The New Creative Stack: OpenAI For Ideas, Meta For Reach, Google For Results

Key Takeaways

• AI browsing reaches campaign level: OpenAI’s ChatGPT Atlas brings real-time web data into daily planning, signalling the next step in AI-assisted research

• Creative automation accelerates: Instagram’s new AI Story tools and Meta’s Advantage updates make it faster to create, refine and test ad visuals.

• Smarter commerce management: Meta’s product catalogue and bidding updates simplify setup and targeting across multiple devices and audiences.

• Greater transparency in ad performance: Google Ads’ new traffic source visibility and Demand Gen improvements help advertisers track spend and optimisation paths more precisely.

• Measurement challenges on the horizon: Ongoing Search Console data delays highlight how dependent analytics and SEO teams are on stable reporting pipelines.

AI, automation and optimisation are becoming inseparable across every stage of digital marketing. 

OpenAI is bringing browsing capabilities directly into ChatGPT for live insight generation, Meta is blending creative automation with commerce and Google is fine-tuning transparency for advertisers navigating complex performance funnels. 

These changes signal a more interconnected ecosystem: one where campaign success will depend on how efficiently teams connect data, content and strategy. 

AI browsing arrives with OpenAI’s ChatGPT Atlas

OpenAI’s ChatGPT Atlas introduces an AI browser that merges live web access with conversational intelligence. The new sidebar experience allows users to browse, compare and summarise information without leaving the page. Atlas also features “Agent Mode,” which enables ChatGPT to take autonomous actions, from researching and analysing data to completing shopping tasks, within the browser environment.

The update marks a shift in how users interact with search and content discovery. It positions Atlas as an early step toward generative engine optimisation, where AI systems interpret and prioritise content directly rather than relying on traditional link-based ranking.

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The Gurus’ take

Atlas signals a turning point in how visibility will work in generative ecosystems. As AI models begin reading and summarising the web in real time, the focus moves from keyword ranking to clarity, authority and machine readability. Businesses optimising for ChatGPT Atlas SEO will need to think less about where they appear in search results and more about how effectively AI can extract and present their information.

This evolution also hints at a new service category: the generative search optimisation agency focused on helping brands build content that AI engines can understand, trust and use to influence user decisions.

Your action plan

Here’s how to prepare for Atlas-style browsing before it reshapes search visibility:

• Update content for AI interpretation: Use schema markup, FAQs and structured formatting so AI browsers can identify and summarise your key points accurately.

• Optimise for natural language: Refine content to answer conversational queries directly, mirroring how users interact with ChatGPT instead of traditional search syntax.

• Track emerging AI referral data: As Atlas and similar tools expand, monitor analytics for traffic attributed to generative engines or third-party summaries.

• Plan for hybrid SEO strategies: Start blending conventional optimisation with AI-driven discovery tactics to future-proof your visibility across both search and generative ecosystems.

Instagram upgrades Stories with AI-powered creative edits

A new AI “Restyle” tool in Stories lets users transform images and videos using natural language prompts or preset filters. The feature enables quick visual changes, like swapping backgrounds and outfits, without the need for reshoots or complex editing. A simple prompt can turn a plain studio shot into a lifestyle scene, or adapt visuals to match seasonal themes instantly.

The Gurus’ take 

Instagram’s “Restyle” feature turns Stories into a real-time creative testing ground. Instead of producing new assets for every theme or trend, marketers can now adjust visuals instantly. This is a major advantage for teams managing frequent Instagram advertising campaigns. This change also signals a shift in how platforms expect advertisers to use AI: not just for automation, but for everyday creative expression.

The ability to swap outfits, environments or tones through prompts could also redefine how product-focused content is made. For example, brands might generate multiple seasonal variants of a single image for different regions or audiences. Instagram ads become faster, cheaper and more adaptive to trend cycles.

Your action plan

Integrate AI-driven creative edits into your Stories strategy through these steps:

• Use prompts for quick visual variants: Generate on-brand image and video variations that fit different seasons, styles or markets without re-shooting.
  
• Test creative refresh speed: Run A/B tests comparing Restyle-edited visuals against traditional assets to measure performance and engagement.
  
• Maintain brand consistency: Create internal guidelines for AI use so tone, colour and composition remain cohesive across campaigns.
  
• Scale creative output: Incorporate Restyle into your short-form strategy to maintain a constant flow of fresh content while reducing production time.

Meta changes how product catalogs are assigned in sales campaigns

Product catalog management in Meta Ads has been simplified. Catalogs are now linked at the campaign level rather than at the ad set or ad level, which gives advertisers a single control point for data while keeping flexibility for audience targeting and creative variations below.

The new structure also streamlines how catalog eligibility and delivery are handled. By reducing mismatched feeds and duplicate setups, campaigns can now run with fewer errors, cleaner reporting and more consistent performance across Meta’s ecosystem.

The Gurus’ take 

This refinement brings catalog-based advertising closer to Meta’s broader goal: making campaigns easier to manage and scale. Moving catalog control higher in the hierarchy allows advertisers to make faster adjustments across multiple ad sets without needing to rebuild or relink assets.

Teams running Facebook ads with large product inventories can enjoy a more streamlined collaboration between creative and data teams. There’s less setup time while keeping campaign logic clean. It also aligns Meta’s sales campaigns with best practices used across ecommerce platforms, where centralised catalogue management is the norm.

Your action plan

To adapt to Meta’s new catalogue structure, try to:

• Review current campaign setups: Check existing catalogue-linked campaigns to confirm they align with the new campaign-level assignment structure.

• Consolidate redundant ad sets: Merge overlapping campaigns where possible to take advantage of simplified catalogue management.

• Centralise product data updates: Manage catalogue edits in one source of truth, such as Commerce Manager or your data feed tool, to maintain consistency.

• Monitor delivery and reporting: Track changes in performance metrics to identify how the new catalogue structure impacts optimisation and reach.

New Demand Gen update improves bidding and ad creation workflows

Google’s latest Demand Gen update brings a suite of improvements that simplify how advertisers bid, target and create ads across its ecosystem. The rollout introduces new customer acquisition goals, including a “New Customer Only” option, alongside expanded Target CPC bidding for more control over performance across platforms.

A standout addition is the new AI-powered video creation tool, which converts existing images and text assets into video ads automatically. This feature is available for YouTube Ads and other Demand Gen surfaces, helping teams produce short engaging video content without full production workflows.

The Gurus’ take 

The latest Demand Gen update is another sign of Google’s strategy to close the gap between video storytelling and measurable conversions. The inclusion of AI video tools means advertisers can now test multiple formats faster, while Target CPC and customer acquisition goals introduce more control into what was once a highly automated campaign type.

It also underscores a key shift in YouTube Ads: no longer just a branding channel, but a direct-response driver within Google Ads. As bidding models evolve, video and performance marketing are becoming part of the same playbook.

Your action plan

This update opens the door for faster creative testing and smarter bidding. Here’s how to put it to work.

• Set new acquisition goals: Test the “New Customer Only” setting to target untapped audiences and measure incremental reach.

• Refine bidding strategies: Experiment with Target CPC to balance cost efficiency with lead quality across campaign types.

• Use AI video tools for scale: Turn existing static assets into short video ads for YouTube and compare performance against manually produced creatives.

• Monitor conversion trends: Track how Demand Gen impacts performance metrics like CPA and engagement time, especially as AI-generated videos enter your mix.

• Integrate creative testing: Build a feedback loop between your creative and performance teams to iterate faster on AI-generated video outputs.

Meta launches Show Spotlights Advantage for improved ad performance

Show Spotlights Advantage is Meta’s new optimisation layer for high-impact visual placements such as Stories and Reels. It automatically prioritises delivery to placements proven to perform best, improving visibility and engagement without manual adjustments.

The rollout also includes updated creative tools within Ads Manager. Motion templates, layout presets and adaptive cropping help teams create platform-ready content directly inside Meta’s ecosystem. The result is faster and more native production for social media ads.

The Gurus’ take 

Show Spotlights Advantage reflects Meta’s ongoing move toward automated personalisation. It gives the system more say in where creative appears, while still keeping control in the advertiser’s hands. The stronger creative toolset also signals how Meta wants more assets produced and optimised within its own platform.

It’s a quiet but significant shift: less time guessing where visuals will perform, more time producing content that fits the way people actually experience Stories and Reels. In a feed saturated with motion and sound, precision placement and speed of production can be the real differentiators in social media ads.

Your action plan

To make the most of Meta’s new optimisation layer and creative suite:

• Update creative workflows: Build Story and Reel variations directly in Meta’s editor to benefit from the new layout and motion options.

• Activate the optimisation layer on select campaigns: Test it on visual-heavy campaigns like launches or awareness pushes to gauge its impact on engagement.

• Monitor placement distribution: Check performance data to see how impressions shift as the system learns.

• Refine creative rhythm: Focus on pacing, framing and transitions since Meta’s optimiser will now favour assets that hold attention longer. These are the details that keep people watching. 

• Iterate fast: With production and delivery now more connected, shorten the feedback loop between creative testing and media planning.

Meta Ads adds device platform targeting to Value Rules

Meta Ads has expanded Value Rules, introducing a device platform targeting that lets advertisers adjust bids based on where conversions happen, whether desktop or mobile. Campaigns can now weigh performance value by device, not just by audience or geography.

The digital marketing update gives advertisers finer control when allocating spend. A brand seeing stronger ROAS from mobile conversions, for example, can now bid more aggressively there without overpaying for desktop traffic. It’s a subtle but impactful layer of optimisation that aligns bidding with the actual value of user behaviour.

The Gurus’ take 

This addition signals Meta’s ongoing focus on precision bidding within its broader automation framework. The ability to distinguish value by device closes a long-standing gap for advertisers who rely heavily on mobile-first conversions but couldn’t fine-tune bids accordingly.

The more Meta connects granular signals, from devices to placements to purchase value, the easier it becomes to link spend directly to business outcomes. This digital marketing update doesn’t require fully surrendering control to automation.

Your action plan

Device-based bidding opens up a new layer of performance tuning. To use it effectively:

• Audit performance by device: Review historical campaign data to identify where conversion value differs most between mobile and desktop.

• Refine Value Rules by segment: Set tailored bid adjustments for each device platform based on ROAS, conversion rate, or average order value.

• Monitor post-change efficiency: Track cost-per-conversion and value metrics for the first few weeks to see if the new rules improve ROI.

• Pair with placement insights: Combine device-level data with placement trends (e.g., Stories, Reels, Feeds) to understand the full context of performance.

• Document learnings: Record which adjustments produce consistent gains, so bidding strategies can be scaled across campaigns.

Google Ads adds traffic source visibility to search term reports

Google Ads has introduced a new “AI Max Sources” column in its search term reports, revealing exactly where impressions and clicks originate. The update separates traffic coming from Search, Display, Shopping, YouTube and partner networks. It finally gives advertisers visibility into the mix of surfaces driving results.

This level of transparency has long been requested by advertisers using automated campaign types like Performance Max and AI Max, where traffic distribution is often unclear. With source-level visibility now accessible, teams can connect performance data directly to the channels that drive it.

The Gurus’ take

This change represents a quiet but important shift toward accountability within Google’s automation ecosystem. It bridges the gap between machine-driven optimisation and human oversight, offering a clearer view of how automated campaigns actually behave.

Greater visibility into traffic sources allows advertisers to confirm whether automation aligns with strategic priorities, such as Search intent versus Display exposure. It’s another move toward making Google Ads more transparent, which helps teams make informed budget reallocations instead of relying purely on aggregated results.

Your action plan

Understanding where traffic originates is key to using this new visibility effectively:

• Enable the AI Max Sources column: Add it to your search term report and review the breakdown of traffic across Search, Display, YouTube, and partner networks.

• Compare sources to performance: Analyse how conversion rates, CPCs, and ROAS differ by source to identify which channels justify more spend.

• Adjust signals or creative focus: Shift assets or audience signals toward higher-performing surfaces rather than relying on uniform optimisation.

• Track shifts over time: Revisit the data monthly to see how Google’s automation reallocates impressions as campaigns evolve.

• Use insights for planning: Incorporate source data into reporting to guide future testing and forecasting — particularly when balancing between intent-driven and discovery-based placements.

Google Search Console data stuck since October 19

Several users have reported that Google Search Console performance reports have not been updated since October 19, with metrics like clicks, impressions and average position showing incomplete or static data. The freeze affects profiles globally and impacts both domain and URL-level property reporting. While indexing and coverage reports remain operational, the performance tab, crucial for keyword tracking and visibility insights, appears to be delayed.

The Gurus’ take 

Short-term disruptions like this highlight how dependent modern reporting systems are on a single data source. The delay doesn’t indicate ranking drops, but it does create blind spots, especially for teams that depend on daily trend monitoring.

It’s a timely reminder that SEO in Australia and beyond benefits from redundancy in analytics. Combining Search Console data with Google Analytics, rank trackers and log files can help maintain a stable picture of performance during outages. The best-prepared teams are those that can continue reporting confidently even when one dataset pauses.

Your action plan

To keep visibility and performance tracking steady during the freeze:

• Cross-check alternative tools: Use Google Analytics, Looker Studio or third-party rank trackers to fill reporting gaps until Search Console data resumes.

• Annotate the reporting period: Flag the outage in performance reports to avoid confusion when data suddenly catches up.

• Monitor Google’s status updates: Follow Search Central’s official X (formerly Twitter) account or community forum for real-time recovery notices.

• Hold off on reactive decisions: Avoid major SEO adjustments until accurate post-freeze data is available to confirm any real trends.

• Evaluate reporting processes: Use this downtime to strengthen data redundancy. Integrate multiple data streams into dashboards for better continuity in the future.

Build your next creative stack with Online Marketing Gurus

Today’s creative ecosystem runs on three engines: OpenAI for ideas, Meta for reach and Google for results. The opportunity lies in how you connect them. From AI-powered brainstorming to precision targeting and data-backed optimisation, the new creative stack is about working smarter across every stage of the campaign lifecycle.
At Online Marketing Gurus, we help brands unify this stack by blending AI tools, social reach and search performance into one cohesive strategy. Let’s build a marketing system that learns, adapts and performs faster than your competitors. Talk to the Gurus about your next campaign.

About the Author

Andrew Raso

Andrew Raso, Co-founder and Global CEO of Online Marketing Gurus, has been instrumental in transforming the agency from a start-up into a $15 million global powerhouse. Since co-founding OMG in 2012 with colleague Mez Homayunfard, Andrew has leveraged his deep expertise in SEO and digital marketing to drive OMG’s expansion across Australia, the US, and Singapore.