I’ve noticed a growing interest in ChatGPT ads as an advertising channel. However, there’s significant uncertainty due to limited data and constantly changing features.
OpenAI is stepping into new territory with their advertising platform, and as an advertiser, I’m experiencing mixed feelings. The data is sparse, performance metrics are unclear, and the rapid evolution of the product adds another layer of complexity.
Driving the News. Two months into ChatGPT ads, I’m finding that although experimenting is underway, the lack of clear measurement tools and established benchmarks is a challenge.
Early campaigns are mostly impression-based, leaving me wanting more insight into their effectiveness.
I’ve heard that CPMs are quite steep, with initial spends in the six-figure range.
Some of us feel the product is still in its infancy and maturing very slowly.
The Vibe Check. When I speak with other advertisers, the sentiment ranges from cautious optimism to frustration. On one hand, there’s excitement due to ChatGPT’s innovative approach as an AI platform.
On the flip side, the lack of transparency and targeted reporting leaves much to be desired.
Why We Care. From my perspective, this highlights the dual nature of investing in AI ad platforms. ChatGPT promises access to a fast-growing audience, but the absence of concrete measurement tools makes large-scale investment risky.
It’s crucial for me to proceed with thoughtful testing and establish a solid AI strategy without committing too much of the budget just yet.
The Bigger Picture. OpenAI is striving for success by balancing AI development and enterprise growth, all while facing stiff competition from giants like Google and Anthropic.
Some industry insiders feel OpenAI’s broad experimentation might dilute its focus. The withdrawal of the Instant Checkout feature and losing ground in video ambitions illustrate this point.
How Ads Actually Show Up. Initial tests indicate that ads might impact user journeys indirectly. For example, a sponsored retailer may be highlighted more prominently among recommendations.
Despite these placements, platforms assure that ads don’t drastically alter the fundamental responses.
Yes, But…. I notice an ongoing push and pull between maintaining consumer trust, ensuring unbiased answers, and fulfilling advertiser goals to boost visibility.
How this balance is managed will inevitably influence the future development of AI ads.
What Marketers Should Do Now. Experts suggest that brands don’t need to make hasty decisions. While large brands might gain from early experiments, others should focus on strategic development as the field evolves. Understanding how AI integrates into overarching media strategies is key.
The Bottom Line. ChatGPT ads are still in their infancy. They hold promise but remain unproven, requiring advertisers like me to tread carefully while waiting for the platform to mature and meet expectations.
I’ve always been intrigued by how technology transforms the way we engage with the world. Recently, OpenAI has taken a significant step by introducing ads in select markets. This move opens up exciting opportunities for brands to connect with users through AI-driven experiences.
OpenAI’s latest initiative to incorporate ads signals a strategic push into monetizing their platforms while keeping the premium tiers ad-free. This careful balancing act allows OpenAI to expand their ad reach without compromising the user experience of their paid plans.
Driving the news. Ads are being rolled out for users on Free and Go plans in Australia, New Zealand, and Canada. This is a fascinating development for those of us observing how AI interfaces evolve.
These changes currently apply solely to lower-tier plans.
The Pro, Business, Enterprise, and Education tiers will continue to offer an ad-free experience.
Why I care. As someone interested in AI and marketing, this presents an incredible opportunity to explore new channels for reaching users. The expansion into more markets means we can experiment and learn how ads can be effectively integrated into conversational interfaces, potentially reshaping the future of search and discovery.
The big picture. Most AI platforms have traditionally steered clear of conventional advertising, relying more on subscription models and enterprise partnerships. But this move by OpenAI might just be the tipping point for change.
It seems that OpenAI is:
investigating new revenue opportunities,
understanding the role of ads in conversational platforms,
and finding that sweet spot between monetization and a seamless user experience.
Yes, but: It’s clear that OpenAI wants to maintain a distinction between their free and premium offerings, ensuring that an ad-free experience remains a coveted advantage.
The bottom line: In cautious steps, OpenAI is exploring the world of ads within AI-driven products, starting with limited markets and tiers. This calculated approach allows them to understand the impact of advertising on their platforms.
As I delve into the latest updates from Google, I discovered that they’ll be retiring Dynamic Search Ads (DSA) in favor of their newer AI Max toolset. This transition will begin in September, and it’s bound to impact those using DSA, automatically created assets (ACA), and campaign-level broad match settings.
It’s fascinating to learn that Google announced AI Max for Search campaigns will exit beta, with “hundreds of thousands” of advertisers already onboard globally. I find this shift intriguing as it hints at the increasing reliance on AI-powered tools in digital advertising.
Starting September, my eligible campaigns utilizing DSA, ACA, or broad match will automatically be migrated to AI Max. This means Google will no longer support the creation of new DSA campaigns through their various platforms.
Why does this matter to us? Embracing AI Max beforehand allows us better control over campaign settings. Google mentions this change could potentially lead to an average 7% improvement in conversions or conversion value while maintaining the same efficiency.
According to Google, AI Max offers more conversions or conversion value at a similar cost per acquisition (CPA) or return on ad spend (ROAS) for non-retail sectors. It achieves this by using comprehensive features like search term matching, text customization, and URL expansion.
A Brief History: DSA has been a valuable tool for capturing traffic beyond keyword-focused campaigns, thanks to its dynamic headline generation and landing page redirection. However, changes in consumer search behavior have prompted Google to innovate further.
AI Max aims to enhance search campaigns by integrating broad real-time intent data beyond traditional landing page signals. It’s designed to adapt to the increasingly complex search landscape we navigate today.
Understanding AI Max: This feature maximizes reach, personalizes ad content, and provides more control over brand, location, and text settings.
So, what should we do now? Google encourages us to make the switch before September to ensure smoother transitions and continuity in our campaigns.
Phase 1: Voluntary Upgrades is happening now. DSA users like me can leverage new tools to smoothly migrate campaign data and settings. Meanwhile, ACA and broad match users will find prompts nudging them toward AI Max.
Phase 2: Automatic Upgrades begins in September, converting dynamic ad groups in DSA campaigns to standard ones while preserving significant settings. ACA and broad match campaigns will migrate with essential features enabled by default.
The Bottom Line: Google’s move to make AI Max the standard signifies a shift towards AI-driven strategies. By acting now, I can test different settings and fine-tune results before the mandatory switch.
I’ve discovered the power of turning AI into a strategic ad partner using prompts that dive deep into buyer emotions, target high-intent audiences, and tackle objections.
Many of us are already tapping into various generative AI tools to breathe life into our marketing ideas and boost the effectiveness of ad campaigns.
Using prompts isn’t just a solo brainstorming alternative; it’s a productivity booster that opens up a world of possibilities.
In this guide, I’ll share some of my favorite marketing prompts for ad campaigns, designed to spark creativity in crafting your own prompts.
Why Use Prompts for Online Ads?
Prompts are your fast track to brainstorming ad elements like triggers, emotions, actions, and your target audience.
The beauty of prompts is they’re versatile. You can tweak outputs across different channels and initiatives like ads, emails, and social media.
Getting closer to optimal campaigns from the outset means saving time, a real boon for low-budget efforts that are hungry for feedback.
The prompts themselves make all the difference. Craft strong questions to extract valuable insights from large language models (LLMs).
Feeling stuck? Ask AI tools for prompt recommendations or use mine. Here’s a selection I often use for online ads.
Emotional Trigger Prompt
Purchases are fueled by emotions, so it’s essential to tap into what makes your audience feel.
Try this prompt: “What are the top emotional triggers that would make X audience buy Y product?”
As an example, I explored what emotional triggers would prompt parents to purchase math learning software for their kids. The LLM highlighted key triggers alongside scarcity and urgency hooks:
Fear of falling behind: Anxiety and a protective instinct. Example: “Ensure your child never falls behind in math.”
Desire to give kids a competitive advantage: Ambition and pride. Example: “Equip your child with math skills that top students develop years ahead.”
Relief from homework stress at home: Relief and peace of mind. Example: “Say goodbye to math homework battles at home.”
Purchase Intent Prompt
Explore these questions to identify who’s ready to buy your product or service now:
Who is most likely to buy immediately?
Who needs convincing?
Who will never buy?
To prevent wasting ad spend, focus on audiences poised for purchase and steer clear of those unlikely to buy.
Keep probing which audiences are most likely to convert. Use the LLM’s feedback to get more specific with your ads.
In the math software scenario, the LLM advised that parents of struggling kids in math were the best converters due to high urgency and low friction.
The second-best group? Homeschooling parents, motivated by the need to manage the entire curriculum. This insight allowed us to craft ads and test conversions.
Overcoming Objections Prompt
Addressing objections is crucial for sealing the deal. Ask for three to five potential objections buyers might have about your product.
In our math software example, the LLM identified these objections:
My child already has too much screen time.
Will this actually improve my child’s math skills?
It’s too expensive.
Next, craft a persuasive counter-argument for each using logic, emotion, and evidence. For “it’s too expensive,” consider:
Logic: “Less than the cost of a tutor.” Establishes a higher anchor, making the price seem reasonable without calling it cheap.
Emotion: “Don’t let your kids fall behind in math.”
Proof: “80% of students improve by one letter grade in two months.”
Psychological Profile Prompt
Request a comprehensive psychological profile of your ideal customer from an LLM. Use questions like:
What are your ideal customer’s fears?
What are their frustrations?
What do they envy?
What do they pretend doesn’t bother them?
What keeps them up at night?
In the math software scenario, I asked, “What or who do my ideal customers envy?”
The response indicated parents envy children in enrichment or advanced classes, seeking future educational opportunities.
Here’s a message for them: “Help your child stay ahead instead of playing catchup.”
The Lifetime Value Prompt
Sustain long-term success by focusing on customer lifetime value (LTV) instead of one-time sales.
Consider these questions:
Why might your customers stick around?
Why might they buy more?
What retention strategies are effective?
For a luxury furniture brand, we turned these into a brief playbook to boost LTV. The LLM suggested shifting from a transactional relationship to a long-term design partnership.
For instance, segment your customer base and use direct mail for your highest-value group by sending a lookbook. Though it seems old-school, it can result in a higher LTV than general mailings.
Your clients deserve strategic thinking and clear priorities. AI tools help us achieve that, supporting both strategy and execution.
Fix Lagging Average Order Value Prompt
When performance dwindles, it’s tempting to ask sweeping questions about metrics like return on ad spend (ROAS).
But that’s a path well-trodden, often leading to generic, uninspired checklists.
We grapple with B2C and B2B search query overlaps. Focusing on B2B users is challenging but crucial for securing high-value, long-term customers.
We noticed a likely cause of a B2B client’s lagging ROAS: average order value (AOV) as reflected in Google Ads’ Value/Conv. Smart Bidding had shifted to high-converting but lower-quality sessions, impacting performance.
We enlisted an LLM to ascertain and address the issue.
With Ads Advisor (Gemini) in Google Ads, the initial response focused on trivial consumer scenarios, like holiday themes.
Upon refining the prompt, we received more targeted, actionable suggestions, saving valuable time.
We doubled down on audience targeting, emphasizing specific Google audience segments and first-party audiences with value rules.
AOV increased. While it didn’t promise higher order values, it honed focus on B2B intent and reduced low-priority consumer purchases.
Key performance metrics improved, guiding the path to growth and profitability.
Better Prompts Lead to Better Campaigns
Begin simply — incorporate one or two of these prompts into your next campaign, tweak the outcomes, and expand from there. Over time, you’ll establish a repeatable system where AI becomes integral to your marketing workflow.
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.
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.
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.
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.
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.
