Industries · Insurance
Value-Based Bidding for Insurance Agencies: Bid on Commission, Not Quotes
Every quote request counts as one lead, whether it binds a home-and-auto bundle or never gets past the first call. Use your own book to estimate the commission each new request is likely to bring, so the ad platforms learn which quotes are worth paying for.
Why lead counts fall short
Why a count of quote requests misses what a policy is worth
Insurance lead forms are cheap to fill in and most of them are shopping. A quote request for a bundle from a homeowner and one for a one-month renters policy arrive as the same event, and bidding that counts them will buy whichever kind is cheapest, which is usually the one that pays the least.
Your agency management system knows what each kind of request became: whether it was quoted, whether it bound, and what the first-year commission was. Those are the facts the ad platforms never see unless they are sent.
Bind rate and commission move separately
Renters binds often for a small commission; a bundle binds less often for many times more. Expected value weighs both, so neither the easy sale nor the big one wins by default.
Commission, not premium
The agency earns the commission, not the premium, and the two do not scale together across carriers and lines. Price on the commission your system records on a bound policy, and the values mean what the business earns.
Rating factors stay out
Age, health, driving record and credit are rating factors for the carrier, not advertising signals, and the product refuses them by column name. Product line, current insurance status, timeline and state are the fields to use.
The funnel
From quote request to commission recorded
- Quote request
- Quoted
- Bound
- Commission recorded
Known when the lead arrives
What a new lead can be priced from
- Product line requested
- Currently insured or not
- When cover is needed
- State or region
- Bundle requested or single line
Learned later
What the history is trained on
- Whether a quote went out
- Whether the policy bound
- The first-year commission on the bound policy
The product line, the timeline and whether they hold cover today are what price a new request. The quote, the bind and the commission are what the history is trained on.
How it works
From your sales history to what the ad platforms see
- 1
Bring in your history
A CRM export or a HubSpot connection: leads with their outcomes, won, lost or still open.
- 2
Find what relates to value
Each field known when a lead arrives is tested against your closed deals. Only the ones that clearly moved outcomes are kept.
- 3
Estimate each new lead
Its expected value: how likely leads like it are to become customers, times what those customers were worth.
- 4
Send the value
To Google Ads or Meta, as a conversion value on the lead. Sending changes no bid by itself.
- 5
Judge it on real outcomes
Compare closed deals before and after your campaigns start optimising on the values, never the values we sent.
Worked example
Three leads, three different values
Expected lead value = the estimated chance of becoming a customer × the expected value of that customer.
Value basis: First-year commission. The commission your system records on a bound policy. If it records premium instead, a single commission share turns it into the same figure; the product does not model a different rate per carrier.
Home and auto bundle, currently insured
- Cover needed: at renewal, next month
- State: FL
35% × $1,400
$490
estimated value of this lead
Auto only, currently insured
- Cover needed: this week
- State: TX
28% × $450
$126
estimated value of this lead
Life quote, no timeline given
- Not currently insured
- State: not given
6% × $900
$54
estimated value of this lead
Illustrative example, not customer results.
The bundle is worth nearly four times the auto-only request and nine times the life quote, even though the life commission is twice the auto one. How likely a request is to bind matters as much as what it pays when it does.
How the product actually estimates this
It does not score each lead on its own. It starts from your overall close rate times your average won deal, with any deal above three times the median counted at that cap, then applies a multiplier for each field that clearly moved outcomes in your history, and rescales so the average estimate matches what your leads were actually worth. Fields that do not clear the evidence thresholds are left out and listed. The formula above is the same idea in one line.
What data you need
Your CRM already has most of it
- Quote request dateWhen the request arrived, not the policy effective date.
- Bound, not bound or still openRequests that were quoted and walked away teach the model as much as the ones that bound.
- Commission on bound policiesFirst-year commission, or premium with one commission share, consistently one or the other.
- Fields from the quote formProduct line, current insurance status, timeline, state and whether a bundle was requested. No age, health, driving or credit details.
- Matching informationGoogle's click ID or the requester's email for Google; email or phone, plus Meta's cookies from your site, for Meta.
What matters most is reliable outcomes and enough of them. The report checks your own file and names anything it could not price, rather than applying a one-size minimum.
How activation works
Estimating, sending and optimising are three steps
The product estimates each lead's value and sends it. Your campaigns use it only once you set them to optimise for value, a change you make in the ad platform, and the platform decides when an account qualifies.
Google Ads
Sends each request's estimated value to a conversion action in Google Ads, matched on the click ID or on email. Your campaigns use it only once they bid on value, for example with Maximize conversion value.
Switching a live campaign, step by stepMeta
Sends a ValuedLead event with the value through the Conversions API. Website-form ad sets bid on values once they qualify for value optimisation; instant-form ad sets can learn from the quoted and bound stages through Conversion Leads.
How the Meta route worksThe full method, from pricing a lead to measuring the result, is in the complete guide. Leads that reach your CRM without a click ID are covered in the click ID guide.
How to judge success
Measured in outcomes, not in the values we sent
Bound policies per request
By product line, before and after the switch.
Cost per bound policy
Ad spend against policies bound, not against quote requests.
Commission per request
First-year commission divided by the requests that produced it.
Reported conversion value going up is not the result; it repeats what we sent. The product's evaluation compares bound policies before and after the switch, with requests from other sources as a control.
Questions
Insurance, specifically
Can we use age, health or driving history to price a request?
No. They are rating factors and, for age and health, protected characteristics. The ad platforms' policies restrict bidding on them and the product refuses such columns by name. Product line, timeline, current cover and state carry the signal.
Our commission differs by carrier. Does one value basis work?
Yes, if your system records the commission actually earned on each bound policy: the model reads that figure. If it records premium, the product applies one commission share across the book, which is a simplification worth knowing about.
Most requests bind within days, but some take weeks. Is that a problem?
No. Values are estimated when a request arrives, from requests like it that already resolved. Fast binding helps: the model can be refitted on fresh outcomes every few weeks.
We buy leads from aggregators too. Should those be in the file?
Include every request with its source, so the channel table shows what each one was worth. Only the requests that came from your own ads are matched to an ad click; aggregator leads inform the model and are not sent anywhere.
What about renewals and cross-sells later?
The product prices on the first-year commission your system records at binding. Renewals and later cross-sells are not forecast, so lifetime value is not a claim the values make.
Check whether your lead data is ready
Upload a CRM export or connect HubSpot. In about five minutes you see which of your fields relate to value, what new leads would be estimated at, and whether your history is enough to send. The file is read in your browser; you are asked for a name and work email before the full report.