Performance Max for Lead Generation: Why Most Accounts Underperform (And the Offline Conversion Fix That Changes Everything)

Here’s a stat that should stop every B2B marketer mid-scroll: top-quartile lead-generation programs achieve a cost per lead of $84. Bottom quartile? $397. That’s a 4.7x spread between the best and the rest, according to HubSpot’s State of Marketing 2026 report.

Same platform. Same campaign type. Same Google Ads interface. Wildly different results.

I was reviewing a Performance Max account last week that perfectly embodied this problem. The marketing director was celebrating a 40% increase in form fills. The sales team was ready to mutiny because lead quality had cratered. Both were right about their numbers, but only one truth mattered: the pipeline was down.

Google claims Performance Max delivers 22% more conversions at the same CPA (Google Internal Data, 2026), and over 1 million advertisers now use it globally (Google, 2025). Those numbers are real. But they obscure a fundamental truth that separates lead generation from ecommerce: for an online store, a conversion IS the sale. For lead generation, a conversion is the beginning of a sales process that might take weeks or months.

This difference creates what I call the Feedback Loop of Doom: without proper data flowing back to Google, Performance Max optimizes for the wrong signals, creating a self-reinforcing cycle of garbage leads. The algorithm learns to find more of what you’re measuring, even if that measurement has nothing to do with revenue.

This article delivers the exact framework NAV43 uses to make performance max for lead generation actually work. You’ll get CRM integrations, offline conversion-tracking setup, and measurement systems that separate top performers from everyone else. No theory. No Google talking points. Just the playbook.

Is Performance Max Actually Good for Lead Generation? (The Honest Answer)

Yes – but only if you solve the data problem that Google won’t tell you about.

Let me be direct: Google’s 22% improvement stat (Google Internal Data, 2026) is misleading for lead-generation accounts. That figure includes brand traffic inflation and primarily reflects ecommerce results where purchase data flows back to Google automatically. For B2B lead gen, the picture is far murkier.

An Adalysis study of 3,300 campaigns found that Search campaigns typically have higher conversion rates when competing for the same search terms as Performance Max. The algorithm’s strength, its ability to find conversions across Google’s entire network, becomes a weakness when it can’t distinguish between a qualified prospect and a job seeker filling out your contact form.

The key principle we follow at NAV43: Performance Max should complement dedicated Search campaigns, not replace them. Search captures high-intent users actively seeking your solution. PMax extends your reach to audiences you might not otherwise reach. Stack them together strategically, and you get the best of both worlds.

But here’s the threshold reality most advertisers miss: Performance Max needs 30+ conversions per month to optimize effectively (YeezyPay, 2026). Accounts below this are essentially feeding the system guesses. If you’re a B2B company generating 15 leads per month, you’re asking Google’s algorithm to learn patterns from a sample size that would make any statistician wince.

Consider a B2B SaaS company selling a $50,000 annual contract. Their conversion path looks like this: form fill → discovery call → demo → proposal → negotiation → closed deal. That journey might span 60-90 days. If they generate 20 form fills per month, the algorithm is optimizing with incomplete lead data that won’t reveal their true value for months.

The Lead Gen vs. Ecommerce Problem Nobody Talks About

When someone buys a pair of shoes on an e-commerce site, Google immediately knows: this user converted, the purchase was $150, and the transaction is complete. That’s a clean, verifiable success signal the algorithm can use to find more users with similar characteristics.

Lead gen form fills? Google cannot tell the difference between:
– A marketing director researching solutions for a genuine business need
– A competitor doing reconnaissance
– A job seeker looking for openings
– A bot scraping your form for email addresses
– A college student doing a class project

Without your help, every form fill looks identical to Google’s algorithm. They all count as “conversions.” They all tell the system it made a good decision.

The attribution problem compounds this. Without enhanced conversions in 2026, attribution is 25-35% incomplete due to privacy restrictions (YeezyPay, 2026). That means even if you’re tracking form fills correctly, you’re missing a third of the picture.

Here’s the result: PMax optimizes for form fills, not revenue. If spam bots fill forms faster than real prospects, PMax learns to find more spam bots. If job seekers convert at higher rates than actual buyers, PMax targets more job seekers. The algorithm is doing exactly what you asked by maximizing conversions, but those conversions don’t correlate with business outcomes.

And the data backs this up: 79% of marketing leads never convert due to poor follow-up or nurturing (FreJun, 2025-2026). That’s not all, lead quality – some of it is the sales process. But a significant portion never had a chance because they weren’t qualified in the first place.

The Feedback Loop of Doom (Why Your PMax Campaign Gets Worse Over Time)

The Feedback Loop of Doom occurs when Performance Max optimizes for conversion quantity rather than conversion quality. Without offline conversion data telling Google which form fills actually became customers, the algorithm makes increasingly confident bets on increasingly wrong signals.

Here’s how the cycle works:

1. Form fill occurs – Someone completes your lead form
2. Google counts a conversion – The algorithm registers a “success”
3. PMax finds more similar users – The system targets audiences with characteristics matching that converter
4. Those users are also low quality – Because the original signal wasn’t meaningful
5. More form fills occur – CPL might even improve
6. Sales team gets worse leads – Pipeline quality collapses
7. Repeat – Each cycle reinforces the pattern

This loop is self-reinforcing because every “conversion” validates Google’s targeting decisions. The algorithm becomes more confident in its bad learning. Your CPL looks stable or even improves, while your MQL-to-SQL rate craters.

The data confirms this is happening at scale: MQL-to-SQL conversion rates compressed from 13% in 2024 to 9.8% in 2026 (Forrester and Demand Gen Report, 2026). That’s a 24% decline in lead qualification rates across the industry. Some of that is economic factors. A meaningful chunk is algorithms optimizing for volume over quality.

Let me paint you a picture. Imagine a B2B SaaS company running Performance Max for lead generation. In month one, they generate 100 form fills at a $50 CPL. Solid start. In month three, they’re generating 150 form fills at a $40 CPL. The marketing dashboard looks fantastic.

But here’s what sales sees: month one, 25 of those 100 leads became SQLs (25% qualification rate). Month three, only 20 of 150 leads qualified (13% qualification rate). Cost per qualified lead went from $200 to $300 – a 50% increase – while the marketing report showed improvement.

This is failure disguised as success.

Contrast this with what happens when you feed qualified lead data back to Google. When you tell the algorithm that lead #47 became an SQL worth $500, and lead #92 became a customer worth $25,000, the system learns which form fills actually matter. It adjusts targeting to find more users who resemble your actual customers, not just your fastest form-fillers.

The NAV43 Feedback Loop Diagnostic

Three warning signs your PMax campaign is trapped in the doom loop:

1. CPL is stable or improving, but sales complains about lead quality – This is the classic symptom. Marketing metrics look good while pipeline metrics deteriorate.
2. Form fills increasing but MQL-to-SQL rate declining – If your conversion volume goes up but your qualification rate goes down, the algorithm is optimizing for the wrong signal.
3. You can’t name the last PMax lead that became a customer – If you can’t trace a closed deal back to a Performance Max campaign, you have no feedback mechanism. The algorithm is flying blind.

The Offline Conversion Fix – How to Make Performance Max Actually Work

Offline conversion tracking is not optional for lead gen PMax. It’s the differentiator between success and failure.

Here’s what offline conversion tracking does: it feeds sales outcomes – MQLs, SQLs, opportunities, closed deals – back to Google so the algorithm learns what a GOOD lead looks like, not just what a FAST conversion looks like.

Think of it as giving Google a report card on its homework. Without it, the algorithm only knows which ads generated clicks and which clicks became form fills. With offline conversion tracking, the algorithm learns which ads generated form fills that became pipeline, and which became revenue.

The concept is the assignment of conversion value at different sales stages. A form fill might be worth $1 to your business. An MQL might be worth $50. An SQL might be worth $250. A closed deal might be worth $10,000. When you pass these values back to Google, the algorithm optimizes for total value, not just conversion count.

For sales cycles exceeding 7 days, which describes virtually every B2B sale, CRM integration and offline conversion imports are essential. Google optimizes on incomplete data without it.

The payoff is significant: companies that excel at lead nurturing generate 50% more sales-ready leads at 33% lower cost (Demand Gen Report/Forrester, 2026). That’s what happens when your acquisition channel learns from your sales outcomes.

CRM Integration Workflows That Actually Work

This is where most competitor content falls short, as they tell you to “set up offline conversion tracking” without explaining the actual workflow. Let me fix that.

HubSpot Workflow:

1. Add a hidden field to your forms for GCLID capture – The Google Click ID is what links the original ad click to the eventual sale
2. Configure the form to pass GCLID to a custom property – Store it on the contact record where it persists through the sales cycle
3. Create lifecycle stage triggers – When a contact moves to MQL, SQL, or Customer status, fire a workflow
4. Use Operations Hub to push conversions to Google – The native integration can send offline conversions automatically when lifecycle stages change
5. Map conversion values to each stage – Assign dollar values that reflect the true worth of each stage transition

Salesforce Workflow:

Salesforce has a native Google Ads integration that simplifies the process. Map your lead status values to conversion actions in Google Ads. When a lead progresses through your pipeline, the integration automatically reports the conversion. The key is to ensure GCLID capture occurs at the Web-to-Lead level and persists through lead-to-account conversion.

Pipedrive Workflow:

Pipedrive requires Zapier or a native integration to connect with Google Ads. Create a custom field for GCLID, then build Zaps that fire when deals reach specific stages. The complexity is higher here, but the principle remains: capture the click ID, preserve it through the pipeline, and report conversions when stages change.

CRM	Native Google Ads Integration	GCLID Tracking Method	Offline Import Complexity	Recommended For
HubSpot	Yes (Operations Hub)	Hidden form field	Medium	Mid-market B2B
Salesforce	Yes (native)	Web-to-Lead field	Low-Medium	Enterprise
Pipedrive	Via Zapier	Custom field + Zap	Medium-High	SMB sales teams

The critical point: GCLID capture must occur upon form submission and persist throughout the entire CRM journey. If your sales team manually enters leads or the GCLID field is overwritten, your offline conversion data breaks down.

For situations where GCLID isn’t available, perhaps the user’s browser blocked tracking, or they came through a non-Google touchpoint first, enhanced conversions for leads use hashed email matching to connect the dots. It’s a backup system, but you need both mechanisms in place for complete coverage.

The Conversion Value Assignment Framework

Assigning different values to conversion stages tells Google’s algorithm that a closed deal matters more than a form fill. Without this, every conversion gets treated equally.

Here’s a sample value assignment framework for B2B lead gen:

• Form fill: $1 (or $0 – track it, but don’t let PMax optimize on this alone)
• MQL: $25-50
• SQL: $100-250
• Opportunity created: $500-1,000
• Closed won: Actual deal value

The question is: how do you calculate these values for your specific business?

NAV43 Conversion Value Calculator

Formula: Value at Stage = (% conversion to next stage) × (Value at next stage)

Example calculation:
– Average deal size: $10,000
– SQL to Close rate: 20%
– MQL to SQL rate: 40%
– Form fill to MQL rate: 30%

Working backwards:
– Closed Won value: $10,000 (actual)
– SQL value: 0.20 × $10,000 = $2,000
– MQL value: 0.40 × $2,000 = $800
– Form fill value: 0.30 × $800 = $240

These are your baseline values. Adjust based on segment-specific data if you have it.

Google needs this value data to optimize for revenue, not just lead volume. When you tell the algorithm that an SQL is worth $2,000 and a form fill is worth $240, it learns to prioritize quality over quantity, which is exactly what you want for lead generation.

Performance Max Campaign Setup for Lead Gen (The Right Way)

The 2026 Performance Max updates transformed the platform from a frustrating black box to something you can actually steer. Google introduced first-party audience exclusions, full audience demographic reporting, asset experiments, and campaign-level negative keywords, which are features that address the control issues that plagued earlier versions.

These features matter because they let you tell Google what you don’t want, not just what you do want. That’s essential for lead generation, where avoiding bad traffic is as important as finding good traffic.

Let me walk you through the essential setup elements specific to lead gen.

Budget Reality Check – Is $20 a Day Enough?

It depends entirely on your industry’s CPC.

Here’s the math: $20/day = $600/month. If your average CPC is $5, that’s only 120 clicks per month. If your form conversion rate is 5%, that’s 6 leads per month, which is well below the 30+ conversion threshold PMax needs for effective optimization.

The average CPC for Performance Max campaigns is $0.68, compared to the Google Ads average of $0.85 (Lebesgue, 2025). But that’s skewed heavily by ecommerce and local services. B2B keywords in competitive industries like legal services can cost $47 per click, while local services might run $1-2 per click.

The average cost per lead in Google Ads is $70.11 (WordStream/LocaliQ, 2025), but that varies wildly by industry. The median B2B cost-per-lead climbed to $213 in 2026 (HubSpot) – nearly triple the overall average.

NAV43’s recommendation: most B2B lead gen needs $50-100/day minimum to gather meaningful optimization data. Anything less and you’re asking the algorithm to find patterns in noise.

Monthly Budget	Assumed CPC	Est. Clicks	Est. Leads (5% CVR)	Viable for PMax?
$600 ($20/day)	$2	300	15	Marginal
$600 ($20/day)	$5	120	6	No
$1,500 ($50/day)	$5	300	15	Marginal
$3,000 ($100/day)	$5	600	30	Yes

Note the June 2026 budget pacing change and its implications for spend projections – Google’s updated algorithm distributes budget differently across the month, which affects how quickly you accumulate conversion data.

Asset Groups, Signals, and Placements That Work

Audience signals in Performance Max are suggestions, not targeting restrictions. They guide the algorithm toward certain user characteristics, but PMax will explore beyond your signals if it finds converting users elsewhere.

That’s why first-party audience exclusions matter so much. Upload your customer lists to exclude current customers from acquisition campaigns. Use CRM segments to create lookalike audiences from closed-won deals, not just all form fills. The difference in signal quality is dramatic. You’re telling Google to find more people like your actual customers, not more people like everyone who ever filled out your form.

Performance Max placements span Google’s entire network: Search, Display, YouTube, Gmail, Maps, and Discover. Your ads show everywhere the algorithm thinks they’ll convert. This is powerful for reach but concerning for brand safety and lead quality.

Create a Performance Max tracking template to monitor where spend is going. While Google’s reporting has improved, you still need to actively review placement performance and use exclusions where necessary. If 40% of your budget is going to Display placements that generate form fills but zero SQLs, that’s actionable intelligence.

For assets, meet or exceed the minimum requirements:
– 5+ headlines (use different value propositions and approaches)
– 5+ descriptions (vary length and specificity)
– 5+ images (mix lifestyle, product, and text-overlay styles)
– At least 1 video (even a simple one beats having none)

The algorithm needs a variety to test. Starve it of assets, and you limit its ability to find what works.

Here’s an example of effective audience signal usage: instead of targeting “all form fills” as your customer match audience, create a segment of only your closed-won deals from the past 24 months. Upload that list. Tell Google: find me more people like these specific accounts. The resulting targeting will be dramatically tighter than optimizing on form-fill lookalikes.

Spam and Bot Prevention for Lead Gen PMax

This is a major content gap in most Performance Max guides – nobody talks about spam prevention, but it’s critical for lead gen.

Here’s why PMax lead gen attracts more spam: the algorithm’s broad targeting combined with form fill optimization creates a magnet for bots and low-quality submissions. Every spam form fill teaches Google that its targeting worked. The system finds more spam sources. The doom loop accelerates.

Specific prevention tactics:

reCAPTCHA v3 implementation – The invisible, score-based version doesn’t interrupt the user experience but assigns a risk score to every submission. Set your threshold aggressively – it’s better to lose a few real leads than train Google on bot conversions.

Honeypot fields – Add a hidden form field that only bots fill out. Legitimate users never see it. If it contains data, reject the submission entirely before it hits your CRM.

Qualifying questions that require thought – Don’t just ask for name and email. Add questions like “What’s your current solution for X?” or “What’s your biggest challenge with Y?” Bots struggle with open-ended questions, and legitimate prospects will answer.

Phone number validation – Require phone numbers and validate the format. Better yet, use a phone verification service that checks whether the number is real and reachable.

Time-on-page minimums – If someone submits a form within 3 seconds of landing on the page, that’s not a real human reading your content and deciding to engage. Track time-on-page and reject instant submissions.

Spam prevention isn’t just about clean data – it’s about not teaching Google’s algorithm to find more spam. Every garbage lead you allow through reinforces bad targeting patterns. Stopping spam at the source protects your entire performance max Google Ads investment.

What Is a Good Lead Generation Conversion Rate? (Benchmarks That Actually Matter)

“Good” depends entirely on what you’re measuring and your industry context.

The average Google Ads conversion rate is 7.52% (WordStream/LocaliQ, 2025). But that number includes everything from local plumbers to enterprise software – categories with radically different buyer behavior.

For B2B SaaS specifically, visitor-to-lead rates run around 1.5-2.5%, while top performers hit 8-15% on demo request forms (First Page Sage, 2026). That’s a massive spread, and it illustrates why benchmarks need context.

Here’s the uncomfortable truth: conversion rate alone is misleading without quality metrics.

You can dramatically increase your form conversion rate by shortening the form, removing qualifying questions, and lowering the commitment threshold. Your CPA will look great. Your sales team will revolt.

The metric that actually matters: cost per qualified lead (CPQL) or cost per SQL, not cost per form fill. When you optimize for this metric, you align marketing and sales on the same definition of success.

Remember that 4.7x CPL spread from the HubSpot data – $84 for the top quartile versus $397 for the bottom quartile? That gap isn’t explained by bid strategy or creative testing. It’s explained by quality optimization.

Top performers track leads through the pipeline and feed that data back to their acquisition channels. They know which campaigns, keywords, and audiences generate SQLs, not just form fills. They optimize for pipeline, not conversions.

For a deep dive into connecting your Google Ads data to HubSpot pipeline reporting, see our guide on HubSpot + Google Ads: The Complete Closed-Loop Reporting Setup.

Is Performance Max Worth It? (The ROI Reality Check)

Yes – if you have the data infrastructure. No – if you’re optimizing blind.

That conditional answer frustrates marketers who want a simple recommendation, but it’s the honest truth. Performance Max is a powerful tool that performs brilliantly when given proper feedback signals and poorly when left to optimize on form fills alone.

Google’s new AI Max + Power Pack strategy combines Performance Max, Demand Gen, and AI Max for Search into an integrated approach. AI Max is showing a 7-27% conversion lift for campaigns that upgrade from heavy exact/phrase match to AI-powered optimization (Google data). The direction is clear: Google is betting heavily on algorithmic campaign management.

But here’s our honest assessment: Performance Max works best as an addition to dedicated Search campaigns, not a replacement. Search campaigns give you precise control over high-intent queries. PMax extends your reach into audiences and placements Search doesn’t cover. Stack them together with proper conversion tracking, and you get the best of both worlds.

For more on how to structure this relationship, read our analysis on Search vs Performance Max for Lead Gen: Which Should You Scale First?.

The quality-over-quantity shift is real and accelerating: 40% of marketers in 2026 prioritize improving lead quality over volume. 73% say CPL optimization is their #1 priority (HubSpot). The industry has learned that cheap leads that don’t convert aren’t actually cheap – they consume sales resources, poison pipeline metrics, and train algorithms to find more garbage.

Performance Max for lead generation is worth it when you:
– Have offline conversion tracking properly configured
– Generate 30+ conversions per month for algorithm learning
– Feed qualified lead data back to Google within your sales cycle
– Use audience exclusions to prevent wasted spend
– Maintain spam prevention on your forms

It’s not worth it when you:
– Rely on form fills as your primary conversion metric
– Have sales cycles so long that the algorithm never gets feedback
– Lack of CRM integration to track lead quality
– Generate too few conversions for meaningful optimization

The Speed-to-Lead Multiplier (What Happens After the Click)

Everything we’ve discussed so far happens before and during the Performance Max campaign. But campaign success depends heavily on what happens after the click, specifically, how fast and effectively your sales team follows up.

This matters for PMax optimization because fast follow-up creates more conversion data. When leads get contacted quickly, they’re more likely to progress through your pipeline, which means more signals to feed back to Google.

The data is stark: responding to leads within 5 minutes makes you 9x more likely to convert them. Leads contacted within 5 minutes closed at 32% versus 12% after 24 hours (Affinco, 2026).

Think about that in PMax terms. If your sales team takes 24 hours to follow up, you’re converting 12% of qualified leads. If they respond in 5 minutes, that jumps to 32%. Same leads, same algorithm, completely different outcomes, and completely different data feeding back to Google.

This is where HubSpot automation becomes critical. Configure immediate lead routing so the right sales rep gets notified the moment a form is submitted. Set up instant notifications via email, Slack, or SMS. Build automated initial outreach to engage the lead while a human rep prepares for a personal follow-up.

For specific workflows to accomplish this, see our guide, HubSpot Sales Nurturing: Build Sequences That Convert.

The AI lead-scoring adoption surge reflects teams catching on to this: adoption jumped from 23% in 2024 to 38% in 2025, then to 61% in Q1 2026 (DigitalApplied B2B Lead Generation Statistics). AI scoring helps teams prioritize which leads get immediate human attention and which enter automated nurturing sequences.

Speed-to-lead multiplies the effectiveness of your Performance Max investment. Slow follow-up wastes the algorithm’s work by letting qualified leads go cold. Fast follow-up converts more leads, generates more pipeline data, and improves the feedback loop that makes PMax smarter over time.

Common Pitfalls (And How to Avoid Them)

After managing Performance Max campaigns for lead gen across dozens of accounts, these are the mistakes we see most often:

Treating form fills as the final conversion – This is the foundational error. Form fills are the beginning of your sales process, not the end. Configure offline conversion tracking so that Google can learn from pipeline outcomes.

Insufficient budget for algorithm learning – Accounts with less than 30 conversions per month are asking PMax to find patterns in insufficient data. Either increase the budget or focus on Search campaigns until volume supports PMax optimization.

Ignoring audience exclusions – Failing to exclude current customers, competitors, and known bad-fit segments wastes budget and confuses the algorithm. Use first-party data to tell Google who you don’t want.

Neglecting spam prevention – Every spam form fill teaches the algorithm to find more spam. Implement reCAPTCHA, honeypots, and qualifying questions to protect the quality of your conversion data.

Optimizing on CPL without quality metrics – A $50 CPL means nothing if those leads don’t become customers. Track cost per SQL and cost per opportunity as your true north metrics.

Slow sales follow-up – Leads contacted within 5 minutes convert at nearly 3x the rate of leads contacted after 24 hours. Speed-to-lead multiplies the value of your ad spend.

For a complete checklist covering setup, measurement, and exclusions, see our PMax Lead Gen Checklist: The Complete Setup, Measurement & Exclusions Playbook.

Conclusion: Breaking the Doom Loop

The 4.7x CPL spread between top- and bottom-quartile B2B programs isn’t random variance. It’s the result of systematic differences in how companies approach performance max for lead generation.

Top performers:
– Connect their CRM to Google Ads with offline conversion tracking that reports pipeline stage changes
– Assign conversion values that reflect the true worth of SQLs and closed deals, not just form fills
– Use audience exclusions to prevent wasted spend on known bad-fit segments
– Implement spam prevention at the form level to protect algorithm learning
– Follow up fast to maximize conversion rates and generate more feedback data

Bottom performers run PMax like ecommerce campaigns, optimizing on form fills and wondering why sales hate their leads.

The Feedback Loop of Doom is real, but it’s breakable. When you feed qualified lead data back to Google – when you tell the algorithm which form fills became pipeline and which became revenue – you transform PMax from a spam generator into a genuine customer acquisition engine.

Key takeaways:

• Performance Max needs 30+ conversions per month and offline conversion tracking to optimize effectively for lead generation
• The algorithm optimizes for whatever you measure – if you only track form fills, you’ll get more form fills regardless of quality
• CRM integration (HubSpot, Salesforce, Pipedrive) is required to close the feedback loop between ad click and sales outcome
• Conversion value assignment teaches Google that SQLs and closed deals matter more than fast form completions
• Speed-to-lead multiplies your Performance Max ROI by converting more leads and generating more feedback data

Next Steps

If you’re running Performance Max for lead generation without offline conversion tracking, stop optimizing until you fix the data problem. Every day you spend optimizing on form fills alone deepens the doom loop.

Start with your CRM integration. Get GCLID capture working on your forms. Map your lifecycle stages to conversion actions in Google Ads. Assign values that reflect the pipeline’s actual worth.

Then audit your spam prevention. Add reCAPTCHA, honeypot fields, and qualifying questions. Review your last 100 form fills and calculate how many became qualified leads. If that number is below 20%, you have a quality problem the algorithm is learning from.

Finally, measure what matters. Set up dashboards that track cost per SQL and cost per opportunity, not just cost per lead. Align marketing and sales on the same definition of success.

Need help connecting your Google Ads account to your CRM for closed-loop reporting? Get a free Growth Plan from NAV43. We’ll audit your current Performance Max setup, identify the gaps in your feedback loop, and build a roadmap to fix them.

The brands winning at Performance Max for lead generation aren’t using secret tactics. They’re just feeding the algorithm better data than everyone else. Start there.