Month: July 2026

  • 7 Best Healthcare Agentic Search Agencies for 2026

    7 Best Healthcare Agentic Search Agencies for 2026

    I see Agentic Search Optimization (ASO) as the latest evolution of SEO. It focuses on improving rankings and conversions among prospects who use agentic search platforms such as ChatGPT Agent or Claude CoWork. With many marketing experts expecting ASO to become a major marketing channel by 2027, I believe healthcare organizations should begin evaluating this opportunity now.

    With that shift in mind, my research team and I set out to identify the ASO agencies best equipped to serve the healthcare sector. In Q2 2026, we evaluated more than 40 agencies with documented AI, GEO, and agentic search capabilities. We scored each agency using six weighted factors:

    • ASO Expertise Score (25%): We measured the breadth and depth of each agency’s agentic search capabilities.
    • Average Review Score (20%): We considered client ratings across Google, Clutch, G2, and other verified review platforms.
    • Leadership Experience Score (20%): We assessed each leadership team’s healthcare marketing expertise, regulatory fluency, and demonstrated experience in Generative Engine Optimization (GEO) and agentic search.
    • Notable Healthcare Clients (15%): We evaluated the quality and prominence of each agency’s documented healthcare client portfolio.
    • Year Established (10%): We used the agency’s founding year as a proxy for institutional depth and its track record in healthcare marketing.
    • Media References (10%): We estimated citations across authoritative industry publications to assess each agency’s standing in healthcare marketing and digital search.

    Based on that methodology, I selected the following seven firms as the best healthcare agentic search optimization agencies of 2026.

    RankCompanyASO Expertise Score (1–5)Average Review Score (1–5)Leadership Experience Score (1–5)Notable Healthcare ClientsYear EstablishedMedia ReferencesSpecialty
    1First Page Sage4.84.94.8Dignity Health, Index Health, GlobalMed2009~810Full-service ASO for healthcare and pharmaceutical organizations
    2Focus Digital4.44.84.3GoHealth Urgent Care, The Chinquee Center, Center for Podiatric Care2018~75Agentic GEO and SEO for healthcare providers and commercial organizations
    3Genevate4.64.84.2PharmaEssentia, Eton Pharmaceuticals, Beghou2025~20ASO and GEO for pharmaceutical organizations
    4Driven Metrics4.44.74.3Mypurmist, TruSkin, Tesseract Medical2025~60Analytics-driven GEO and ASO for healthcare and wellness organizations
    5Medico Digital4.14.44.6Merit Medical, Teleflex2013~40SEO, GEO, and PPC for UK-based medical device and pharmaceutical organizations
    6Signal Hill Strategies4.04.54.1Opus Genetics, DOCS Medical, Affirmed Home Care2026~15Revenue-driven SEO and GEO for medical organizations
    7MGMT Digital3.74.43.9Elevation Behavioral Health, Pacific Mind Health, ABA Revolution2017~35Digital marketing and GEO for behavioral health and addiction treatment providers

    1. First Page Sage

    I ranked First Page Sage first because it earned the highest scores across all three of my primary criteria: ASO expertise, average client reviews, and leadership experience. I also found that the agency entered agentic search early and approached it deliberately. FPS President Evan Bailyn published pioneering research on ASO in June 2026, and the agency built its healthcare ASO program directly from that framework. Its experience spans healthcare providers, pharmaceutical companies, medical device manufacturers, and health technology companies.

    I consider credibility especially important in health and medical search because AI platforms treat this content conservatively, and inaccurate information can have direct consequences for the public. As a result, an organization must clear a high credibility threshold before an AI agent will act on its behalf. I found that First Page Sage begins by mapping what AI platforms appear to believe about a healthcare organization, comparing those beliefs with competitors, and identifying gaps before developing a content strategy.

    From that baseline, I found that the agency develops thought-leadership content and intake infrastructure intended to move an AI agent from discovering an organization to selecting it and completing an action. That action might include downloading a clinical study or booking a consultation.

    • ASO Expertise Score: 4.8
    • Average Review Score: 4.9
    • Leadership Experience Score: 4.8
    • Notable Healthcare Clients: Dignity Health, Index Health, GlobalMed
    • Year Established: 2009
    • Media References: ~810
    • Specialty: Full-service ASO for healthcare and pharmaceutical organizations
    • Contact: First Page Sage website

    What I found in online reviews: Healthcare clients described First Page Sage as “ahead of the curve when it comes to agentic search” and “extremely meticulous in their research and content creation.” Others said that working with the firm was “the first time we didn’t have to choose between ranking well and staying compliant,” although some cautioned that “[their] process is pretty involved.”

    2. Focus Digital

    I found Focus Digital particularly well suited to smaller practices and midsize provider groups. Its healthcare work spans urgent care clinics, specialty practices, and outpatient care categories. The agency’s ASO service addresses the full path from helping an organization get discovered to ensuring it is evaluated favorably and selected by an AI agent acting for a patient or buyer.

    I also see Focus Digital’s cost structure and team model as an accessible option for organizations that want agentic optimization without the overhead associated with a large agency. However, I found that its pricing and staffing are better suited to focused engagements than enterprise-scale campaigns. A single-site practice may be a natural fit, while a health system managing numerous locations, competing service lines, or high patient-acquisition volume may need a larger delivery model.

    • ASO Expertise Score: 4.4
    • Average Review Score: 4.8
    • Leadership Experience Score: 4.3
    • Notable Healthcare Clients: GoHealth Urgent Care, The Chinquee Center, Center for Podiatric Care
    • Year Established: 2018
    • Media References: ~75
    • Specialty: Agentic GEO and SEO for healthcare providers and commercial organizations
    • Contact: Focus Digital website

    What I found in online reviews: Clients described Focus Digital as “straightforward about timelines and what to expect” and “more responsive than we anticipated.” Some also said that the experience was “less polished than working with a larger agency.”

    3. Genevate

    I found Genevate’s ASO practice most relevant to pharmaceutical companies and other highly regulated healthcare organizations. In this market, FDA promotional restrictions, YMYL-related caution in the way AI platforms handle drug information, and the gap between older AI training data and a company’s current positioning can combine to create a credibility problem that standard optimization methods may not address.

    Genevate’s healthcare ASO program stood out to me because it aims to align what major AI platforms believe and communicate about a brand with what the organization can legitimately claim and what patients or providers want to know. That focus makes the agency a compelling specialist for pharmaceutical organizations navigating strict regulatory boundaries.

    At the same time, I see its pharmaceutical specialization as a less natural fit for healthcare providers, health systems, and health technology companies whose AI-search challenges are driven more by market competition than regulatory constraints. Because Genevate launched in 2025, I also found fewer documented outcomes and third-party validations than I would expect from a more established agency. That may matter to pharmaceutical companies with rigorous vendor-vetting requirements.

    • ASO Expertise Score: 4.6
    • Average Review Score: 4.8
    • Leadership Experience Score: 4.2
    • Notable Healthcare Clients: PharmaEssentia, Eton Pharmaceuticals, Beghou
    • Year Established: 2025
    • Media References: ~20
    • Specialty: ASO and GEO for pharmaceutical organizations
    • Contact: Genevate website

    What I found in online reviews: Clients called Genevate “surprisingly agile for such a young company” and described its strategic direction as “responsive and specific.” Some noted that “results in AI search take longer to appear than traditional SEO” and that “their healthcare expertise is still developing.”

    4. Driven Metrics

    I found that Driven Metrics differentiates itself through a measurement system that many GEO and agentic search agencies do not offer. Instead of treating AI search as a discipline whose results will appear at an undefined point in the future, the agency tracks which AI-generated placements produce qualified inquiries, which belief corrections influence agentic selection, and how performance changes over time.

    I see that approach as particularly useful for healthcare organizations that must connect their AI-search investment to measurable patient acquisition and demonstrate marketing ROI internally. It can provide a level of clarity that many organizations struggle to achieve when evaluating an emerging channel.

    However, I found Driven Metrics’ analytics-first model stronger in measurement and optimization than in the foundational content development and authority building that shape credibility on AI platforms. A healthcare organization that needs equal depth in both areas may have to supplement the agency’s service.

    • ASO Expertise Score: 4.4
    • Average Review Score: 4.7
    • Leadership Experience Score: 4.3
    • Notable Healthcare Clients: Mypurmist, TruSkin, Tesseract Medical
    • Year Established: 2025
    • Media References: ~60
    • Specialty: Analytics-driven GEO and ASO for healthcare and wellness organizations
    • Contact: Driven Metrics website

    What I found in online reviews: Clients described Driven Metrics as “refreshingly data-driven” and said its reporting was “more transparent than what we received from previous agencies.” Some also noted that “their healthcare experience is still developing” and that the engagement “requires more internal effort” than they initially expected.

    5. Medico Digital

    I found Medico Digital to be a strong UK-based healthcare digital marketing specialist with experience serving pharmaceutical and medical device companies. The agency develops GEO programs around the queries hospital procurement teams, surgeons, and clinicians use when researching products and treatment options.

    However, I found that GEO is only one part of its wider offering, which also includes PPC, web design, and traditional SEO. Its website did not indicate that ASO was currently part of its services. I also see its UK location as a potential limitation for US healthcare organizations seeking a domestic partner with deep familiarity with FDA requirements and US market dynamics.

    For UK-based pharmaceutical and medical device companies that have not yet expanded deeply into agentic search, however, I believe Medico Digital may still be worth considering.

    • ASO Expertise Score: 4.1
    • Average Review Score: 4.4
    • Leadership Experience Score: 4.6
    • Notable Healthcare Clients: Merit Medical, Teleflex
    • Year Established: 2013
    • Media References: ~40
    • Specialty: SEO, GEO, and PPC for UK-based medical device and pharmaceutical organizations
    • Contact: Medico Digital website

    What I found in online reviews: Clients described the Medico Digital team as “versed in pharma regulations” and praised its ability to “translate complex product information into content.” Some said working with a UK-based agency created “difficult coordination around US market nuances” and felt that “their agentic knowledge appears limited.”

    6. Signal Hill Strategies

    I found Signal Hill Strategies focused on converting AI and organic search demand into qualified inquiries for healthcare and pharmaceutical organizations. Its GEO work aims to place medical clients in AI-generated results for the queries most likely to produce leads. In my view, that visibility supplies the foundation an agentic search strategy needs before an AI agent can select an organization and complete an action.

    I would nevertheless weigh the agency’s recent founding, limited documented client portfolio, and relatively small number of media references carefully. Together, those factors create a risk profile that may concern more conservative healthcare organizations. For medical or pharmaceutical organizations prioritizing qualified lead volume from AI search in the near term, I still believe the model is worth evaluating within those limitations.

    • ASO Expertise Score: 4.0
    • Average Review Score: 4.5
    • Leadership Experience Score: 4.1
    • Notable Healthcare Clients: Opus Genetics, DOCS Medical, Affirmed Home Care
    • Year Established: 2026
    • Media References: ~15
    • Specialty: Revenue-driven SEO and GEO for medical organizations
    • Contact: Signal Hill Strategies website

    What I found in online reviews: Clients described Signal Hill Strategies as “ROI focused” and praised its “dedication to healthcare clients.” Some cautioned that the agency’s “newness means less to evaluate upfront” and said it “require[s] more vetting than usual.”

    7. MGMT Digital

    I found MGMT Digital distinctive because of its focus on behavioral health marketing, including addiction treatment and mental health. Its GEO service reflects how behavioral health patients actually search. In this field, queries are often indirect and hesitant, and I see AI platforms increasingly becoming the first touchpoint for people who are not yet ready to search explicitly for treatment.

    I also see that specialization as the agency’s primary limitation. Health systems, pharmaceutical companies, medical device manufacturers, and other organizations outside behavioral health may find its expertise difficult to translate to their needs. For behavioral health and addiction treatment providers, however, I believe its depth of sector knowledge makes it a strong niche option.

    • ASO Expertise Score: 3.7
    • Average Review Score: 4.4
    • Leadership Experience Score: 3.9
    • Notable Healthcare Clients: Elevation Behavioral Health, Pacific Mind Health, ABA Revolution
    • Year Established: 2017
    • Media References: ~35
    • Specialty: Digital marketing and GEO for behavioral health and addiction treatment providers
    • Contact: MGMT Digital website

    What I found in online reviews: Clients appreciated MGMT Digital’s “thoughtful approach.” However, some felt that the agency was “too specialized to fit other healthcare markets.”

    How I Would Choose a Healthcare ASO Agency

    I would begin by matching each agency’s specialty and delivery model to the organization’s specific needs. First Page Sage offers the strongest overall combination of ASO expertise, reviews, leadership experience, and institutional depth in this ranking. Focus Digital appears more accessible for smaller providers, while Genevate stands out for pharmaceutical organizations facing strict regulatory constraints.

    I would consider Driven Metrics when measurement and attribution are central priorities, Medico Digital for UK-based pharmaceutical or medical device marketing, Signal Hill Strategies for near-term lead generation, and MGMT Digital for behavioral health or addiction treatment. Before making a final decision, I would also examine the proposed scope, compliance process, reporting standards, team capacity, and evidence that the agency can influence both AI visibility and completed patient or buyer actions.

    Source


    Inspired by this post on First Page Sage Blog.


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  • 6 Best Transportation & Logistics GEO/AEO Agencies for 2026

    6 Best Transportation & Logistics GEO/AEO Agencies for 2026

    We see GEO (generative engine optimization) and AEO (answer engine optimization) becoming increasingly important entry points for B2B buyers in freight, logistics, and supply chain. These practices help companies earn recommendations when prospective customers ask AI platforms to suggest providers. To identify the agencies doing this work most effectively, our research team evaluated 34 firms with documented GEO and AEO capabilities.

    We weighted six factors in our assessment:

    • AI Visibility (25%): We measured how consistently each agency gets transportation and logistics clients recommended when prospective customers ask AI platforms for provider suggestions.
    • Transportation and Logistics Specialization (20%): We considered the agency’s industry knowledge and understanding of how transportation and logistics businesses operate.
    • GEO/AEO Expertise (20%): We evaluated each team’s hands-on knowledge of GEO and AEO mechanics.
    • Notable Clients (15%): We looked for documented experience with transportation, logistics, freight, or supply chain clients.
    • Leadership Experience (10%): We assessed the leadership team’s digital marketing background and firsthand experience building and executing GEO programs for transportation and logistics companies.
    • Average Review Score (10%): We aggregated ratings across Google, Clutch, and G2.

    Based on those criteria, we identified the following agencies as the strongest transportation and logistics GEO partners for companies seeking customers through the expanding field of AI-driven search.

    Our Top Transportation and Logistics GEO Agencies

    RankCompanyAI Visibility (1–5)T&L Specialization (1–5)GEO/AEO Expertise (1–5)Leadership Experience (1–5)Average Review Score (1–5)Notable Clients
    1First Page Sage4.94.65.04.84.9iGPS, Montway Auto Transport, BKM Transport, Summa Energy
    2Genevate4.64.14.84.24.8Missionary Expediters & Cargo
    3Focus Digital4.24.34.54.34.8Bowker Transport
    4Driven Metrics4.44.04.44.34.7AutoStar Transport Express
    5Virayo3.84.53.93.84.8Truckstop, Onfleet, TruckLabs
    6Elevation Marketing3.24.73.54.54.3Chasewater Industries, Caterpillar, GE

    1. First Page Sage

    We found that two qualities separate First Page Sage from the rest of the field. First, the agency has spent nearly two decades working with freight carriers, third-party logistics firms, and supply chain providers. Second, its president, Evan Bailyn, pioneered GEO as a service in 2023, before most agencies had begun determining how to optimize content for AI.

    Those advantages help explain why First Page Sage is the only agency in our ranking to earn a 5.0 for GEO/AEO Expertise. Its AI Visibility score of 4.9 also leads the field by a meaningful margin.

    We were particularly impressed by the agency’s depth of freight and logistics content across asset-based carriers, third-party logistics providers, freight technology platforms, and supply chain consultancies. The work is designed to strengthen clients’ reputations and generate qualified leads by getting those companies named when shippers and brokers ask AI platforms for recommendations. For transportation and logistics providers comparing GEO/AEO partners, we believe this combination of industry knowledge and GEO expertise puts First Page Sage in a category of its own.

    • AI Visibility: 4.9
    • T&L Specialization: 4.6
    • GEO/AEO Expertise: 5.0
    • Notable Clients: iGPS, Montway Auto Transport, BKM Transport, Summa Energy
    • Leadership Experience: 4.8
    • Average Review Score: 4.9

    What We Found in Online Reviews

    One freight technology client said the team “got us showing up when brokers ask ChatGPT for recommendations.” Another reported that “leads actually started coming in around month four.” We also noticed that several reviewers had continued working with the agency for years.

    2. Genevate

    Founded in 2025 by PR and communications leader Brett Kleinberg, Genevate was built specifically for the generative AI era instead of being retrofitted from an older SEO model. We found its approach especially interesting because the team considers not only whether AI platforms mention a company, but also whether they describe that company accurately.

    Genevate uses strategic PR and citation building to influence how AI platforms characterize a brand, helping the company appear as the specialist it truly is. In our view, this focus addresses an important part of GEO/AEO that many agencies overlook.

    We should note that Genevate is a newer agency, so its portfolio is still developing, which is reflected in its Leadership Experience score. Even so, we consider it a strong fit for logistics companies that want GEO support and are comfortable partnering with a newer firm.

    • AI Visibility: 4.6
    • T&L Specialization: 4.1
    • GEO/AEO Expertise: 4.8
    • Notable Clients: Missionary Expediters & Cargo
    • Leadership Experience: 4.2
    • Average Review Score: 4.8

    What We Found in Online Reviews

    Clients describe Genevate as a company that “makes sure AI actually describes us right, not just that we show up.” We also found a few clients who pointed out that the agency is “still pretty new, so their portfolio’s thinner than other options.”

    3. Focus Digital

    We see Focus Digital as an appealing option for smaller transportation companies that want an enterprise-level GEO/AEO methodology without the pricing of a larger agency. Clients receive founder-level attention, straightforward reporting, and realistic timelines. That makes the agency a particularly good fit for regional carriers, smaller freight brokers, and supply chain firms that still want visibility in AI-generated results.

    The trade-off, in our assessment, is industry coverage. Focus Digital deliberately maintains a narrow scope, while its case study portfolio leans toward professional services, manufacturing, and home services. We recommend that transportation clients carefully review industry-specific content for accuracy before publication.

    • AI Visibility: 4.2
    • T&L Specialization: 4.3
    • GEO/AEO Expertise: 4.5
    • Notable Clients: Bowker Transport
    • Leadership Experience: 4.3
    • Average Review Score: 4.8

    What We Found in Online Reviews

    Focus Digital clients appreciate that the team is “straight with us about what is realistic.” One client said they began to “show up in AI answers within a few months.” We also saw reviewers caution that “replies slow down when they’re busy.”

    4. Driven Metrics

    Driven Metrics offers what we consider an enterprise-grade GEO/AEO framework at a price that growth-stage companies can manage. Its operating model emphasizes weekly meetings, transparent reporting, and conversion tracking instead of relying solely on raw traffic. As a result, content that fails to earn citations or generate leads can be identified and revised quickly.

    For a logistics company seeking disciplined, high-end GEO/AEO execution without a large-agency price tag, we believe that combination is difficult to find elsewhere.

    We did identify a couple of considerations. Driven Metrics has respectable transportation and logistics experience, but its client base is still growing. Its depth within a particular freight category or logistics model may therefore be thinner than that of a more established agency. We believe transportation companies will get the best results by investing time upfront to explain their operational models, helping the team create content that accurately reflects how buyers in each niche search.

    • AI Visibility: 4.4
    • T&L Specialization: 4.0
    • GEO/AEO Expertise: 4.4
    • Notable Clients: AutoStar Transport Express
    • Leadership Experience: 4.3
    • Average Review Score: 4.7

    What We Found in Online Reviews

    One client said, “We got results with no excuses, which was refreshing.” Another appreciated that the team “got timely reporting.” However, we also found comments about the agency’s “more limited transportation experience.”

    5. Virayo

    We found that Virayo has a strong marketing track record with freight and logistics companies. The agency published a case study with specific traffic and lead figures from its work with Truckstop, one of North America’s largest load boards. It has also delivered results for TruckLabs and the last-mile platform Onfleet.

    That experience matters for GEO/AEO because the authority and citation work that helped these clients earn organic rankings can also help them appear when brokers and carriers ask AI tools for recommendations.

    In our assessment, Virayo still leans more heavily toward SEO than GEO/AEO, and transportation clients compete for attention alongside a broad B2B SaaS roster. Nevertheless, we consider it a strong choice for logistics and freight technology companies seeking proven search fundamentals supported by a credible and expanding AI layer.

    • AI Visibility: 3.8
    • T&L Specialization: 4.5
    • GEO/AEO Expertise: 3.9
    • Notable Clients: Truckstop, Onfleet, TruckLabs
    • Leadership Experience: 3.8
    • Average Review Score: 4.8

    What We Found in Online Reviews

    A transportation software client called the Virayo team “super responsive and easy to work with.” We also found a reviewer who said its work “leans more toward SEO than strong AI strategy.”

    6. Elevation Marketing

    Elevation Marketing has served B2B transportation and logistics clients for more than two decades. Based on our review, that longevity makes the vertical a core part of its practice rather than an adjacent service. The agency operates a dedicated trucking and logistics offering and brings substantial leadership depth. President Scott Miraglia has held COO and CFO positions at a major regional agency and has helped place companies on the Inc. 5000 list five times.

    We found, however, that Elevation is still developing its GEO and AEO services. Its established toolkit centers on account-based marketing, demand generation, and integrated B2B campaigns, while its AI practice is newer than those core offerings.

    Companies primarily focused on maximizing citation volume may find a better fit elsewhere. For a transportation company that wants an experienced, full-service B2B partner with genuine freight knowledge, however, we believe Elevation remains a compelling option.

    • AI Visibility: 3.2
    • T&L Specialization: 4.7
    • GEO/AEO Expertise: 3.5
    • Notable Clients: Chasewater Industries, Caterpillar, GE
    • Leadership Experience: 4.5
    • Average Review Score: 4.3

    What We Found in Online Reviews

    Clients say the agency “actually get how B2B buyers think.” A few reviewers felt it was “pricier than the smaller shops we looked at,” although most emphasized that “nothing felt cookie-cutter.”

    Source


    Inspired by this post on First Page Sage Blog.


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  • Google UCP and SEO: How I’m Preparing for AI Commerce

    Google UCP and SEO: How I’m Preparing for AI Commerce

    Google's Universal Commerce Protocol changes the path from search to sale

    For as long as I’ve worked in search marketing, I’ve viewed the path to purchase as a simple sequence: search query → click → buy.

    I’ve approached SEO through much the same model, using organic traffic, impressions, and click-through rate (CTR) as the primary measures of success.

    Google’s Universal Commerce Protocol (UCP) tells me that this familiar path is changing. Google is evolving from a discovery engine into a transaction layer where searching and buying can happen inside the same experience.

    With the rise of “agentic commerce,” I’m seeing Google gain the ability to discover, evaluate, compare, and purchase products on a user’s behalf within AI-powered experiences such as AI Mode, Gemini, YouTube, and Gmail.

    I believe the SEO implications are substantial. Instead of optimizing only for clicks, I now need to think about optimizing for AI-assisted transactions. If a brand cannot communicate through UCP and the product data that supports it, it risks becoming invisible to the next generation of shoppers.

    Here’s how I understand UCP, why I think it will reshape digital marketing, and what I recommend doing now to prepare an SEO strategy for agentic commerce.

    UCP: The infrastructure behind AI transactions

    I think of UCP as an open-source, vendor-agnostic standard that supports the entire commerce lifecycle inside an AI interface. That lifecycle can extend from product discovery and cart creation through checkout, fulfillment, and post-purchase tracking.

    Google co-developed UCP with Shopify, Walmart, Target, Wayfair, Etsy, and other commerce leaders. From my perspective, it acts as a universal translator between AI shopping agents and the systems merchants use to operate their online stores.

    Google UCP - Pay with GPay

    The clearest analogy I can make is that UCP may become the ecommerce equivalent of HTTPS. HTTPS standardizes secure communication between browsers and servers; UCP standardizes how AI agents interact with online stores. Instead of building a custom one-to-one integration for every merchant, an AI agent can use a shared framework to browse inventory securely and complete purchases across many stores.

    How I see AI transactions flowing through UCP

    Imagine I ask AI Mode to “find and order a replacement water filter for a 2021 Samsung French-door fridge with the fastest shipping.” UCP can coordinate that transaction through a structured workflow.

    Capability publication

    First, I expect the merchant to publish the capabilities its store supports, including product search, live pricing, fulfillment options, and accepted payment methods. This gives the AI agent a clear picture of what it can request and complete.

    Three mobile screens show a Monos suitcase listing, Google Pay order review, and completed checkout through Google’s Universal Commerce Protocol.
    From product discovery to payment and confirmation, this mobile shopping sequence shows a Monos suitcase purchase completed with Google Pay through Google’s Universal Commerce Protocol.

    Handshake

    Next, the AI agent reads the merchant’s profile, compares those capabilities with its own, and establishes a secure path forward. I see this step as the point where the systems can align on details such as loyalty programs and supported digital wallets.

    Action execution

    Once the systems are aligned, the AI searches for the product, verifies real-time inventory, builds the cart, and uses the Agent Payments Protocol (AP2) to complete a secure, tokenized transaction.

    Human escalation

    If the transaction needs my input—perhaps to select a delivery window or confirm a shipping address—UCP can pause the process and prompt me. After I respond, control returns to the AI so it can finish the workflow.

    Dig deeper: How Google’s Universal Commerce Protocol could reshape search conversions


    Why I believe UCP matters for search and SEO

    I don’t see UCP as merely a technical update. I see it changing the way AI discovers, evaluates, and purchases products—and that makes it directly relevant to SEO.

    1. I’m shifting from click-throughs to buy-throughs

    In an agentic search environment, I can no longer treat website traffic as the only measure of business value. Features such as Universal Cart can let shoppers add products from multiple retailers to one Google cart and check out with Google Wallet, dramatically shortening the buying journey.

    A shopper may never visit my homepage, category page, or product detail page. That changes my SEO objective: I need to earn product selection within the AI recommendation layer so a search query can become a sale even when it generates no intermediate website visit.

    2. I’m planning for hyper-personalized queries

    I’m also rethinking keyword research. Shoppers are moving beyond broad searches such as “men’s running shoes” and using detailed, situational prompts like “Best running shoes for flat feet under $150 that can arrive by Friday.”

    To match a request that specific, I know a search engine needs more than polished on-page copy. It needs rich, structured, and queryable product attributes. UCP helps bridge that gap by giving AI agents a way to match merchant inventory with a shopper’s precise requirements.

    3. I expect less checkout friction

    I continue to see cart abandonment as a major ecommerce challenge, especially when shoppers encounter long forms, broken checkout flows, or unexpected shipping costs. Because UCP can work with secure digital wallets and automatically pass verified user data, I expect it to eliminate many of those friction points.

    Glowing blue streams of people converge on a search bar and digital portal, symbolizing SEO traffic, AI visibility, and customer acquisition.
    As AI reshapes search, every glowing path to discovery carries commercial value—turning SEO investment into a conversation about pipeline, risk, and customer acquisition costs.

    For high-intent, urgent, or repeat purchases, I believe merchants that support UCP may capture more conversions than competitors that send every shopper to a separate checkout experience.

    4. I can retain brand control and customer ownership

    One detail I consider especially important is that the merchant remains the Merchant of Record when a transaction takes place through UCP. I can still control pricing, fulfillment, and return policies while retaining the customer relationship and first-party data. UCP provides the transactional infrastructure without replacing the merchant’s role.

    Dig deeper: Winning the AI decision layer: From AI discovery to agentic commerce

    How I recommend preparing a brand for UCP

    If I limit an SEO strategy to blog articles and meta descriptions, I overlook the technical infrastructure that powers AI commerce. To make products eligible for UCP-powered experiences, I recommend focusing on the following priorities.

    I would optimize the Merchant Center feed

    I no longer view Google Merchant Center (GMC) as a tool used only for Shopping ads. I see it becoming a primary source of product information for AI discovery, which makes feed quality central to both visibility and transaction eligibility.

    • Enable the native_commerce attribute: To opt into UCP-powered checkouts, I would add the native_commerce attribute to the product feed. Google recommends using supplemental feeds to apply it at the product level without changing the primary feed.
    • Map product identifiers: I would make sure every product ID in the GMC feed maps one-to-one with the corresponding ID in the internal checkout API. If the identifiers differ, I would use the merchant_item_id attribute to align them.
    • Complete policy data: I would keep returns, shipping, and customer-support information complete and current. Clear policy data gives an AI agent the details it needs to evaluate a merchant confidently.

    I would align structured data with the product feed

    Because AI search depends on consistent information, I would keep the Product, Offer, and Review schema on the website synchronized with the Merchant Center feed. If the price, availability, identifiers, or other details conflict, validation problems could make a product ineligible for AI-powered checkout.

    I would prepare for conversational attributes

    As Google introduces semantic attributes designed for conversational AI search, I would prepare inventory and product-information systems to supply richer answers. In particular, I would prioritize:

    • Real-time inventory availability.
    • Direct answers to product FAQs, such as “Is this jacket machine washable?”
    • Detailed compatibility information, including accessory pairings, sizing guides, and model-specific replacements.

    I would treat these details as more than feed enhancements. They are the signals that help an AI agent decide whether a product satisfies a nuanced request involving price, fit, compatibility, delivery speed, or another real-world constraint.

    Beyond clicks: The next SEO opportunity I see

    To me, the Universal Commerce Protocol reflects a broader transformation in search. It expands the role of SEO beyond generating traffic and brings product data, inventory systems, checkout infrastructure, and conversion readiness into the search conversation.

    By prioritizing structured product data, reliable commerce information, and readiness for agentic transactions, I can position a brand to capture demand at the exact moment a shopper expresses intent.

    I don’t believe the future of search will be only about getting found. Increasingly, it will be about making sure the products I represent can be evaluated, selected, and bought.


    Inspired by this post on Search Engine Land.


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  • Why Frontloading Ad Spend Backfires—and How I Scale

    Why Frontloading Ad Spend Backfires—and How I Scale

    Why frontloading your ad spend usually backfires

    I don’t recommend launching most paid media campaigns with the biggest budget available.

    When I see advertisers spend aggressively before validating performance, the outcome is often predictable: acquisition costs rise, optimization slows, and stakeholder confidence weakens when the promised results fail to appear.

    I prefer a phased rollout because it gives a campaign time to generate meaningful data, improve bidding efficiency, and reveal which audiences, keywords, and creative ideas deserve more investment.

    Here, I’ll explain why frontloading ad spend usually backfires, when a more aggressive launch may be justified, and how I scale budgets without sacrificing long-term performance.

    Fire bullets before cannonballs

    For those of us who make a living driving growth through paid media, there’s one problem almost as frustrating as a tiny advertising budget: an advertiser determined to spend too much, too soon.

    I believe every paid media launch should follow a deliberate plan. As Jim Collins wrote in Great by Choice, successful companies fire “bullets” first, learn from the results, and then fire “calibrated cannonballs” with greater confidence.

    In my experience, most campaigns aren’t ready for a cannonball on day one. The algorithms are still learning, Quality Scores haven’t matured, and I don’t yet know which audiences, keywords, or creative assets will perform best. That is usually when acquisition costs and inefficiencies are highest.

    I recognize that exceptions exist. Years of relevant historical data or unusually strong evidence may occasionally justify a more aggressive launch, but I consider those situations rare.

    More often, I see frontloaded spending create expensive lessons instead of faster growth. The following scenarios illustrate why companies choose this approach and why I usually recommend a measured rollout instead.

    Your budget isn’t a KPI

    I never confuse the amount spent on advertising with actual performance, regardless of how an ad platform labels its reporting columns.

    The Modify Columns workflow in Google Ads. Its Performance bucket is… not actual performance.
    The Modify Columns workflow in Google Ads. Its Performance bucket is… not actual performance.

    From what I’ve observed, street-smart owner-operators tend to begin with careful ad budgets. Deep-pocketed decision-makers are more likely to focus on how much they are capable of spending.

    By deep-pocketed decision-makers, I mean anyone from a high-ranking Fortune-something executive or venture capitalist to a serial entrepreneur who has suddenly received an unusually generous investment from a single backer.

    When Nassim Taleb praises people with “skin in the game,” I take the point to be that risk looks different when I must personally bear its consequences. Risk asymmetry allows a splashy failure to hurt the company far more than it hurts the person who encouraged the gamble.

    Google Trends chart comparing U.S. searches for “bruno mars concert” and “concert near me” over the past year, with a sharp Bruno Mars spike in early 2026.
    Bruno Mars briefly steals the spotlight: Google Trends shows his concert query surging to peak popularity in early 2026, while “concert near me” maintains steadier interest across the year.

    Directly or indirectly, I’ve analyzed close to 1,000 ad accounts over the years. The pattern has been clear: advertisers that overspend early in pursuit of hypergrowth often flame out and lose stakeholder support.

    Dig deeper: PPC budgeting in 2026: When to adjust, scale, and optimize with data

    Four frontloading arguments—and why I question them

    1. “It’s a land grab. We need to spend aggressively to gain market share quickly.”

    I rarely consider this a prudent strategy, but I understand the motivation behind it.

    The goal is to capture market share and secure a first-mover advantage before new entrants catch up. I can think of plenty of fast-moving customer acquisition environments, particularly among technology startups, where that prospect feels irresistible.

    I once joined a project to help a startup with a greatly diminished, modest, incremental Google Ads campaign. What shocked me was how little the company had learned—and how little money remained after it had raised more than $250 million. Nearly all of that funding had been burned, including large sums spent on advertising, and there wasn’t going to be more where it came from.

    My team helped the company measure KPIs such as “new accounts that actually led to revenue” and “lifetime revenue from those accounts.” Despite three years of relentless nine-figure spending, no one had made those outcomes a serious measurement priority.

    I’ve also seen bootstrapped startups become carried away after celebrating their first $1 million to $2 million in “real” venture funding. They may have less money to burn, but the faulty logic is the same—and the risk can be even greater.

    Over the years, I’ve helped niche SaaS startups such as Clio in legal practice management and SuccessFactors in HR management achieve prominence without pretending they were already operating at their future scale.

    I don’t see small beginnings or cautious ad budgets as barriers to unicorn status. I can match customer acquisition spending to a company’s current growth stage without sentencing it to permanent smallness.

    For initial paid growth, I recommend defining the addressable market relatively tightly. I save the “huge addressable market” story for longer-horizon conversations with investors instead of using it to justify immediate overspending.

    To keep early-stage growth in perspective, I remind myself how a behemoth like Uber began. Its seed round was $1.25 million, and the company was valued at a modest $4 million.

    I’m happy to think big, but I don’t try to act bigger than the company really is when the money and product-market fit aren’t there yet. If the business establishes a meaningful lead, network effects and access to more capital can accelerate growth later.

    Futuristic rocket launches from an industrial ad campaign control center with gauges for budget, bids, conversions, optimization, and quality score.
    A paid media campaign blasts toward growth, but the glowing budget controls offer a warning: validate performance, optimize carefully, and earn the right to scale.

    I often wonder why founders race through essential growth stages by setting their newly raised—but finite—cash on fire. Sometimes investors encourage it. In other cases, the growth team treats fresh funding like permission to spend without restraint.

    I know what happens when the hangover arrives. Investors see high churn, stratospheric customer acquisition costs, or few tangible signs of customer acquisition at all. They react as though they have been mortally wounded, even when they helped create the strategy.

    I always return to unit economics because they still matter. Other founders may appear to have repealed the laws of economics, but I remember the familiar parental warning: “If Billy jumped off a cliff, would you do it too?”

    2. “We’ll learn faster.”

    I agree that predictive bidding algorithms perform poorly when conversion and value signals are sparse. More data can help them recognize the patterns associated with higher-value sessions.

    My team also needs to move through feedback loops to understand what works, what fails, and how the campaign should evolve.

    One genuine benefit of higher volume is that I can discover necessary negative keywords more quickly. With low query volume, many bad searches may remain hidden in “Other Search Terms” for a long time.

    Even so, I find that spending becomes counterproductive beyond a certain point. More money does not automatically turn incomplete data into reliable insight.

    • I consider the length and variability of the sales cycle. If two or three months normally pass between the first ad view and a sale, forcing too much budget into month one leaves me running ads almost blind, with little opportunity to learn and iterate before the money is gone.
    • I watch for self-inflicted CPC inflation. If I charge into an auction that has reached a workable equilibrium and bid too aggressively, I may raise my own costs and prompt competitors to bid higher as well.
    • I expect early metrics to be relatively weak because the campaign hasn’t established mature Quality Scores. In one account, CPCs eventually fell by 80% as Quality Scores developed and our optimizations took effect. I was relieved that the initial pilot had used a modest budget.

    I see little logic in pouring a flood of money into what may be the worst ROI environment the campaign will ever face. Even four to six weeks later, ROI is often substantially better as Quality Scores mature and statistical confidence improves.

    Dig deeper: Stop looking for the perfect PPC budget split

    3. “We’re pre-revenue, and our investor wants a quick market-size estimate.”

    Whenever I hear this argument paired with a hefty new check, I have to ask: What could possibly go wrong?

    To me, this takes the land-grab strategy even further into the intellectual ether. Customers—or almost any other concrete business outcome—may not be the immediate goal.

    From where I sit, the investor’s instruction often amounts to this: “We don’t care if we spend a huge amount of cash in the first month. Just get us a pile of data.”

    Glowing blue streams of people converge on a search bar and digital portal, symbolizing SEO traffic, AI visibility, and customer acquisition.
    As AI reshapes search, every glowing path to discovery carries commercial value—turning SEO investment into a conversation about pipeline, risk, and customer acquisition costs.

    When a powerful backer’s name comes up, it’s tempting for everyone to shrug and think, “Billionaire knows best.” I’ve watched teams dutifully throw money at a performance channel without asking it to perform, only to learn 35 days later that the investor won’t contribute another penny. The founder is then left without a credible Plan B.

    I can imagine the next investor arriving with a few basic questions.

    • “Q: What is the company, exactly? I mean, what product or service do you provide?”
    • “A: We’re still figuring that out, but we know there must be a gold mine in there somewhere, given how many music fans are searching for [music examples redacted to protect the innocent].”

    I don’t consider that a true launch because the project was never clearly defined in the first place.

    To be fair, I do believe fail-fast market research can be valuable. My team once spent about $10,000 over a short period for a client exploring a telecommunications business model. The test gave him a definitive answer about demand patterns, and he decided not to enter that vertical.

    I regard Google Ads as an invaluable market research tool when I use it with discipline. I define a meaningful business outcome and require potential customers to clear a credible threshold of intent. If I don’t need that level of evidence, I can explore the question with Google Trends, Google Analytics on a purpose-built content site, Semrush, or a dedicated market research company.

    Free Google Trends market research shows “bruno mars concert” giving “concert near me” a solid run for its money.
    Free Google Trends market research shows “bruno mars concert” giving “concert near me” a solid run for its money.

    In an unusual research scenario like this, my goal is to control waste. I may not be able to eliminate it entirely, but I can keep it proportional to the value of the answer I’m seeking.

    4. “A vendor won’t work with us unless we spend more immediately.”

    I know that some ad platforms, third-party software tools, and managed services impose steep minimums. I also understand why advertisers feel pressured by FOMO to overspend for entry into an exclusive club.

    I think the early OpenAI ad pilot offered a timely example. Steep minimums and uncomfortably high CPMs appeared to exclude the typical advertiser.

    I won’t twist myself into a pretzel to rationalize wildly overpaying for every ad interaction. Eventually, the market may become more accessible. I only have to compare how easy it is to begin with StackAdapt in programmatic advertising against the higher barriers associated with Google DV360 and The Trade Desk.

    When I advise a smaller company, I encourage it to grow first and enter a more demanding platform only when its size and budget justify the move. I see this as a version of The Millionaire Next Door logic: buying a house I can’t afford or driving a luxury car doesn’t make me wealthy. It might prevent me from ever getting there.

    Dig deeper: How to diagnose and fix the biggest blocker to PPC growth

    Earn the right to scale

    My core conclusion is that frontloaded ad spending often destroys the support a campaign needs to succeed. I don’t want to taint an entire channel—or the company’s broader growth function—by accelerating so hard that the campaign skids into a ditch. I can travel much farther after building solid traction.

    For an owner-operated business with real skin in the game, this is about more than stakeholder confidence. Severe waste isn’t merely bad optics; it can threaten the company’s future.

    So, when an overconfident investor or ad platform sales representative urges me to go from “zero to sixty in 3.5,” I’m inclined to tap the brakes. I would rather earn the right to scale than discover too late whether the airbags work.


    Inspired by this post on Search Engine Land.


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  • How I Build a Powerful SEO Budget Case My CFO Can’t Ignore

    How I Build a Powerful SEO Budget Case My CFO Can’t Ignore

    You're losing the SEO budget conversation before you walk into the room

    If I walk into a budget meeting armed only with rankings, traffic, and keyword reports, I know I am making the wrong case. CFOs do not approve SEO budgets because channel metrics look encouraging. They approve investments that reduce business risk, improve commercial outcomes, and justify the way capital is allocated.

    As AI reshapes search economics and customer acquisition costs continue to climb, I believe translating SEO into business risk is becoming as important as the search strategy itself. This is how I prepare for that conversation before I enter the room.

    Why I see SEO budget conversations break down

    A global enterprise software company recently shared a revealing example with us, and I keep returning to it because it captures the problem so clearly.

    One of the company’s core product lines generated 291 inbound demo requests during a single month in 2008. In the corresponding month of 2026, it generated only 274. Nearly two decades later, and despite a digital marketing budget roughly eight times larger, the business was producing fewer qualified opportunities.

    I do not see that as a simple search strategy problem. I see it as a structural problem—and the CFO had already noticed it.

    The head of search entered the budget review with a 24-slide deck. Slide 3 documented ranking improvements. Slide 7 highlighted year-over-year organic traffic growth. Slide 12 outlined keyword opportunities.

    Every number was accurate, but none of them answered the question that mattered to the CFO: Why was the company spending more each year to generate roughly the same number of qualified opportunities?

    The CFO let the presentation continue. Then, at slide 19, she put down her pen and said, “This is all interesting. But I can’t see the connection to pipeline.”

    The head of search began to explain. The CFO looked toward the CMO, and the meeting was effectively over.

    The lesson I take from this is that many search leaders lose the CFO budget conversation before they enter the room. Their strategies may be sound, and their numbers may hold up, but they arrive speaking in sessions, rankings, and organic traffic share. That is not the language of financial decision-making.

    When I prepare for this kind of meeting, I assume the CFO wants to discuss the P&L, risk, payback periods, and opportunity cost.

    If I open with “organic traffic grew 23% year over year,” I risk telling the CFO, unintentionally, that I cannot connect my work to revenue. If the CFO has already seen cost per opportunity moving in the wrong direction, that disconnect does more than create skepticism. It creates a reason to cut the budget.

    The structural shift I diagnose first

    I start with the diagnosis before I discuss tactics. Without a clear diagnosis, everything else becomes a more polished way to lose the same argument.

    In 2008, paid search behaved like an undersupplied monopoly channel: high intent, limited competition, and relatively linear returns. A dollar invested could produce a reasonably predictable return. There was no AI layer absorbing clicks before they happened, no army of comparison aggregators siphoning away high-intent traffic, and no group of competitors with 18 years to build organic authority in the category.

    That environment is gone.

    Today, I operate in a search landscape where organic authority is fiercely contested. AI Overviews can intercept high-intent queries before users reach paid ads, while attribution models designed for the old environment are still being used to defend budgets in the new one.

    The message I bring to a CFO is not simply, “I need more budget,” or, “Our rankings are improving.” I explain that the structural conditions that once made search efficient have changed, show how those changes affect commercial performance, and present my plan for adapting.

    Why I do not lead with channel metrics

    I understand the temptation to showcase channel performance. After spending months building organic authority, improving rankings, and growing traffic, I naturally want that work to be visible. The problem is that presenting it without a commercial connection can undermine the very case I am trying to make.

    CFOs have been burned by marketing attribution models before. They have seen enough ranking charts and organic traffic reports to know that neither metric connects directly to the P&L without additional evidence.

    When I lead with channel metrics, I invite two immediate questions: “According to which model?” and “What does this mean for revenue?” Every slide that raises those questions before I have framed the argument spends some of my credibility.

    How I handle the counterfactual problem

    The deeper issue is the question I expect every CFO to bring into the room: “Would this revenue have happened anyway?”

    I consider that the hardest question in marketing attribution, yet many budget presentations never answer it. They treat the connection between organic performance and commercial outcomes as self-evident. It is not. A CFO who has watched the marketing budget expand for a decade while blended customer acquisition cost drifts upward is right to challenge that assumption.

    If I am asked, “How do we know those customers would not have found us anyway?” and I do not have a prepared answer, I have lost the thread. That is why I do not build my budget case on an attribution model I cannot defend under pressure. I build it around something much harder to dismiss: measurable business risk.

    Dig deeper: Stop paying for traffic: The enterprise CMO’s guide to ROI-driven SEO

    How I frame SEO as business risk

    I think of CFOs primarily as risk managers, not channel optimizers. Their job is to protect the business from downside scenarios, allocate capital efficiently, and prevent unpleasant surprises in the P&L.

    If I enter the room talking only about upside—what a larger budget might achieve—I am appealing to the wrong instinct.

    Instead, I lead with downside and focus on three risks that a CFO can price, model, and act on.

    1. Competitive displacement risk

    I never treat organic search positions as permanent assets. They are contested positions in a live market. If I reduce investment, competitors do not pause and reduce theirs to match. They usually accelerate.

    I also avoid saying only, “We will lose rankings.” Rankings are still a channel metric. I frame the risk in commercial terms:

    • “A 30% budget reduction will not create a simple 30% reduction in output. I expect it to trigger a compounding decline over the next three to 18 months as competitor content accumulates, our positions erode, and the cost of recovering those positions exceeds the cost of maintaining them.”

    I am presenting a deferred-liability argument, not merely a channel-performance argument. It gives the CFO a risk that can be modeled. For example, I can calculate how much a 20% decline in organic share of voice would add to CAC over 12 months if paid search had to compensate for the lost visibility.

    When I show that calculation, I can move the conversation from “Can we afford this investment?” to “Can we afford the cost of withdrawing it?”

    2. AI visibility risk

    I see AI visibility as the newest and least understood risk in many boardrooms. That gives me an opportunity if I can explain it clearly and connect it to financial outcomes.

    As AI Overviews and LLM citations become a primary discovery layer for high-intent queries, I no longer think of organic authority solely in terms of rankings. I also ask whether our brand appears in the AI-generated answer.

    A paid campaign can often be restarted next quarter by adding budget. AI citation share is different. It depends on content depth, structured data, brand signals, and domain authority built over months or years. I cannot rebuild that visibility with a quick media buy; I need a content and authority program measured in quarters rather than weeks.

    The commercial connection is crucial. If I lose AI visibility, I do not just lose traffic. The business may have to buy back those same high-intent users through paid search, often at CPCs inflated by competitors that continued investing and preserved their citation share.

    I do not treat this as a distant concern. For many organizations, declining AI visibility can be the trigger for a broader CAC blowout, so I price the risk explicitly.

    The framing I use with the CFO:

    • “We currently hold strong AI citation share across our 10 most important commercial queries. I do not expect that position to maintain itself. Here is what it cost us to build, what I estimate it would cost to recover if we lost it, and the quarterly investment I recommend to defend it.”

    Dig deeper: The bureaucracy tax: How disruptors are winning AI search visibility

    3. CAC blowout risk

    I find that this risk lands hardest because it is already materializing in many enterprise organizations.

    Glowing blue streams of people converge on a search bar and digital portal, symbolizing SEO traffic, AI visibility, and customer acquisition.
    As AI reshapes search, every glowing path to discovery carries commercial value—turning SEO investment into a conversation about pipeline, risk, and customer acquisition costs.

    When I return to the enterprise software example, the year-over-year picture is even more revealing than the 18-year comparison:

    • April 2025: Roughly $420,000 in Google spend, 681 inbound demo requests, and approximately $617 per opportunity.
    • April 2026: Roughly $310,000 in Google spend, 418 inbound demo requests, and approximately $741 per opportunity.

    Spend fell by 26%, qualified opportunities fell by 39%, and cost per opportunity increased by 20% in one year. The deterioration happened not simply despite the budget reduction, but partly because of it.

    I expect a CFO to test a simpler explanation: Perhaps performance was already declining and the budget was cut in response. That is a reasonable hypothesis, but it does not fully fit the data. Cost per opportunity had started rising before the reduction. The cut did not create the original efficiency problem; it exposed a structural problem that already existed.

    The search environment had changed, but the budget strategy had not. AI Overviews were absorbing high-intent category and solution queries before many of those searches became clicks.

    At the same time, the organic authority that took years to build was generating fewer visits as zero-click search expanded. When paid spend fell, the organic foundation was not strong enough to carry the load. Together, the two effects caused more damage than either would have caused independently.

    This is how I explain the CAC blowout mechanism: When organic visibility weakens and paid media has to compensate, blended CAC rises. If paid investment is then reduced before the organic gap is repaired, CAC can rise even further.

    The CFO sees a negative trend and may conclude that search no longer works. I see a different problem: The structural relationship between paid and organic was never actively managed.

    I do not consider this unique to enterprise software. It is a predictable outcome when paid and organic search are managed as separate budget lines with separate accountability, as they still are in many enterprise organizations.

    The framing I use with the CFO: I show the relationship between organic share of voice and blended CAC across the previous 18 to 24 months. If organic visibility declined while paid CPCs rose, I have direct evidence of the risk.

    If I have completed a cannibalization audit and redirected spend away from terms where paid ads competed with strong organic coverage, I also present that work. Moving the budget toward genuine demand gaps gives me a concrete example of the structural fix in action.

    Why I brief the CMO before the meeting

    One of the most valuable preparation steps I can take is briefing the CMO before I enter the budget meeting. I do this not simply to seek approval, but to stress-test my argument.

    The CMO has usually participated in more CFO conversations than I have. They know which objections carry the most weight, which risks currently concern the CFO, and which parts of my case are likely to receive the greatest scrutiny. I cannot gain that perspective if I build the deck in isolation.

    A CMO who has already challenged and strengthened my argument becomes an ally in the room. A CMO who hears the case for the first time alongside the CFO can become a liability. If the CMO hesitates over a number or qualifies a claim I presented with confidence, the CFO will notice.

    That is why I brief the CMO and enter the meeting aligned. In my experience, much of the budget conversation is won or lost before anyone sits down.

    How I prepare for three inevitable questions

    Before I prepare the answers, I plan my opening move.

    I do not spend the first 60 seconds summarizing last quarter’s performance, and I do not jump into risk without establishing common ground. Instead, I begin with the structural diagnosis.

    I might say:

    • “Before I walk through the data, I want to explain why we are having this conversation. The search environment has changed materially over the past three years. I want to show how that change is affecting our cost per opportunity and what I recommend we do about it.”

    From there, I present the evidence, explain the risks, and prepare for the questions. These questions are not hypothetical. Search leaders hear them repeatedly, so I want my answers ready before I enter the room.

    “What happens if we cut this by 30%?”

    I do not respond by declaring the cut unacceptable or catastrophic. A CFO asking this question may be testing how well I understand the program’s efficiency curve rather than announcing an actual reduction. If I become defensive, I signal that I have not modeled the scenario.

    I prepare a specific answer in advance:

    • “A 30% reduction applied evenly across the program would cost us approximately [X] in organic traffic within six months. At our current organic conversion rate, that represents [Y] in pipeline impact. If we need to remove 30%, I would make these specific cuts to minimize commercial damage. This is the threshold below which I believe the program becomes structurally unsustainable and the cost of recovery exceeds the savings.”

    With that answer, I demonstrate P&L literacy, anticipate the follow-up questions, and shift the meeting from budget defense to business problem-solving. I am not protecting a line item; I am helping the CFO make a better capital allocation decision.

    “How do we know these conversions would not have happened anyway?”

    I do not try to defend an attribution model as if it were indisputable. I am unlikely to win that argument, and fighting it can damage the credibility of everything else I have presented.

    Instead, I acknowledge the attribution problem and pivot to incrementality:

    • “I agree that last-click attribution overstates organic search’s contribution, so I do not use it as my primary evidence. Instead, I track periods when organic visibility declined across our most important commercial queries and paid CAC increased as paid search compensated. I consider that our most defensible proxy for organic search’s incremental contribution, and I have deliberately kept the estimate conservative.”

    I find that intellectual honesty about attribution limitations builds credibility with a financially trained audience. CFOs have seen too many models that appear designed to prove whatever the presenter wants to prove.

    By acknowledging the limitation first and offering a conservative proxy, I can earn more trust than I would by making an aggressive ROI claim.

    “What is the payback period?”

    I avoid answering with a broad argument about long-term brand equity or compounding authority. CFOs working within quarterly reporting cycles are unlikely to approve capital based only on a three-year organic growth narrative. If I lead with that answer, I suggest that I do not understand how the allocation decision is being made.

    I separate the investment into two components with different payback profiles.

    Maintenance spend covers the work required to preserve existing positions, keep content current, and maintain technical health. I frame its payback as immediate because it protects value the business has already created. The relevant comparison is the future cost of recovering the positions if they are lost.

    Growth spend covers new content, category expansion, and authority building. For content aimed at existing demand with known search volume, I model the payback across six to 12 months. I make the assumptions visible, including query volume, conversion rate, and revenue per conversion.

    I show my work. If the CFO stress-tests my assumptions and challenges specific numbers, I consider that constructive engagement with the model. It is a better outcome than polite agreement followed by a budget cut because my methodology failed to inspire confidence.

    The data I leave behind—and the data I bring

    Before I build the deck, I decide what to remove. Most search budget presentations do not fail because they lack useful data. They fail because the valuable evidence is buried beneath metrics that erode credibility before the important numbers appear.

    What I leave behind

    • Keyword rankings in isolation: Unless I can connect a specific ranking movement to pipeline impact, I treat it as another channel metric that invites the counterfactual question.
    • Organic sessions without market context: If my traffic grew by 15% while the market grew by 40%, I lost ground. Without an external benchmark, year-over-year traffic growth gives the CFO little basis for evaluation.
    • Metrics that require a glossary: If I have to explain what a metric means before I can explain why it matters, I leave it out of the meeting. Every definition delays the commercial argument.
    • Long-term brand equity arguments: I do not reject these arguments, but I recognize that they are difficult to act on within a quarterly budget cycle. Leading with them creates a mismatch between my timeline and the CFO’s.

    What I bring

    Before I finish the deck, I decide what deserves the most important slide. I do not choose a generic traffic graph or ranking summary. I begin with a commercially meaningful statement such as:

    • “I estimate that organic search offset $[X] in paid-search dependency this quarter.”

    I lead with the money the program saved the business, expressed in language the CFO already uses. The supporting evidence follows:

    • Blended CAC across the previous 18 to 24 months, segmented by channel. I use this chart to expose the relationship between paid and organic performance and connect search investment to the P&L.
    • Organic share of voice compared with the three leading competitors over time. I use this to make competitive displacement measurable. If a competitor gained ground while our investment remained flat, I show it.
    • Pipeline contribution by channel under a conservative, clearly labeled attribution model. I state whether the model is last-touch, position-based, or something else. I find that transparent disclosure builds more credibility than an optimistic number that invites a methodological dispute.
    • A pre-modeled 30% reduction scenario with specific commercial consequences. I consider this the most powerful analysis I can bring because it answers the likely budget question before it is asked.
    • AI Overview citation share across the 10 most important commercial queries. I use our own data to ground the AI visibility argument. It demonstrates that I understand the changing discovery landscape without relying on vague industry generalizations.

    How I turn the meeting into a capital allocation conversation

    I do not consider the enterprise software company in this example an outlier. I see the same pattern across enterprise search: budgets rise, efficiency declines, and CFO skepticism grows as AI Overviews absorb intent, paid and organic remain disconnected, and reporting continues to reward channel metrics instead of commercial outcomes.

    I have learned that winning this conversation does not depend only on having the best search strategy. It depends on translating SEO into business risk in language a CFO can evaluate and act on.

    Before I enter the room, I brief the CMO, model the commercial effect of a budget cut, prepare a conservative answer to the attribution question, and separate maintenance investment from growth investment. That preparation is within my control, even though the structural shift in search—and the CFO’s skepticism—are not.

    Ultimately, I choose which conversation I am ready to have. I can defend a collection of channel metrics, or I can help the CFO make a capital allocation decision. Only one of those approaches gives my SEO budget a compelling business case.


    Inspired by this post on Search Engine Land.


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  • Meet Pages: My Command Center for Content Performance

    Meet Pages: My Command Center for Content Performance

    Pages in Profound content performance command center

    I’m introducing Pages in Profound—my single command center for monitoring content citations, tracking bot activity, and understanding page health.

    Dark Profound content analysis dashboard reviewing a Relay vs Ledgerly startup ERP article, with a 65% overall score and quality metrics.
    Profound’s content command center puts page analysis beside the article itself, surfacing a 65% score and signals for freshness, structure, readability, and information density.
    Dark Profound dashboard comparing bot and human-readable content, showing 25% bot readability and an Unhealthy status.
    A side-by-side content audit reveals a stark visibility gap: bots can read just 25% of the page, while the JavaScript-rendered human view exposes far more content.

    Inspired by this post on Try Profound Blog.


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  • How Gemini Intelligence Will Reshape Search and Commerce

    How Gemini Intelligence Will Reshape Search and Commerce

    Google brings AI to Android — here's what it means for search

    I see Google’s unveiling of Gemini Intelligence at the May 12 Android Show as a significant step toward an agent-powered future. Announced alongside a new laptop called the Googlebook, Gemini Intelligence is designed as an underlying layer that works across the Android operating system on laptops, phones, watches, and glasses.

    The Googlebook makes that vision tangible to me. Built from the ground up around an AI agent, it can understand what is on the screen and act on it. I could point to a date in an email and have the agent schedule a meeting, or select furniture in an app and see how those pieces might look in my living room.

    I believe this ability to complete tasks without requiring someone to open a webpage will fundamentally change how people search, discover information, and conduct commerce. Here is how I expect that shift to affect the search industry.

    What the shift to an agentic operating system means

    Until now, I have viewed search as a familiar sequence: someone has a question or intent, enters it into a search engine, receives a list of links, and chooses one. Earning a prominent position on that list was the prize, and much of the SEO industry was built around winning that click.

    Gemini Intelligence starts from a very different assumption. Search intent still exists, but an AI agent can handle the steps between the request and the outcome. It can read pages, complete forms, and increasingly finish the entire task. Instead of visiting a website myself, I may have an agent visit and use it on my behalf.

    When I look for an early example, Chrome Auto Browse stands out. Launched in January and built on Gemini 3, it can manage multistep tasks such as researching flights, filling out forms, scheduling appointments, and managing subscriptions. It then pauses for approval before making a purchase.

    That efficiency gives me a clear reason to believe ecommerce will continue moving toward agentic AI.

    A 2025 preprint supports this view. Researchers evaluated the declared-tools approach across online shopping, authentication, and content management. They found that giving an agent pre-structured interaction data reduced processing requirements by 67.6% and lowered costs by 34% to 63% compared with parsing a complete HTML document. Task success declined only slightly, from 98.8% with the traditional method to 97.9%.

    The architecture behind Gemini Intelligence

    To me, the architecture is as important as the interface. AI agents naturally favor websites they can interact with cleanly and efficiently, and Gemini Intelligence can only deliver on its promise if those agents can perform tasks reliably.

    I see two protocols as central to making that possible. WebMCP turns a website’s actions into callable tools, while the Universal Commerce Protocol (UCP) allows an agent to complete a sale. Together, they enable an agent to finish a task without requiring a person to load and navigate the underlying webpage.

    Glowing blue streams of people converge on a search bar and digital portal, symbolizing SEO traffic, AI visibility, and customer acquisition.
    As AI reshapes search, every glowing path to discovery carries commercial value—turning SEO investment into a conversation about pipeline, risk, and customer acquisition costs.

    WebMCP

    I think of WebMCP as a labeled menu for AI agents. The API allows a website to declare functions as structured tools an agent can call, including searching inventory, beginning checkout, or submitting a support request.

    Google co-developed WebMCP with Microsoft. An origin trial is live in Chrome 149, Firefox has committed to the third quarter of 2026, and Safari is expected to follow in the fourth quarter.

    Universal Commerce Protocol (UCP)

    I see UCP as the transactional counterpart to WebMCP. It gives AI agents a shared language for discovering products, building a cart, completing checkout, and managing orders without requiring someone to visit the merchant’s website.

    Google also offers a consumer-facing layer called Universal Cart. It can collect items as I move across Search, Gemini, YouTube, and Gmail, creating a more connected shopping experience across Google’s products.

    The range of companies behind UCP shows me how seriously the industry is taking this shift. Google, Shopify, Walmart, Target, Etsy, Wayfair, PayPal, and Stripe co-developed the protocol, which launched in January.


    How I would prepare for agentic AI

    My main takeaway is that websites are rapidly evolving from destinations into backends—from places people actively visit into systems agents quietly use. As the operating system becomes a search and action layer, I no longer think ranking is the only question that matters. I also need to ask whether an agent can actually use the site.

    To prepare, I would begin by auditing the site’s most valuable actions, whether that means submitting a lead form, completing a booking flow, or reaching checkout. I would determine whether an agent could complete each action reliably and check the site’s Lighthouse Agentic Browsing score much as I would review Core Web Vitals. The goal is to understand whether an agent can use the site, not merely read it.

    If I ran an ecommerce business, I would confirm whether the checkout process is accessible through UCP or ACP. I would also continue investing in retrieval and visibility because an agent still needs to find and trust the business before it can act on anyone’s behalf.

    Dig deeper: Are we ready for the agentic web?


    Inspired by this post on Search Engine Land.


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  • OpenAI to Retire ChatGPT Atlas Aug. 9: What I’m Watching

    OpenAI to Retire ChatGPT Atlas Aug. 9: What I’m Watching

    ChatGPT Atlas

    I’m watching OpenAI discontinue ChatGPT Atlas, its standalone desktop browser, and move its browser-based AI features into the new ChatGPT desktop app. That app brings together ChatGPT Work, OpenAI’s work-focused agent, and ChatGPT Codex.

    The end of Atlas. I’m taking note of an Aug. 9 retirement date after OpenAI’s James Sun confirmed the plan on X.

    I’m also noting Sun’s exact wording: “The current targeted date for deprecation is 8/9, and we’ll share more information in the upcoming days both in-app and via email.”

    One desktop app. I see the new ChatGPT desktop app becoming OpenAI’s primary desktop product, complete with built-in browser capabilities. Instead of maintaining a separate AI browser, OpenAI is combining browsing, work-agent features, and Codex in one place.

    Chrome users can keep Chrome. If I prefer using Chrome, I can access ChatGPT and Codex through OpenAI’s Chrome extension without switching to a dedicated OpenAI browser.

    Glowing blue streams of people converge on a search bar and digital portal, symbolizing SEO traffic, AI visibility, and customer acquisition.
    As AI reshapes search, every glowing path to discovery carries commercial value—turning SEO investment into a conversation about pipeline, risk, and customer acquisition costs.

    Why I care. I see this as an important shift because OpenAI is moving AI browsing into the main ChatGPT experience, where more people can ask questions, research brands, and complete tasks. In my view, that gives ChatGPT another opportunity to influence discovery beyond traditional search results.

    My quick recap. ChatGPT Atlas will be retired as a standalone browser less than a year after its launch.

    I first saw ChatGPT Atlas launch on Mac in October. OpenAI later released a dedicated Codex app and added an in-app browser in April. Now, I’m watching those capabilities move into the new unified ChatGPT desktop app.


    Inspired by this post on Search Engine Land.


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  • Google Says Canonicalization Fixes May Take Two Weeks

    Google Says Canonicalization Fixes May Take Two Weeks

    I noticed that Google updated its canonicalization troubleshooting guide to clarify how long it may take for fixes to appear in Google Search results. According to the revised guidance, Google might keep pages in a duplicate cluster for up to two weeks after content issues have been fixed.

    What changed. I found a new section at the top of the guide that explains the expected timeline for canonicalization fixes. Google now makes it clear that the process can take up to two weeks.

    I also saw additional technical details about clustering. Google explains that pages need to be sufficiently similar before its systems can group them into a duplicate cluster and select one version as the canonical page.

    Screenshot of Google Search Central’s “Fix canonicalization issues” guide highlighting that duplicate-cluster reevaluation can take up to two weeks.
    Google’s updated canonicalization guidance sets expectations for SEOs: fixed pages may remain in a duplicate cluster for up to two weeks, while clearer content differences can speed reevaluation.

    Here is the section Google added:

    Why I care. This clarification gives me a more realistic timeline when monitoring canonicalization fixes. Once Google has processed an update, I know I may need to wait the full two weeks before deciding whether the change worked.

    Glowing blue streams of people converge on a search bar and digital portal, symbolizing SEO traffic, AI visibility, and customer acquisition.
    As AI reshapes search, every glowing path to discovery carries commercial value—turning SEO investment into a conversation about pipeline, risk, and customer acquisition costs.

    That waiting period can help me avoid making unnecessary page changes while Google is still consolidating duplicate URLs and evaluating the appropriate canonical version.


    Inspired by this post on Search Engine Land.


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  • Credibility-First Link Building: How We Earn Lasting Authority

    Credibility-First Link Building: How We Earn Lasting Authority

    Link building for lasting brand authority

    At Resolve, we define link building for legitimacy as earning authoritative backlinks, brand mentions, and media coverage that demonstrate trust, expertise, and credibility to search engines and AI systems. Instead of chasing link volume, we use digital PR, original research, thought leadership, and journalist relationships to earn genuine editorial citations. These are the authority signals behind Google’s E-E-A-T framework, and they can help us appear in AI Overviews, earn citations from large language models, and build visibility that survives ranking swings.

    We believe a little competition is healthy. It challenges us, sharpens our thinking, and pushes us to pursue bigger and better results.

    However, today’s search environment is changing faster than ever. Large language models, AI-generated answers, and frequent algorithm updates are reshaping how people find information, making it increasingly difficult for us to rely on yesterday’s playbook.

    The metrics we once used to keep brands afloat — traffic, domain authority increases, and keyword rankings — no longer define SEO success on their own. We can reach the top of a search results page and still see very few conversions.

    If we continue chasing those numbers in isolation, we risk being left behind. We have to adapt.

    We now widen our view to the outcomes that matter most: trust and brand authority. Unlike a temporary ranking or traffic spike, trust and authority are not earned quickly or easily.

    We need time to spread the word about our brand, and we need even more time to prove that people can rely on us. Once we establish that trust, however, it becomes much harder to dislodge.

    An algorithm update can cut our traffic overnight. It cannot erase genuine trust overnight.

    Our challenge is learning how to build trust and strengthen our brand while every competitor is trying to do the same. We also need meaningful ways to measure concepts that can initially seem difficult to quantify.

    We have found that the answers involve some nuance, but they are simpler than they appear. The process begins with a shift in perspective.

    For years, we treated link building like a popularity contest. The site that collected the most votes, in the form of backlinks, was often rewarded with a prominent position in the search results.

    Infographic showing 86% of journalists use PR-pitched stories, 54% rarely answer pitches, and 61% of Gen Z use generative AI instead of Google.
    Relevance and trust beat volume: 86% of journalists use at least some PR-pitched stories, yet 54% seldom respond, while 61% of Gen Z turn to generative AI instead of Google.

    Over time, Google and other search engines updated their algorithms to improve the search experience. With each change, Google cracked down on more sites that tried to manipulate the system with backlink volume instead of earning links with real editorial and audience value. Countless sites lost traffic, and many still feel the effects.

    Today, we see Google place more emphasis on relevance, industry trust, and authority. That helps explain why a familiar brand can attract more searchers than a smaller competitor even when both publish similar content and target similar keywords.

    Large language models and Google’s AI Overviews have widened this divide. These systems can use retrieval-augmented generation, or RAG, to retrieve relevant sources, often favoring authoritative publications and proprietary information. If we merely repeat a statistic already cited by a top-tier publication, an AI system may choose the better-known source to reduce the risk of spreading inaccurate information.

    We also see younger searchers moving toward AI tools. In a 2025 Resolve study, 61% of Gen Z respondents said they used generative AI instead of Google.

    None of this means every form of link building looks like spam to Google or an LLM. It means we need backlinks to work alongside a broader set of authority signals.

    When publications and journalists cite our brand, they signal authority. When we publish original content and proprietary data, we signal authority. When we create useful graphics and informative videos, we signal authority again.

    Once Google and AI systems recognize these signals, the backlinks supporting them become meaningful votes of confidence. Our site may then be more likely to rank prominently, appear in AI Overviews, and receive citations in LLM-generated answers.

    How we use E-E-A-T in a competitive search environment

    In 2018, Google updated its quality-rater guidance to place greater focus on expertise, authoritativeness, and trustworthiness, commonly shortened to E-A-T. In 2022, Google added another E for experience. Together, these qualities provide a framework for understanding how Google considers credibility and legitimacy.

    • Experience: We demonstrate that an author has personally engaged with the subject. Examples include a forum where people describe testing a product or a gardener documenting firsthand pest-prevention trials.
    • Expertise: We show that the author has relevant knowledge, qualifications, or credentials supporting the information and advice.
    • Authoritativeness: We earn recognition from credible sources and industry voices that cite or link to our work, helping establish us as a respected participant in the field.
    • Trustworthiness: We remain transparent, accurate, and honest. We avoid deceiving readers or using manipulative link-building practices.

    We apply E-E-A-T both on and off the page. Author biographies can demonstrate expertise, while accurate sourcing can demonstrate trustworthiness. Off the page, we strengthen E-E-A-T signals through the quality of the sites that link to us and the journalists who rely on us as a source. Both dimensions influence how search engines assess whether our information is useful, accurate, and credible.

    If we consistently earn backlinks from dozens of irrelevant websites, that pattern can look like a low-quality or manufactured signal. If several respected journalists mention our brand because we published a valuable study, those mentions are much more likely to function as genuine votes of confidence.

    Infographic comparing vanity SEO metrics like traffic and backlinks with durable authority metrics such as media placements, conversions and branded search.
    Move beyond fragile SEO numbers. This side-by-side graphic shows how earned media, branded searches, industry citations and conversions build authority that can survive algorithm updates.

    For us, link quantity is no longer a reliable proxy for legitimacy. We look for backlinks that demonstrate real relevance and value.

    We cannot earn those links half-heartedly. We need a coordinated strategy that strengthens credibility both on and off our site.

    The off-page SEO tactics we use to demonstrate value

    When we ask how to earn links that search engines and LLMs will treat as signs of trust, we do not look for a single outreach tactic. Strong links usually emerge from several activities that we sustain over time.

    We create genuinely linkable assets

    To prove that people genuinely want to reference our site, we first create content worth referencing. If we are accustomed to quick and easy links, this may require a larger investment in content than we have made before. A routine how-to article or listicle is rarely enough by itself.

    We define linkable content as something journalists, publishers, and readers find distinctive and useful — something they have not already encountered dozens of times. We often draw from the following content formats.

    • Original data and proprietary research: We publish information people cannot find elsewhere. In a crowded search environment, that means conducting original research rather than recycling familiar statistics. When a journalist needs a statistic and our site is the primary source, we can earn a natural backlink.
    • Thought leadership and expert commentary: We share an original perspective from a credible expert within our organization, giving publishers a useful idea or quotation they may cite in future coverage.
    • Authoritative long-form guides: We answer the main question thoroughly and anticipate the follow-up questions a reader is likely to ask. This depth can help us earn links as audiences move further into their research.
    • Engaging visuals and infographics: We invest in visual assets that make complex information easier to understand and share. Ahrefs found that YouTube mentions strongly correlated with inclusion in AI Overviews. Videos can be especially valuable, but informative infographics also give publishers a useful visual for their own audiences.

    These formats demand more time, effort, and money, but we have found that they are often more sustainable than disposable content. They help us earn credible editorial citations and build industry authority that is more resilient to algorithm updates.

    We connect link building with digital PR

    We place digital PR at the center of authority building because it connects brand development with link acquisition. It helps us earn coverage, attract links, and introduce our organization to new audiences through credible journalists. Those are precisely the kinds of signals search engines can consider when assessing legitimacy.

    Unlike traditional PR, our digital PR work focuses on online coverage and backlinks from news organizations and media outlets. We create useful assets or proprietary data, identify the journalists most likely to care, and pitch stories that fit their established beats.

    Many of these publications carry significant influence and reach large audiences that can introduce our brand to more people. When a highly authoritative outlet covers our story, other journalists may discover and cite it organically. Syndication can amplify the effect further when a media group republishes an article across its network, potentially producing many relevant links from one story.

    Our strongest digital PR campaigns typically use one or more of the following approaches.

    Infographic outlining five steps for a credibility-focused SEO strategy, from targeting trusted publications and creating linkable assets to measuring results.
    Build lasting brand authority in five steps: target trusted publications, create citation-worthy assets, launch digital PR, nurture journalist relationships, then measure and refine your approach.
    • Data-led PR campaigns: We begin with what journalists and their readers care about, not simply what we find interesting. We review local news, Google News, and current coverage to understand which subjects are gaining attention. By considering journalist intent from the start, we improve our chances of receiving responses and earning placements.
    • Newsjacking or reactive PR: When we can move quickly, we contribute expert opinions, data, or commentary to breaking stories that relate to our brand. This gives journalists material they can use while the topic is still timely.
    • Proactive PR: We anticipate trends before they break and prepare insights around recurring news cycles, holidays, and other relevant media moments.
    • Contributed content and guest features: We place useful content written by our experts in relevant publications, allowing us to speak directly to established audiences and earn recognition.

    When we combine these tactics effectively, we can elevate our brand to a level that competitors cannot reproduce with a batch of low-value links.

    We build relationships with journalists and publishers

    We know that even fascinating proprietary data, packaged in an expertly designed analysis, can fail if our journalist outreach is poorly targeted.

    Resolve data about journalist outreach and PR pitches

    Journalists receive an enormous number of PR pitches, and those messages can either support or obstruct their work. According to a 2026 Muck Rack study, nearly nine in 10 journalists said at least some of their stories originated with PR pitches.

    The same survey found that 54% of journalists seldom or never responded to most pitches. Relevance was a central problem: nearly half said a genuinely relevant pitch was rare.

    If we send a journalist at an economics publication a pitch about music-listening habits, we should expect a rejection because the subject may matter to only a small part of that publication’s audience. We do not take that response personally. Journalists build their careers around particular topics and beats, and our job is to support that work rather than distract from it.

    We therefore approach outreach as relationship building: a two-way exchange that should benefit everyone involved. Above all, we remember that there is a real person on the other side of every email.

    • We personalize our emails and explain why a story fits the journalist’s audience.
    • We respond graciously when a journalist says no because our next idea may be a better fit.
    • We share relevant work from journalists and publications through social media.
    • We contribute thoughtful comments when we have something useful to add.
    • We cite journalists’ reporting in future content when it genuinely supports our work.

    As we strengthen these relationships, journalists become more likely to consider future opportunities. A thoughtful follow-up or second pitch can receive a warmer response when a reporter already knows that we provide reliable data and useful commentary.

    PR relationships grow over time. Even when our first pitch does not fit a journalist’s beat, we remain willing to return with a better story or a new set of relevant data.

    How we measure real brand authority

    We recognize that authority, trust, and legitimacy feel less concrete than traffic or keyword position. Yet they have become more important. A traffic surge may look encouraging while reflecting temporary attention, weak intent, or an advantage that disappears after an algorithm update.

    Authority and legitimacy are more durable. We can also measure the impact of credibility-focused work through several meaningful indicators.

    Infographic showing EZ Contacts’ digital PR results: 1,000+ media placements, a Domain Rating of 43, and doubled visibility in ChatGPT and AI Overviews.
    EZ Contacts’ six-month digital PR campaign delivered 1,000+ media placements, raised Domain Rating from 40 to 43, and doubled visibility across ChatGPT and Google AI Overviews.
    • Earned media placements: We track the publications that cover our brand, including coverage containing an unlinked mention. These placements help us assess brand credibility.
    • Branded search volume: We monitor whether more people search for our company or products after discovering us through media coverage.
    • Industry coverage: We look for the point at which publications we have not contacted begin citing our work. That organic pickup is a valuable sign that our authority is spreading.
    • Conversions: We measure whether greater credibility leads more people to trust our organization, products, or services and ultimately take meaningful action.
    • Organic ranking improvements for target keywords: We still review rankings, but we treat them as one indicator within a broader picture. Sustained movement can show that search engines increasingly view us as a credible result relative to competing pages.
    Metrics for measuring brand authority and credibility

    We do not expect these indicators to appear overnight.

    • We invest real effort in creating proprietary data.
    • We build trust with journalists through repeated, useful interactions.
    • We grow authority through sustained work over time.

    Our advice is simple: we stay patient, keep improving, and allow credible results to compound.

    How we build a credibility-focused link strategy

    Knowing the principles of SEO authority is one thing; building an entire campaign around them is another. We use the following five-step process to turn those principles into consistent action.

    1. Step 1 — We define our target publications: We identify five to 10 publications that our audience trusts and that search engines are likely to recognize as authoritative within our field. These become our priority coverage targets.
    2. Step 2 — We develop linkable assets: We create at least two content or media assets designed around the interests of those publications. We may use original survey data, visual guides, proprietary analysis, or expert thought leadership.
    3. Step 3 — We launch a digital PR campaign: We proactively pitch our assets to relevant publications. We can also use platforms such as Connectively or Muck Rack to identify ongoing opportunities with writers covering subjects related to our research.
    4. Step 4 — We nurture relationships: We treat every positive media interaction as the beginning of a longer relationship. We follow up with useful information, engage with published coverage, and build the kind of rapport a journalist can rely on.
    5. Step 5 — We measure and iterate: We review our authority indicators each quarter, learn from the response to our campaigns, and adjust our content and outreach accordingly.
    Resolve credibility-focused link-building process

    We know this process can consume a team’s time, particularly when resources or specialized expertise are limited.

    In those situations, we may benefit from working with a link-building and digital PR specialist who can expand our capacity and keep pace with search changes. The right support can help us establish sustainable visibility without allowing every minor ranking fluctuation to pull us off course.

    How we build authority that lasts at Resolve

    We know that quality usually stands the test of time better than quantity. The difficult part is maintaining that focus when competitors appear to be winning with sudden traffic spikes or eye-catching vanity metrics.

    We do not let temporary numbers distract us from the larger goal. We focus on lasting authority and legitimacy earned through sustained content creation, thoughtful PR outreach, and genuine relationship building.

    When an internal team lacks the time or patience required to maintain that effort, we can step in.

    At Resolve, we work with brands to build credibility-focused SEO campaigns through linkable content, data-led digital PR, and hands-on link building. Our goal is sustainable organic growth, not a burst of visibility that disappears after the next algorithm update.

    Resolve results from credibility-focused digital PR

    We have seen this approach pay off. In a recent data-led campaign for EZ Contacts, we earned more than 1,000 placements in outlets including the New York Post and Yahoo. As the coverage grew, the brand’s visibility in ChatGPT and Google’s AI Overviews doubled. That is the kind of durable growth we want to build — growth that extends beyond the next algorithm update.

    Large Google logo over colorful stacks of digital pages and folders, symbolizing search advertising, web content, and online marketing updates.
    A bold Google logo sits atop layered, colorful digital documents, evoking the fast-moving world of search marketing, ad formats, campaign assets, and platform updates.

    When we are ready to build links that last, we can visit growresolve.com to learn more.

    We see considerable overlap between link building and digital PR, but we do not treat them as identical. Link building is the broader practice of acquiring backlinks from other websites to improve search authority. Digital PR is a particular approach within that practice, focused on earning links through media coverage, journalist relationships, and placements in credible publications rather than relying on directory submissions, guest-post exchanges, or other lower-authority tactics.

    We often use digital PR to pursue the strongest editorial backlinks because reputable outlets have real audiences and established review standards. At the same time, this work builds brand visibility and consumer trust in ways that many conventional link-building methods do not.

    How long do we wait for meaningful results?

    We do not expect authoritative backlinks or earned media coverage to produce results overnight. That is an honest trade-off when we choose a credibility-focused approach instead of more aggressive tactics. Most brands can begin seeing meaningful domain-authority gains and early ranking movement after three to six months of consistent execution, while highly competitive keywords and top-tier placements may require more time.

    The advantage is that our results can compound. Links from credible publications tend to endure, strong journalist relationships can create repeat opportunities, and the authority generated through consistent coverage can keep delivering value long after the initial campaign.

    We define an authority backlink as a link from a source that search engines and its audience regard as credible and trustworthy. These sources typically have genuine readers, clear editorial processes, established authority, and topical relevance to our industry.

    A regular backlink can come from any website willing to link to us, regardless of its relevance, quality, or editorial standards. That distinction matters because search engines do not evaluate every link equally. One editorial link from a respected industry publication can be more valuable than dozens of links from low-authority sites, while also supporting the kind of E-E-A-T credibility that bulk link acquisition cannot reproduce.

    Do we value brand mentions without hyperlinks?

    Yes. We recognize that Google can associate brand mentions with entities even when a publication does not include a hyperlink. Relevant, unlinked mentions in credible coverage can still contribute to the wider authority signals surrounding our brand.

    That is why we consider digital PR valuable even when every placement does not produce a direct link. A credibility-focused off-page strategy should not be reduced to backlink acquisition alone. Our larger objective is to build a brand that respected publications genuinely want to mention, cite, and cover.

    We see risks ranging from wasted effort to serious search penalties. Link buying, reciprocal-link schemes, private blog networks, and manipulative anchor-text optimization can violate Google’s spam policies. These tactics may trigger manual actions or algorithmic suppression that substantially reduces our search visibility.

    Even when outdated tactics do not produce an immediate penalty, they can lose their value as search systems become better at identifying manufactured signals. Recovering from a link-related penalty can be slow and expensive. We would rather invest in credible link building from the beginning than repair the damage caused by shortcuts later.


    Inspired by this post on Search Engine Land.


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