LGG Media builds exclusive home insurance lead generation on Google Ads for brokerages, MGAs, and carriers spending $100,000 or more per month. Your CRM's bound-policy data feeds the bidding algorithm, so budget flows to the projected lifetime value of the policy sold, not the call that filled a queue.
Bound-policy acquisition for carriers, MGAs, and independent agencies writing homeowners, dwelling fire, and landlord policies. Value lands at bound premium, seasonality follows catastrophe exposure and rate filings, and routing follows underwriting appetite by peril and territory.
Personal auto and P&C on our auto insurance page. Under-65 and ACA on our health insurance page. Medicare Advantage, Supplement, and D-SNP on our Medicare page. Term, final expense, and annuities on our life insurance page.
The method behind every line, from tracking to lifetime-value bidding, is on our insurance lead generation page.
This page is written for brokerages and agency groups buying at volume, not a single captive agent. LGG sells exclusive leads, each to one broker and never resold to multiple buyers, and also builds and manages the lead generation architecture for insurance clients directly. The same methodology that runs our published health insurance case study extends to home: bid on the projected lifetime value of the policy sold against the ad spend required to acquire the customer, not on a flat price per lead.
That single idea, projected lifetime value as the conversion value, is the primary bidding signal across every line we run, home included. It is what lets a brokerage compare a $900 dwelling policy in a low-risk inland territory against a $4,000 coastal policy on the same ratio, instead of pricing both as identical leads. The same ratio also holds across channels: Google, Meta, and Microsoft Advertising all accept an offline conversion value, so a brokerage running paid social alongside search does not have to maintain two different pricing logics for the same book of business.
Third-party home insurance lead quality is volatile for a structural reason: the vendor is not plugged into your CRM and cannot maintain quality on its own. It can only optimize on what it can see, a form fill or a call, and it sells that same signal to every brokerage buying from it.
LGG plugs into the brokerage's CRM in a compliant, private manner and sends the resulting data back to the ad channels, so bidding runs on the projected lifetime value of the plan actually sold. Removing the lead-quality guesswork this way is the differentiator: volume scales while quality holds constant, because the algorithm is learning from bound premium, not from a vendor's proxy signal.
How offline conversion tracking works → · Setting Target ROAS against real revenue →
A bound homeowners policy is worth different things to different buyers, so the value passed to bidding is modeled per buyer type, never flat.
Retention-adjusted, catastrophe-loss-adjusted lifetime value to cost. Carriers hold the loss-ratio and renewal data to share downstream retention, so bidding optimizes against the true multi-year value of every bind, by territory and peril.
Override rate to cost, or a target acquisition cost per bound policy, aligned to underwriting margin and the appetite of the carrier paper behind the program.
First-year commission or premium to cost with a flat target CAC. Multi-policy households get pushed as one order with multiple line items, home and auto together, with each line item's projected lifetime value normalized before bidding sees it.
Programs start at premium to cost as the baseline, elevate to commission to cost, and scale into retention-adjusted lifetime value once postback data exists. Each rung makes the bidding smarter, and the ladder is identical to the one we run on auto and life.
A quote request is not revenue, and neither is a bind that lapses in the first billing cycle. The primary conversion event is the bound policy with first premium cleared at the effective date, passed back through our offline conversion pipeline so Smart Bidding learns from bound premium, not form fills. Hashed first-party data flows through enhanced conversions for leads to keep match rates high.
Data-integrated buyers feed server-to-server postbacks or offline batch updates on 30 or 60 day windows. The algorithm computes a net-bind multiplier, gross binds minus cancel-flats and early lapses, and bids strictly on refund-adjusted lifetime value. Carriers and large MGAs with a data team typically reach server-to-server postbacks within the first 60 to 90 days of a program. Independent agencies more often start on the batch-upload path and graduate once the volume justifies the integration work.
Recommended minimum spend. LGG builds owned home insurance machines for brokerages, MGAs, and carriers spending $100,000 or more per month. $500 per day is the absolute floor: below that, the account cannot accumulate enough bound-policy data for the value curve to stabilize.
Coastal wind, wildfire interface, and hail-belt territories convert differently and carry different loss curves than inland, low-peril homes, so they never share a value curve with preferred risk. Specialty and E&S carriers want that volume at the right cost, so the system segments it and bids it down instead of refusing it.
Routing follows appetite dynamically: if a preferred carrier tightens underwriting in a wildfire-interface ZIP code or a coastal county after a rate filing, the traffic routes to surplus-lines and specialty buyers whose appetite wants it, in real time.
Multi-line intent prices at a premium. Home-and-auto and home-and-umbrella shoppers retain far better and carry higher total household lifetime value, so our bidding treats bundled intent as its own high-value cohort from the first click, exactly as it does on the auto insurance side of the same household.
A negative list keeps definition searches, DIY policy comparisons, and general insurance-education queries off the budget before they ever reach bidding. What remains is a homeowner or property owner actively shopping bound coverage.
Preferred inland risk, coastal wind exposure, wildfire interface, and hail-belt territories each carry their own value curve, so they run as separate ad groups inside one campaign rather than as separate campaigns split by geography. Conversion value rules apply the territory-specific multiplier at auction time, and Google's own guidance notes that performance generally improves with fewer, larger campaigns that accumulate more conversions, the same principle our auto and life insurance accounts run on.
Landlord and dwelling-fire policies get their own ad groups too. A rental property and an owner-occupied home carry different loss curves and different commission structures, so the two never share a value curve even inside the same territory.
A hurricane landfall, a hail outbreak, or a wildfire evacuation order can multiply home insurance search volume within a single day, concentrated in the counties the event just touched. A budget cap written for a normal week starves the account exactly when bound-policy volume is easiest to win.
The fix is the same one our roofing accounts run on: set a daily budget with real headroom, hold a Target ROAS or Target CPA as the actual constraint, and let the campaign expand into the spike on its own. Google Ads documents the mechanics: a campaign can spend up to 2 times its average daily budget on any single day, and is never charged more than the daily budget multiplied across 30.4 days in a month. Headroom this size means the target, not the budget, decides how far the campaign reaches into the event.
Since August 17, 2026, Google's changes to target-based bid strategies deliver budget-limited Target CPA and Target ROAS campaigns more consistently toward the set target, which makes uncapped headroom a cleaner strategy than it used to be. A campaign that never actually hits its budget ceiling never enters the budget-limited state at all.
Appetite can tighten at the same moment demand spikes. A carrier or MGA that pulls back new business in a just-hit county after a catastrophe does not want that traffic bid up. Routing has to check appetite in real time, the same architecture described above under segmentation, so a budget with headroom never buys volume nobody can bind.
It is easy to buy third-party home insurance leads. The question that matters is who holds the liability when a consent record does not hold up. Companies get sued over this more often than the industry likes to admit, and LGG does not work with brokerages that do not have their legal compliance in order first.
The standard we hold every program to: generate leads by the book, work leads in your system by the book, fully compliant, start to finish. Prior express written consent is still required for marketing calls and texts under the TCPA. The one-to-one consent rule the FCC adopted in December 2023 was vacated by the Eleventh Circuit in January 2025, and the FCC confirmed in April 2025 it would not challenge that ruling, so the standard reverted to consent obtained per seller rather than disappearing. We build campaigns to the standard as it stands today and verify it before every launch, not from memory.
The FCC's one-to-one consent order and its current status →
We do not touch aged home insurance leads. Aged form submissions are the segment most likely to carry unresolved TCPA liability, because the original consent, if it existed at all, was never scoped to the buyer calling on it months later.
Live transfers are acceptable only when they originate from an inbound call the consumer placed. A live transfer manufactured from outbound dialing of a purchased list carries the same liability problem as an aged lead wearing a faster costume, and we do not run it.
The difference is not lead quality, it is what the ad platform gets to learn from. A vendor reselling home insurance inquiries to competing brokerages can only ever optimize on the shallowest signals it can see. In-house infrastructure, CRM-connected, feeds the deep ones.
A form fill scored by the answers in it. An inbound call, or a call past a duration threshold. That is the entire list, and the vendor's algorithm optimizes it across every brokerage the lead is resold to, never on whether a policy bound.
Bound policies. Projected lifetime value by territory and peril. Multi-policy households normalized across line items. These signals only exist inside your CRM, and only in-house infrastructure feeds them back to the ad platforms, on your account, for your book of business only. Vendors have no reason to build this, since a vendor whose leads bind well loses the case for switching to an owned program. The incentive only lines up once the brokerage owns the account and the CRM feeding it.
Start on the lead generation pillar to see the full architecture →
We sell exclusive leads, each to one broker and never resold to multiple buyers, and we also build and manage the lead generation architecture for insurance clients directly. Every campaign runs on the buyer's own ad account with the buyer's own CRM feeding value back to bidding, so the leads a brokerage receives are exclusive to it, not resold shared inventory.
Projected lifetime value of the policy sold, used as the conversion value with Target ROAS bidding against ad spend. For multi-policy households, home and auto push as one order with multiple line items, each normalized to its own projected lifetime value before bidding sees it.
No. Aged home insurance leads carry the highest unresolved TCPA liability in the category, because the original consent was rarely scoped to the buyer calling on it later. We do not touch them.
Only when they originate from an inbound call the consumer placed. A live transfer built from outbound dialing of a purchased list carries the same consent problem as an aged lead. We run inbound-originated transfers only.
No. LGG does not work with companies that do not have their legal compliance in order. Generate by the book, work leads by the book, or we do not take the engagement.
LGG works with advertisers spending $100,000 or more per month. $500 per day is the absolute floor below which the account cannot accumulate enough bound-policy data for value-based bidding to stabilize.
The bidding architecture is identical across all three: bid on the projected lifetime value of the policy sold, never on a flat lead price. What changes is the value driver. Auto insurance value tracks bound premium and claims history. Life insurance value tracks placed-and-paid commission by product. Home insurance value tracks bound premium adjusted for peril and territory, since a coastal wind policy and an inland preferred policy are worth different amounts even at the same premium.
Yes. Coastal wind, wildfire interface, and hail-belt territories run as their own ad groups with their own value curve, and the budget carries headroom so a hurricane, hail outbreak, or wildfire event does not starve the account the day search volume spikes. Appetite is checked in real time, since a carrier can pause new business in a just-hit county the same day demand rises.
Platform mechanics: Google Ads Help, About offline conversion imports, About Target ROAS bidding, About Target CPA bidding, About conversion value rules, and Changes to target based bid strategies. TCPA consent status: the FCC's one-to-one consent order and its current status. Operator guidance on this page comes from LGG Media's active insurance accounts and is labeled as such.
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Send us the account. We will show you what your conversion signal is teaching the algorithm and what bound-policy, lifetime-value bidding would change. Minimum $100,000 per month in ad spend. Scope, price and terms set in the proposal. No annual contracts.
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