Last updated: August 2026. Data through July 31, 2026.
Across June and July 2026, 20 home services contractors ran paid ChatGPT placements that produced 117 leads, $17,632 in closed revenue, and $98,678 in open revenue potential. The channel books jobs and generates revenue.
It also underperforms the organic ChatGPT referrals those same contractors receive for free. Paid booked at 33.9% against organic’s 42.3%, and produced an average ticket of $1,259 against $3,483.
The more interesting number is the direction of travel. Paid ChatGPT lead volume grew 38.8% from June to July while organic ChatGPT declined 4.0% across the same portfolio.
This page reports what happened to those leads after the click.
Method
Period: June 1 to July 31, 2026. Portfolio: 500+ home services accounts across HVAC, plumbing, electrical, and adjacent trades.
Paid ChatGPT cohort: 117 unique leads, 118 customers, across 20 contractors in July and 17 in June.
Rates are pooled, not averaged. Book rate is total booked customers divided by total customers, not the mean of per-account rates. Average ticket is closed revenue divided by paying customers.
A lead qualified as paid ChatGPT when the attribution channel was ChatGPT and one of the following held: the campaign name matched a ChatGPT ad pattern, the medium was paid_ai, ads, cpc, or clickad, or the CRM campaign category was PAID.
ChatGPT Ads Revenue: Home Services, June–July 2026
| Paid ChatGPT | Organic ChatGPT | |
|---|---|---|
| Unique leads | 117 | 1,731 |
| Closed revenue | $17,632 | $1,365,276 |
| Sold revenue | $15,606 | $331,632 |
| Open revenue potential | $98,678 | $3,747,165 |
| Closed revenue per lead | $151 | $789 |
| Potential per lead | $843 | $2,165 |
| Average ticket | $1,259 | $3,483 |
Closed revenue is invoiced work. Sold revenue is signed but not yet invoiced. Revenue potential is the projected value of the full open pipeline, which matters here because most of this cohort has not had time to close.
The ratio between the two channels narrows considerably depending on which measure is used. On closed revenue per lead, organic is worth 5.2x paid. On revenue potential per lead, 2.6x. Much of that difference is measurement timing rather than channel quality, for reasons covered in the trend section below.
Funnel Benchmarks
| Metric | Paid ChatGPT | Organic ChatGPT |
|---|---|---|
| Customers | 118 | 1,857 |
| Book rate | 33.9% | 42.3% |
| Paying customer rate | 11.9% | 21.1% |
The gap held across both months independently. Paid booked at 34.7% in June and 33.3% in July, against organic at 43.4% and 41.2%. An eight point spread reproducing in two separate months across different advertiser sets is a pattern rather than sampling noise.
Why the paid version underperforms the free one
The two are not the same product.
An organic ChatGPT referral occurs when someone asks an assistant to recommend a contractor and receives a direct answer naming that business. That is a recommendation carrying implied endorsement, delivered to someone at the end of a research process.
A paid placement is an ad surfaced alongside a conversation. Relevant and well-targeted, but the person did not ask for a vendor recommendation. They asked about their problem.
Same platform, different intent depth. The funnel reflects it.
Month-Over-Month: June to July 2026
Paid ChatGPT
| Metric | June | July | Change |
|---|---|---|---|
| Advertisers | 17 | 20 | +17.6% |
| Unique leads | 49 | 68 | +38.8% |
| Booked customers | 17 | 23 | +35.3% |
| Book rate | 34.7% | 33.3% | -1.4 pts |
| Paying customer rate | 10.2% | 13.0% | +2.8 pts |
| Sold revenue | $1,790 | $13,816 | +672% |
| Revenue potential | $35,959 | $62,718 | +74.4% |
| Closed revenue | $9,532 | $8,100 | -15.0% |
| Average ticket | $1,906 | $900 | -52.8% |
Organic ChatGPT
| Metric | June | July | Change |
|---|---|---|---|
| Unique leads | 883 | 848 | -4.0% |
| Book rate | 43.4% | 41.2% | -2.2 pts |
| Paying customer rate | 22.3% | 19.9% | -2.4 pts |
| Revenue potential | $1,957,680 | $1,789,486 | -8.6% |
| Closed revenue | $799,680 | $565,596 | -29.3% |
| Average ticket | $3,808 | $3,108 | -18.4% |
Reading these two tables together
Volume is diverging. Paid ChatGPT grew 38.8% in leads and 17.6% in advertisers while organic ChatGPT contracted 4.0%. Revenue potential moved the same way: paid up 74.4%, organic down 8.6%. Whatever is happening to ChatGPT referral volume generally, paid placements are not following it.
The revenue declines are a measurement artifact, not channel degradation. Closed revenue per paid lead fell from $195 to $119, and average ticket halved. Read alone, that looks like the channel getting worse. But organic ChatGPT fell the same way over the same window, with average ticket down 18.4% and closed revenue down 29.3%, and nothing about organic changed.
Both months were measured at the same early-August data pull. June has had roughly a month longer for jobs to close. Home services revenue matures over 30 to 90 days, so the more recent month always looks worse until it catches up. June’s paid cohort, at greater maturity, shows a $1,906 average ticket. July’s $900 is the same channel measured too early.
This is the single most important caveat for anyone tracking this channel monthly. A 30-day read understates revenue by roughly half.
Lead quality is improving, slightly. Book rate slipped 1.4 points, within noise. Paying customer rate rose 2.8 points, from 10.2% to 13.0%, while organic’s fell 2.4 points. Two months is not a trend, but paid moved up against an organic baseline that moved down.
Contact Method: 82% Arrive by Phone
| Contact method | Leads | Share | Share of closed revenue |
|---|---|---|---|
| Phone call | 56 | 82% | 100% |
| Web form | 10 | 15% | 0% |
| Unknown | 2 | 3% | 0% |
In July’s cohort, 82% of paid ChatGPT leads arrived as tracked phone calls, and every dollar of closed revenue came through a call. No web form submission had closed at time of measurement, though $12,914 of open potential remained in that group.
The pattern is consistent with the format. Someone describing a problem to an assistant in natural language is already mid-explanation, and a phone call is the shorter path from there than a form.
It also means measured performance on this channel is bounded by call answer rate. A contractor missing calls will see ChatGPT Ads underperform for reasons that have nothing to do with ChatGPT.
What Contractors Are Advertising
| Service intent | Share of paid leads | Closed revenue |
|---|---|---|
| HVAC / cooling | 79.4% | $5,650 |
| Plumbing | 7.4% | $0 |
| Unspecified | 7.4% | $0 |
| Water heater | 2.9% | $2,450 |
| Electrical | 1.5% | $0 |
| Brand | 1.5% | $0 |
Roughly four in five paid ChatGPT leads were cooling-related during peak season. Early adopters are testing the channel with their highest-urgency, shortest-cycle work rather than with high-ticket replacement or install campaigns.
That shapes how the ticket figures should be read. The $1,259 average is not evidence that ChatGPT Ads cannot carry a large job. It is evidence that few contractors have pointed it at one. The two water heater leads are the only signal in the dataset that the channel can carry considered-purchase work, and both booked.
Do ChatGPT Ads Cannibalize Organic ChatGPT Referrals?
Given that the organic version outperforms the paid version, the obvious risk is paying for leads that would have arrived free.
Organic ChatGPT lead change from June to July, grouped by what each account did with paid:
| Cohort | Accounts | Organic leads, Jun → Jul |
|---|---|---|
| Ran paid both months | 10 | 7 → 15 (+114%) |
| Started paid in July | 10 | 10 → 14 (+40%) |
| Ran paid in June only | 7 | 35 → 15 (-57%) |
| Never ran paid (control) | 261 | 593 → 568 (-4.2%) |
The 261-account control group is the anchor. Organic ChatGPT volume among non-advertisers was roughly flat. Advertisers did not follow that baseline. Every advertising cohort grew organic leads while adding paid volume on top.
There is no evidence in this data that ChatGPT Ads cannibalize organic ChatGPT referrals.
The advertiser cells are small, and a +114% move represents eight additional leads. That is not enough to claim ads cause organic lift, and contractors who choose to test a new channel likely differ systematically from those who do not. The defensible conclusion is the negative one: the cannibalization risk is not appearing.
One further observation from the June data. Seven of June’s 17 ChatGPT advertisers produced no paid leads in July, roughly 40% single-month drop-off. Without spend data it is not possible to distinguish campaigns being switched off from campaigns running with no result from tagging breaking. All three are plausible.
What This Data Cannot See
No view-throughs. Every lead counted here is a direct referral that initiated a new sales cycle through a click or tracked call. There is no view-through window, no assisted conversion credit, no multi-touch modeling. A homeowner who saw a ChatGPT ad, kept talking to the assistant, and searched the business by name two days later sits in a brand search bucket with no record of the ad that caused it.
Google Ads and Meta receive view-through and assist credit. ChatGPT Ads, as measured today, receives credit only for last-click sessions that opened a new opportunity. These figures are a floor. They should not be compared against Google Ads or Local Services Ads benchmarks, which are measured under looser rules. The paid-versus-organic ChatGPT comparison holds because both sides are measured identically.
No cost data. ChatGPT Ads has no spend connector into attribution platforms. Across 117 leads, one campaign reported spend: $474.92 producing 2 leads. That is a single data point, not a cost-per-lead benchmark.
Measurement depends entirely on advertiser tagging. There is no auto-tagging parameter equivalent to Google’s gclid, no conversion import, and no platform-side reporting to reconcile against. Across 68 July leads there were 24 distinct campaign naming conventions and 4 distinct utm_medium values describing the same channel, and only 2 of 68 were filed as paid media in the CRM. Untagged paid leads currently sit in organic buckets, which inflates organic performance and deflates paid performance. That runs against this page’s own headline finding and is disclosed for that reason.
Frequently Asked Questions
Do ChatGPT Ads work for home services contractors? Yes. Across 117 leads at 20 contractors in June and July 2026, ChatGPT Ads produced $17,632 in closed revenue and $98,678 in open pipeline, at a 33.9% book rate and an 11.9% paying customer rate. Both rates are below organic ChatGPT referrals in the same portfolio.
How much revenue do ChatGPT ad leads generate? $151 in closed revenue per lead and $843 in open revenue potential per lead, across June and July 2026. Organic ChatGPT referrals produced $789 closed and $2,165 potential per lead over the same period.
What is a good book rate for ChatGPT Ads? Paid ChatGPT leads booked at 33.9% pooled across June and July 2026, against 42.3% for organic ChatGPT referrals. Book rate is booked customers divided by total customers.
What is the average ticket from a ChatGPT ad lead? $1,259 pooled across June and July 2026, against $3,483 for organic ChatGPT referrals. The July figure alone is $900, but that reflects incomplete revenue maturity rather than channel performance. June’s cohort, measured a month later in its lifecycle, shows $1,906.
How much do ChatGPT Ads cost for contractors? No reliable cost benchmark exists. ChatGPT Ads does not push spend data into attribution platforms, so cost-per-lead cannot be measured at portfolio scale. One campaign in this dataset reported $474.92 producing 2 leads. Most published ChatGPT Ads cost figures are modeled planning estimates rather than measured outcomes.
Are ChatGPT Ads growing? In this portfolio, yes. Paid ChatGPT leads grew 38.8% from June to July 2026 and advertiser count grew 17.6%, while organic ChatGPT leads declined 4.0% over the same window.
Do ChatGPT Ads cannibalize organic ChatGPT leads? No evidence of cannibalization appears in this data. Contractors running ChatGPT Ads grew their organic ChatGPT leads from June to July while a 261-account control group of non-advertisers was flat at -4.2%.
Do ChatGPT ad leads call or fill out forms? 82% arrived as tracked phone calls in July 2026, and all closed revenue came through calls.
Limitations
- 117 leads across 20 advertisers in July and 17 in June. Small. Directional, not absolute.
- Two months. Longer trend unavailable.
- Cost data effectively absent. No CPL, CAC, or ROAS.
- Revenue immature. July leads measured in early August will continue to close, and month-over-month revenue comparisons are affected by differing maturity.
- Peak cooling season, skewed toward emergency HVAC demand.
- Cannibalization cohort cells are small. The 261-account control group is the reliable component of that comparison.
- Advertiser cohorts are self-selected, so no causal claim is made about organic lift.
- The paid cohort is likely undercounted because identification depends on advertiser tagging.
SearchLight builds neutral measurement infrastructure for home services. We are not an ad agency and hold no media spend incentives.