Auto Insurance Campaign Setup: Targeting & Bid Modifiers

This SOP defines the foundational targeting rules and bid modifiers that must be applied to every new auto insurance campaign launched on the GOAL Platform. These settings represent the baseline configuration that filters out undesirable traffic and adjusts bid prices based on lead quality attributes. It is intended for all GOAL account managers and should be referenced during initial campaign setup for any new auto insurance client.

Note

These are starting-point configurations. Further optimization should occur based on client-specific data, carrier appetite, and performance trends.

Key terminology

Targeting rules: Hard filters that determine whether a lead is accepted or rejected before it ever reaches the bidding engine. If a lead fails any targeting rule, it is blocked entirely and the client will never see it or pay for it.
Targeting group: A set of targeting rules evaluated together with AND logic. Every condition in the group must be true for a lead to pass through.
Modifiers: Percentage adjustments that move the bid price up or down based on lead attributes. Unlike targeting rules, modifiers do not block leads; they change how much the client bids for a lead based on its quality signals.
Attribute modifiers: Modifiers that adjust bids based on lead characteristics like homeownership, age, or vehicle count. These are the modifiers covered in this SOP.
Source modifiers: Modifiers that adjust bids at the traffic channel level based on right-pricing data, such as bidding more on search traffic than on referral traffic. They are configured separately using right-pricing reports and are not part of this foundational SOP.

How targeting and modifiers work

Targeting, accept or reject logic

Targeting rules act as hard filters, so a lead that fails any rule is blocked before it reaches the bidding engine. All rules within a single targeting group use AND logic, meaning every condition must be true for a lead to pass through. If any single condition fails, the lead is rejected.

Targeting should not be overly restrictive on initial campaign setup. The philosophy is volume first, then optimize with data. Tight targeting on a new campaign with no historical performance data can starve the client of leads and prevent them from building a meaningful sample size to evaluate the platform. Keep targeting focused on filtering out genuinely uninsurable or low-quality traffic, not on narrowing to a "perfect" lead profile.

Tip

The "If data is unknown" setting controls what happens when a data field is missing from the lead. Setting this to "Accept" means you will still receive leads where that attribute was not collected, which is usually the safer default to avoid over-filtering.

Modifiers, bid adjustment logic

Modifiers change how much the client bids for a lead based on its quality signals.

Modifier	Effect on the bid
150%	Bid multiplied by 1.5x, bid more aggressively
100%	Bid unchanged
50%	Bid multiplied by 0.5x, bid less aggressively

Multiple modifier groups operate with OR logic between them. If a lead matches more than one modifier group, only the highest modifier applies. Within a single modifier group, conditions use AND logic, so all conditions must match.

Modifiers are context-dependent

Modifiers cannot be set in isolation. They must always be evaluated in the context of four factors working together.

Base bid: What the client pays per click before any adjustments.
Targeting breadth: How tight or wide the targeting filters are set.
Geography: How many zip codes and which state or market.
Daily budget: How much the client is willing to spend per day.

For example, a client spending $50/day needs much more careful pricing than one spending $250/day. Overshooting modifiers on a small budget means the client hits their daily cap within the first hour, gets a tiny sample of leads, and can't properly evaluate the platform. The goal is to price traffic so the budget is distributed throughout the day, generating enough volume for the client to measure results.

How attribute and source modifiers stack

The GOAL Platform has two distinct types of modifiers: attribute modifiers, covered in this SOP, and source modifiers, which are configured separately using right-pricing reports. Be aware that both types stack multiplicatively.

Warning

Attribute modifiers stack multiplicatively with source modifiers. A 150% attribute modifier on a source that already has a 120% source modifier would result in 1.5 x 1.2 = 1.8x the base bid. Be mindful of combined effects, especially on small-budget accounts where overshooting can exhaust the daily budget in minutes.

Initial strategy, volume first then optimize

For brand new campaigns with no historical data, the initial setup strategy is to generate volume first, then use the data to optimize. Don't try to perfectly optimize a campaign on day one. Get enough leads flowing that the client can evaluate the product and you have real performance data to work with. The foundational modifiers in this SOP are designed to give a reasonable starting bid profile, not a final-state optimization.

Right-pricing reports, meaning Periscope data, are useful for initial source modifier calibration, but they should target second position pricing, not first position. Overshooting for first position blows up the budget with insufficient volume. If you're going to overshoot on any channel, search is safer than referral because search traffic carries higher intent and better quality.

Foundational targeting rules

The following targeting group must be configured on every new auto insurance campaign. All conditions are AND logic within the group, meaning every rule must pass for a lead to be accepted.

Targeting group 1, required for all auto campaigns

Attribute	Operator	Value	If unknown	Rationale
Credit Rating	Doesn't Equal	Poor	Accept	Poor credit leads convert at significantly lower rates and many carriers won't write them.
License Status	Equals	Active	Accept	Suspended or revoked licenses are uninsurable by most carriers.
Age	More Than	25	Accept	Under-25 drivers carry higher risk and most agencies prefer 25+ traffic.
Currently Insured	Equals	Yes	Accept	Currently insured consumers are shopping for better rates, indicating higher purchase intent.
DUI	Equals	No	Accept	DUI history severely limits carrier options and drives up loss ratios.
SR-22	Equals	No	Accept	SR-22 filings indicate high-risk drivers; most standard carriers decline them.
Current Carrier	Doesn't Equal	[Client's Own Carrier]	Accept	Non-negotiable. Without this, the client receives leads from people who are already their customers. This wastes budget and erodes trust in the platform immediately. Set this every time, no exceptions.

Critical

The Current Carrier exclusion is a placeholder. You must update this value to match each specific client's carrier. If the client writes for multiple carriers, add each one as a separate "Doesn't Equal" rule. Missing this filter means the client pays for leads who are already their customers; this has happened in production and is one of the most common and damaging setup mistakes.

Tip

How to identify the carrier. Check the client's email domain, for example jlocasano@allstate.com tells you they're an Allstate agent. You can also confirm during onboarding or check their Close CRM record. For independent agents who write for multiple carriers, ask which carriers they represent and add a "Doesn't Equal" rule for each one.

Foundational bid modifiers

The following 9 modifier groups should be configured on every new auto insurance campaign. They are organized below from highest multiplier, meaning most aggressive bidding, to lowest, meaning least aggressive bidding.

Group	Multiplier	Conditions (AND logic)	Bid effect	Rationale
1	150%	Multiple Vehicles = Yes AND Home Owner = Yes	+50% above base	Multi-vehicle homeowners are the highest-value auto leads.
3	135%	Home Owner = Yes AND Multiple Vehicles = No	+35% above base	Homeowners indicate stability and cross-sell opportunity.
2	125%	Multiple Vehicles = Yes AND Home Owner = No	+25% above base	Multi-vehicle signals larger policy premium.
4	125%	Auto/Home Bundle = Yes	+25% above base	Bundle shoppers have high cross-line intent and lifetime value.
7	125%	Age Between 25 and 40	+25% above base	Prime demographic: low risk, high retention, growing needs.
6	115%	Current Carrier = [Target Carrier]	+15% above base	Placeholder, replace with carrier the client competes well against.
5	110%	Continuous Coverage = 1+ years	+10% above base	Loyalty signal: continuous coverage indicates responsible consumer.
8	50%	Multiple Vehicles = No AND Home Owner = No	-50% below base	Lowest value segment. Reduce exposure.
9	50%	Age More Than 70	-50% below base	Limited carrier options and elevated loss ratios for 70+ drivers.

Warning

Modifier Group 6 (Current Carrier) is a placeholder. Update this to a carrier the specific client competes well against. Consult the client or their bind rate data.

Tip

Groups 1, 2, 3, and 8 form a complete matrix covering all four combinations of Multiple Vehicles x Home Owner. This ensures every lead gets an appropriate bid adjustment based on these two key attributes.

Note

Why homeownership is the number 1 attribute. Of all the attribute modifiers, homeowner status is the single most important signal for auto lead quality. Homeowners represent stability, higher premiums, bundling potential (auto plus home), and better retention. When evaluating how a campaign is set up, the first question should be: "Are we bidding appropriately on homeowners?" The entire modifier matrix is built around this attribute for a reason.

Detailed modifier breakdown

Group 1, 150%: Premium multi-vehicle homeowners

Attribute	Operator	Value
Multiple Vehicles	Equals	Yes
Home Owner	Equals	Yes

This is the highest-value segment. Consumers with multiple vehicles who own their home represent the ideal auto insurance customer: larger premiums, bundling potential, and strong retention. Homeownership is the single most important attribute signal in auto campaigns; it's the core indicator around which the entire modifier matrix is built.

Group 2, 125%: Multi-vehicle, non-homeowner

Attribute	Operator	Value
Multiple Vehicles	Equals	Yes
Home Owner	Equals	No

Multi-vehicle households that don't own a home still represent above-average premium opportunity. The additional vehicle signals a larger policy.

Group 3, 135%: Homeowner, single vehicle

Attribute	Operator	Value
Home Owner	Equals	Yes
Multiple Vehicles	Equals	No

Homeownership is a strong quality signal even with a single vehicle. These consumers tend to have stable lifestyles, better credit profiles, and are prime candidates for auto/home bundling.

Group 4, 125%: Auto/home bundle

Attribute	Operator	Value
Auto/Home Bundle	Equals	Yes

Consumers actively shopping for an auto/home bundle have high purchase intent and represent significantly higher lifetime value through multi-policy retention.

Group 5, 110%: Continuous coverage 1+ years

Attribute	Operator	Value
Continuous Coverage	Equals	1+ years

A track record of continuous coverage signals a responsible consumer who is less likely to lapse. These leads convert and retain at higher rates than those with coverage gaps.

Group 6, 115%: Target carrier conquest

Attribute	Operator	Value
Current Carrier	Equals	[Target Carrier, replace per client]

This modifier bids more aggressively on leads currently insured with a carrier the client has a competitive advantage against. It must be customized per client based on pricing competitiveness and bind rate data. This is a separate concept from the targeting exclusion: the targeting rule blocks leads from the client's own carrier, while this modifier bids up on leads from a competitor the client consistently beats on price.

Critical

Always replace the placeholder with the actual target carrier for each client.

Group 7, 125%: Prime age, 25 to 40

Attribute	Operator	Value
Age	Between	25 and 40

The 25 to 40 age bracket represents a commonly desirable auto insurance demographic and serves as a reasonable starting point. These consumers have passed the high-risk young driver stage, are often growing families, and have decades of potential retention ahead. However, this range should be customized per client. Some carriers have specific data on their ideal age demographic by region; if the client provides this, for example from their carrier's internal reports, adjust the range to match their actual sweet spot.

Group 8, 50%: Low-value, single vehicle, non-homeowner

Attribute	Operator	Value
Multiple Vehicles	Equals	No
Home Owner	Equals	No

Single-vehicle non-homeowners represent the lowest-value auto insurance segment: smaller premiums, limited cross-sell potential, and higher churn rates. The 50% modifier ensures the client doesn't overpay while still remaining in the market.

Group 9, 50%: Senior drivers, age 70+

Attribute	Operator	Value
Age	More Than	70

Drivers over 70 face limited carrier options, higher premiums, and elevated loss ratios. Many carriers restrict new business for this age group. The 50% modifier reduces bid aggressiveness to reflect lower expected value.

Procedure, two stages

Follow these steps in order when setting up a new auto insurance campaign. This assumes you have already created the campaign and set the base bid and geography.

1. Configure targeting

Open the campaign in the GOAL Platform and scroll to the Targeting section. Create Targeting Group 1; all rules below go inside this single group.

Add rule: Credit Rating, Doesn't Equal, Poor, if unknown: Accept
Add rule: License Status, Equals, Active, if unknown: Accept
Add rule: Age, More Than, 25, if unknown: Accept
Add rule: Currently Insured, Equals, Yes, if unknown: Accept
Add rule: DUI, Equals, No, if unknown: Accept
Add rule: SR-22, Equals, No, if unknown: Accept
Add rule: Current Carrier, Doesn't Equal, [Client's Own Carrier], if unknown: Accept
Verify all 7 rules are within the same group (AND logic) and save

2. Configure modifiers

Scroll to the Modifiers section of the campaign and build the nine groups.

Quality assurance checklist

Before marking the campaign as fully configured, run through this checklist.

Targeting checklist

All 7 targeting rules are in a single Targeting Group (AND logic)
Credit Rating is set to "Doesn't Equal" (not "Equals")
Current Carrier exclusion uses the client's actual carrier name (not the placeholder)
All "If data is unknown" fields are set to "Accept"
Age threshold is set to "More Than 25" (not "Equal to" or "Less Than")
DUI and SR-22 are both set to "No" (not "Yes")

Modifier checklist

All 9 modifier groups are present with correct multiplier values
Group 1 (150%) has both conditions: Multiple Vehicles = Yes AND Home Owner = Yes
Groups 1, 2, 3, 8 cover all four combinations of Multiple Vehicles x Home Owner
Group 6 carrier conquest target has been customized (not left as placeholder)
Group 7 age range is 25 to 40 using the "Between" operator
Groups 8 and 9 are set to 50%, not 150%, as these are bid-down modifiers
No duplicate or conflicting modifier groups exist

Common mistakes to avoid

Mistake	Why it matters
Forgetting to replace placeholders	The Current Carrier targeting exclusion and Modifier Group 6 conquest carrier both need customization per client. Leaving defaults means incorrect bidding from day one.
Targeting rules in separate groups	All targeting conditions must be in the same group for AND logic. Separate groups create OR logic, which would accept leads matching only one condition.
Reversing operator direction	Setting Credit Rating to "Equals Poor" instead of "Doesn't Equal Poor" would accept only poor credit leads. Always double-check red vs green operator badges.
"If data is unknown" set to Reject	This blocks all leads where that field isn't populated, which can be a significant portion of traffic. Always default to Accept unless there's a specific reason to reject.
Confusing modifier percentages	150% = bid 1.5x the base (up). 50% = bid 0.5x the base (down). 100% = unchanged. Make sure bid-down modifiers are below 100%.
Overshooting source modifiers for first position	Right-pricing data should target second position, not first. Overshooting for first position on referral channels especially can result in a CPC double the market rate, exhausting the daily budget in minutes. If overshooting on any channel, search is safer due to higher intent.
Over-optimizing a brand new campaign	New campaigns have no historical data. The initial strategy is volume first, then optimize. Don't try to perfectly tune every modifier on day one. Get enough leads flowing for the client to measure results, then use real performance data to refine.

Example

An Allstate agent's campaign was set up without excluding Allstate leads, resulting in the client paying for leads who were already their customers. This is the single most damaging setup mistake and erodes client trust immediately.

Client-specific customizations

While this SOP covers the foundational setup, certain adjustments should be made per client.

Current Carrier exclusion, targeting

Replace the placeholder with the carrier or carriers the client already represents. If they write for multiple carriers, add a separate "Doesn't Equal" rule for each.

Carrier conquest target, modifier group 6

Identify which competitor's customers the client wins most often. Review bind rate data or ask the client directly.

Age thresholds

Some clients may want to adjust the 25+ targeting threshold or the 25 to 40 prime age modifier range based on their carrier's appetite.

Additional modifiers

Clients may want modifiers for credit tier, specific vehicle types, or geographic sub-regions based on competitive positioning.

Budget-aware modifier calibration

How aggressively you set modifiers depends on daily budget. A client spending $50/day needs conservative pricing to ensure enough leads flow throughout the day for a meaningful sample size. A client spending $250/day has more room for aggressive bidding. Overshooting modifiers on a small budget causes the client to hit their cap within the first hour, receive very few leads, and be unable to evaluate the platform.

Geography and volume considerations

A campaign targeting 700 zip codes in a major metro will behave differently than one targeting 50 rural zip codes. Wider geography generally means more available volume and less need for aggressive bidding to maintain lead flow. Consider the mix of geographic breadth, targeting tightness, and budget when calibrating modifiers.

Non-standard market clients

If a client specializes in non-standard or high-risk auto insurance, many targeting rules such as DUI, SR-22 and Credit Rating should be adjusted or removed entirely.

No competing campaigns

Never run two auto campaigns targeting the same zip codes for the same client. They will compete against each other, driving up costs. If you want to test different configurations, use a single campaign with different modifier groups rather than separate campaigns.

Revision history

Date	Version	Author	Changes
March 2026	1.0	Tom Panos	Initial SOP created with foundational targeting and modifier configurations.

GOAL Platform, Auto Campaign Setup SOP, version 1.0, March 2026. Internal use only.