How to make automation work for lead gen PPC

B2B advertising faces a distinct challenge: most automation tools weren’t built for lead generation.

Ecommerce campaigns benefit from hundreds of conversions that fuel machine learning. B2B marketers don’t have that luxury. They deal with lower conversion volume, longer sales cycles, and no clear cart value to guide optimization.

The good news? Automation can still work.

Melissa Mackey, Head of Paid Search at Compound Growth Marketing, says the right strategy and signals can turn automation into a powerful driver of B2B leads. Below is a summary of the key insights and recommendations she shared at SMX Next.

The fundamental challenge: Why automation struggles with lead gen

Automation systems are built for ecommerce success, which creates three core obstacles for B2B marketers:

• Customer journey length: Automation performs best with short journeys. A user visits, buys, and checks out within minutes. B2B journeys can last 18 to 24 months. Offline conversions only look back 90 days, leaving a large gap between early engagement and closed revenue.
• Conversion volume requirements: Google’s automation works best with about 30 leads per campaign per month. Google says it can function with less, but performance is often inconsistent below that level. Ecommerce campaigns easily hit hundreds of monthly conversions. B2B lead gen rarely does.
• The cart value problem: In ecommerce, value is instant and obvious. A $10 purchase tells the system something very different than a $100 purchase. Lead generation has no cart. True value often isn’t clear until prospects move through multiple funnel stages — sometimes months later.

The solution: Sending the right signals

Despite these challenges, proven strategies can make automation work for B2B lead generation.

Offline conversions: Your number one priority

Connecting your CRM to Google Ads or Microsoft Ads is essential for making automation work in lead generation. This isn’t optional. It’s the foundation. If you haven’t done this yet, stop and fix it first.

In Google Ads’ Data Manager, you’ll find hundreds of CRM integration options. The most common B2B setups include:

• HubSpot and Salesforce: Both offer native, seamless integrations with Google Ads. Setup is simple. Once connected, customer stages and CRM data flow directly into the platform.
• Other CRMs: If you don’t use HubSpot or Salesforce, you can build a custom data table with only the fields you want to share. Use connectors like Snowflake to send that data to Google Ads while protecting user privacy and still supplying strong automation signals.
• Third-party integrations: If your CRM doesn’t integrate directly, tools like Zapier can connect almost anything to Google Ads. There’s a cost, but the performance gains typically pay for it many times over.

Embrace micro conversions with strategic values

Micro conversions signal intent. They show a “hand raiser” — someone engaged on your site who isn’t an MQL yet but clearly interested.

The key is assigning relative value to these actions, even when you don’t know their exact revenue impact. Use a simple hierarchy to train automation what matters most:

• Video views (value: 1): Shows curiosity, but qualification is unclear.
• Ungated asset downloads (value: 10): Indicates stronger engagement and added effort.
• Form fills (value: 100): Reflects meaningful commitment and willingness to share personal information.
• Marketing qualified leads (value: 1,000): The highest-value signal and top optimization priority.

This value structure tells automation that one MQL matters more than 999 video views. Without these distinctions, campaigns chase impressive conversion rates driven by low-value actions — while real leads slip through the cracks.

Making Performance Max work for lead generation

You might dismiss Performance Max (PMax) for lead generation — and for good reason. Run it on a basic maximize conversions strategy, and it usually produces junk leads and wastes budget.

But PMax can deliver exceptional results when you combine conversion values and offline conversion data with a Target ROAS bid strategy.

One real client example shows what’s possible. They tracked three offline conversion actions — leads, opportunities, and customers — and valued customers at 50 times a lead. The results were dramatic:

• Leads increased 150%
• Opportunities increased 350%
• Closed deals increased 200%

Closed deals became the campaign’s top-performing metric because they reflected real, paying customers. The key difference? Using conversion values with a Target ROAS strategy instead of basic maximize conversions.

Campaign-specific goals: An underutilized feature

Campaign-specific goals let you optimize campaigns for different conversion actions, giving you far more control and flexibility.

You can set conversion goals at the account level or make them campaign-specific. With campaign-specific goals, you can:

• Run a mid-funnel campaign optimized only for lead form submissions using informational keywords.
• Build audiences from those form fills to capture engaged prospects.
• Launch a separate campaign optimized for qualified leads, targeting that warm audience with higher-value offers like demos or trials.

This approach avoids asking someone to “marry you on the first date.” It also keeps campaigns from competing against themselves by trying to optimize for conflicting goals.

Portfolio bidding: Reaching the data threshold faster

Portfolio bidding groups similar campaigns so you can reach the critical 30-conversions-per-month threshold faster.

For example, four separate campaigns might generate 12, 11, 0, and 15 conversions. On their own, none qualify. Grouped into a single portfolio, they total 38 conversions — giving automation far more data to optimize against.

You may still need separate campaigns for valid reasons — regional reporting, distinct budgets, or operational constraints. Portfolio bidding lets you keep that structure while still feeding the system enough volume to perform.

Bonus benefit: Portfolio bidding lets you set maximum CPCs. This prevents runaway bids when automation aggressively targets high-propensity users. This level of control is otherwise only available through tools like SA360.

First-party audiences: Powerful targeting signals

First-party audiences send strong signals about who you want to reach, which is critical for AI-powered campaigns.

If HubSpot or Salesforce is connected to Google Ads, you can import audiences and use them strategically:

• Customer lists: Use them as exclusions to avoid paying for existing customers, or as lookalikes in Demand Gen campaigns.
• Contact lists: Use them for observation to signal ideal audience traits, or for targeting to retarget engaged users.

Audiences make it much easier to trust broad match keywords and AI-driven campaign types like PMax or AI Max — approaches that often feel too loose for B2B without strong audience signals in place.

Leveraging AI for B2B lead generation

AI tools can significantly improve B2B advertising efficiency when you use them with intent. The key is remembering that most AI is trained on consumer behavior, not B2B buying patterns.

The essential B2B prompt addition

Always tell the AI you’re selling to other businesses. Start prompts with clear context, like: “You’re a SaaS company that sells to other businesses.” That single line shifts the AI’s lens away from consumer assumptions and toward B2B realities.

Client onboarding and profile creation

Use AI to build detailed client profiles by feeding it clear inputs, including:

• What you sell and your core value.
• Your unique selling propositions.
• Target personas.
• Ideal customer profiles.

Create a master template or a custom GPT for each client. This foundation sharpens every downstream AI task and dramatically improves accuracy and relevance.

Competitor research in minutes, not hours

Competitive analysis that once took 20–30 hours can now be done in 10–15 minutes. Ask AI to analyze your competitors and break down:

• Current offers
• Positioning and messaging
• Value propositions
• Customer sentiment
• Social proof
• Pricing strategies

AI delivers clean, well-structured tables you can screenshot for client decks or drop straight into Google Sheets for sorting and filtering. Use this insight to spot gaps, uncover opportunities, and identify clear strategic advantages.

Competitor keyword analysis

Use tools like Semrush or SpyFu to pull competitor keyword lists, then let AI do the heavy lifting. Create a spreadsheet with columns for each competitor’s keywords alongside your client’s keywords. Then ask the AI to:

• Identify keywords competitors rank for that you don’t to uncover gaps to fill.
• Identify keywords you own that competitors don’t to surface unique advantages.
• Group keywords by theme to reveal patterns and inform campaign structure.

What once took hours of pivot tables, filtering, and manual cleanup now takes AI about five minutes.

Automating routine tasks

• Negative keyword review: Create an AI artifact that learns your filtering rules and decision logic. Feed it search query reports, and it returns clear add-or-ignore recommendations. You spend time reviewing decisions instead of doing first-pass analysis, which makes SQR reviews faster and easier to run more often.
• Ad copy generation: Tools like RSA generators can produce headlines and descriptions from sample keywords and destination URLs. Pair them with your custom client GPT for even stronger starting points. Always review AI-generated copy, but refining solid drafts is far faster than writing from scratch.

Experiments: testing what works

The Experiments feature is widely underused. Put it to work by testing:

• Different bid strategies, including portfolio vs. standard
• Match types
• Landing pages
• Campaign structures

Google Ads automatically reports performance, so there’s no manual math. It even includes insight summaries that tell you what to do next — apply the changes, end the experiment, or run a follow-up test.

Solutions: Pre-built scripts made easy

Solutions are prebuilt Google Ads scripts that automate common tasks, including:

• Reporting and dashboards
• Anomaly detection
• Link checking
• Flexible budgeting
• Negative keyword list creation

Instead of hunting down scripts and pasting code, you answer a few setup questions and the solution runs automatically. Use caution with complex enterprise accounts, but for simpler structures, these tools can save a significant amount of time.

Key takeaways

Automation wasn’t built for lead generation, but with the right strategy, you can still make it work for B2B.

• Send the right signals: Offline conversions with assigned values aren’t optional. First-party audiences add critical targeting context. Together, these signals make AI-driven campaigns work for B2B.
• AI is your friend: Use AI to automate repetitive work — not to replace people. Take 50 search query reports off your team’s plate so they can focus on strategy instead of tedious analysis.
• Leverage platform tools: Experiments, Solutions, campaign-specific goals, and portfolio bidding are powerful features many advertisers ignore. Use what’s already built into your ad platforms to get more out of every campaign.

Watch: It’s time to embrace automation for B2B lead gen 

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