When I dive into AI-driven advertising, it’s clear that our lead generation strategies must evolve. Here’s what I’m focusing on to make the most of these exciting tools.
Many of today’s PPC tools cater to ecommerce, but that’s not to say they can’t benefit lead gen. It just takes a more intentional approach on my end.
Even though lead gen with AI demands creativity and adaptation of traditional ecommerce tools, they don’t always apply in the same manner. Here’s how I’m ensuring success.
Disclosure: As a Microsoft employee, my examples might lean towards Microsoft Advertising. However, the principles I discuss apply broadly across platforms.
1. Fix your conversion data first
This is the single most crucial step as AI becomes more intertwined with media buying. Changes in attribution models, privacy policies, platform interactions, and consumer behavior mean I frequently question if my data reflects reality.
My initial step is always to audit my CRM or lead management system. I ensure the data I send to advertising platforms is clean, consistent, and intentional.
While data issues often arise from human decisions over technical faults, I never overlook essential technical checks:
- I confirm that conversions fire consistently.
- I regularly review conversion goal diagnostics.
- I validate that status updates and downstream signals flow back as they should.
Since AI systems learn from this data, it’s crucial for me to ensure that the feedback loop accurately reflects my operations.
Dig deeper: How to make automation work for lead gen PPC
2. Make landing pages easy to ingest and easy to understand
Lead gen campaigns can offer users multiple conversion paths. But from an AI standpoint, unclear paths pose a risk.
This means my landing pages need to clearly communicate:
- The action I want users to take.
- What happens after they take action.
- Which conversions are of priority.
Ambiguous conversion paths can confuse both users and systems. If AI crawlers detect inconsistent outcomes, they might question the accuracy of what my site claims, limiting my eligibility for certain placements.
It’s vital for me to use simple language, free of jargon or eccentric terms. This clarity helps AI systems better understand who I am and what I offer, aligning my creative with the right audience.
Using Performance Max campaign builders is a practical test. I review how the system positions my business. If its messaging aligns with my goals, my site is probably clear enough. If not, I take that feedback seriously.
I also utilize AI assistants to gauge how they describe my services. Accurate descriptions mean I’m on the right track; inconsistencies signal needed refinements.
Behavioral analytics tools, like Clarity, offer insights into user engagement on my site and frequency of AI tool crawlers.
Dig deeper: AI tools for PPC, AI search, and social campaigns: What’s worth using now
3. Budget across the entire funnel
Lead gen often faces long conversion cycles, an issue that AI can amplify. AI-driven systems evaluate sentiment, visibility, and contextual signals beyond just last-click performance. Therefore, if my budget only emphasizes immediate traffic, I risk missing significant impact higher in the funnel.
I aim to:
- Budget intentionally across awareness, consideration, and conversion stages.
- Apply the right metrics for each stage.
- Look beyond traffic as the primary success indicator.
In many lead gen models, citations, qualified leads, and eventual revenue provide a more accurate performance story than mere clicks.
Dig deeper: Lead gen PPC: How to optimize for conversions and drive results
4. Clean up your feeds and map data
I might assume I don’t have a “feed” in my lead gen setup, but that assumption puts me at a disadvantage.
Feeds provide AI systems with insights into my business structure and services. Keeping a simple Excel feed can grant platforms valuable context, even if my site isn’t massive.
Proper feed hygiene increases understanding. I use clear, specific columns, adhere to platform standards, and ensure full category representation.
On the local level, I claim and maintain all map profiles for accuracy. Consistent information is crucial. If I use call tracking, I carefully review labels to prevent attribution chaos caused by AI pulling mismatched data.
Adjust for potential AI-driven inflation in reporting and ensure changes reflect in conversion goals.
5. Pressure-test your creative for clarity
AI might mix, match, or shorten creative assets, meaning I often get one chance through a single headline to convey my entire value proposition.
If my selling points need multiple elements to make sense, that’s a risk. I review my creative to ensure it stands alone, communicating:
- What I do
- Who I help
- Why it matters
Lack of clarity can cause AI-driven placements to quickly become muddled.
Dig deeper: Why creative, not bidding, is limiting PPC performance
The fundamentals that still move the needle
Lead gen doesn’t need to be overly complex. Most impactful actions remain the same: clean data, clear messaging, rational budgeting, and disciplined execution. What’s shifting is attribution and the value AI places on different signals.
The fundamentals win out. AI merely highlights weaknesses and scales strengths. Emphasizing clarity, accuracy, and comprehensive funnel alignment sets up the best future performance.
Inspired by this post on Search Engine Land.
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