Tag: LinkedIn

  • LinkedIn Ads CPC Benchmarks: What I Budget vs Google

    LinkedIn Ads CPC Benchmarks: What I Budget vs Google

    Linkedin Ads vs Google Ads

    I know LinkedIn Ads has a reputation for being expensive, and at first glance, the data backs that up. Across the client accounts I analyzed, LinkedIn’s average CPC was $11.12, compared with $5.45 on Google Ads.

    But that simple comparison misses the more useful story. When I compare the cost of reaching new, high-intent B2B buyers, the gap gets much smaller. Non-branded Google Search campaigns averaged a $12.48 CPC, while comparable LinkedIn prospecting campaigns averaged $13.94.

    To understand how LinkedIn CPCs really compare with Google Ads across campaign types and industries, I reviewed more than $700,000 in LinkedIn ad spend and compared it with CPC data from the same accounts on Google Ads.

    What I included in this analysis

    I focused on CPC and performance data from clients that had active campaigns on both LinkedIn Ads and Google Ads over the past year.

    The main questions I wanted to answer were straightforward: What CPCs are we actually seeing? Do CPCs change by ad objective and industry? And how do those costs compare with Google Ads?

    For LinkedIn Ads, I analyzed more than $700,000 in spend across 63,000+ clicks and 8.1 million impressions.

    The clients fell into two main business categories: B2B SaaS, which represented approximately 97% of spend, and professional services.

    I looked at LinkedIn CPCs by ad set objective and business category. For Google Ads, I pulled CPC data from the same client accounts across branded search, non-branded search, Demand Gen, and display campaigns.

    Client names are withheld. The date range for this analysis was May 2025 through May 2026.

    Image

    LinkedIn looks more expensive, but the comparison needs context

    LinkedIn’s blended average CPC across all objectives was $11.12. Google’s blended average CPC across all campaign types was $5.45. On the surface, LinkedIn costs about twice as much per click.

    There is an important caveat. In Google Ads, a large share of those lower-cost clicks came from display campaigns, which averaged $0.89 per click, and branded search, which averaged $1.71 per click. Both are naturally less expensive because display generally reaches lower-intent audiences, while branded search captures people already looking for your company.

    When I narrow the comparison to the cost of reaching new, high-intent audiences, the difference becomes much less dramatic.

    • Google Ads non-branded search averaged a $12.48 CPC across the clients in this study.
    • LinkedIn prospecting campaigns, excluding retargeting and using lead generation, website conversion, or website visit objectives, averaged a $13.94 CPC.

    I used those LinkedIn objectives because they most closely represent high-intent direct-response campaigns, which makes the comparison with non-branded search more useful.

    When I compare the cost of reaching a new audience, LinkedIn is still more expensive, but it is not twice as expensive. In practical terms, I am looking at roughly $12 CPCs on Google and $14 CPCs on LinkedIn.

    LinkedIn CPCs change a lot by objective

    One of the clearest findings in this data set is how widely LinkedIn CPCs vary by campaign objective.

    • Website visits: $6.75
    • Brand awareness: $8.34
    • Website conversions: $4.84
    • Engagement: $4.45
    • Lead generation: $31.29
    • Video views: $71.43

    Lead generation campaigns, where LinkedIn lead gen forms capture contact information directly inside the platform, cost nearly five times more per click than website visit campaigns.

    That higher CPC can still make sense because these campaigns often convert at much higher rates than ads that send people to a website or landing page.

    Image

    Here is the full breakdown of CPCs by campaign objective:

    LinkedIn CPCs by campaign objective

    The number that jumps out most is video views. CPCs for those campaigns look extremely high, but cost per view is the more relevant metric there, so CPC alone can be misleading.

    If I were planning a LinkedIn campaign focused on click volume or site traffic, I would budget for CPCs in the $6-$8 range. For lead gen ads, which in my experience often produce stronger conversion rates and better lead quality, I would plan for $30+ CPCs.

    LinkedIn CPCs also change by industry

    The two business categories in this analysis showed noticeably different CPC profiles on LinkedIn.

    • B2B SaaS: $11.02 average CPC on $681,000 in spend
    • Professional services: $15.25 average CPC on $23,000 in spend

    I would be careful not to overstate that comparison because the spend levels were very different. B2B SaaS had a much broader mix of campaign types, which likely affected the average CPC. The professional services campaigns also used very specific targeting, which may have pushed CPCs higher.

    B2B SaaS CPCs by campaign objective:

    B2B SaaS LinkedIn CPCs by campaign objective

    Professional services CPCs by campaign objective:

    Professional services LinkedIn CPCs by campaign objective

    One interesting twist is that lead gen CPCs in professional services were lower than website visit CPCs. Lead gen CPCs were also much lower for professional services than they were for B2B SaaS.

    Image

    If I were budgeting for a professional services firm on LinkedIn, I would factor in $15-$20 CPCs. For B2B SaaS, I would plan for a wider range, roughly $7-$35, depending on the campaign objective.


    How this compares with Google Ads

    The pattern is fairly consistent across channels. Professional services had higher CPCs than B2B SaaS in this data set. Even when I compare only non-branded search between the two industries, the CPCs are closer, but professional services still comes out higher.

    Here is the breakdown of Google CPCs by campaign type:

    Google Ads CPCs by campaign type

    What I would budget for LinkedIn Ads

    Your targeting will have a major impact on CPCs and budget needs, but I use this data as a practical planning framework.

    Minimum viable budget: $3,000-$5,000 per month

    Below this level, I would not expect enough traffic to drive meaningful lead volume or conversions. You may still be able to get started, but trend-spotting will be slow, and you will probably be limited to one or two campaigns.

    Testing and learning: $5,000-$10,000 per month

    At this level, I would expect enough budget to run two or three objectives, launch more campaigns, test creative and audiences, and generate more meaningful lead volume.

    Scaling: $10,000+ per month

    With this budget, I can run always-on brand awareness and thought leadership campaigns alongside lead gen and website visit campaigns. I can also support event registrations, test more advanced list-targeted campaigns, and use retargeting without starving direct-response efforts.

    For B2B SaaS or professional services companies with an ACV above $20,000, I would rarely recommend starting LinkedIn with less than $5,000 per month. A single closed deal worth $30,000-$50,000 in ACV can justify meaningful investment, even at a $500+ CPL, as long as the pipeline quality is there.

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    The B2B channel mix I recommend

    For most B2B clients, I do not see LinkedIn and Google as either-or channels. I use them for different jobs.

    Use Google Ads and Microsoft Ads for intent capture

    Non-branded search reaches buyers who are actively researching. Branded search and remarketing are lower-cost and essential. If someone is searching for your category keywords, I want your brand to be visible.

    I also use Demand Gen and Performance Max where they make sense to fill gaps and support brand awareness.

    Use LinkedIn Ads for audience-led demand generation

    If the ideal customer profile is highly specific, such as VP-level decision-makers at mid-market SaaS companies, LinkedIn’s targeting is hard to replace. No other platform gives me the same ability to reach that kind of professional audience at scale.

    Run both channels in parallel

    The strongest setup is to run both channels together. Google captures existing demand. LinkedIn helps create new demand and keeps the brand visible to the exact buyers I want in the pipeline.

    Why I still think LinkedIn is worth the higher CPCs

    LinkedIn is more expensive than Google on a raw CPC basis. But when I compare the platforms more fairly, with both reaching cold, qualified B2B buyers, the gap narrows significantly.

    Higher CPCs can still be worth paying if they put the brand in front of the right customers earlier in the decision-making process. Over time, that can be more valuable than relying only on high-intent keywords after buyers have already narrowed their list of options.

    The best scenario is for the brand to become an active part of the buyer’s decision, shaping the narrative before competitors do it instead.

    My take is simple: I use LinkedIn Ads to build intent and tell the story, and I use Google Ads and Microsoft Ads to capture intent. The right budget depends on targeting, but I want enough spend to generate at least 100 clicks per month. Anything less usually means spending money without giving the system enough data to learn from.


    Inspired by this post on Search Engine Land.


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  • How AI Search Engines Prefer Reddit, YouTube, and LinkedIn

    How AI Search Engines Prefer Reddit, YouTube, and LinkedIn

    AI citations

    During a recent study, I discovered that Reddit stands out as the most-cited domain in AI-generated answers. In fact, it’s ahead of heavyweights like YouTube and LinkedIn, thanks to an analysis of 30 million sources conducted by Peec AI, a tool specializing in AI search analytics.

    The findings: I’ve learned that Reddit claims the top spot across various AI platforms including ChatGPT, Google AI Mode, Gemini, Perplexity, and AI Overviews. Top contenders YouTube, LinkedIn, Wikipedia, and Forbes are right behind. Platforms like Yelp and G2 frequently appear when searching for recommendations.

    As I delved deeper into the research, it became clear which domains the AI models tend to lean on:

    • ChatGPT values Wikipedia, Reddit, and editorial sites like Forbes.
    • Google shows preference for platforms such as Facebook and Yelp.
    • Perplexity favors Reddit, LinkedIn, and G2 for queries within the B2B realm.

    Why we care: The insight that resonated with me was the importance of having authority beyond just our own websites. Brands that consistently feature on reputable third-party platforms have a better chance of being cited by AI.

    Why these sources? It’s fascinating to see how AI systems are wired to prioritize both authority and authentic user input:

    • I’ve found that Reddit excels because it mirrors genuine user discussions.
    • YouTube shines in video citations, owing to their comprehensive transcripts and descriptions.
    • Wikipedia not only serves real-time data but also acts as a foundation for training datasets.

    About the data: The analysis spanned 30 million sources, providing a comprehensive look at how often domains are directly cited in AI answers, effectively revealing what shapes these responses.

    The study. For those interested in a deep dive, the full study is available here: Top domains cited by AI search: Analysis based on 30M sources

    Dig deeper. For more on citation research, check out these fascinating reads:


    Inspired by this post on Search Engine Land.


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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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  • Elevate Your LinkedIn Ads: Reserved Slots Now Available

    Elevate Your LinkedIn Ads: Reserved Slots Now Available

    Recently, I’ve been exploring LinkedIn’s Reserved Ads feature, which is now open to all managed advertisers. This exciting update lets me secure the prized top-of-feed placement, fundamentally boosting visibility and engagement for my B2B campaigns.

    LinkedIn has now made Reserved Ads accessible to all managed accounts, allowing me to grab the first ad slot in the feed. This prime location guarantees premium visibility for my advertising efforts.

    What’s new. With Reserved Ads, I can secure top-of-feed placement at a consistent rate, ensuring predictable delivery and enhanced reach. According to LinkedIn, this format drives up to 75% higher dwell time, 88% higher view-through rates, and achieves 99% of forecasted impressions, making it a powerful choice for my marketing strategy.

    How it works. These ads appear in the most visible ad slot on LinkedIn’s feed and support a variety of Sponsored Content formats like Video, Single Image, and Carousel Ads. My LinkedIn account representative assists me in reserving this valuable inventory and setting the pricing strategy.

    Why we care. For me, LinkedIn Reserved Ads are a game-changer, providing guaranteed top-of-feed placement. This increases my campaign’s visibility and engagement, helping me stand out in the competitive B2B space. The premium positioning enhances brand recall and influences potential leads early in the funnel.

    LinkedIn feed showing a digital advertisement for a payment system called Oustia, with a visual of a card reader.
    Explore the future of payments with Oustia's sleek new card reader! Secure, stylish, and efficient — the perfect tool for modern businesses.

    The predictable delivery and fixed pricing models mean I can plan my campaigns with more certainty, while also building high-quality retargeting audiences for future conversions.

    The big picture. By utilizing Reserved Ads, I’m effectively bridging brand awareness and demand generation. Anchoring my campaigns at the top of LinkedIn’s feed enables me to create higher-quality retargeting pools, with LinkedIn reporting up to a 101% increase in mid-funnel engagement as a result.

    The bottom line. LinkedIn’s Reserved Ads provide me, as a B2B marketer, with a predictable way to command attention and transform it into significant demand.


    Inspired by this post on Search Engine Land.


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