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Category: Microsoft Advertising

  • How to Manage Ad Targeting and API Updates Without Chaos

    How to Manage Ad Targeting and API Updates Without Chaos

    An advertising-platform release can create two very different jobs. A targeting feature asks whether you can reach a better audience. An API change asks whether your reporting, security checks, stored data, and automation will continue to work. Treat both as features to try, and you can spend budget before measurement is ready or discover a broken data dependency after the damage is done.

    That distinction matters now because Microsoft Advertising has extended LinkedIn profile targeting to connected TV campaigns, while Google Ads API v24.1 adds reporting, creative-control, experiment, authentication, and retention-related changes. You need a release process that protects existing operations first, validates measurement second, and tests growth opportunities third.

    Classify each change before scheduling the work

    The loudest feature should not automatically become the first task. Rank changes by what happens if you ignore them. A new audience may represent an opportunity, but a data-retention limit can permanently narrow the history available to your reporting system.

    Use five practical classes:

    • Continuity changes: retention limits, unsupported requests, client compatibility, and anything else that can interrupt a production workflow.
    • Measurement changes: new segments or metrics that alter how performance can be divided and interpreted.
    • Security changes: fields that help you identify account protections or authentication gaps.
    • Control changes: options that affect how an approved creative is uploaded, transformed, or displayed.
    • Growth changes: new audiences, inventory, campaign types, and experiment surfaces.

    Work through them in that order unless a documented dependency changes the sequence. Continuity comes first because lost history or a failed reporting job can affect every campaign. Measurement comes before growth because you cannot judge a new audience reliably until you know what the reporting can and cannot observe.

    For the current updates, the 37-month Google Ads data-retention boundary belongs in the continuity queue. The mobile-device platform segment belongs in measurement. The passkey field belongs in security. Demand Gen image control belongs in control. LinkedIn-based CTV targeting belongs in growth. That classification gives your team an actionable backlog rather than an undifferentiated list of announcements.

    Test professional CTV targeting as an audience hypothesis

    A media planner runs a small connected TV audience test by selecting one professional audience cluster for comparison.

    Microsoft’s CTV expansion lets advertisers use professional attributes such as industry, job function, company category, and professional identity signals. For a B2B advertiser, that can connect broad streaming exposure with a more relevant professional audience.

    It does not turn a professional attribute into buying intent. A viewer’s job function may indicate fit, but it does not prove that the viewer is researching a purchase. Treat the targeting as a testable audience hypothesis: people matching this professional profile should respond differently from a suitable comparison audience when the message and measurement remain consistent.

    Build the first test in this order:

    1. Choose one buying group. Describe it with the smallest useful combination of industry, function, and company characteristics. If you begin with a heavily stacked audience, you will not know which condition created the result or restricted delivery.
    2. Write down what the attributes mean. Record the exact audience definition, intended buying role, exclusions, eligible markets, and date of activation. Platform labels are not a substitute for an internal audience specification.
    3. Hold avoidable variables steady. Use comparable creative, offers, geography, inventory conditions, and evaluation windows across the audience cells. Otherwise, a creative or delivery difference can masquerade as a targeting effect.
    4. Select an observable outcome before launch. Do not let an easy-to-read delivery metric become the business objective by default. Use the conversion, lift, or qualified-response signal that your measurement stack can support consistently.
    5. Set a decision rule. Define what evidence would justify expanding, revising, or stopping the audience. Making that decision after seeing the result invites selective interpretation.
    6. Review privacy and compliance. Confirm that the proposed professional segmentation, creative, data handling, and market coverage fit your organization’s requirements before the audience begins receiving ads.

    Measurement deserves extra attention. CTV has traditionally operated as a brand-oriented channel with less direct attribution than search or shopping. Professional targeting can improve audience relevance, but it does not automatically resolve that measurement gap. Keep exposure quality, downstream response, and attribution confidence separate in your readout.

    Several implementation details remain uncertain, including market availability, segmentation granularity, measurement capabilities, and privacy considerations. Verify those items in the account and market you intend to use. Do not build a forecast around targeting combinations or reporting dimensions you have not confirmed are available.

    Turn Google Ads API v24.1 into an engineering checklist

    An engineer checks reporting, security, creative, experiment, automation, and data modules before an API workflow reaches production.

    API adoption is not complete when a client library installs successfully. The real work sits downstream: query builders, schemas, dashboards, experiment records, asset workflows, authentication reports, exception handling, and historical storage.

    Start by mapping each v24.1 capability to the system it can affect:

    The retention change deserves a separate migration task. Search your query code, scheduled exports, dashboards, year-over-year reports, model-training inputs, and audit workflows for requests that can reach beyond 37 months. Then verify what history is still queryable and preserve future data at the granularity your business actually needs.

    An archive is useful only if you can interpret and restore it. Store the account identifier, reporting period, timezone, currency context, field definitions, extraction timestamp, and relevant attribution or configuration metadata alongside the metrics. Test a restore into a clean table before relying on the archive. A successful export file is not proof of a recoverable reporting history.

    Update error handling as well. DateRangeError.REQUESTED_DATE_GRANULARITY_NOT_SUPPORTED identifies an unsupported date-range request. Treat a confirmed policy boundary as a query-design problem, not a transient failure to retry indefinitely. Logging the requested dates and granularity will make the remediation far faster.

    Put targeting and API work through one change-control loop

    Marketing and engineering do not need separate definitions of a successful platform update. They need one shared record that distinguishes a business hypothesis from a technical dependency.

    Change typeQuestion to answer firstEvidence requiredSafe response if it fails
    New audienceCan you isolate the audience effect?Documented audience cells, stable measurement, and a predefined decision rulePause the new segment without disturbing the existing campaign structure
    Reporting dimensionCan every downstream system accept and interpret it?Schema validation and reconciled totals against a baselineRemove the new dimension from production queries while preserving the test
    Creative-control fieldDoes the delivered asset match the approved intent?Asset-level quality review and recorded campaign mappingReturn to the previously approved asset path
    Retention boundaryCan analysis continue after platform history expires?External archive plus a successful restore testNo platform rollback exists; repair the archive and shorten unsupported queries
    Authentication-status fieldWho acts when an account lacks the expected protection?Verified field ingestion, ownership, and a remediation queueKeep the current authentication flow while correcting the reporting or rollout process

    Every change ticket should name an owner, impacted accounts, affected queries or campaigns, the validation evidence, a rollback path, and the date when someone will make a keep-or-revert decision. If no one owns that decision, the change is not ready for production.

    Keep the Microsoft audience test and Google API migration separate even if they appear in the same planning cycle. One measures whether professional targeting improves an advertising outcome. The other protects and expands the systems used to report that outcome. Combining them creates two moving parts and a result that is harder to diagnose.

    Key takeaways

    • Prioritize continuity and data-retention work before testing new reach.
    • Treat professional CTV attributes as proxies for audience fit, not proof of current purchase intent.
    • Confirm Microsoft CTV availability, measurement, segmentation, and compliance conditions in the actual account and market before forecasting results.
    • Test every new Google Ads API field through queries, schemas, storage, and dashboards before promoting it to production.
    • Maintain an external, restorable archive if your reporting requires more than 37 months of Google Ads history.
    • Give every rollout a named owner, acceptance evidence, rollback path, and decision date.

    At your next platform-change review, create two queues: one for operational deadlines and one for controlled growth tests. Clear the dependencies that can damage data or reporting, validate the measurement layer, and then give the new audience or creative capability a fair test.

    References

  • Unlock More with Microsoft’s Customizable Conversion Metrics

    Unlock More with Microsoft’s Customizable Conversion Metrics

    As someone exploring the ins and outs of Microsoft Advertising, I’ve discovered an update that’s sure to enhance our campaign analysis. Microsoft is now allowing us to customize columns with all conversion metrics, providing us with deeper insights and aligning reports with our unique business goals.

    What does this mean for us? Well, according to Navah Hopkins, our go-to expert at Microsoft, we can now build custom metrics by leveraging the full spectrum of conversion data available in the platform. This means we can track all conversions and primary conversions, enabling us to tailor our reporting to meet our specific objectives more closely.

    Please note the new image showcasing Microsoft’s enhanced custom columns feature. It’s a visual reminder of how these updates can transform our analytical capabilities.

    Why am I excited about this? Because the standard reporting often doesn’t mirror how we truly measure success. By giving us the tools to expand custom columns, Microsoft allows us to define metrics that truly matter—be they lead quality, revenue, or a combination of conversion actions.

    This flexibility is crucial for managing a variety of conversion types or navigating complex marketing funnels. Now, I can create custom columns, using ratios and metric combinations such as cost per qualified lead or conversion rates focused on primary goals.

    Moreover, I appreciate that the revenue and ROAS calculations will now reflect the values that align with my conversion goals, providing more accurate insights directly linked to business outcomes.

    ```json { "alt": "Screenshot of a campaign management interface showing options for creating a new column with metrics and performance criteria.", "caption": "Exploring campaign metrics has never been easier with this detailed interface for customizing columns and viewing performance data.", "description": "This image displays a campaign management interface used for customizing and modifying columns. It includes options to name a new column, add an optional description, and formulate its metrics. The interface allows users to select metrics such as CPA, conversion rates, and revenue, as well as specify the format, in this case, currency. A list of campaigns is visible on the left, indicating a total of 2,581 campaigns, with options to apply saving or cancelling at the bottom." } ```

    What does this change imply for us in a broader sense? It represents a shift toward a more flexible and advertiser-defined measurement approach, instead of relying solely on standardized platform metrics.

    This update highlights the ongoing demand for improved reporting customization as campaigns become increasingly automated and intricate.

    So, what should we keep an eye on? I’ll be observing how advertisers like us utilize these custom metrics to guide optimization decisions, whether consistency in reporting improves across teams, and if similar flexibilities will roll out in other areas of the platform.

    Bottom line? With Microsoft giving us more control over how we measure success, custom columns are evolving into a vital asset for campaign analysis. Read more about this update here.

    Inspired by this post on Search Engine Land.

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  • Microsoft Automated Bidding: How to Choose CPA or ROAS

    Microsoft Automated Bidding: How to Choose CPA or ROAS

    When Microsoft Advertising presents Maximize Conversions or Maximize Conversion Value instead of a standalone Target CPA or Target ROAS strategy, you have not lost those performance controls. Microsoft has moved them inside two broader automated bidding choices.

    Your real decision is now clearer: decide whether the campaign should produce more completed actions or more reported conversion value, then add a CPA or ROAS target only if you can defend it with reliable tracking and business economics.

    Microsoft changed the setup path, not the performance target

    The simplified setup organizes automated bidding around two main strategy families with optional targets. Maximize Conversions can include a target CPA. Maximize Conversion Value can include a target ROAS.

    Your campaign objectiveMain bidding strategyOptional performance targetSignal that must be trustworthy
    Generate more completed conversion actionsMaximize ConversionsTarget CPAWhich actions count as conversions
    Generate more reported conversion valueMaximize Conversion ValueTarget ROASThe value assigned or passed with each conversion

    Microsoft says this restructuring does not change the fundamental bidding behavior. Treat that as a description of the product change, not as a promise that every campaign will produce identical results. Auction conditions, tracking quality, budgets, and the business value of the conversions still matter.

    You also do not need to rebuild existing campaigns that use Target CPA or Target ROAS. They can continue as configured. Portfolio bid strategies are outside this change, so keep them separate when you document or audit the transition.

    Choose between conversion count and conversion value first

    Two channels sort conversion tokens by total quantity on one side and differing economic value on the other.

    Do not begin with the target field. Begin with the outcome the business wants the bidding system to prioritize.

    Choose Maximize Conversions when the counted actions are reasonably comparable. That can fit a campaign built around one qualified lead action, one appointment type, or one product category with similar economics. The important condition is not the name of the conversion. It is whether an additional counted action has roughly the same business meaning as the next one.

    Choose Maximize Conversion Value when one conversion can be materially more valuable than another and Microsoft receives values that represent that difference. A campaign cannot optimize sensibly for value if every conversion receives the same placeholder number or if the values measure revenue while the business actually manages toward margin.

    • Use Maximize Conversions when your primary question is: How many valid actions can this budget produce?
    • Use Maximize Conversion Value when your primary question is: How much meaningful value can this budget produce?
    • Fix measurement before choosing either one when duplicate conversions, low-intent actions, missing values, or inconsistent value rules distort the signal.

    ROAS may sound like the more financially sophisticated choice, but it is only as useful as the conversion values behind it. If those values do not reflect business priorities, Maximize Conversion Value can optimize a clean-looking metric that leads you in the wrong direction.

    Add a CPA or ROAS target only when the number is defensible

    The optional target is a control layered onto the main strategy. Target CPA expresses the average cost per conversion you want the campaign to pursue. Target ROAS expresses the relationship you want between reported conversion value and advertising spend. Neither target repairs weak tracking, and neither should be treated as a guaranteed result.

    1. Connect the target to unit economics. A CPA target should reflect what the business can afford for the specific conversion being counted. A ROAS target should reflect how reported conversion value relates to the economic result the business actually needs.
    2. Check that the target matches the strategy. Do not manage a value-based campaign against CPA simply because CPA is familiar. Do not impose ROAS on a campaign whose conversions lack meaningful value differences.
    3. Inspect the measurement inputs. Confirm that the campaign counts the intended actions, excludes accidental or irrelevant actions, and uses consistent value rules.
    4. Separate a real constraint from a preferred outcome. If exceeding a certain acquisition cost makes the campaign uneconomic, record that explicitly. If the number is merely an aspiration, do not present it internally as a hard financial limit.
    5. Leave the target unset until you can justify it. The target is optional. An invented number creates the appearance of control without a sound business instruction behind it.

    This is where many setup mistakes begin. An advertiser copies a target from another campaign, another market, or an old reporting period without checking whether the conversion definition and economics are comparable. The setting is precise, but the reasoning is not.

    Audit the inputs before changing campaign settings

    Hands inspect connected tracking, value, margin, and history modules before adjusting a campaign target dial.

    The interface change is a good reason to standardize how your team approves automated bidding. Use the same short audit for a new campaign and for any existing campaign you are considering changing.

    1. Write the primary objective in one sentence. State whether the campaign should maximize the number of valid actions or their reported value.
    2. Name the conversion actions included in bidding. If a low-intent event and a completed sale both count, decide whether maximizing their combined count represents the outcome you want.
    3. Test the meaning of conversion values. Ask what each value represents, where it originates, and whether two different values genuinely indicate different business importance.
    4. Map the objective to the strategy. Count maps to Maximize Conversions; value maps to Maximize Conversion Value.
    5. Add the matching target only if approved. CPA belongs with Maximize Conversions. ROAS belongs with Maximize Conversion Value.
    6. Label existing and portfolio strategies correctly. Existing Target CPA and Target ROAS campaigns do not require migration, while portfolio strategies are unaffected.
    7. Evaluate the metric the strategy is designed to optimize. Review conversion quality alongside CPA, or the integrity of reported value alongside ROAS. A favorable platform metric is not enough if the underlying business outcome deteriorates.

    Avoid changing strategy, target, conversion definitions, and value rules at the same time unless a measurement error makes an immediate correction necessary. Multiple simultaneous changes make it harder to identify which decision altered the result and can expose more budget to a poorly understood setup.

    Key takeaways

    • Microsoft Advertising now centers setup on Maximize Conversions and Maximize Conversion Value.
    • Target CPA remains available as an optional control within Maximize Conversions.
    • Target ROAS remains available as an optional control within Maximize Conversion Value.
    • Existing Target CPA and Target ROAS campaigns can continue without required changes.
    • Portfolio bid strategies are unaffected.
    • Your most important choice is whether reliable conversion counts or reliable conversion values better represent the business objective.

    Before your next setup, add four fields to the campaign brief: primary outcome, bidding strategy, optional target, and measurement owner. If the team cannot complete all four with a clear rationale, resolve the tracking or economics question before handing more control to automation.

    References

  • Performance Max Creative and Targeting Controls That Matter

    Performance Max Creative and Targeting Controls That Matter

    If you manage Performance Max, the uncomfortable choice can seem to be full automation or a maze of duplicated campaigns. That is the wrong choice. You can give the system better creative and stronger intent signals without rebuilding the account every time a limit changes.

    The useful distinction is simple: video assets shape what Performance Max can show, while search themes help steer the demand it should explore. Neither gives you deterministic control. Each gives the automation better inputs, and each needs a different plan.

    Know which Performance Max controls are signals

    A hand places colored beacons beside branching routes that guide an automated system without forcing it onto one fixed path.

    Performance Max controls do not all behave like conventional campaign settings. A hard limit determines what you can upload. A signal communicates what matters to your business. Confusing those roles leads to two common mistakes: treating themes like exact-match keywords and treating every new asset slot as an instruction to create another variation.

    ControlWhat it changesWhat it does not guaranteeDecision to make
    Video assetsThe creative ideas, formats, and ratios available within an asset groupThat every upload becomes an isolated or equally weighted testWhich missing asset would add meaningful coverage or test a clear idea?
    Search themesThe queries and intent patterns you want automation to prioritizeA strict keyword boundary around the traffic the campaign can pursueWhich customer intents deserve a stronger signal?
    Audience signalsAdditional context about the people likely to matterA fixed audience that automation can never move beyondWhich customer characteristics improve the meaning of the intent signal?

    This distinction gives you a useful operating rule: diagnose whether the campaign lacks material to show, clarity about demand, or a coherent asset-group structure. Add the control that addresses that specific deficit.

    Expand video coverage without filling slots for its own sake

    A creative director arranges a small set of distinct video scenes in horizontal, square, and vertical display frames while leaving extra frames empty.

    Google has been testing a change from a five-video limit to as many as 15 videos per asset group. The observed option had not received a formal announcement, so treat it as a test or gradual rollout until your own interface exposes it. Do not restructure a live campaign in anticipation of capacity your account does not yet have.

    If the larger limit is available, use the extra room in this order:

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  • Master LinkedIn Targeting in Microsoft Advertising

    Master LinkedIn Targeting in Microsoft Advertising

    Here’s how LinkedIn professional attributes enhance intent, automation, and creative decisions in Microsoft Advertising.

    Using LinkedIn targeting within Microsoft Advertising allows me to align creative strategies with the perfect audience. By engaging with this thoughtfully, I can apply professional insights to intent-driven inventory without breaking the bank.

    The key is understanding how these targeting methods collaborate across different campaign types. In this guide, I’ll walk you through leveraging LinkedIn data within Microsoft Advertising, including:

    • LinkedIn in Search campaigns, including Multimedia ads.
    • Using LinkedIn insights for an enhanced audience strategy.
    • Performance Max targeting signals.
    • Audience reach and composition insights via Audience Planner.

    Disclosure: As a Microsoft employee, I’ve kept this article objective, focusing on LinkedIn targeting mechanisms, targeting action items, reporting, and message mapping strategies.

    LinkedIn Profile Targeting in Search

    Microsoft Advertising search campaigns fully support LinkedIn profile targeting, allowing me to layer professional attributes on top of keyword targeting. The supported attributes include:

    • Company
    • Industry
    • Job function

    These audiences can be utilized across Microsoft‑owned environments, such as Bing Search, Microsoft Edge, Microsoft Start, and other eligible search surfaces, provided users are signed in.

    ```json { "alt": "Options for selecting targets in Company, Industry, and Job function with no targets selected.", "caption": "Explore potential by selecting targets in Company, Industry, and Job Function, and tailor your strategy to meet specific goals.", "description": "This image shows a user interface for selecting potential targets within three categories: Company, Industry, and Job function. Currently, no targets are selected, and an option to edit targets is available. Icons depict each category, offering a structured approach to refining goals or strategies within a platform. This interface is useful for customizing and targeting specific business or marketing objectives." } ```

    In search, LinkedIn targeting works as a contextual guide rather than a standalone target. Keywords carry the main weight, while LinkedIn data helps me adjust my response when professional relevance is present.

    How to Approach It

    • Start with keywords that already convert: LinkedIn targeting enhances existing intent with proven keywords. I apply bid adjustments to campaigns or ad groups where search terms already demonstrate business value, potentially increasing bids by 10%-15% for aggressive bidding or more aggressive adjustments when impression share is lost to rank.
    • Choose one professional dimension first: I begin with either company, industry, or job function instead of applying all three simultaneously. This approach prevents double-bidding on potential customers.
    • Use bid-only mode to establish a baseline: Observation mode provides performance clarity before I make delivery decisions. This acts as audience research to identify who engages profitably.

    Dig deeper: LinkedIn Ads retargeting: How to reach prospects at every funnel stage

    LinkedIn Professional Demographics in Audience Ads

    Audience Ads leverage LinkedIn Professional Demographics as both a targeting and observation layer, introducing professional context into native, display, and video formats tailored for scalable reach.

    Audience Ads aren’t driven by keyword intent; however, Professional Demographics anchor delivery and insights in real-world business contexts, bridging broad reach with professional relevance.

    These ads let me apply company, industry, and job function as professional audience layers, which I can use to observe performance trends or influence delivery, depending on campaign objectives.

    ```json { "alt": "Industry targeting settings in an ad platform, showing potential monthly impressions of 80.95 billion.", "caption": "Explore industry-specific ad targeting options to maximize your campaign's reach with an estimated 80.95 billion impressions.", "description": "The image displays an ad platform interface focused on industry targeting options. Users can specify or exclude industries like Manufacturing, Consumer Goods, and Health Care. A sidebar indicates potential monthly impressions of 80.95 billion, with options to adjust bid increments and targeting settings. Keywords: ad targeting, industry selection, impressions, bid adjustment." } ```

    How to Approach It

    • Start in observation to understand natural performance: By observing performance trends in Professional Demographics, I learn which industries, job functions, or company types naturally engage with Audience Ads before imposing delivery constraints.
    • Let LinkedIn data inform creative, not just delivery: In content-rich environments, creative matters more than targeting alone. I use insights from high-performing professional segments to shape tone, examples, and value framing in my messaging.
    • Align format choice with professional mindset: Different formats perform distinct roles. For example, native and display formats excel in awareness and education within professional segments, while video supports storytelling and industry-specific narratives. Professional Demographic insights guide the most suitable formats for varied business audiences.

    LinkedIn Data in Performance Max: Guiding Automation with Purpose

    LinkedIn profile targeting is available within Performance Max campaigns, where it functions as an audience signal. These signals help the system identify professional profiles most likely to yield profit for my business and influence budget allocation.

    Within Performance Max, professional signals are most effective when representative and directional, rather than exhaustive, providing the system a strong starting point.

    How to Approach It

    • Select signals that reflect your best customers, not every customer: Using LinkedIn attributes to describe my most valuable segments is crucial, especially if different personas represent varying ROAS/CPA goals, as this affects PMax campaign asset groups’ shared ROAS/CPA bidding.
    • Pair LinkedIn signals with strong conversion definitions: Automation improves when reinforced by clear success metrics. Ensuring at least 30 conversions over a 30-day period is vital for autobidding effectiveness.
    • Allow time for learning: Audience signals need sufficient volume to influence delivery, so I avoid frequent changes during the initial learning period (two weeks). Afterward, budget adjustments up to 15% can be made without triggering learning period fluctuations.

    Dig deeper: Google and Microsoft: How their Performance Max approaches align and diverge

    Reporting: Turning Audience Data into Decisions

    Aggregated LinkedIn audience reporting is divided by company, industry, and job function, letting me analyze how professional segments contribute to campaign performance. This reporting, found under Reporting > Professional demographics, includes LinkedIn targeting or audiences applied through predictive targeting.

    How to Approach It

    • Look for consistency across time, not single spikes: Patterns emerging over weeks or months are more actionable than short-term anomalies. I allow “observation” audiences ample time to prove themselves or use Audience Planner for informed decisions at scale.
    • Use reporting to inform creative and bids together: Upon identifying outperforming professional segments, I scrutinize messaging and bidding before initiating changes. It’s crucial to confirm creative resonance without overbidding.
    • Avoid over-segmentation early: Excessive audience segmentation can weaken signal strength, especially when conversion scarcity is a concern.

    Bidding with LinkedIn Audiences

    In Microsoft Advertising, I use bid adjustments alongside automated strategies, enabling flexibility in how LinkedIn audiences influence auctions. Overlapping audiences can amplify bid adjustments, necessitating overlap awareness as part of my bid strategy.

    ```json { "alt": "Interface for targeting users by company, industry, and job function with a search feature.", "caption": "Explore precise targeting options by company, industry, or job function, enhancing your marketing strategy with tailored user engagement.", "description": "This image showcases a digital interface for targeting users based on company affiliation, industry, and job function. It features search boxes for entering specific queries and lists various industries such as Manufacturing, Health Care, and Design. Job functions like Education and Media are highlighted, with a 'Target' option beside each. The interface emphasizes strategic ad placement while advising against using personal demographics for certain services. Keywords: targeting, industry, job function, company, advertising." } ```

    Effective bidding adjustments should be incremental and reversible, aiming for calibration rather than acceleration.

    How to Approach It

    • Keep initial bid adjustments small: Single-digit percentage changes preserve learning while allowing differentiation.
    • Audit audience overlap before increasing bids: I review how company, industry, and job function audiences intersect within campaigns.
    • Apply bid changes gradually and sequentially: Adjusting one audience dimension at a time helps me understand its individual impact.
    • Reassess after enough volume accumulates: Decisions are based on performance reaching statistical relevance.

    Dig deeper: The future of remarketing? Microsoft bets on impressions, not clicks

    Creative Strategy: Professional Relevance Without Narrow Assumptions

    LinkedIn targeting controls ad visibility, but creative determines engagement. Professional cohorts encompass a variety of experiences, identities, and viewpoints. My aim is effective creative that respects diversity while remaining relevant to shared contexts.

    Effective creative exhibits professional empathy, addressing challenges, goals, and constraints without reliance on stereotypes.

    How to Approach It

    • Anchor creative in shared problems, not titles: I focus on challenges common to roles and seniority levels within a LinkedIn targeting segment.
    • Keep language inclusive and adaptable: I avoid assumptions about background, experience, or decision-making authority.
    • Use AI tools to localize, not homogenize: Adapting tone or examples by region or industry while preserving message intent is crucial.
    • Test creative alongside audience layers: I evaluate messaging performance within LinkedIn segments to refine both together.

    Extending LinkedIn Insights Across B2B Campaigns

    LinkedIn targeting in Microsoft Advertising provides an opportunity to combine professional expertise with intent-driven media scalably, in a privacy-conscious and economical manner.

    ```json { "alt": "Screenshot of a professional demographics reporting interface with options for filters and column selections.", "caption": "Explore insights with the professional demographics reporting tool, offering customizable filters to analyze various data points effectively.", "description": "This image shows a screenshot of a professional demographics reporting interface. The interface includes options such as 'Add filter' and 'Add conditional formatting', alongside columns like Account, Campaign, Ad group, Company name, Industry name, and more. The 'Modify' button is present to alter settings. This tool is used for analyzing demographic data with focused filters, aiding in targeted analysis and reporting. Keywords: professional demographics, reporting interface, data analysis." } ```

    Teams already using LinkedIn Ads can leverage this strategy to extend learnings into additional inventory via automation, amplifying reach and efficiency.

    The value lies not in complexity, but in alignment – aligning data, mechanics, and human behavior enhances results.

    Key takeaways:

    • LinkedIn profile targeting is fully accessible in Search and Performance Max on Microsoft surfaces.
    • Professional attributes act as targeting layers in search and optimization signals in Performance Max.
    • An observation-first approach fosters understanding before commitment.
    • Aggregated reporting aids informed optimization without revealing individual data.
    • Thoughtful, incremental bid adjustments maintain performance stability.
    • Empathy-anchored creative fosters professional relevance.

    When I use LinkedIn data with curiosity and care, it offers a way to view audiences more clearly rather than control them more tightly. For B2B advertisers navigating complex buying journeys, such clarity often becomes the most valuable optimization.

    Dig deeper: 5 LinkedIn Ads mistakes that could be hurting your campaigns

    Inspired by this post on Search Engine Land.

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  • Microsoft Ads Asset-Level Compliance Reviews: A Practical Workflow

    Microsoft Ads Asset-Level Compliance Reviews: A Practical Workflow

    You open Microsoft Advertising and find that one headline or image has been disapproved. Do not start by rewriting the entire ad. The useful question is narrower: which component failed, what can still run, and does the remaining creative still communicate what you intended?

    Asset-level compliance reviews make that diagnosis possible. Once you treat each component as its own reviewable unit, you can correct the actual problem, preserve compliant creative, and keep a small editorial issue from turning into an unnecessary campaign rebuild.

    Read the asset status before judging the whole ad

    Microsoft Advertising can review individual components such as headlines and images separately. A non-compliant component can be blocked without automatically preventing compliant components from continuing to run. This replaces the more disruptive all-or-nothing approach in which one problem could hold back the complete ad.

    That changes what a disapproval means. You now need to read the account at three levels:

    • Asset level: Identify the exact headline, image, or other component carrying the disapproved status.
    • Ad level: Confirm which compliant components remain available and whether the ad still has a usable creative set.
    • Campaign level: Decide whether the remaining components still represent the offer, required qualifications, and intended call to action.

    Do not confuse editorial approval with creative quality. A compliant asset has cleared the review represented by its status; it has not necessarily proved that it is persuasive, accurate for every audience, or strong enough to meet your performance goal. In the other direction, one disapproved asset does not mean that every other component is defective.

    The dashboard now flags the blocked element and provides an asset-specific status. Use that status as the starting point for your investigation instead of guessing from the ad’s overall performance.

    What you seeWhat to noticeWhat to do next
    One headline is disapproved while other components are compliantThe review outcome is localized to that headlinePreserve the compliant components and revise only the blocked headline
    One image is disapproved while copy remains compliantRewriting approved copy will not address the identified componentInspect or replace the image first
    Several blocked assets share similar wording or imageryA common characteristic may be causing repeated problemsCompare the blocked assets before making separate edits
    Assets are compliant but the campaign is not meeting its goalEditorial review is not a performance diagnosisInvestigate creative strength, targeting, bidding, measurement, and the offer separately

    Use a narrow workflow for every disapproved component

    An isolated ad component moves through symbolic diagnosis, policy review, correction, and verification steps while compliant components remain untouched.

    The fastest-looking response is often a broad rewrite. It is also the response that destroys the clearest evidence. If you change every headline and image together, you lose the distinction between the component that failed and the components that were already acceptable.

    Use this sequence instead:

    1. Locate the exact asset. Open the detailed status and identify whether the blocked item is a headline, image, or another component. Do not begin from a general impression that the entire ad was rejected.
    2. Record what the dashboard shows. Save the asset text or image filename, its location, the visible warning, and the date you noticed it. A screenshot can preserve context if the status changes later.
    3. Protect the compliant set. Leave approved components unchanged unless they have a separate accuracy or performance problem. Their continued eligibility is the operational benefit of asset-level review.
    4. Correct the smallest defensible unit. If the blocked item is a headline, work on that headline. If it is an image, inspect the visual rather than polishing unrelated copy. Make the correction substantive enough to address the apparent issue; a cosmetic near-duplicate is unlikely to improve your understanding of the problem.
    5. Check the revised status. Return to the asset view after the correction has been reviewed. Do not infer approval merely because other components are serving.
    6. Search for reuse. If the same wording or visual appears elsewhere in the account, inspect those locations before the issue creates repeated cleanup work.

    If the displayed warning is too broad to tell you what should change, stop editing at random. Preserve the exact status and creative, then use the review or support path available in your account. Random rewrites may eventually produce a compliant variation, but they will not teach your team what caused the original failure.

    Keep compliance corrections separate from performance experiments as well. When an asset is changed because of a review outcome, label that reason in your campaign notes. Otherwise, a later analyst may mistake a mandatory compliance change for a deliberate creative test and draw the wrong conclusion from subsequent performance.

    Build an asset ledger that turns disapprovals into reusable knowledge

    Asset-level review is most valuable when your internal records are equally granular. A campaign-level note such as “ad rejected” is no longer precise enough. It cannot tell the next person what failed, which components remained usable, or whether the same issue has appeared before.

    A simple asset ledger should capture:

    • The campaign and ad containing the asset
    • The asset type, such as headline or image
    • The exact copy or the image filename used by your team
    • The current status shown in Microsoft Advertising
    • The warning or explanation visible in the dashboard
    • The date the status was observed
    • The correction made and the reason for it
    • The revised version’s status
    • Other ads or campaigns that reuse the same message or visual

    Treat edited copy as a separate version in this ledger. If you overwrite the original wording in your records, you erase the comparison that could reveal why one variation was blocked and another was accepted.

    The ledger is operational history, not a substitute for the platform’s current status or Microsoft Advertising’s policies. Its purpose is to reveal patterns. Repeated problems attached to the same claim, visual treatment, or approval handoff deserve a process change upstream rather than another round of one-off fixes.

    Use those patterns to improve your preflight review. Before new creative is submitted, compare it with previously blocked assets, verify that required wording has not disappeared during editing, and confirm that image and copy versions belong together. This is more useful than a generic instruction to “check compliance” because it directs reviewers toward the failure modes your team has actually encountered.

    Check message coverage even when compliant assets keep running

    A strategist reviews active and inactive ad components, with a visible gap in the remaining creative message pathway.

    Reduced disruption does not mean zero business impact. The remaining components may continue serving while an important part of your message has disappeared. If the blocked asset carried the only clear explanation of the offer, a key qualification, or the intended call to action, the ad may still be active without doing the job you designed it to do.

    After any asset-level disapproval, check the remaining creative against a short coverage list:

    • Identity: Can a user still tell who is advertising?
    • Offer: Is the product, service, or proposition still clear?
    • Qualification: Are important limits or conditions still represented where your organization requires them?
    • Action: Does the remaining creative still tell the user what to do next?
    • Consistency: Do the surviving components make sense together rather than creating a misleading or incomplete combination?

    If a blocked component contains wording your legal or compliance team requires, do not assume that continued serving is automatically safe. The specific downside is that an ad could remain active without the language your organization considers necessary. Use the campaign controls available to prevent that exposure until a compliant replacement preserves the required meaning.

    Record the disapproval and correction in the same change log you use for campaign analysis. A component becoming unavailable changes the creative set that can run. If you omit that event from your notes, a later performance shift may be attributed to bidding, targeting, or seasonality when the message mix also changed.

    Once the revised asset is compliant, verify more than its status. Confirm that it restores the intended message, that it does not contradict the other components, and that your reporting period identifies when the asset set changed. Compliance recovery and performance recovery are related, but they are not the same checkpoint.

    Key takeaways

    • Microsoft Advertising reviews individual components such as headlines and images, allowing compliant assets to continue while a problematic component is blocked.
    • A disapproved asset is a localized diagnosis. Identify the exact component before editing anything else.
    • Preserve compliant assets and correct the smallest relevant unit instead of rebuilding the complete ad.
    • Track each asset, visible status, correction, and reused location so recurring issues can be fixed upstream.
    • Continued serving does not prove that the remaining creative still communicates the full offer or required qualifications.
    • Keep compliance changes in your campaign log so they are not mistaken for performance experiments.

    At the next disapproval, begin with the component named in the dashboard. Preserve what passed, document what failed, and inspect the message that remains. That small discipline is what turns asset-level review from a status display into a reliable compliance workflow.

    References

  • Bing’s Grouped Search Ad Design: What Advertisers Should Do

    Bing’s Grouped Search Ad Design: What Advertisers Should Do

    If your Bing search ad click-through rate rises while conversions barely move, do not congratulate the creative team yet. The interface itself may have changed what a click means.

    Bing is testing a grouped ad design that makes paid listings look more like a continuous set of search results. The practical response is not to guess whether the format is good or bad. It is to separate useful demand from interface-driven clicks before you change bids, budgets, ads, or landing pages.

    The interface change alters what a click can mean

    In the observed Bing test, several paid listings appear beneath one “Sponsored results” label. The individual ads below the first one do not receive their own labels. Searchers can also use a “Hide” control to collapse the block and a “Show” control to restore it.

    That changes the visual unit a searcher encounters. Instead of evaluating several clearly separated ads, the user may perceive one sponsored section containing results that resemble the organic listings below it. The format could make ads more noticeable, but it could also make the paid status of an individual listing easier to miss.

    The experiment remains limited, so you should not assume every impression in your account uses this design. You also should not infer that the test changes auctions, targeting, ranking, or attribution rules. A presentation change is enough to affect behavior even when the campaign underneath it stays the same.

    This distinction matters when you review performance. A click has always combined two things: the searcher’s underlying interest and the interface’s ability to attract attention. Grouping can change the second factor. If you treat every resulting CTR increase as stronger intent, you may bid more aggressively for traffic that is no more valuable than before.

    Diagnose performance with a metric chain, not CTR alone

    Four linked visual modules represent an impression, click, landing-page visit, and completed action under a magnifying lens.

    CTR is clicks divided by impressions. It tells you whether an impression produced a click, but not whether the person understood that they were selecting an ad or whether the visit created business value. Read CTR alongside conversion rate, cost per acquisition, conversion volume, search-term quality, and post-click behavior.

    A comparable grouped design on Google prompted an informal X poll in which 63% of respondents said they had clicked an ad unintentionally. That number is a warning signal, not a forecast for Bing. A voluntary social-media poll cannot establish the accidental-click rate among Bing users or prove that grouping caused every reported mistake.

    Your own conversion economics are more useful than that headline number. Read changes as a sequence:

    What you observeWhat it may meanWhat to do next
    CTR rises, while conversion rate and cost per acquisition remain healthyThe additional clicks may be useful, although the design is not necessarily the causeCheck lead or order quality before increasing bids or budgets
    CTR rises, conversion rate falls, and cost per acquisition worsensThe extra clicks may carry weaker intent, or another campaign change may have altered traffic qualitySegment the shift by query, device, campaign, and audience before changing the whole account
    Clicks and spend rise, but conversions remain flatIncremental traffic is consuming budget without producing a matching business resultProtect the account’s cost guardrail and reduce exposure in the affected segment if necessary
    CTR rises alongside shorter or less engaged visitsUsers may be arriving with the wrong expectation, but landing-page speed or message mismatch can produce the same patternCompare the ad promise, query intent, and first visible landing-page message
    Paid clicks rise while organic clicks fall for the same query familyThe new presentation may be redistributing existing demand rather than creating more of itEvaluate total search conversions and revenue instead of celebrating one channel’s gain

    The combination of higher CTR and lower conversion rate deserves particular attention. If clicks grow faster than conversions, conversion rate falls by definition. If spend then grows faster than conversions, cost per acquisition deteriorates. That is the signature to investigate when you suspect interface-driven traffic.

    Do not automatically call it an accidental-click problem. A promotional change, broader matching, altered bids, seasonality, a slow landing page, or weaker offer alignment can create the same pattern. The layout is one hypothesis to test against the rest of the account history.

    Build an audit trail while test exposure is uncertain

    A search advertising specialist compares a grouped-results layout with campaign signals while arranging blank snapshot tiles on a desk.

    You need a record that lets you distinguish a search-interface shift from your own campaign changes. Start before performance looks unusual, because reconstructing the sequence later is difficult.

    1. Document every confirmed sighting. Save a screenshot and record the query, device type, location, date, signed-in state if known, and whether the Hide and Show controls appeared. A screenshot proves the layout was visible in that context; it does not prove all campaign impressions used it.
    2. Annotate changes under your control. Record bid, budget, targeting, keyword, creative, conversion-tracking, offer, and landing-page changes. Without this log, a performance shift that follows your own edit can easily be blamed on the interface.
    3. Create a comparable baseline. Use periods that make sense for your sales cycle and account volume. Account for promotions, weekdays, seasonality, and major demand changes. A large but poorly matched baseline is less useful than a smaller comparable one.
    4. Segment before averaging. Review brand and non-brand traffic separately, then inspect query themes, campaigns, devices, locations, and audiences using the dimensions available in your reporting. A localized problem can disappear inside an account-wide average.
    5. Pair every attention metric with an outcome metric. Match impressions with clicks, clicks with qualified visits or conversions, and spend with revenue, pipeline value, or another business result. For lead generation, include accepted-lead quality when possible; a form submission alone may hide low-intent traffic.
    6. Define your response before the numbers move. Use the CPA, return, margin, or lead-quality limits already required by the business. If performance crosses a financial guardrail, contain the affected segment rather than waiting for perfect causal proof.
    7. Label causal claims honestly. If you cannot identify which impressions received the grouped layout, you have a correlation, not a controlled test. Say that clearly in stakeholder reporting.

    The strongest comparison would separate traffic exposed to the grouped design from otherwise similar unexposed traffic. If you do not have a reliable exposure indicator, screenshots and timing can support an investigation, but they cannot turn normal account reporting into an experiment.

    Adjust the campaign without chasing a temporary layout

    A limited interface test does not justify rewriting an entire account. Start with changes that improve informed selection under any search design.

    • Make the advertiser and offer unmistakable. Use clear brand, product, service, and destination language. Do not rely on the visual ad label to explain what the person will reach.
    • Qualify before the click when it helps the user. Accurate price, location, audience, availability, or eligibility details can discourage unsuitable visits. Add only qualifications that are true and material to the decision.
    • Keep the landing-page handoff literal. The first visible page content should confirm the same offer and intent expressed by the query and ad. A user who has clicked quickly should not have to infer why the page is relevant.
    • Inspect search terms for the affected segments. If the increase comes from irrelevant or weakly related queries, refine targeting and exclusions. A visual redesign cannot rescue poor query-to-offer alignment.
    • Use meaningful conversion actions. Separate valuable outcomes from shallow actions where your measurement permits it. Otherwise, an increase in low-value activity can disguise deteriorating customer quality.
    • Protect budget at the narrowest useful level. If spend rises without a corresponding result, constrain the specific campaign, query class, device, or audience showing the problem. Broad account cuts can suppress traffic that remains profitable.

    For lead-generation campaigns, adding deliberate qualification to the page or form can reveal whether new clicks reflect genuine interest. That does not mean creating pointless friction. Ask only for information needed to assess fit, and track whether accepted leads improve rather than judging success by raw form volume.

    For ecommerce campaigns, compare paid click growth with completed orders, revenue, and margin. If traffic rises but product engagement and purchases do not, check whether the query, ad, price, and landing product still describe the same proposition. The grouped design may expose an existing mismatch rather than create it.

    SEO and paid-search teams should also review overlapping query families together. A paid CTR gain accompanied by an organic click loss may be a redistribution of the same demand. The better question is whether total qualified search traffic, conversions, and revenue increased after accounting for the added ad spend.

    Key takeaways for Bing search advertisers

    • Bing is testing multiple ads beneath one “Sponsored results” label, with controls that let users hide and restore the entire sponsored block.
    • The test is limited, so do not assume all impressions use the grouped format or attribute every account change to it.
    • A CTR increase is useful only when conversion quality and cost efficiency hold up downstream.
    • The reported 63% accidental-click figure came from an informal poll about a comparable Google design; it identifies a risk to investigate, not a Bing benchmark.
    • Document confirmed sightings and your own campaign edits so that timing alone does not become your evidence.
    • If costs deteriorate, contain the affected segment using existing business guardrails while continuing to investigate.
    • Judge paid and organic search together when both channels serve the same query intent.

    Treat the redesign as a measurement problem first. Preserve your baseline, watch the path from impression to business outcome, and make the smallest defensible campaign change when the economics require one. If Bing expands the format, you will already have the evidence needed to decide whether its extra clicks are helping you or merely costing you more.

    References

  • Comparing Google & Microsoft: Unraveling Performance Max

    Comparing Google & Microsoft: Unraveling Performance Max

    In the ever-evolving world of AI-driven advertising, I’ve noticed that Performance Max campaigns have become absolutely crucial. Both Google and Microsoft offer these innovative opportunities, allowing advertisers to bring together creative assets, audience signals, and automation into a single seamless campaign type.

    While Google and Microsoft share this foundational concept, they execute it uniquely. I am excited to offer an in-depth comparison of Google PMax and Microsoft PMax as they stood toward the end of 2025, hoping to shed light on the intricacies that could shape your 2026 advertising strategies.

    What I found universally true across both platforms is the replacement of ad groups with asset groups. These groups encompass a blend of creatives, such as images and headlines, along with audience signals, but also carry an absence of any prioritization.

    Significantly, PMax is built for automation. Both platforms request the use of Maximize Conversions or Maximize Conversion Value strategies, underlining the need for conversion tracking that can keep pace with no less than 30 conversions in a month.

    Goal alignment is another crucial aspect. I realized that accurate reflection of business goals in your campaigns is imperative, for an artificially low ROAS target will likely backfire by yielding unexpectedly lower returns.

    Search term visibility is an area where Google offers broader negative keyword support, unlike Microsoft who is still piloting this feature. However, Microsoft’s PMax creatives have been involved in AI placements longer, demonstrating proven results and thus indicating a stronger track record in this area.

    Google’s PMax has evolved impressively, offering tools such as channel-level reporting and video asset support, which are particularly beneficial for visual marketing endeavors.

    On the flip side, Microsoft’s edge, especially for B2B advertising, includes higher campaign limits, impression-based remarketing, and the integration of LinkedIn targeting signals, appealing for advertisers looking at high-quality lead generation.

    Reflecting on both platforms, I believe PMax should be seen as a tool for incrementality rather than a replacement for proven search campaigns. The optimal approach involves leveraging both platforms’ strengths, whether it’s Google’s affinity for creative automation or Microsoft’s prowess in B2B targeting and remarketing.

    Inspired by this post on Search Engine Land.

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