How to Improve Lead Quality, Not Just CPL, in Google Ads: The Value-Based Bidding Playbook for B2B

Accounts implementing offline conversion tracking and value-based bidding generate 3× more pipeline at 31% lower cost per lead (Involve Digital, 2026). Let that sink in for a moment. Not 10% better. Not incrementally improved. Three times the pipeline at nearly a third less cost.

I was reviewing a B2B SaaS client’s Google Ads account last week that perfectly embodied a common problem. Their cost per lead looked great on paper: $45 against the 2026 benchmark of $66.69 (WordStream/LocaliQ, 2026). The dashboard was green. The marketing team was celebrating.

Then we looked at what happened after the form was filled out.

Their MQL-to-SQL conversion rate was 4%. Out of every 100 “leads” they celebrated, four became actual sales conversations. They weren’t generating leads. They were generating expensive noise.

Here’s the shift happening right now that most B2B marketers haven’t fully grasped: Google has introduced distinct ‘Qualified Lead’ and ‘Converted Lead’ conversion goals, replacing the single ‘Imported Lead’ category entirely. This isn’t a minor UI update. It’s Google telling advertisers explicitly: we know CPL optimization is broken, and we’re giving you the tools to fix it.

This article outlines the exact framework for transitioning from CPL optimization to lead-quality optimization in Google Ads. You’ll learn how to assign accurate values to different lead stages, integrate your CRM for offline conversion tracking, and handle the B2B-specific challenge of sales cycles that exceed Google’s 90-day GCLID window.

Why does this matter right now? AI Overviews now appear on 48% of tracked queries (BrightEdge, 2026), and paid click-through rates on those queries have dropped to 6.34%, down from 19.70% in mid-2024 (Seer Interactive, 2025). Every click costs more in this environment. You cannot afford to waste them on leads that will never close.

What Is a “Lead” in Google Ads, and Why the Definition Matters More Than You Think

The Three Types of Leads Every B2B Marketer Must Distinguish

Before we fix your lead quality problem, we need to agree on what a “lead” actually means. The confusion starts here, and it’s costing you money.

The B2B Lead Hierarchy:

• Lead: Anyone who submits a form, downloads content, or otherwise provides contact information
• MQL (Marketing Qualified Lead): A lead that meets your defined criteria for marketing engagement, such as job title, company size, or behavioral signals
• SQL (Sales Qualified Lead): A lead that sales has accepted and determined has genuine buying intent and authority
• Opportunity: An SQL with an active deal in your CRM pipeline
• Customer: Closed-won revenue

For SaaS companies with freemium or trial models, add PQL (Product Qualified Lead): a user whose product behavior signals buying intent.

Here’s the critical insight most Google Ads accounts miss: in Google Ads, a “lead” is technically any conversion action you designate as such. If you’re only counting form fills as leads, Google optimizes for form fills, regardless of whether those form fills ever become customers.

The MQL-to-SQL conversion rate typically ranges from 10% to 20% across industries (HubSpot, 2025). If your rate falls below 10%, you have a lead quality problem, not a volume problem. Throwing more budget at Google Ads will simply give you more expensive garbage.

Example scenario: A B2B tech company generates 100 leads at $50 CPL, spending $5,000 total. With a 10% MQL-to-SQL conversion rate (HubSpot, 2025), that’s 10 SQLs at $500 each. With a 20% rate using the same spend, it’s 20 SQLs at $250 each. Same spend, same volume of raw leads, but wildly different economics.

Google’s New Lead Categories: Qualified Lead vs. Converted Lead

Google’s recent distinction between “Qualified Lead” and “Converted Lead” goal types reflects a fundamental shift in how the platform thinks about B2B lead generation.

Qualified Lead: A lead that meets your qualification criteria, equivalent to an MQL or SQL in your CRM. This signals to Google that the lead progressed beyond initial contact.

Converted Lead: A lead that became a customer or reached the opportunity stage. This is the ultimate signal of lead quality.

Using these specific goal types unlocks Google’s lead funnel report feature, giving you visibility into how leads progress through your sales process. You can finally see which campaigns, keywords, and audiences generate leads that actually convert to revenue, not just leads that fill out forms.

The setup requirement is non-negotiable: both goal types require CRM integration and offline conversion tracking. No CRM connection means no access to these features, and no ability to optimize for what actually matters.

We’ve seen clients unlock 30%+ efficiency gains simply by giving Google’s algorithm accurate signals about which leads actually converted to opportunities. The machine learning works remarkably well, but only if you feed it the right data.

The NAV43 Lead Quality Hierarchy

Stage	Definition	Typical Conversion Rate to Next Stage	Relative Value
Raw Lead	Form fill, demo request	25-40% to MQL	1×
MQL	Meets marketing criteria	10-20% to SQL (HubSpot, 2025)	3-5×
SQL	Sales accepted, qualified	15-25% to Opportunity	10-15×
Opportunity	Active deal in pipeline	20-40% to Customer	25-50×
Customer	Closed-won	–	Full deal value

The CPL Lie: How Optimizing for Cost Per Lead Destroys Pipeline

The Math That Should Terrify You

CPL optimization sends a clear signal to Google’s algorithm: find me the cheapest people willing to fill out a form. The algorithm is excellent at this task. It will find you form-fillers all day long.

The problem is that the cheapest form-fillers are almost always the lowest-quality prospects. They’re the people who fill out every form they see, who have no buying authority, who work at companies that would never purchase your product.

Consider two scenarios with identical spend:

Scenario A (CPL Optimized):
– 100 leads at $50 CPL = $5,000 spend
– 5% close rate
– $10,000 average contract value
– Revenue: $50,000
– ROAS: 10×

Scenario B (Quality Optimized):
– 50 leads at $100 CPL = $5,000 spend
– 20% close rate
– $10,000 average contract value
– Revenue: $100,000
– ROAS: 20×

Scenario B has double the CPL, but generates double the revenue from the same ad spend. If you’re only looking at cost per lead, Scenario A appears to be “winning,” but it’s actually costing you $50,000 in lost revenue.

This problem compounds in B2B specifically. B2B tech CPCs averaged $8.86 in 2024, significantly higher than all-industry averages (Firebrand, 2024-2025). You’re already paying a premium for B2B clicks. Wasting them on low-quality leads that never convert is doubly expensive.

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CPL vs. Pipeline Value Comparison

Metric	CPL-Optimized Campaign	Quality-Optimized Campaign
Total Spend	$5,000	$5,000
Leads Generated	100	50
Cost Per Lead	$50	$100
Lead-to-Close Rate	5%	20%
Customers Won	5	10
Revenue (@ $10K ACV)	$50,000	$100,000
Cost Per Customer	$1,000	$500
ROAS	10×	20×

The Smart Bidding Feedback Loop Problem

Google’s Smart Bidding algorithms optimize toward whatever conversion signals you provide. This is both their greatest strength and their biggest pitfall for B2B advertisers.

If you only signal “form fill” as your conversion action, Google optimizes for form fills. The algorithm has no visibility into what happens after the form submission. It doesn’t know that 90% of your leads ghost your sales team or that only leads from enterprise companies ever close.

This creates a destructive feedback loop:

1. You optimize for CPL
2. Google finds low-quality leads (they’re cheapest)
3. Low-quality leads don’t convert to sales
4. No revenue signal returns to Google
5. Google keeps finding more low-quality leads
6. Your pipeline suffers while your CPL looks great

Breaking this loop requires offline conversion tracking. When you feed closed-won and closed-lost data back to Google, you teach the algorithm what a good lead actually looks like. The algorithm can then identify patterns: which user characteristics, search queries, times of day, and devices correlate with leads that eventually become customers.

The volume threshold challenge complicates this for many B2B advertisers. Smart Bidding needs approximately 30+ conversions per month to optimize effectively. If your sales cycle is long and your deal volume is low, you may not generate enough “customer” conversion events for the algorithm to learn from. This is precisely why importing earlier funnel stages, such as MQLs and SQLs, as conversion events with appropriate values is essential.

Value-Based Bidding: The Framework That Delivers 3× More Pipeline

What Value-Based Bidding Actually Means

Value-based bidding represents a fundamental shift in how you communicate with Google’s algorithm. Instead of telling Google, “get me leads at $50 each,” you tell Google, “this lead type is worth $500, this one is worth $2,000, and this one is worth $35,000. Optimize for total value.”

The strategic shift moves from Maximize Conversions / Target CPA to Maximize Conversion Value / Target ROAS.

Brands switching from target CPA to target ROAS have seen a median 14% increase in conversion value at similar ad spend (Google/Launchcodex, 2026). This improvement comes purely from giving the algorithm better information about what you actually want.

Why does this work? Google’s algorithm is sophisticated enough to identify patterns in how users convert into high-value versus low-value leads. It can learn that users searching at 10 AM on Tuesdays from enterprise IP addresses convert at 4× the rate of users searching at 11 PM on weekends from personal devices.

But the algorithm can only learn these patterns if you provide the value data. Without offline conversion tracking and value assignment, you’re asking a brilliant optimization engine to drive blindfolded.

The Lead Value Assignment Formula

Assigning accurate values to your conversion actions is more art than science, but this formula provides a solid foundation:

Conversion Value = Average Deal Size × Profit Margin × Lead-to-Close Rate

Worked example:

• Average deal size: $50,000
• Profit margin: 70%
• Lead-to-close rate: 5%
• Conversion Value = $50,000 × 0.70 × 0.05 = $1,750

This tells Google that each raw lead is worth $1,750 in expected value. But we can get more sophisticated by assigning tiered values for different funnel stages:

Tiered Value Assignment:

Funnel Stage	Value Calculation	Example Value
Raw Lead (form fill)	Placeholder value or deal size × margin × full-funnel conversion rate	$100-$500
MQL	Deal size × margin × MQL-to-close rate	$1,500-$2,500
SQL	Deal size × margin × SQL-to-close rate	$5,000-$8,000
Opportunity	Deal size × margin × opportunity-to-close rate	$15,000-$25,000
Closed-Won	Actual revenue	$50,000

The critical insight here is that you don’t need perfect values. You need directionally correct relative values. What matters is that an SQL is worth 5× an MQL, not whether the exact dollar figure is $7,500 or $8,200.

The NAV43 Lead Value Calculator

Use this template to calculate your own conversion values:

Step 1: Gather your data
– Average deal size: $_
– Profit margin: _%
– Lead-to-MQL rate: _%
– MQL-to-SQL rate: _%
– SQL-to-Opportunity rate: _%
– Opportunity-to-Close rate: _%

Step 2: Calculate expected values
– Raw Lead Value = Deal Size × Margin × (Lead-to-MQL × MQL-to-SQL × SQL-to-Opp × Opp-to-Close)
– MQL Value = Deal Size × Margin × (MQL-to-SQL × SQL-to-Opp × Opp-to-Close)
– SQL Value = Deal Size × Margin × (SQL-to-Opp × Opp-to-Close)
– Opportunity Value = Deal Size × Margin × Opp-to-Close Rate

Step 3: Validate ratios
Ensure each stage is worth 2-5× as much as the previous stage. Adjust the ratios if they seem off based on your experience.

Setting Up Value-Based Bidding in Google Ads

Once you have your values calculated, implementation follows a clear sequence:

Step 1: Ensure offline conversion tracking is implemented and functioning. This is the non-negotiable foundation. Skip to the next section if you haven’t set this up yet.

Step 2: Assign conversion values to each conversion action in Google Ads. Navigate to Goals > Conversions > Edit conversion settings. Enter your calculated values for each action.

Step 3: Switch your bidding strategy from Target CPA to Target ROAS (or Maximize Conversion Value if you want Google to find the optimal ROAS automatically).

Step 4: Set a realistic Target ROAS based on your value calculations. If your average lead value is $1,750 and you’re willing to pay $250 per lead, your target ROAS is 7:1 (700%).

Step 5: Allow 2-4 weeks for the learning period before evaluating performance. Smart Bidding needs time to calibrate to the new optimization target.

Practitioner warning: Don’t switch bidding strategies during your highest-volume months. The learning period will temporarily reduce performance as the algorithm recalibrates. Pick a quieter period for the transition, and communicate with stakeholders that short-term metrics may dip before improving.

Offline Conversion Tracking: The Non-Negotiable Foundation for Lead Quality Optimization

Why Most B2B Accounts Are Flying Blind

Without offline conversion tracking, Google only sees the form fill. It never learns whether that lead became a customer, scheduled a demo, or immediately marked your email as spam. You’re asking Google to optimize for the pipeline while only showing it the tip of the iceberg.

Advertisers using first-party data alongside GCLIDs saw a median 10% increase in conversions compared to GCLID-only tracking (Google Ads Help, 2026). This improvement comes from better match rates and more complete attribution data.

The deprecation reality makes this urgent: GCLID-only import is now considered legacy. Google’s API deprecation for older import methods is scheduled for June 2026. Enhanced Conversions for Leads is the new standard, and if you’re still manually uploading CSVs with GCLIDs, you’re using a method Google is actively sunsetting.

For more on connecting your CRM data to advertising platforms, our guide on HubSpot and Google Ads closed-loop reporting provides step-by-step implementation instructions.

Enhanced Conversions for Leads: The New Standard

Enhanced Conversions for Leads uses first-party customer data, specifically email and phone number hashed and matched to Google’s records, rather than relying solely on GCLIDs.

Why Enhanced Conversions outperforms GCLID-only tracking:

• Cross-device attribution: Works even when a user converts on a different device than they clicked from
• Better privacy compliance: Uses hashed first-party data rather than persistent identifiers
• Higher match rates: Email-based matching succeeds more often than click ID tracking
• No expiration window: Unlike GCLIDs, email-based matching doesn’t expire after 90 days

Set up requirements:

1. Google Ads account with conversion tracking enabled
2. CRM that can export lead data with email/phone and conversion timestamps
3. Google Ads API access or a connector tool (HubSpot native integration, Salesforce connector, or Zapier)

HubSpot integration example: HubSpot’s native Google Ads integration can automatically sync lifecycle stage changes back to Google Ads as offline conversions. When a contact moves from MQL to SQL to Customer, each stage triggers a conversion event with its assigned value. No manual exports, no GCLID management, just continuous closed-loop data flow.

Our LinkedIn and HubSpot integration guide covers similar principles for connecting ad platforms with your CRM.

Enhanced Conversions for Leads Setup Checklist

Account Requirements:
– [ ] Google Ads conversion tracking enabled
– [ ] Enhanced Conversions enabled in account settings
– [ ] Customer data policy acknowledged

CRM Requirements:
– [ ] CRM can capture and store GCLID or user email at lead creation
– [ ] CRM tracks lifecycle stage changes with timestamps
– [ ] CRM can export or sync data via API

Data Requirements:
– [ ] Email address captured on all lead forms
– [ ] Phone number captured (optional but improves match rates)
– [ ] Lifecycle stage values mapped to Google Ads conversion actions
– [ ] Conversion values assigned to each stage

Integration Setup:
– [ ] Native integration configured (HubSpot, Salesforce) OR
– [ ] Zapier/webhook automation built OR
– [ ] Custom API integration developed
– [ ] Test conversions imported and verified in Google Ads

Validation:
– [ ] Conversion events appearing in Google Ads within 24-48 hours
– [ ] Attribution window set appropriately for sales cycle length
– [ ] Values importing correctly for each conversion type

Handling Long B2B Sales Cycles: The 90-Day GCLID Problem

Here’s the challenge that trips up many enterprise B2B advertisers: GCLIDs expire after 90 days. If your lead converts to a customer 120 days after clicking your ad, the GCLID-based attribution is lost. For enterprise sales cycles that commonly run 6-12 months, this creates a significant attribution gap.

Solution 1: Use Enhanced Conversions for Leads

Email-based matching doesn’t rely on GCLID expiration. As long as you capture the user’s email at form fill, you can import the conversion months later and still get attribution.

Solution 2: Import Earlier Funnel Stages

Even if a closed-won happens outside the 90-day window, earlier stages likely don’t. Import MQL (typically 30 days), SQL (60 days), and Opportunity Created (75 days) as conversion events with appropriate values.

Solution 3: Use Proxy Values for Optimization

If your average time-to-MQL is 15 days and time-to-SQL is 45 days, Google can optimize effectively toward SQLs even if it never sees the closed-won. The key is to ensure your SQL value accurately reflects the expected downstream revenue.

We had an enterprise client with a 9-month average sales cycle. We imported MQL (on day 30), SQL (on day 60), and Opportunity Created (on day 75) as conversion events. Google never saw the closed-won event, but it learned to optimize for leads that reached the Opportunity stage. Since the Opportunity-to-Close rate was relatively consistent at 35%, optimizing for Opportunities effectively meant optimizing for revenue.

The Long Sales Cycle Workaround

For B2B companies with 90+ day sales cycles:

1. Map your typical timeline: How many days from click to MQL? MQL to SQL? SQL to Opportunity?
2. Identify which stages fall within 90 days: These are your primary optimization targets.
3. Assign proxy values: Calculate the expected revenue for each stage and assign it.
4. Import all qualifying stages: Don’t just import the final conversion. Import every stage that reliably predicts eventual revenue.
5. Enable Enhanced Conversions: Email-based matching removes the 90-day limitation entirely for future conversions.

Campaign-Level Tactics That Improve Lead Quality Without Sacrificing Volume

Quality Score and Its 27% CPL Impact

While value-based bidding addresses the strategic problem, Quality Score optimization addresses the tactical reality of paying less for better clicks.

Improving Quality Score from 5 to 8 reduces cost per lead by approximately 27% (LeadGen Economy/Lionelz, 2026). This isn’t about vanity metrics. Lower CPCs mean more budget for high-intent keywords, which directly improves lead quality.

Quality Score has three components:

1. Expected CTR: How likely users are to click your ad
2. Ad Relevance: How closely your ad matches search intent
3. Landing Page Experience: How useful and relevant your landing page is

Actionable improvements:

Ad Copy:
– Match exact search intent in your headline
– Use the primary keyword in Headline 1
– Address the specific pain point the searcher is trying to solve
– Include proof points or differentiation in descriptions

Landing Pages:
– Create dedicated landing pages per ad group, not generic “Contact Us” pages
– Match the landing page headline to the ad headline
– Minimize distractions and competing CTAs
– Ensure mobile responsiveness and fast load times

Keyword Selection:
– Prune low-intent, high-volume keywords that drain budget
– Use exact match for your highest-value terms
– Move to phrase match only after establishing baseline performance

For deeper technical optimization guidance, our technical SEO audit checklist covers page speed and user experience factors that impact Quality Score.

Keyword Strategy for Lead Quality

Not all keywords are created equal in terms of lead quality. The hierarchy matters:

Bottom-funnel keywords (buy, hire, pricing, demo, quote) signal immediate buying intent. These users are actively evaluating solutions.

Mid-funnel keywords (comparison, vs, reviews, alternatives) indicate a user in active research mode. They’re closer to a decision than discovery.

Top-funnel keywords (how to, what is, guide, tutorial) may drive volume but rarely drive a qualified pipeline. These users are learning, not buying.

B2B-specific insight: Target job title and company size modifiers. A search for “[Software] for enterprise” signals a higher-value deal prospect than a generic “[Software].” Someone searching “HR software for 500+ employees” has a different intent than someone searching “free HR tools.”

Negative keyword hygiene is essential:

Add these as account-level negatives for B2B lead gen:
– Free, cheap, discount, coupon
– Jobs, salary, careers, hiring (unless you’re recruiting)
– DIY, homemade, template
– Login, support, customer service (existing customers, not prospects)
– Download, PDF, tutorial (often indicates research, not buying intent)

Example: A B2B HR software client reduced raw lead volume by 30% but increased SQL rate by 85% by shifting budget from generic “HR software” to “enterprise HR software pricing” and “HR software for 500+ employees.” Total SQLs increased while total spend remained flat.

Audience Layering and Exclusions

Strategic audience targeting improves lead quality by ensuring your ads reach the right people, not just anyone who types your keyword.

First-party audiences:
– Upload customer lists to create lookalike audiences
– Exclude current customers to avoid wasting budget on existing relationships
– Create audiences from high-value customers specifically for lookalike modeling

Essential exclusions:
– Current customers and active opportunities
– Competitors (if identifiable)
– Job seekers and career-oriented traffic
– Students and academic domains
– Geographic regions you don’t serve

In-market audiences for B2B:
Layer B2B-relevant in-market audiences on top of keyword targeting:
– Business Services
– Enterprise Software
– Business Financial Services
– Technology categories relevant to your product

Observation vs. targeting mode:
Start with observation mode to gather data on which audiences perform best. Run for 2-4 weeks, then shift to targeting mode for audiences that significantly outperform baseline metrics.

The Performance Max asset group strategy guide covers additional audience segmentation tactics for lead generation campaigns.

AI-Qualified Call Leads: Improving Phone Lead Quality Without CRM Integration

Not all lead quality improvements require CRM integration. Google’s AI-Qualified Calls feature provides a lower-lift option for businesses that generate phone leads.

What it is: Google’s AI analyzes call recordings to determine if a call represented a qualified sales conversation or a low-value interaction like a customer service inquiry or wrong number.

How it works:
1. You enable call recording consent in your Google Ads account
2. Google’s AI listens for conversation patterns that indicate buying intent
3. Calls are classified as “qualified” or “not qualified” based on conversation content
4. You can then optimize bidding toward qualified calls specifically

When to use AI-Qualified Calls:
– Your business generates significant phone lead volume
– You don’t yet have CRM integration in place
– Your sales calls follow predictable patterns that AI can learn

Limitations:
– Requires call recording and user consent
– Works best with consistent call scripts and conversation patterns
– Doesn’t capture full downstream conversion data like closed revenue
– Not a replacement for offline conversion tracking, but a useful interim solution

For service businesses that rely heavily on phone leads, this feature can meaningfully improve lead quality with minimal technical implementation.

Common Pitfalls When Optimizing for Lead Quality

Pitfall 1: Cutting Volume Below Smart Bidding Thresholds

In the pursuit of quality, some advertisers tighten targeting so aggressively that conversion volume drops below 30 per month. At this point, Smart Bidding loses the data density it needs to optimize effectively.

The fix: Balance quality improvements against volume requirements. If tightening targeting drops you below the threshold, consider expanding to include additional high-value audience segments rather than returning to broad, low-quality targeting.

Pitfall 2: Assigning Arbitrary Values Without Data

Guessing at conversion values undermines the entire value-based bidding approach. If you assign an MQL value of $1,000 when it’s actually worth $500, you’ll overpay for leads across the board.

The fix: Calculate values from actual CRM data. Even if your data is imperfect, directionally correct values based on real conversion rates outperform guesswork.

Pitfall 3: Switching Bidding Strategies Without a Learning Period

Changing from CPA to ROAS bidding triggers a learning period where performance typically dips. Advertisers who panic and revert after a week never see the long-term improvements.

The fix: Commit to 2-4 weeks of learning time. Communicate with stakeholders in advance that short-term metrics may decline. Set calendar reminders to evaluate performance only after the learning period ends.

Pitfall 4: Ignoring Performance Max Lead Quality Issues

Performance Max campaigns can generate high lead volume from Display, Gmail, and Discover placements, but these leads often convert at far lower rates than Search-origin leads.

The fix: Implement offline conversion tracking before scaling Performance Max. Use the PMax lead gen checklist to ensure proper measurement and exclusions are in place.

Pitfall 5: Optimizing for Single-Touch Attribution

Assigning all credit to the last click before conversion ignores the reality of B2B buying journeys that involve multiple touchpoints over weeks or months.

The fix: Use data-driven or position-based attribution models in Google Ads. Our HubSpot attribution reporting guide covers the configuration of multi-touch attribution.

Conclusion and Key Takeaways

The shift from CPL optimization to lead quality optimization represents one of the highest-impact changes a B2B marketer can make in their Google Ads program. The math is compelling: 3× more pipeline at 31% lower cost per lead is achievable with the right foundation.

Key takeaways:

• CPL alone is a vanity metric. A $50 lead that never converts costs more than a $100 lead that closes. Optimize for pipeline value, not form-fill volume.
• Offline conversion tracking is non-negotiable. Without CRM integration, Google’s algorithm optimizes blindly. Enhanced Conversions for Leads is the new standard, with the GCLID-only import to be deprecated in June 2026.
• Value-based bidding outperforms CPA bidding. Brands switching to Target ROAS see a median 14% increase in conversion value at similar spend.
• Long sales cycles require proxy values. Import earlier funnel stages (MQL, SQL, Opportunity) that fall within 90 days and assign values based on expected downstream revenue.
• Quality Score still matters. Improving from 5 to 8 reduces CPL by approximately 27%, freeing up budget for high-intent keywords.

Next Steps

If you haven’t started: Implement Enhanced Conversions for Leads this week. This is the foundation on which everything else is built. Connect your CRM to Google Ads using native integrations (HubSpot, Salesforce) or Zapier workflows.

If you have offline tracking but not value-based bidding: Calculate your lead values using the NAV43 Lead Value Calculator formula. Assign values to each conversion action in Google Ads. Plan your bidding strategy transition for a low-volume week.

If you’re already using value-based bidding: Audit your conversion values quarterly. As deal sizes and conversion rates evolve, your values should update accordingly. Layer additional audience exclusions to further improve quality.

Ready to accelerate your lead quality improvements? Get your free growth plan from NAV43. We’ll audit your current Google Ads configuration, identify the highest-impact opportunities to optimize lead quality, and provide a roadmap for implementation.

Stop celebrating cheap leads that never close. Start building a Google Ads program that generates a pipeline.