Google is phasing out offline conversion imports through the Google Ads API for some developers starting June 15th.

Advertisers and martech providers that rely on offline conversion imports, including enhanced conversions for leads, will need to migrate workflows to the Data Manager API to avoid disruptions.

Details. Google notified developers that offline conversion imports using the UploadClickConversions request will stop working after June 15, for accounts that have not used the functionality in the last 180 days.

The change applies to offline conversion imports and enhanced conversions for leads. Other Google Ads API operations will continue functioning normally.

Google says affected developers should move those workflows to the Data Manager API going forward.

Why we care. Offline conversion imports are critical for measuring leads, sales, and other actions that happen outside the web journey. If integrations are not migrated in time, conversion data could stop flowing into Google Ads, which may impact reporting, attribution, and automated bidding performance. The update also signals Google’s continued shift toward centralized, AI-driven data infrastructure tied more closely to first-party data and automation.

The bigger picture. The move is part of Google’s broader push toward centralized data ingestion and automated measurement infrastructure.

Google describes the Data Manager API as a unified ingestion system for sending advertiser data into Google Ads, including Customer Match and conversion imports. The company also says the newer API offers a better developer experience and additional functionality not available in the existing workflow.

Between the lines. As attribution becomes more privacy-focused and increasingly dependent on first-party data, Google continues consolidating advertiser tools into fewer systems that are more tightly connected to automation and AI-driven campaign products.

For developers and platforms, the migration may require updating integrations, rebuilding import processes, and testing new ingestion workflows ahead of the deadline.

What’s next. Developers can continue using the Google Ads API for all non-offline conversion operations.

However, any workflows involving offline conversion imports should be migrated to the Data Manager API before June 15th, when the existing functionality begins failing for affected accounts.

First spotted. This update was spotted by PPC Specialist Arpan Banerjee who shared the comms he received on LinkedIn.

Microsoft Advertising is bringing LinkedIn profile targeting to connected TV campaigns, giving advertisers a new way to blend professional audience data with streaming inventory.

The announcement was made by Product Liaison Navah Hopkins during the SEM Stories event on May 14.

Why we care. Microsoft has long differentiated itself through access to LinkedIn audience data. Bringing that targeting capability into connected TV extends those signals into a fast-growing upper funnel format that has historically lacked precise professional targeting.

For B2B advertisers especially, the move could help bridge the gap between brand awareness and performance measurement.

What’s new. According to Hopkins, advertisers can now target connected TV audiences using LinkedIn profile attributes tied to a user’s profession.

That means marketers may be able to reach viewers based on professional characteristics such as:

• Industry
• Job function
• Company category
• Professional identity signals

Hopkins framed the feature as a way to build “really meaningful” audience lists that are less dependent on click-based intent signals.

The bigger picture. The announcement fits into Microsoft’s broader push toward AI-powered and audience-first advertising experiences.

During the session, Hopkins repeatedly emphasized the convergence of brand and performance marketing, arguing that AI-driven journeys are collapsing traditional funnels.

Connected TV sits squarely in that conversation.

Historically, CTV has been treated as a brand-heavy channel with weaker attribution than search or shopping campaigns. LinkedIn-powered audience targeting could make those campaigns more actionable for performance-minded marketers who need tighter audience controls.

The update also strengthens Microsoft’s positioning against competitors in both the streaming and B2B advertising markets.

What to watch. Key questions remain around, available markets, measurement and attribution capabilities, how granular LinkedIn audience segmentation will become in CTV campaigns and privacy and compliance controls for professional audience targeting.

Still, the announcement gives Microsoft another differentiator in a crowded CTV market where advertisers increasingly want stronger audience precision without sacrificing scale.

Google released version 24.1 of the Google Ads API, introducing deeper reporting segmentation, expanded experiment support, and new security features as advertisers continue adapting to increasingly automated campaign environments.

The update also prepares developers for Google’s upcoming data retention policy changes, which take effect next year.

Why we care. The release focuses on three areas that have become increasingly important for advertisers: visibility into performance, creative control, and testing automation.

The update also gives brands more control over how creatives appear in Demand Gen campaigns, an area where automation has often limited customization.

Advertisers and developers that rely heavily on reporting infrastructure will also need to prepare for Google’s upcoming 37-month data retention limit before it starts affecting historical performance analysis in 2026.

Mobile reporting gets more granular. One of the biggest additions is a new mobile device platform segment that lets advertisers break out reporting by operating system.

Using the new segments.mobile_device_platform field, developers can now isolate campaign and customer-level performance across iOS and Android traffic.

That matters because user behavior often varies significantly between operating systems, particularly for app marketers, ecommerce advertisers, and brands optimizing conversion value.

Demand Gen adds classic image support. Google is also giving advertisers more creative control inside Demand Gen campaigns.

The release adds support for static image ads through the classic_display_images field in DemandGenMultiAssetAd, allowing brands to upload creatives that run on the Google Display Network exactly as designed, without AI-generated asset combinations.

The feature appears targeted at advertisers that want stricter control over branding and asset presentation.

Passkeys come to Google Ads. Security is another major focus in v24.1.

Google introduced a new passkey_enabled field that indicates whether a user has enabled passkey authentication for their Google Ads account.

The update follows Google’s broader push toward passwordless authentication and increased protection around sensitive account actions.

Experiment support expands. Google is significantly expanding support for Experiments, one of the platform’s core testing frameworks.

Advertisers can now run and compare experiments across:

• AI Max campaigns
• Video campaigns
• Demand Gen campaigns
• Performance Max campaigns

The release also adds more transparent reporting across experimental arms, including metrics such as clicks, conversions, and impressions, making side-by-side analysis easier.

The move reflects Google’s broader strategy of standardizing experimentation across its AI-driven campaign products.

A major data retention change is coming. Google also reiterated that beginning June 1st, Google Ads and related measurement APIs will move to a 37-month retention limit for granular reporting data, including daily, weekly, and hourly statistics.

To support the transition, v24.1 introduces a new error code: DateRangeError.REQUESTED_DATE_GRANULARITY_NOT_SUPPORTED.

Developers querying older granular datasets will need to update reporting workflows before the policy change takes effect.

What’s next. Google says updated client libraries and code samples for v24.1 are already available.

The company is also hosting a live walkthrough of the release across Discord, YouTube Live, and LinkedIn Live.

Google is expanding its push into AI assistants for advertisers and retailers, embedding guidance tools directly into Merchant Center to simplify setup, troubleshooting and optimization.

What’s happening. Google has been spotted testing Merchant Advisor, an AI-powered chatbot integrated into Google Merchant Center. The feature is currently in beta and appears designed to provide merchants with personalized recommendations and support inside the platform.

How it works. Merchant Advisor proactively surfaces tasks and suggestions, such as setting up a returns policy or completing account configuration steps. The goal is to give merchants an always-on assistant that can help improve feed quality and overall account health.

The bigger trend. The rollout fits into Google’s broader strategy of embedding AI assistants across its marketing products. Merchant Advisor follows earlier launches like Google Ads Advisor and Analytics Advisor, signaling a future where AI copilots become standard across campaign management and measurement tools.

Between the lines. Merchant Center can be technically complex, especially for smaller retailers managing feeds, policies and diagnostics. An embedded AI assistant could reduce friction, speed up onboarding and help merchants identify optimization opportunities they might otherwise miss.

Spotted by. The feature was first seen live by Tamara Hellgren after earlier references surfaced in a Google Ads Decoded podcast episode focused on retail.

The bottom line. Google is turning Merchant Center into a more guided, AI-assisted experience, part of a larger shift toward automation and embedded support across its advertising ecosystem.

Google Search Query Reports are becoming less literal and more AI-interpreted, reflecting inferred intent rather than exact user searches.

What’s happening. Google has clarified that the search terms shown in Search Query Reports may not exactly match what users typed. Instead, the platform may display the “closest approximation” of a query because of the complexity of modern search behavior.

What’s behind it. The change reflects how heavily AI now influences Google Ads matching systems. Rather than relying solely on exact keywords, Google increasingly interprets user intent, context and behavior signals to determine which ads to show.

Why we care. For advertisers, this means Search Query Reports may become less of a direct mirror of user language and more of a summarized representation of intent. That could make query analysis, negative keyword decisions and match-type strategy more complicated and less reliable.

Discovered by. The update was spotted by Adsquire founder, Anthony Higman on an official Google help page covering ad group and asset group prioritization within Google Ads.

The bottom line. Google Ads is continuing its shift from keyword matching toward AI-driven intent modeling — and advertisers may now have less visibility into the exact searches triggering their ads.

Google is bringing Gemini into Google Ads dashboards, aiming to make data analysis more interactive, visual and accessible.

What’s happening. Google Ads is rolling out a new Dashboards feature that lets advertisers explore performance data using charts, graphs and tables, powered by Gemini.

Users can customise views simply by typing prompts, with the dashboard updating in real time based on their queries.

Why we care. Data analysis in Google Ads has traditionally required manual setup and navigation across reports.

This update shifts that workflow toward a more conversational model, where advertisers ask questions and get instant visual answers.

Zoom in. Dashboards will display key metrics like impressions, clicks, video views and cost, alongside visual breakdowns of performance across devices, audiences and campaign types.

The goal is to give advertisers a clearer, faster way to understand what’s happening in their accounts.

What to watch. How widely advertisers adopt prompt-based reporting, and whether this reduces reliance on custom-built reports and external analytics tools.

What’s next. Google says more details will be shared at Google Marketing Live.

Bottom line. Google is turning reporting into a conversation — using AI to help advertisers get answers faster and act on them sooner.

OpenAI is making a clearer push into e-commerce advertising by letting retailers generate ads directly from their product catalogues inside ChatGPT.

What’s happening. Retailers can now connect product feeds to ChatGPT, allowing the platform to automatically create ads using product names, images and attributes, instead of building campaigns manually.

The ads themselves don’t change for users. They still appear beneath responses and are clearly labelled as sponsored.

Why we care. Running ads at scale has been a major barrier for e-commerce brands in ChatGPT.

This update removes that friction, especially for retailers with large inventories, by turning product catalogues into ready-to-run ad campaigns.

Zoom in. Brands set rules for which products to include, then let the system generate ads automatically.

It mirrors how shopping campaigns work on platforms like Google, where structured feeds power both organic and paid visibility.

What’s new. Previously, product data could inform ChatGPT’s answers, but it couldn’t be used for advertising.

Now, that same data powers both, effectively linking organic presence with paid campaigns.

Between the lines. This signals a shift in how OpenAI plans to monetise shopping.

Rather than taking a cut of transactions, it’s moving toward capturing ad budgets already spent on platforms like Amazon and Meta.

What they’re saying. Industry analyst Debra Aho Williamson called feed-based automation “table stakes,” noting that ChatGPT’s edge lies in serving ads based on conversational intent rather than traditional signals.

Ad tech partners like StackAdapt say the setup integrates easily with existing feeds, lowering adoption barriers.

Context. The move follows a series of performance-focused updates, including cost-per-click bidding and new conversion tracking tools.

Cost-per-action models are also reportedly in development, pointing to a deeper push into performance advertising.

What to watch. Expect more retailers to test ChatGPT as a performance channel as setup becomes easier. The bigger question is whether conversational intent can drive conversions as effectively as traditional search or marketplace signals.

Bottom line. OpenAI is turning product feeds into ads — making ChatGPT a more viable, scalable channel for e-commerce advertising.

Google is set to automatically link Google Ads accounts with associated YouTube channels — according to communications sent to multiple advertisers — tightening the connection between video engagement and ad performance.

What’s happening. Advertisers have received notices that, from June 10, 2026, Google Ads accounts that aren’t already linked to a YouTube channel will be automatically connected.

The update removes the need for manual linking and ensures advertisers can access video engagement data and targeting features by default.

Why we care. Linking a YouTube channel unlocks deeper insights and more advanced targeting options — something many advertisers either overlook or delay setting up.

By automating the process, Google is effectively making video data a standard part of campaign optimisation.

Zoom in. Once linked, advertisers can access organic video metrics, including view counts, directly within Google Ads.

They can also build audience segments based on how users interact with their YouTube content — from video views to channel engagement.

What else. The integration allows advertisers to track “earned actions,” such as subscriptions or additional views driven by ads, and use those engagements as conversion signals.

That creates a clearer picture of how video campaigns influence user behaviour beyond just clicks.

What to watch. How advertisers adapt their measurement strategies once organic and paid video data are combined, and whether this leads to broader use of engagement-based conversion tracking in campaigns.

Bottom line. Google is making YouTube data harder to ignore — turning automatic linking into a default step for better targeting, measurement and performance.

First spotted. Several advertiser reported getting the comms from Google, including Founder of JXT Group, Menachem Ani, founder of PPC News Feed Hana Kobzová, and PPC Specialist Arpan Banerjee.

Adthena is bringing competitive visibility to ChatGPT ads — launching a new platform designed to track how brands show up across prompts, placements and competitors.

What’s happening. Adthena has unveiled its ChatGPT Intelligence Platform, positioning it as the first tool to offer whole-market visibility into ChatGPT Ads — similar to what it already provides for Google Ads.

The platform monitors more than 300,000 daily prompts, tracking which brands are advertising, where ads appear, and what messaging they use.

Why we care. ChatGPT’s native ads tools currently show advertisers a limited, self-focused view of performance.

Adthena is stepping in to fill that gap — giving advertisers insight into competitors, share of voice and prompt-level activity in a channel that’s still largely opaque.

Zoom in. The platform offers a full view of how ads appear across ChatGPT conversations, alongside competitive intelligence on who is bidding, where and with what creative.

It also includes real-time recommendations to optimise campaigns, helping advertisers act on insights rather than just observe them.

What else. Advertisers can analyse ad copy performance, monitor brand presence and track share of voice — all within a single dashboard that combines ChatGPT and Google Ads data.

That cross-channel view is designed to help teams make smarter budget decisions as search behaviour shifts.

Context. The launch follows Adthena’s earlier AdBridge tool, which helps advertisers migrate Google Ads campaigns into ChatGPT’s Ads Manager.

Together, the tools signal a growing ecosystem forming around AI-driven search advertising.

What they’re saying. CMO Ashley Fletcher said early adopters will shape the competitive landscape — and that the new platform “tells you exactly what to do about it.”

What to watch. Expect to see more third-party tools emerge as advertisers demand better visibility into AI-driven ad environments. Adoption will likely depend on how quickly brands start treating ChatGPT Ads as a core performance channel, while pressure may build on platforms like ChatGPT to improve their own native reporting capabilities.

Bottom line. Adthena is positioning itself as the visibility layer for ChatGPT Ads — giving advertisers a clearer view of a fast-growing but still opaque channel.

Google is expanding Merchant Center for Agencies worldwide, giving agencies a centralized way to manage product data, diagnose issues and spot growth opportunities across multiple clients.

What’s happening. After launching in the U.S. and Canada, Merchant Center for Agencies is now rolling out globally to all agency users.

The tool is designed to help agencies manage merchant accounts at scale as product data becomes more critical to performance across shopping and discovery experiences.

Why we care. Managing product feeds across multiple clients has long been fragmented and time-consuming.

This update brings those workflows into one place — helping agencies monitor account health, fix issues faster and optimize product data more efficiently.

Zoom in. The platform introduces a unified dashboard that gives agencies a bird’s-eye view of all client accounts, including onboarding status and critical alerts.

Portfolio-wide diagnostics allow teams to quickly identify issues across accounts, filter by market or campaign type, and prioritise fixes based on potential impact.

What else. Agencies can also monitor store quality metrics and inventory health, including out-of-stock products, while managing promotions directly within the platform.

On the performance side, new insights help identify high-potential products with low visibility — which can then be tagged and prioritised in ad campaigns.

What to watch:

• How agencies integrate this into existing workflows
• Whether this reduces reliance on third-party feed management tools
• If more advanced optimisation features follow

Bottom line. Google is giving agencies a more scalable way to manage product data — turning Merchant Center into a more strategic performance tool, not just a feed repository.

In this episode of PPC Live The Podcast, I sit with Veronika Höller to unpack a real-world PPC mistake — from campaigns that looked perfect on the surface to the deeper issues that were quietly killing performance.

From “perfect” campaigns to zero revenue

Veronika Holler didn’t walk into a broken account. Quite the opposite. Everything looked right — clean structure, strong creatives, solid budgets, conversions coming in. On paper, it was a high-performing PPC setup.

But there was one problem: it wasn’t driving revenue.

That disconnect forced a deeper look beyond surface-level metrics. Because while impressions, clicks and conversions were ticking up, the campaigns weren’t actually delivering business impact — and that’s where things started to unravel.

The real issue: nothing stood out

The turning point didn’t come from inside the account. It came from looking outside it.

During competitor research, Veronika realised the brand sounded just like everyone else. The messaging blended into the market. There was no clear reason for a user to choose them over competitors.

From a user perspective, the ads weren’t wrong — they were just forgettable. And in a crowded category, “good” isn’t enough.

That insight reframed the entire problem: it wasn’t a performance issue. It was a positioning issue.

Starting again — from scratch

Instead of tweaking the existing campaigns, Veronika made a bold call: rebuild everything.

That meant new messaging, new creatives, and a new strategic foundation. One key shift was defining not just ideal customers, but also who they didn’t want to target — using anti-ICPs to sharpen the messaging.

They also introduced stronger localisation, tailored landing pages by market, and platform-specific strategies instead of copying campaigns across channels.

It wasn’t optimisation. It was a reset. And it worked.

The mistake that nearly broke everything

But earlier in her career, Veronika made a far more painful mistake — one that many PPC marketers will recognise.

She applied a recommended target CPA… without increasing the budget.

The result? Campaigns stopped delivering. Performance tanked. And worst of all, it went unnoticed over a weekend.

By Monday, the damage was clear — and the client was not happy.

Owning the mistake — and fixing it fast

There was no hiding from it.

Veronika immediately admitted the mistake, explained what happened, and took responsibility. That honesty changed the outcome. While the client was initially frustrated, the situation de-escalated quickly because there was no deflection — just a clear plan to fix it.

The lesson stuck: don’t blindly apply recommendations, and always understand the full context before making changes.

Why failure is part of getting good

For Veronika, mistakes aren’t something to avoid — they’re essential.

“You can only be good if you fail,” she said.

That mindset now shapes how she works and how she mentors others. Mistakes aren’t a sign of incompetence — they’re a sign that work is being done, tested, and improved.

And more importantly, sharing those mistakes helps others avoid repeating them.

The biggest issue she still sees today

Despite all the changes in PPC, one problem keeps showing up: tracking.

Broken implementations, over-reliance on micro conversions, and poor setup in tools like Google Tag Manager are still common.

In a world of smart bidding and automation, bad data doesn’t just limit performance — it actively misleads it.

Without clean tracking, even the best campaigns will fail.

AI won’t fix average marketing

Veronika is clear on one thing: AI is not a shortcut to better performance.

If you feed it average data, you’ll get average results.

Too many marketers rely on AI tools to analyse accounts without first understanding what needs to be improved. But AI can’t create differentiation — it can only optimise what’s already there.

Standing out still requires human thinking, strategy, and creativity.

The mindset that matters now

The biggest takeaway isn’t tactical — it’s mental.

Don’t aim for perfection. Don’t blindly follow recommendations. And don’t assume tools will do the thinking for you.

Instead, trust your instincts, test your ideas, and accept that mistakes are part of the process.

Because in performance marketing, the real risk isn’t failing — it’s playing it safe and blending in.

Google appears to be pulling parts of the Google Tag Manager interface directly into Google Ads — a move that could simplify how advertisers manage tracking and tags.

What’s happening. Advertisers are spotting a new “Manage” option inside the Data Manager section of Google Ads that opens Tag Manager controls without leaving the platform.

The update was first shared by Marthijn Hoiting and Adriaan Dekker, who posted screenshots showing Tag Manager elements embedded within the Google Ads environment.

Why we care. Tag setup and troubleshooting have long been a friction point for advertisers, often requiring multiple tools and technical handoffs.

Bringing Tag Manager functionality into Google Ads could reduce that complexity — especially for smaller teams or advertisers without dedicated dev support.

Zoom in. Inside the Data Manager interface, users can see connected data sources (including Tag Manager) and trigger management actions directly from within Google Ads.

That suggests Google is moving toward a more unified measurement workflow, where tagging, data connections and campaign setup live closer together.

Between the lines. This aligns with Google’s broader push to simplify measurement and improve data accuracy — particularly as privacy changes and signal loss make clean tracking more critical.

It also mirrors recent efforts to make tagging more accessible without heavy technical setup.

What to watch:

• Whether full Tag Manager functionality gets embedded or remains partial
• How this impacts workflows between marketers and developers
• If this becomes the default way to manage tags for advertisers

Bottom line. Google is quietly reducing the gap between campaign setup and measurement — bringing tagging closer to where ads are actually managed.

First seen. This update was shared by Adrian Dekker on LinkedIn, who credited Data and Analytics specialist Marthijn Hoiting for spotting it.

Microsoft Advertising is giving advertisers more flexibility in reporting, with custom columns now supporting all conversion metrics — a move aimed at deeper, more tailored campaign analysis.

What’s happening. According to Microsoft’s product liaison Navah Hopkins, advertisers can now build custom metrics using the full range of conversion data available in the platform.

This includes both all conversions and primary conversions, allowing marketers to align reporting more closely with their specific goals.

Why we care. Standard reporting often doesn’t reflect how businesses actually measure success. By expanding custom columns, Microsoft is enabling advertisers to create metrics that better reflect their own performance definitions — whether that’s based on lead quality, revenue or blended conversion actions.

This is especially useful for advertisers managing multiple conversion types or complex funnels.

More control over performance metrics. Advertisers can now create custom columns using ratios and combinations of metrics that matter most to them — such as cost per qualified lead, blended CPA or conversion rate based on primary goals.

Revenue and ROAS calculations will also reflect the values set at the conversion goal level, giving more accurate insights tied to business outcomes.

Between the lines. This update signals a shift toward more flexible, advertiser-defined measurement — rather than relying solely on platform-standard metrics.

It also reflects ongoing demand for better reporting customisation as campaigns become more automated and complex.

What to watch:

• How advertisers use custom metrics to guide optimisation decisions
• Whether this leads to more consistent reporting across teams and stakeholders
• If similar flexibility expands across other areas of the platform

Bottom line. Microsoft is giving advertisers more control over how they measure success — turning custom columns into a more powerful tool for campaign analysis.

Advertisers are starting to push back on gaps in AI Max capabilities — particularly around landing page control — as Google continues its shift away from legacy Dynamic Search Ads (DSA).

What’s happening. In a LinkedIn exchange, digital marketing expert Gabriele Benedetti raised concerns about AI Max lacking the same level of URL-based targeting controls that DSA campaigns offered.

His point: DSA allowed advertisers to structure campaigns around website architecture — using categories, URL paths and page rules to guide where traffic lands. That level of control, he argued, is not yet fully replicated in AI Max.

Why we care. For many advertisers — especially those managing large or structured websites — aligning campaign structure with site architecture is key to performance. Losing granular control over landing destinations could impact relevance, user experience and ultimately conversion rates.

This highlights a broader tension in Google Ads today: automation vs control.

Google responds. Google Ads Liaison, Ginny Marvin responded, clarifying that AI Max does support several URL-based controls, including:

• URL rules and combinations
• Page feeds with custom labels
• URL inclusions at ad group level and exclusions at campaign level

However, she acknowledged that not all DSA targeting rules are currently supported — such as “page contains” conditions.

Between the lines. Google is not removing control entirely — but it is reshaping how that control works. Instead of granular rule-building, advertisers are being pushed toward structured inputs like page feeds and labels that AI can interpret.

Migration reality check. For advertisers moving from DSA to AI Max, existing URL rules will carry over — but with limitations. Unsupported rules will remain active as read-only, meaning they’ll continue to function but cannot be edited.

That’s a temporary bridge, not a long-term solution.

What’s next. Google says it plans to expand controls further, including bringing content and title-based exclusions to the account level later this year.

This would complement AI Max’s existing “inventory-aware” features, which already exclude out-of-stock items automatically.

Bottom line. AI Max is evolving, but it’s not yet a full replacement for DSA when it comes to granular control — and advertisers are making that clear.

Dig deeper. Full discussion on LinkedIn.

Google is rolling out new AI-driven bidding and budgeting features across Search, Shopping and Performance Max — aimed at helping advertisers capture more demand without increasing manual effort.

What’s happening. Google is expanding its automation stack with updates like Journey-aware Bidding, Smart Bidding Exploration and demand-led budget pacing. Together, these changes are designed to help campaigns respond more dynamically to shifting consumer behaviour.

The focus: letting AI identify and act on opportunities advertisers may not see themselves.

Why we care. These updates aim to capture more conversions without increasing manual work, using AI to find new demand and optimise spend in real time. By improving how bids respond to full-funnel signals and how budgets adapt to peak demand, campaigns can become more efficient and less reliant on constant adjustments.

Ultimately, it’s about getting more value from the same budget while staying competitive in a fast-changing search landscape.

Smarter bidding gets more context. Journey-aware Bidding (beta) allows advertisers to feed more of the customer journey into optimisation, including non-biddable conversions. This gives Google AI a fuller picture of what leads to actual sales — not just initial actions like form fills.

At the same time, Smart Bidding Exploration is expanding beyond Search. Already delivering an average 27% increase in unique converting users, it will soon roll out to Performance Max and Shopping campaigns, helping advertisers tap into less obvious, incremental queries.

Budgets that follow demand. On the budgeting side, Google is building on its campaign total budgets feature, which allows advertisers to set spend across a defined period instead of relying on daily limits.

The next step is demand-led pacing — where AI automatically adjusts spend based on real-time demand, increasing budgets on high-opportunity days and pulling back during slower periods, without exceeding overall limits.

Advertisers using total budgets have already seen a reported 66% reduction in manual budget adjustments.

Why this is a big deal. Budget management has historically been one of the most manual parts of campaign optimisation. By automating pacing, Google is reducing the need for constant monitoring while aiming to improve efficiency.

What to watch:

• How much control advertisers are willing to give up for automation
• Whether incremental gains from exploration translate into profitable growth
• How transparent these systems remain as they scale

Bottom line. Google is directing advertisers to AI to handle both bidding and budgeting — shifting the advertiser role from manual optimisation to guiding inputs and trusting the system to find growth.

Google is expanding its Analytics Data API to include cross-channel conversion reporting — giving developers programmatic access to paid and organic performance data.

What’s happening. The new feature, currently in alpha, allows Google Analytics and Google Ads users to pull conversion data across channels via the API — mirroring what’s available in the Conversion performance report in the Analytics interface.

This means developers can now access the same insights without relying on manual reporting.

Why we care. As measurement becomes more complex, advertisers need unified views of performance across paid and organic channels. This update enables teams to automate reporting, integrate data into their own systems and build more advanced analysis workflows.

It’s particularly valuable for businesses managing multiple platforms and looking to centralise performance data.

The caveat. This feature may not be available to every Google Analytics property yet. Google says it is actively working to expand access, and advertisers should check with their support teams to confirm eligibility.

What to watch:

• When the feature moves beyond alpha and becomes widely available
• How advertisers use API access to build custom attribution models
• Whether more reporting capabilities are added to the Data API

Bottom line. By bringing cross-channel conversion data into the API, Google is giving advertisers and developers more control over how they access, analyse and act on performance data.

Looking to take the next step in your search marketing career?

Below, you will find the latest SEO, PPC, and digital marketing jobs at brands and agencies. We also include positions from previous weeks that are still open.

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(Provided to Search Engine Land by SEOjobs.com)

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• Sr. SEO/AEO Manager (B2B SaaS – US or Canada Based)
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  The Basics: Growth Plays is hiring a Senior SEO/AEO Manager based in the US, Canada or LATAM, to support and manage ongoing customer engagements and relationships. You’ll act as the main point of contact for your clients, and focus on building relationships and trust while driving strategy-aligned growth for the long term. This role is […]
• Intermediate Search Specialist
  April 17, 2026
  We are seeking an intermediate-level SEO Specialist for Hive Digital, a cutting-edge and award-winning agency that prides itself on helping change the world for the better. We offer a highly collaborative team that works together to deliver the best possible outcomes for our clients in a fast-paced, fun work environment. Are you ready to bring […]

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• Growth Marketing Associate
  May 15, 2026
  About the Role We’re looking for a contract-to-hire Growth Marketing Associate to help drive measurable growth across our digital channels. This role combines creative social media content, the analytical rigor of performance marketing, and the project management muscle to run a real event end-to-end. You’ll own a meaningful slice of the funnel — producing the […]
• Sr. Product Manager, Programmatic Advertising
  May 15, 2026
  FreeWheel, a Comcast company, provides comprehensive ad platforms for publishers, advertisers, and media buyers. Powered by premium video content, robust data, and advanced technology, we’re making it easier for buyers and sellers to transact across all screens, data types, and sales channels. As a global company, we have offices in nine countries and can insert […]
• Growth Marketing Senior Associate: Digital Acquisition & AI
  May 15, 2026
  DraftKings is hiring a Growth Marketing Senior Associate in New York, NY. This role involves developing and executing digital marketing campaigns across various channels to drive customer acquisition and engagement. Ideal candidates have at least 2 years of digital marketing experience, a relevant Bachelor's Degree, and skills in optimizing campaigns, A/B testing, and performance analysis. […]
• Growth Marketing Manager — Home Rebuilds & Real Estate
  May 15, 2026
  A construction and rebuilding firm in California seeks a Marketing Manager to drive lead generation efforts central to helping homeowners rebuild. You will design and optimize multi-channel campaigns aimed directly at victims of the Eaton Fire, blending aggressive marketing with empathetic communication. The ideal candidate has a proven background in generating high-ticket B2C leads, specializes […]
• Strategic Growth Marketing Account Lead
  May 15, 2026
  A leading technology firm in North Bethesda seeks an Associate Account Manager to enhance client relationships through strategic marketing solutions. The successful candidate will provide insights and develop client-focused strategies in a collaborative environment. To thrive, candidates should possess 1-3 years of digital marketing experience, excellent communication skills, and some familiarity with SEO and marketing […]

Other roles you may be interested in

Senior Search Marketing Manager, Acadaca (Remote)

• Salary: $75,000 – $85,000
• Strategize & Execute: Develop, launch, and manage comprehensive paid search, display, shopping, pmax, demand gen, youtube and ctv campaigns from conception to optimization, ensuring alignment with client business objectives.
• Performance Optimization: Proactively manage bids, budgets, and targeting to achieve and exceed key performance indicators (KPIs) such as Revenue and ROAS.

Senior Manager, SEO/AEO, ActiveCampaign (Remote)

• Salary: $140,500 – $193,200
• Identify opportunities for technical improvements across the ActiveCampaign website, prioritize them based on their potential business impact, and collaborate with cross-functional stakeholders to implement them.
• Pioneer LLM optimization and Answer Engine Optimization (AEO) by developing content strategies that ensure ActiveCampaign is the authoritative source material used by LLMs.

SEO Marketing Manager, Care.com (Hybrid, Dallas, TX)

• Salary: $85,000 – $95,000
• Organic Growth: Build and execute the SEO roadmap across technical, content, and off-page. Own the numbers: traffic, rankings, conversions. No handoffs, no excuses.
• AI-Optimized Search (AIO): Define and drive CARE.com’s strategy for visibility in AI-generated results — Google AI Overviews, ChatGPT, Perplexity, and whatever comes next. Optimize entity coverage, content structure, and schema to ensure we’re the answer, not just a result.

Manager, SEO, KINESSO (Hyrid, New York, NY)

• Salary: $90,000 – $95,000
• Manage senior analysts and help analysts grow into the next level of their career.
• Translate clients’ business goals and marketing objectives into successful search engine optimization strategies.

Senior Marketing Manager, Vanguard Renewables (Remote)

• Salary: $120,000 – $182,000
• Work closely with CMO and RNG team to develop and execute a strategic marketing roadmap aligned with business priorities.
• Serve as the primary marketing liaison for RNG team, acting as the connective tissue between the Marketing and Commercial groups.

SEO Manager, Veracity Insurance Solutions, LLC, (Remote)

• Salary: $100,000 – $135,000
• Lead, coach, and develop a high-performing team of SEO Specialists
• Set clear expectations, quality standards, workflows, and growth paths across the team

Marketing, Social Media & PR Manager, PARTNERS Staffing (Fort Myers, FL)

• Salary: $75,000 – $85,000
• Develop and execute integrated marketing campaigns for shows, content releases, events, and brand initiatives
• Identify target audiences and create strategies to grow reach and engagement

Senior Paid Media Manager, Brightly Media Lab (Remote)

• Salary: $70,000 – $100,000
• Directly build, manage, and optimize campaigns within Google Ads, Microsoft Ads, and Facebook Ads (Meta).
• Serve as the lead point of contact for your book of clients, taking full ownership of their success and growth.

Marketing Specialist, The Bradford group (Hybrid, The Greater Chicago area)

• Salary: $60,000 – $62,000
• Launch and manage paid social campaigns primarily on Meta platforms.
• Oversee daily budgets and performance optimizations against revenue and ROI goals, using data-driven insights to continuously improve results.

Paid Search Specialist, Maui Jim Sunglasses (Peoria, IL)

• Salary: $65,000 – $70,000
• Plan, set up, and manage paid search, display, and shopping campaigns on Google Ads.
• Manage and optimize advertising budgets to achieve revenue and efficiency targets.

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