%
1
4.3%
$4.84
$4.84
$1.11
↓7.3%
203
↑2.5%
39
↓23.5%
2
5.1%
$4.13
$2.07
199
↓0.5%
5
↑66.7%
1
20.0%
$2.40
$2.40
$0.74
↑7.1%
217
↑3.3%
62
↑19.2%
0
0.0%
$0.00
$0.00
216
↑3.3%
23
no change
0
0.0%
$0.00
$1.72
↑74.9%
217
↑3.3%
14
↑600.0%
0
0.0%
$0.00
217
↑3.3%
1
↓50.0%
0
0.0%
$0.00
210
no change
0
$0.00
$1.85
no change
209
no change
0
$0.00

Needs attention100 leads — 20% of everything sent — went to 4 buyers that bought none: Datalot (62), DMS (23), Rocket Quote (14), and others.

Zero sales from an established buyer is more often a broken postback than total rejection. Pull their own delivery report and compare their sold count to ours — if theirs is also zero it is a lead-quality problem, if not, revenue is being under-reported everywhere on this page.

How to act on this

Establish whether the leads were rejected or the sales were never reported.

  1. Not a Meta problem. Pull the buyer's own delivery report for the same dates and compare their sold count to the one here. This single comparison decides everything else.
  2. If theirs is also zero, it is lead quality or a filter mismatch — ask which filter, and whether leads are being rejected at ping or at post. Those have different fixes.
  3. If theirs is NOT zero, the postback is broken and every revenue figure on this page is understated, not only theirs. That makes it the highest-priority item in the account, ahead of anything in Ads Manager.

Watch out: Cutting the buyer before checking loses the volume AND leaves the reporting bug in place for the next one.

WorkingApollo accepts 9.5% of leads, up 95%.

WorkingAlpine accepts 6.9% of leads, up 76%.

This account runs under Meta’s Financial products and services special ad category — its own description covers “insurance services” — so the guidance above is written to work inside these limits rather than around them:

  • Age is fixed at 18–65+ and cannot be narrowed. (Financial-services advertisers in Europe are the one exception; US accounts are not.)
  • Gender is fixed to all genders.
  • Some detailed targeting options — demographics, behaviours and interests — are unavailable.
  • No ZIP or postal-code targeting. Any city, address or pin must include everything within a 15-mile radius.
  • Lookalike audiences are unavailable.
  • Saved audiences cannot be used or created, so every ad set is built by hand — which is why duplicating beats rebuilding.
  • Custom audiences DO still work, provided the selection is not discriminatory. They are the one audience tool you keep, and the basis of converter exclusions and retargeting.
  • Copy naming a guaranteed rate or a specific saving gets rejected, and repeated rejections restrict the account.

Each figure shows its change against the same figure last period, so a buyer paying less per lead reads differently from one accepting fewer. Accept is sold ÷ sent, this buyer’s own acceptance rate — not the dashboard’s sold rate, which spans every buyer. RPU is revenue per lead sold, so price and acceptance stay separable. A row with bids but no sends is a buyer in the auction receiving nothing. Expanded rows cover only what traces back to an ad — about half of pings and sends carry a resolvable identity — so the rates there read higher than the buyer’s own row: traffic that resolves is traffic that tracks, and it converts better.

DemographicsOld Account only

Car make / Campaign / AdFeed bidLead bidLeadsSoldSold rateAvg lead revAvg feed revRev/leadCost/leadNet/leadTotal rev
$2.30$1.033438.8%$0.17$3.72$3.89$14.48-$10.59$132.31
$2.66$1.2234411.8%$0.22$5.27$5.49$16.28-$10.79$186.62
$2.30$1.0328414.3%$0.27$5.02$5.29$14.88-$9.59$148.05
$2.46$0.8521314.3%$0.16$4.24$4.41$16.96-$12.55$92.57
$2.62$0.911600.0%$0.00$4.95$4.95$15.65-$10.70$79.22
$2.79$2.011516.7%$0.16$4.66$4.82$14.22-$9.40$72.35
$2.59$0.991300.0%$0.00$4.08$4.08$14.78-$10.69$53.10
$2.77$1.0311218.2%$0.18$3.79$3.98$18.00-$14.03$43.73
$2.64$1.477228.6%$1.22$5.82$7.04$17.62-$10.58$49.31
$2.33$1.376116.7%$0.40$4.28$4.67$17.50-$12.82$28.04
$2.72$0.595240.0%$0.41$4.69$5.11$14.64-$9.53$25.53
$3.34$0.935120.0%$0.26$3.75$4.01$21.13-$17.12$20.06
$2.58$1.14400.0%$0.00$6.89$6.89$17.69-$10.80$27.57
$2.21$1.004125.0%$1.03$3.76$4.79$15.81-$11.01$19.17
$2.30$0.47400.0%$0.00$2.79$2.79$17.06-$14.27$11.14
$2.79$1.64400.0%$0.00$5.30$5.30$19.06-$13.76$21.20
$3.07$1.173133.3%$0.67$6.38$7.05$18.37-$11.32$21.15
$2.46$1.67300.0%$0.00$3.14$3.14$20.17-$17.03$9.42
$2.26$1.30300.0%$0.00$6.32$6.32$15.47-$9.15$18.95
$2.12$1.13300.0%$0.00$2.78$2.78$15.82-$13.04$8.34
$3.89$2.0033100.0%$3.47$3.12$6.58$21.13-$14.55$19.75
$2.47$1.323133.3%$0.55$7.81$8.36$16.62-$8.26$25.07
$2.65$0.76200.0%$0.00$3.42$3.42$17.31-$13.90$6.83
$2.27$1.12200.0%$0.00$5.73$5.73$18.44-$12.71$11.45
$3.63100.0%$0.00$14.84$14.84$15.81-$0.97$14.84
$2.33$0.75100.0%$0.00$5.19$5.19$12.85-$7.66$5.19

No car make segment has 40+ leads yet, so differences between them are still chance.

Leads are counted in the window they arrived, and a sale counts toward them whenever it lands — so a demographic is judged on the leads it produced, not on the day money happened to arrive. Recent windows therefore understate sold rate. Sold rate is coloured against this scope’s 12.3% baseline, and only once a row has at least 40 leads — below that a rate is chance, not a finding. Feed bid is dollars per click into the click feeds and Lead bid is dollars per lead offered by lead buyers — two different markets valuing the same person, never averaged together. Avg sold is confirmed revenue per lead sold, not the price field on the lead row.

Rev/lead, Cost/lead and Net/lead are measured over the same population — the leads that resolve to an ad, since spend exists only at ad grain and a lead with no ad has no cost to carry. Cost charges an ad’s whole spend across the leads it produced, so it is deliberately conservative: that same spend also bought clicks from people who never became a lead, and their click revenue is excluded from both sides. Net therefore reads worse here than the blended business does. Expanding shows only leads that trace back to an ad, so campaigns sum to less than the row above them.

TimingOld Account only

HourFeed bidFeed bidsLead bidLead bidsClicksClick revLeadsSoldSold rateAvg sold
$2.0473$0.515126$23.054250.0%$2.13
$2.4447$0.923935$26.974125.0%$1.00
$2.1037$1.202637$27.593133.3%$2.01
$2.8646$0.522619$15.983133.3%$1.00
$2.2264$0.906521$22.4050.0%
$3.15104$0.87103300$41.6680.0%
$3.0754$1.294751$18.1040.0%
$2.9897$1.248048$34.147114.3%$4.56
$2.73111$1.709945$51.249222.2%$1.32
$2.49134$1.4914148$56.6011218.2%$2.19
$2.55159$1.8916849$63.881616.3%$3.31
$2.5468$1.719733$31.089222.2%$4.53
$2.38110$1.0310347$45.899111.1%$2.38
$2.68225$1.1918145$106.5118211.1%$1.73
$2.63238$1.2824665$89.6419315.8%$2.38
$2.5092$1.0710248$42.818112.5%$4.13
$2.36204$1.0121269$93.53170.0%
$2.77126$1.1711359$26.799111.1%$1.00
$2.41238$1.2722868$78.2419315.8%$1.92
$2.86256$0.9324276$81.40200.0%
$2.42125$0.5817642$60.1714321.4%$1.04
$2.2697$0.589154$40.097114.3%$1.00
$2.3448$0.996422$20.235120.0%$1.00
$2.0782$0.996430$18.2770.0%

Not enough leads per hour yet to separate real patterns from chance.

Buckets are Mountain time, DST included — the warehouse stores UTC, and raw UTC hours would sit six or seven hours off what the business actually experienced. Feed bid is dollars per click into the click feeds; Lead bid is dollars per lead offered by lead buyers. Different units, never averaged together. Bids and clicks are bucketed by when they happened; leads, sold and avg sold by when the lead arrived, so a late-night lead that sells at 9am counts toward the night — the question here is what traffic from an hour is worth. Sold rate is coloured against the 12.3% baseline once a bucket has 25+ leads. There is no cost column: Facebook spend is ingested at daily grain, so CPL and ROAS cannot be split by hour without an hourly pull.

Expand a hour to see it per counterparty — which feed was paying then, which buyer was accepting. A buyer that is both appears once, with both halves filled. Inside an expanded row, Leads means leads sent to that buyer and sold rate is their acceptance of them, where the row above counts every lead that arrived — same question, narrower denominator. Those figures are bucketed by when we contacted the buyer, which is the clock a daypart rule acts on.

Before switching a feed off for an hour, check the volume behind it: a single fortnight gives each weekday two or three samples, and each hour fewer still.