Category: News

  • Boost Your B2B Brand on LinkedIn: New Tools for Personalization and Impact

    Boost Your B2B Brand on LinkedIn: New Tools for Personalization and Impact

    I’ve discovered that LinkedIn is rolling out some exciting ad tools aimed at making B2B brand advertising more predictable and personal. These new features are designed to enhance brand awareness using premium placements, personalized messaging, and scalable AI-powered creativity.

    Recently, I learned about LinkedIn’s latest innovations for B2B marketers. These tools are all about helping us strengthen brand awareness and personalize our messaging. Their aim is clear: reach potential buyers early in the sales funnel.

    What’s new in LinkedIn advertising:

    Firstly, Reserved Ads provide prime visibility in the LinkedIn feed. This ensures a predictable number of impressions and grabs more attention than our competitors. This format works seamlessly with Video, Thought Leader, Single Image, and Document Ads, allowing us to maximize our creative impact.

    Additionally, Ad personalization empowers us to tailor messages dynamically using member profile data like first name, job title, and company. Personalized ads matter: a McKinsey study shows that while 71% of consumers expect personalized ads, 76% feel frustrated in their absence.

    This isn’t all. With AI-powered creative tools, I find it easier to test various ad versions. AI Ad Variants create fresh, on-brand content from a single input. Plus, the upcoming Flexible Ad Creation, expected in early 2026, will let us upload multiple assets, which LinkedIn will mix and optimize for top performance.

    Why these updates matter to me. With these tools, building a brand on LinkedIn becomes more effective. The boost in visibility and enhanced personalization capabilities simplify our creative production process immensely. Reserved Ads, for example, guarantee prime placement at the top of users’ feeds, capturing attention even when the audience isn’t actively searching.

    Meanwhile, by tailoring messages dynamically (like by name, company, or job title), Ad Personalization makes advertisements more relevant. Plus, AI tools such as AI Ad Variants and the soon-to-come Flexible Ad Creation streamline our creative workflows. This allows us to test more variants quickly, enhance engagement, and reach audiences effectively at the top of the funnel.

    The big picture in advertising. As buyers take non-linear, self-directed paths, establishing an early-stage brand presence is crucial. These tools help deliver scalable, personalized creativity efficiently, boosting awareness, engagement, and conversion across campaigns.

    What’s next for me as a marketer. I plan to experiment with Reserved Ads, delve into ad personalization, and leverage AI-driven creative tools. This approach should enhance my impact at the funnel’s top, refine our messaging, and optimize our performance—all with minimal manual effort.

    The bottom line on LinkedIn’s ad innovations. These advancements are designed to make brand building more predictable, relevant, and scalable. They enable marketers to reach the right audience with the right message at the right time.


    Inspired by this post on Search Engine Land.


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  • Boost Your Reach with Shopify’s New Product Network

    Boost Your Reach with Shopify’s New Product Network

    I’ve just come across some exciting news from Shopify. They’ve launched something called the Product Network, which essentially allows advertisers to connect with potential shoppers across various merchant sites using contextually relevant products. It’s a game-changer!

    What’s amazing is that this system can suggest products from other merchants, even when I’m shopping at a store that doesn’t have what I’m looking for. For instance, if I search for “organic cleaning supplies” and the store doesn’t carry them, the Product Network might still offer me alternatives from different merchants. This means I can add everything to a single cart, without even realizing some items come from other merchants.

    Here’s how Shopify is positioning themselves: It reminds me of ad platforms like Google Performance Max or Meta Advantage+ Shopping, where advertisers set a cost-per-acquisition goal, and the platform handles the rest. But Shopify is focusing more on the merchandising aspect rather than traditional advertising, which I find quite refreshing.

    Amanda Engelman, who’s their advertising product director, summed it up nicely by saying, “It’s just a different approach to the world.”

    Historically, Shopify has shied away from profiting heavily off advertising. Their Audiences program is a good example; it creates customer segments for various channels like Google and Meta, but doesn’t take a share of the ad spend.

    For merchants, there’s an added incentive to join the network. They earn commissions on the sale of products from other merchants, either in cash or Shopify ad credits. It’s like getting extra ad budget support without the usual upfront investment.

    In the early stages, placements in the Product Network are determined by context rather than being driven by revenue targets, though there’s potential for optimization in favor of higher commission items.

    The reason this is relevant is that Shopify’s Product Network now allows brands to extend their reach with ease. Shoppers are introduced to relevant products seamlessly, as these can be featured on search results or even on different stores’ homepages.

    Unlike typical ads, the focus here is on driving conversions through relevant, context-driven placements rather than simply filling ad space. This could mean better traffic quality and merchants benefiting from third-party sales commissions, thereby expanding the network’s reach and impact.

    Looking ahead, Shopify is planning to further enhance the personalization and monetization of this network, all while keeping users within their ecosystem. The whole aim is to support merchants in selling more, even if the products aren’t their own.


    Inspired by this post on Search Engine Land.


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  • Semify Expands Global Reach with Dragon Metrics Acquisition

    Semify Expands Global Reach with Dragon Metrics Acquisition

    Semify acquires Dragon Metrics

    I’m excited to share that Semify, a leading white-label digital marketing platform, has acquired Dragon Metrics, a prominent international SEO and AI reporting provider based in Hong Kong. This acquisition marks a significant enhancement in our reporting capabilities and AI optimization tools as we adapt to a shifting search landscape increasingly focused on AI.

    Why this matters to you. If you’re a Dragon Metrics customer, you can continue to expect the same great service, along with more frequent product updates. According to co-founder Simon Lesser, who shared on LinkedIn, the platform will still operate as an independent brand retaining its existing contacts and product experience. Additionally, you’ll now benefit from Semify’s expanding AI optimization strategies and the potential for future software integrations.

    Details of the acquisition. On December 8th, Semify announced the acquisition of Dragon Metrics:

    • Semify was founded in 2008 and operates as a U.S.-based white-label digital marketing platform.
    • Dragon Metrics was founded in 2011 and supports multinational brands and agencies in over 50 countries, especially in regions where Google isn’t the main search engine, like China, Korea, and Japan.
    • This acquisition provides Semify with an enterprise-grade reporting system and comprehensive global data coverage as we intensify our focus on AI-driven metrics.

    The finer points. Simon Lesser will take on the role of chief product officer at Semify, steering our AI optimization product strategy.

    • The Dragon Metrics engineering team will join forces with Semify’s team under the leadership of CTO Brian Sappey.
    • Our resellers are set to experience improved reporting capabilities via Dragon Metrics accounts, with more integrated solutions on the horizon.
    • Dragon Metrics customers will remain on their distinguished platform but with the advantage of increased engineering support.
    • White-label fulfillment will continue to be exclusive to approved agencies, aligning with our existing reseller model.

    Inspired by this post on Search Engine Land.


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  • Exciting News: Profound Expands with a New Office in London

    Exciting News: Profound Expands with a New Office in London

    Today is a monumental day for Dylan and me, as we are overjoyed to announce that Profound is opening its very first UK office in the vibrant city of London.

    The addition of this office marks an exciting chapter in Profound’s journey, representing a significant step forward in our pursuit of global growth and innovation.

    This expansion is not just a testament to our dedication and hard work but also to the incredible support from our clients and partners who have believed in our vision.

    With this new location, we’re eager to bring our expertise closer to our UK clients and partners, ensuring we continue to offer exceptional service and support.


    Inspired by this post on Try Profound Blog.


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  • Unlocking the Truth Behind Google Ads Recommendations

    Unlocking the Truth Behind Google Ads Recommendations

    As someone who navigates the complexities of Google Ads, I know the mere mention of ‘Recommendations’ can send shivers down your spine. It’s like a pop-up that corners you on every platform screen—when you’re tweaking keywords, setting campaigns, or batching bids, even when you’re simply checking on things!

    I’ve had countless emails from clients fretting over why their ‘Optimization Score’ has suddenly dipped. In this article, I want to demystify what Google Ads Recommendations really are, dispel some myths, and share some tactical advice on how to handle them.

    Why do Google Ads Recommendations get such a bad rap?

    So why this widespread disdain? To me, it’s plain: the expectations simply don’t align. While the system tailors Recommendations to our accounts, it often lacks the nuance needed for unique business goals.

    The algorithm’s designed to spot patterns and suggests tweaks based on what’s working in other accounts. Say you only use Exact and Phrase match keywords—the system might suggest ‘Test Broad Match’ because, theoretically, it could broaden reach, but it may not align with budget constraints or niche specifics.

    Bear in mind, Recommendations initially served as a tool for Google Ads sales reps to identify potential client improvements. In their hands, human insight ensured suggestions were relevant. Now, the human filter is absent, making Recommendations feel less tailored.

    Is the Optimization Score really that important?

    When Google tells you your Optimization Score is low, it’s tempting to perceive it as a failing report card. Many fall into the trap of blindly accepting every suggestion just to see that 100% score light up.

    Let me be candid: resist the urge. This score doesn’t reflect performance but rather measures how actively you are reviewing recommendations. Dismissing a suggestion has the same impact on your score as applying it. So, keep your score at 100% if it’s crucial to your Google Partner status—but otherwise, let it slide.

    Decoding Recommendations vs. Real Issues

    Recommendations might pop up anywhere across the ad platform, not just the designated tab. You’ll see them during account setup, keyword addition, or bid adjustment. These prompts can set off alarms due to their visibility.

    Remember, blue or yellow notifications are mere suggestions. Red or purple signals require immediate attention, potentially indicating a billing error or disapproved ad. Maintain a calm head, and only adopt changes that align with your objectives.

    Are Recommendations just Google’s strategy to boost spending?

    An argument often made is that Recommendations aim to skyrocket spending, subtly capturing more dollars. And sure, Google is profit-driven, but they understand you’ll curb spending if returns don’t justify the expense.

    Suggestions are twofold: some aim at increasing reach and expenditure, while others focus on ROI and account refinements that might not increase costs but enhance efficiency.

    Turn Off Auto-Apply Recommendations

    It’s crucial to mention Auto-Apply Recommendations when discussing these aspects. It’s a feature Google previously championed, enabling automatic implementation of suggestions without checks. Thankfully, it’s losing focus now.

    To take control, head to the Recommendations tab, switch to All Campaigns, click Auto-Apply Settings, and ensure all selections are unchecked. Keep the reins in your hands—Google doesn’t need unsupervised access to your budgets, bids, or keywords.

    Recommendations aren’t inherently good or bad. They are mere prompts to evaluate and test. Listen to your instincts: review, test if promising, or move on if irrelevant.

    This article is part of our ongoing Search Engine Land series, Everything you need to know about Google Ads in less than 3 minutes. In each edition, Jyll highlights a different Google Ads feature and how to maximize it efficiently.


    Inspired by this post on Search Engine Land.


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  • How Google Discover’s Shifts Impact Content Visibility

    How Google Discover’s Shifts Impact Content Visibility

    I’ve noticed a shift in how Google is choosing content for its Discover feed, and it seems less tied to traditional search rankings these days.

    Yesterday, Andy Almeida from the Google Trust and Safety team shared some insights at the Google Search Central Live event in Zurich. He mentioned that Google Discover isn’t as closely aligned with Google Search rankings as it once was.

    Andy presented a slide illustrating how existing systems assist the Google Discover team in addressing challenges. The slide highlighted:

    “Minimal alignment to search ranking gives us the tools we need to combat emerging abuse.”

    Understanding the Implications. This indicates that Google Discover is moving away from relying heavily on Google’s established search systems, particularly concerning combating platform abuse.

    ```json
{
  "alt": "Person presenting at a Google event about search quality systems on a stage with colorful lights.",
  "caption": "A speaker at a Google event discusses solutions in combating web spam and enhancing search recommendations.",
  "description": "The image shows a speaker presenting at a Google event, standing at a wooden podium with a red microphone. On the large screen, there's information about Google's efforts to combat web spam through its search quality systems. The background features a colorful light display, emphasizing Google's innovative environment. Keywords: Google, presentation, search quality, web spam, technology event."
}
```

    When I asked Andy what this meant for publishers, he explained that Google Discover aims to showcase content from lesser-known and smaller publishers. It seems while Google Search may not always favor them, Discover does, focusing more on its own evaluation systems.

    The Challenge with Spam. I’ve been aware of the significant spam issues confronting Google Discover, primarily caused by sites exploiting expired or throwaway domains for spam content. This is a challenge not as prevalent in Google Search.

    Back in 2019, Google stated that its core ranking systems affected visibility in Google Discover, especially after a core update. However, this new approach seems to diverge from that stance.

    Why This Matters. As Google continues to address these spam problems, it’s balancing the visibility of smaller sites on Discover while curbing spam. This is great news for emerging publishers who focus on niche topics, as long as the spam issue can be effectively managed.


    Inspired by this post on Search Engine Land.


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  • Google Quietly Releases Unannounced Core Updates

    Google Quietly Releases Unannounced Core Updates

    I recently learned that Google has been rolling out smaller core updates without any announcements. This revelation came from a new section added to the core updates documentation for developers. While Google has mentioned this before, they’ve now made it official in their documentation.

    What’s New: Google included the following new information:

    We don’t have to wait for a major core update to see the impact of any improvements we’ve made. Google’s search algorithms are continually evolving through minor core updates. These updates may not be announced because they’re usually not very noticeable. However, they’re another opportunity for improved content to climb in search rankings.

    Google’s Explanation: According to Google, this addition to the documentation helps site owners understand that significant improvements can lead to better positions in search results without awaiting a major core update.

    Even Danny Sullivan, the former Google Search Liaison, shared similar insights with us back in August 2019. He explained how broad core updates occur every few months and improvements might not reflect until the next one. However, he emphasized that Google’s ongoing algorithm tweaks, like these smaller updates, can help recovery if content has been improved.

    A Larger Update Is On The Way: At the Google Search Central Live event in Zurich, John Mueller from Google hinted that a core update is in the works and might be released soon. He thinks it’ll take a bit longer than a couple of weeks but left us with no exact date.

    Why It’s Important: This confirmation is a reminder that Google regularly implements these smaller core updates. It’s crucial to keep our content optimized and anticipate a significant core update soon, which could lead to even more prominent changes in search results and rankings.


    Inspired by this post on Search Engine Land.


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  • AI Chats: Unveiling the Surprising Lack of Commercial Intent

    AI Chats: Unveiling the Surprising Lack of Commercial Intent

    I recently discovered something fascinating about how people interact with AI. It turns out most AI chats don’t have any commercial intent! This insight came from a thorough analysis by Dan Petrovic, the director of AI SEO agency Dejan, who scrutinized millions of conversational turns to shed light on actual AI assistant usage.

    Why is this important to us? As someone involved in SEO and marketing, I’m often focused on optimizing for AI. However, Petrovic’s research suggests we might be misunderstanding how people genuinely engage with AI assistants. They don’t typically flood AI with purchase queries. Instead, they explore issues and weigh options.

    By the numbers, Petrovic dived into 4.4 billion characters across 613 million words and 3.9 million conversation turns. Here’s what that looks like:

    • Median chat: Just 2 turns, usually involving a quick question and an immediate response.
      • While most interactions are short, there are lengthy sessions when users paste documents for summarization or analysis.
    • Median words per session: 430 words.
      • Astonishingly, more than 80% of chats contain fewer than 1,000 words.
      • Only a small fraction, 4.2%, exceed 2,500 words. These are often complex tasks, like editing, coding, or tutoring.
    • Mean words: 732. This statistic is heavily influenced by long document submissions.
    • Assistant output: Typically, it’s 1.5 times more than what users contribute.
    • Median user contribution: Users make up about 16-17% of the conversation.

    In exploring how people utilize AI assistants, Petrovic examined 24,259 sessions across 42 intent categories. Surprisingly, 64.6% of chats didn’t align with any purchase funnel. People used AI for writing, brainstorming, planning, learning, analyzing, or just simply chatting. Here’s the breakdown:

    • Other: 25%
      • Included are jailbreak attempts, role-playing, and specific requests.
    • Brainstorming: 7.7%
    • Planning: 6.5%
    • Conversation / emotional support: 6.2%
    • Analysis: 5.7%
    • Learning: 4.7%
    • Transformation (summaries, translations): 4.6%
    • Creation (writing, code, docs): 3.9%

    Only 35.4% of chats showed any commercial intent, and most were in the early stages of the buying process. Other insights:

    • Awareness (10%) and consideration (8.5%) combined to form 18.5%, which Petrovic noted as prime territory for product content.
    • Post-purchase needs (5.1%) outpaced transactional support (4.8%), discovery (4.1%), and decision support (2.8%), suggesting users seek AI more for ‘How do I use or fix this?’ rather than ‘Should I buy this?’

    Bottom line, my takeaway is that AI assistants are utilized far more for creation, cognition, and conversation than for commerce.

    If you’re keen to dive deeper into the findings, check out the full report titled How do people use AI assistants?


    Inspired by this post on Search Engine Land.


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  • Unlock Google Data Manager API for Enhanced Ad Performance

    Unlock Google Data Manager API for Enhanced Ad Performance

    I’ve just discovered a game-changer from Google that could simplify our advertising efforts significantly. Their new Data Manager API offers a streamlined way for us to feed our valuable first-party data directly into Google’s sophisticated AI systems.

    As an advertiser, utilizing the Data Manager API means I can seamlessly connect our first-party data with Google’s AI-driven ad tools. This connection is poised to elevate our measurement, targeting, and overall performance, eliminating the hassle of managing multiple systems.

    Why I care. By leveraging the Data Manager API, I’m able to inject high-quality data into Google’s AI, which optimizes targeting, measurement, and bidding processes. It replaces the need for various APIs, reducing our engineering workload and accelerating insights into our campaigns. With the decline of cookies, this API is crucial for maximizing the data we already have.

    Driving the news. This API serves as a single integration point, unifying multiple Google platform APIs. It’s designed for advertisers, agencies, and developers, making our lives a lot easier.

    Here’s what I can do with it:

    • Upload and refresh audience lists
    • Send offline conversions for improved measurement
    • Enhance bidding performance by providing Google AI with richer signals

    This API expands upon Google’s existing codeless Data Manager tool, which is already in use by thousands of advertisers to activate first-party data.

    Partnership push. To speed up adoption, Google is integrating with several partners, including AdSwerve, Customerlabs, Data Hash, and others.

    State of play. Starting today, the API is available across Google Ads, Google Analytics, and Display & Video 360, with more integrations to follow.

    The bottom line. Adopting the Data Manager API empowers us by enhancing Google’s AI capabilities, improving measurement, reducing technical complexities, and driving better ad performance, all while gearing up for a future that prioritizes privacy.


    Inspired by this post on Search Engine Land.


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  • Boost Local Sales with Google Shopping’s New Location Labels

    Boost Local Sales with Google Shopping’s New Location Labels

    I’ve noticed something exciting: Google is testing an innovative feature that enhances the local feel of Shopping ads. Some ads that utilize local inventory feeds now showcase the merchant’s city or town just above the product title. Imagine seeing ‘London’ or ‘Tonbridge’ alongside your favorite product, giving you an instant connection to where the store is located.

    Why this matters to me. The addition of these location labels makes Shopping ads significantly more personable and trustworthy. For retailers in my vicinity, this could be a game-changer, as it helps them stand out against a sea of competitors. By clearly indicating a store’s location, there’s a greater likelihood of increased click-through rates and more in-store visits from shoppers, just like myself, who prefer supporting local businesses.

    This feature also offers merchants using local inventory feeds a competitive advantage by promoting their proximity without the need for new ad formats or extra configuration.

    How it operates. These labels are integrated into Shopping ads that already incorporate local inventory data. This addition complements existing tags like:

    • In-store
    • Pickup later
    • Curbside pickup

    What’s unique about this label is its exclusive focus on the store’s location, as opposed to fulfillment options.

    ```json
{
  "alt": "Sponsored product listing showing three colouring books with prices and collect locations.",
  "caption": "Explore creative opportunities with these sponsored colouring books, available for pickup in Tonbridge and London. Prices start at just £4.00!",
  "description": "The image displays a sponsored product listing for three colouring books: 'Zen Colouring 51: Advanced Art', 'Floral Pocket Colouring Book', and 'Kawaii Mandala Colouring Book'. The Zen Colouring book is priced at £6.99 and available in Tonbridge, while the other two are priced at £4.00 and £7.99, available for collection in London. The listing features collecting details, pricing, and user ratings to assist potential buyers."
}
```

    The drawback. Google hasn’t officially announced this feature, and details about its rollout, eligibility, and technical requirements are still under wraps.

    Reading between the lines. For merchants operating in renowned or high-trust locations, this could significantly boost visibility. As a customer, I’m nudged to prefer nearby retailers over expansive marketplaces or distant sellers, which is a win for local communities.

    Spotted first. This update was originally reported by Hana Kobzová, founder of PPC News Feed. Her keen eye on these developments certainly keeps us informed.


    Inspired by this post on Search Engine Land.


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