Soft Wash Leads That Arrive as Booked Appointments

Most "leads" are just contact info. A homeowner clicks an ad, a form fires, and the platform sells that same record to a handful of contractors who then race to call first. With StingLeads, a lead is a confirmed free-quote appointment. Our AI assistant texts the homeowner, confirms it is a soft wash job (roof, siding, stucco, or another low-pressure surface), qualifies the property, and books a specific visit time that lands on your calendar.

Because the homeowner agreed to a time and is expecting you, the conversation on-site starts warm instead of cold. You are not chasing, you are not competing to answer first, and you are not paying to be one of five voices leaving voicemails. Every appointment is yours alone. To date the platform has booked 1,372+ appointments with a 94% show-up rate across 200+ companies served.

Shared-lead marketplaces are honestly good at one thing: volume. They spend heavily on ads and can put a lot of contact records in front of you fast. The trouble is the business model underneath. Shared platforms commonly sell the same lead to three to five contractors and charge you whether or not you ever win the job. That turns a cheap-looking per-lead price into an expensive cost per closed job.

The math is not subtle. Industry analysis pegs shared-lead close rates at roughly 6 to 15 percent, which pushes the real cost per closed job past $1,700 once you count every lead you paid for and lost. Exclusive leads convert at roughly 25 to 40 percent, landing cost per closed job around $240 to $320. For soft wash work, where each visit takes real time to inspect and quote, chasing the same homeowner as four competitors is not just annoying, it is a margin killer.

This is not just contractor frustration, it is documented. In 2023 the Federal Trade Commission ordered HomeAdvisor, the company that sells Angi Leads, to pay up to $7.2 million over deceptive claims about lead quality, source, and how often leads turned into actual jobs. That November the FTC returned more than $3 million to affected businesses through 110,372 checks.

The pattern has continued. In October 2025 the Vermont Attorney General settled with Angi for $100,000 over its misleading "Angi Certified Pro" marketing. Angi is not BBB accredited and carries roughly 1,946 complaints on its BBB profile over the last three years. None of this means these companies are worthless, but it does mean the shared model has real, on-the-record problems you should price in before spending a dollar there.

When a homeowner in your service area shows interest, our AI SMS assistant opens a natural text conversation within minutes. It confirms the job is a soft wash fit, gathers the details that matter (surface type, roughly the scope, and the property), and proposes a specific free-quote visit time. Once the homeowner agrees, that appointment is written to your calendar and the record is yours exclusively.

• Exclusive: one appointment, one contractor, never resold.
• Pre-booked: a real time slot, not a name and number to cold-call.
• Qualified: soft wash intent confirmed before it reaches you.
• Protected: bad-lead and no-show protection so you are not paying for junk.

You focus on quoting and closing the jobs; the assistant handles the texting, the qualifying, and the scheduling.

You choose how you pay. Pay per lead for predictable per-appointment pricing, or pay per close if you would rather tie cost to booked revenue. Either way there are no long-term contracts and no obligation to keep buying credits you may never use. Founding per-lead pricing starts around $30 for pressure washing and $50 for tree service, with soft wash priced alongside our exterior-cleaning trades as we scale.

Every appointment carries bad-lead and no-show protection, so a wrong number, an out-of-area request, or a homeowner who never should have qualified does not come out of your pocket. Across the platform, companies see a 94% show-up rate and rate the service 4.8 out of 5. You keep the exclusivity, we keep the risk on our side of the table.