In my experience, the open web often feels like the Wild West, especially in recent times. Many creators, myself included, have watched as our hard work is scraped and fed into large language models without any hint of permission.
This situation has become a free-for-all, leaving website owners with almost no means to opt out or safeguard their creative endeavors. There have been attempts to address this, such as Jeremy Howard’s llms.txt initiative. Much like robots.txt helps us manage site crawlers, llms.txt aims to provide guidelines for AI companies’ crawling bots.
However, a promising new protocol is on the horizon, potentially granting site owners like myself more control over how AI firms utilize our content. It looks like this might become part of robots.txt, allowing us to set definitive rules around AI system access and usage.
IETF AI Preferences Working Group
In response to this issue, the Internet Engineering Task Force (IETF) began the AI Preferences Working Group earlier this year in January. Their mission is to craft standardized, machine-readable rules to empower site owners to articulate AI usage preferences for their content.
Since its inception in 1986, the IETF has established core Internet protocols like TCP/IP, HTTP, DNS, and TLS. Now, they’re laying down foundations for the open web’s AI era. Leading this group are co-chairs Mark Nottingham and Suresh Krishnan, joined by figures from Google, Microsoft, Meta, and more.
Of particular interest is Google’s involvement via Gary Illyes, who is part of this working group.
“The AI Preferences Working Group will standardize building blocks that allow for expressing preferences about how content is collected and processed for Artificial Intelligence (AI) model development, deployment, and use.”
What the AI Preferences Group is Proposing
This group aims to deliver new standards that empower site owners to determine how LLM-powered systems can utilize their open web content.
A standard track document detailing a vocabulary to express AI-related preferences, independent of content association methods.
Standard track document(s) that explain how to associate these preferences with content using IETF-defined protocols and formats, for example, Well-Known URIs and HTTP response headers.
A standard approach for reconciling multiple preference expressions.
At the time of writing, nothing is set in stone yet. Early documents, however, provide a sneak peek into potential standards.
This working group published two crucial documents in August.
These documents propose significant updates to the Robots Exclusion Protocol (RFC 9309), suggesting new rules and definitions enabling site owners to specify AI content usage permissions.
How It Might Work
AI systems on the web are categorized and assigned standard labels. Whether a directory will exist for site owners to identify system labels remains unclear.
Currently, the defined labels include:
search: for indexing/discoverability
train-ai: for general AI training
train-genai: for generative AI model training
bots: for all types of automated processing, such as crawling and scraping
For each label, you can set two values:
y to allow
n to disallow.
I found it interesting that these rules can be applied at the folder level and customized for different bots. In robots.txt, they’re implemented using a new Content-Usage field, akin to existing Allow and Disallow fields.
Here’s an example robots.txt that the working group shared in their document:
Explanation Content-Usage: train-ai=n indicates that no content on this domain may be used for training any LLM model, whereas Content-Usage: /ai-ok/ train-ai=y permits model training using content within the /ai-ok/ folder.
Why Does This Matter?
There’s significant buzz about llms.txt within the SEO community and its use alongside robots.txt. Yet, no AI company has confirmed adherence to these guidelines, and Google disregards llms.txt.
Website owners, including myself, crave more explicit control over how AI companies leverage our content—be it for training models or RAG-based responses.
I feel that the IETF’s new standards signify positive progress. With Illyes as a contributing author, I remain optimistic that once finalized, companies like Google will embrace these standards, respecting new robots.txt rules during content scraping.
When people ask me how to assess the ROI of their marketing campaigns, I always suggest starting with the customer acquisition cost (CAC). CAC, alongside Customer Lifetime Value (LTV or CLV), is vital in navigating the realm of B2B marketing.
By examining your CAC, you can identify which marketing channels deserve more attention and which aspects of your marketing strategy could use improvement. Benchmarking your CAC against industry standards is key.
The aim of this article is to guide you in recognizing what qualifies as a good CAC in your industry and to encourage you to even explore how your CAC fares compared to related industries.
Calculating Your Customer Acquisition Cost
To calculate your CAC, simply divide your total marketing and sales expenditures by the number of new customers acquired, using the formula below:
Make sure to perform this calculation annually or on a rolling basis to accommodate seasonal customer behavior changes. If your B2B business enjoys consistent year-round sales, consider quarterly CAC analysis to gauge the impact of new initiatives.
Additionally, calculating CAC per channel allows you to compare different marketing strategies effectively.
This report emphasizes B2B CACs. For B2C data, see our B2C Edition.
After determining your CACs, you can measure them against the industry averages shared below.
Average Customer Acquisition Cost (CAC) By Industry
The table below presents average CACs across 29 B2B industries, gathered from client data spanning January 2022 to August 2025. Consider these dataset limitations:
Within each industry, we categorize CAC as Organic or Inorganic. Organic CAC includes mainly SEO and Organic Social, while Inorganic CAC covers PPC / SEM and Paid Social.
Email marketing, events, and other channels are excluded due to insufficient data.
Data from client analytics is anonymous. Organic data leans towards SEO and Inorganic towards PPC / SEM, given our B2B clientele and service focus.
Below are the analysis results:
[Insert table block here]
Average Customer Acquisition Cost (CAC) for SaaS Companies
Our team also reviewed average customer acquisition costs across 22 SaaS industries to determine each industry’s B2B CAC.
SaaS Industry
CAC
[Insert table rows here]
How Your CAC Relates to Customer Lifetime Value
While CAC reflects acquisition costs, Customer Lifetime Value (LTV) reveals the average profit per customer. Calculate LTV by dividing your profit over a chosen period by the number of unique customers, and multiply by their average purchase frequency. Aim for an LTV to CAC ratio of at least 3:1 for optimal financial health.
Keep in mind historical trends and competitor data. A 2:1 LTV to CAC ratio isn’t necessarily negative if you’re seeing improvement over time.
Particularly during new campaigns or long-term strategies, your ratios may fluctuate. For example, if you’ve launched an SEO campaign, results typically appear after 4-6 months.
How to Lower Your CACs
Organic CAC often triumphs over inorganic due to its longevity and skill-based approach. Investing in organic channels yields sustainable results without ongoing cash infusion.
If you’re curious about organic marketing to reduce your CAC, feel free to contact us. Our firm, with multiple U.S. locations, has helped various B2B sectors achieve superior ROI with SEO strategies.
Further Reading
For deeper insights into CAC and its relation to LTV, browse the following resources:
Have you ever wondered how to make your products stand out in Google AI Shopping and its AI Mode? I’ve discovered that optimizing feeds, utilizing schema, improving imagery, and crafting conversational Product Detail Page (PDP) content are key strategies to enhance visibility.
Have you ever wondered how amplifying content from creators can actually save money and build trust with your audience? Well, I’ve seen firsthand how paid amplification not only cuts down media costs but also brings in new potential partners.
Brands, including mine, often invest in influencer and affiliate promotions. Yet, many of us stop short of giving the content the reach it deserves, believing the creator’s audience alone is sufficient. But there’s so much more we can do.
By using paid marketing, integrating it into my site, and sharing it across different channels, I’m not just promoting their work. I’m leveraging their brand recognition and strengthening my relationship with them.
It’s true, I may pay influencers an upfront fee, commission, or give them a product for their promotion. But that’s not where our relationship ends.
Amplification truly becomes an advantage here, unlocking more value from the creator relationships I’ve already established.
Why amplifying creator content pays off
Let’s dive into why amplifying creator content can be so beneficial.
Trusted validation
When someone trustworthy backs up my product, store, or company, I gain credibility, especially in competitive fields where trust isn’t always assured, like jewelry or insurance.
For example, picking a hotel near Disney or on a Caribbean island can be daunting with so many choices and mixed opinions. But if someone trusted chooses my brand, that might just sway the decision.
I can utilize this content in ads to reach new audiences or test it with email or SMS list subscribers who haven’t converted yet. The same strategy works for remarketing efforts too.
A third-party endorsement can make a significant difference, even when I sing my own praises.
Lower media costs
Certain influencers might be out of budget, but promising them that their ads will reach new, similar audiences might bring their costs down.
By allowing them to use their affiliate links in this amplified content, they can earn commissions, which shares the risk on both ends by reducing fees and incorporating commission-based rewards.
If the influencer earns more through commissions, they might drop their fees altogether and join as a regular affiliate, freeing up my budget for experimentation with new partners.
Alternatively, we could split the costs, covering part of their media fee while they earn the rest via commissions—opening new avenues to explore and test partners.
There’s magic in content that’s naturally shareable—be it for its humor, virality, or relevance. More people sharing amplified content can lead to wider discovery and referencing, with additional pathways directing traffic back to my site.
Public accounts mean search engines and tools like ChatGPT can index these links, boosting my visibility and traffic.
Affiliate recruitment
When reputable accounts start promoting a vendor, it’s an indicator of earning potential. By amplifying this content, I open up opportunities for others who resonate with those influencers to join as affiliates.
Some might reach out for collaborations, while others might dive into the affiliate world themselves.
Big names endorsing my brand builds trust, making newer partners feel assured that my program is credible.
We encourage our clients to pursue this approach as it effectively streamlines affiliate recruitment and activation, two of the most challenging aspects of the affiliate marketing sphere.
Starting ambassadors and influencers as affiliates ensures fairness. If collaborations prove lucrative, we can transition to hybrid models, minimizing risk while granting them entry.
Not all clients are keen on this model, but those who adopt it see significant benefits, expanding their partner network while sharing risks.
You are not hiring a manufacturing SEO agency to produce rankings in isolation. You are hiring a team to help technical buyers find the right capability, trust what they find, and take a measurable commercial step. An agency can grow traffic and still fail if visitors reach generic pages, cannot verify whether your product fits their application, or never become qualified opportunities.
The decision becomes much easier when you separate proof from pitch. Define the business job first, shortlist agencies by their real specialty, inspect how they turn technical knowledge into accurate content, and make them explain how search activity will connect to sales. The framework below gives you a practical way to do that.
Define the commercial job before you compare agencies
A vague objective such as increasing organic traffic gives an agency room to succeed on paper without improving the business. Start with the action you need a qualified visitor to take. That action should shape the keyword strategy, page architecture, content plan, tracking, and reporting.
Select a primary commercial action for the initial scope. Depending on your sales model, that might be:
Submitting an RFQ with enough technical detail for sales to respond.
Requesting a consultation, sample, prototype, demonstration, or facility visit.
Downloading a CAD file, specification sheet, technical drawing, or selection resource.
Finding an authorized distributor or contacting a regional sales representative.
Requesting maintenance, retrofit, replacement, or field-service support.
Then define what qualified means. A workable internal sentence is: A qualified inquiry comes from [target account or buyer], in [served market], asking about [priority product or capability], for [relevant application], with [information sales needs]. If your marketing and sales teams cannot complete that sentence together, an agency will not be able to build reliable conversion reporting around it.
Give every prospective agency the same one-page campaign brief. It should identify:
The product families, processes, applications, or aftermarket services that matter most.
The people involved in discovery, technical evaluation, approval, purchasing, and implementation.
The countries, regions, industries, account types, and distribution arrangements you can actually serve.
The approved evidence available to support claims, such as data sheets, certifications, test information, case material, drawings, videos, and subject-matter experts.
The commercial action attached to each part of the buying journey.
The way your CRM or sales team distinguishes a qualified opportunity from spam, recruitment inquiries, consumer requests, and poor-fit leads.
Constraints the agency must respect, including approval workflows, dealer relationships, regulated claims, legacy systems, and pages that cannot be changed without review.
Use a measurement ladder rather than a single traffic target. At the top are accepted opportunities, qualified pipeline, and attributable revenue where your systems support that connection. Below those are primary conversions such as qualified RFQs and consultations. Supporting actions might include specification downloads, distributor lookups, return visits, or contact with a technical representative. Search visibility and site-health metrics belong underneath those commercial measures, not in place of them.
This hierarchy exposes incentive problems early. If a proposal promises sessions and keyword positions but does not define qualified demand, the agency can complete its stated job while your sales team sees no improvement.
Build your shortlist around the bottleneck, not the rank
You can start with eight names drawn from a November 2025 field of 54 firms. Because First Page Sage evaluated that field and placed itself first, use the names as candidates to investigate rather than as an independent endorsement. That conflict does not make the information useless; it changes what the placement itself can prove.
Agency
Documented November 2025 focus
Interview when your main need is
First Page Sage
Thought leadership, SEO, and AI search optimization
Turning internal expertise into organic and generative-search visibility
Kula Partners
SEO-focused web design and account-based marketing
Connecting a website program with named-account demand generation
Industrial Strength Marketing
Brand strategy and sales enablement
Aligning market positioning, marketing assets, and the sales conversation
Windmill Strategy
Technical SEO and web design
Improving the technical and structural foundation of a complex site
Factory Web Source
Social media and video SEO
Making demonstrations, processes, equipment, and other visual material discoverable
Aviate Creative
Branding for manufacturing companies
Clarifying or modernizing the brand before scaling acquisition
Ecreative
Paid search and web development
Coordinating organic search, paid acquisition, and website execution
Brandpoint
MAT releases combined with SEO
Connecting distributed editorial material with search visibility
The third column is a decision heuristic, not a claim that the firm will fit your account. Treat every service label from November 2025 as time-bound. Ask each agency to confirm its current scope, current delivery team, and current examples before putting it on a final shortlist.
AI-search capability needs that freshness check in particular. Only First Page Sage was marked as offering GEO in the November 2025 comparison. That does not establish that the other seven still lack a GEO service, nor does a checked box establish the depth of any service. Ask what the agency actually changes, what it measures, which systems it observes, and how the work differs from its conventional SEO program.
If technical accuracy is the constraint, prioritize the subject-matter-expert workflow, writer background, and claim-approval process.
If an old website is the constraint, prioritize technical diagnosis, development capacity, migration controls, quality assurance, and ownership of implementation.
If buyers do not understand a new category, prioritize positioning, thought leadership, evidence development, and sales alignment.
If named accounts drive growth, prioritize the connection between SEO, account-based marketing, CRM data, and sales follow-up.
If visibility in generative systems matters, prioritize a current GEO method with explicit deliverables and observable measures.
Longevity, recognizable clients, reviews, and media mentions can support confidence. None of them answers the decisive question: Can the people assigned to your account execute the work your commercial problem requires?
Pressure-test the delivery system before you buy it
Run the same diligence exercise with every finalist. Comparable inputs make vague answers, hidden dependencies, and major scope differences easier to notice. You are evaluating a production system, not just the strategy presented in a sales call.
Test whether the specialty is real
Many agencies can list manufacturing among the sectors they serve. That is not the same as having a manufacturing operating model. Ask:
What does your agency specialize in, and which services are secondary?
Which part of manufacturing SEO do you deliberately not lead?
What type of manufacturer, sales motion, or website is a poor fit for your team?
Which deliverables are completed in-house, and which are handled by partners or freelancers?
Can you show an engagement with comparable technical complexity, channel structure, or buying process?
What changed because of your work, and how was that change connected to a business measure?
Do not grade the answer by the prestige of a client logo alone. A familiar manufacturer may have bought a different service, worked with a different team, or presented a much simpler problem. Ask what the agency owned, who performed it, and which evidence the example can legitimately support.
Test the technical-content workflow
Give each finalist the same public or sanitized set of product materials. The goal is to test the process without exposing proprietary information. Ask the team to explain how it would turn those materials into a search and content plan. Do not ask for a free finished campaign; ask for the operating logic.
A credible answer should identify:
Which document, system, or person becomes the source of truth for each technical claim.
How search intent will be separated across products, capabilities, applications, industries, problems, and buying stages.
How writers will interview engineers, product managers, service teams, salespeople, or other relevant experts without wasting their time.
Who drafts, technically verifies, edits, approves, publishes, and maintains each asset.
How conflicting terminology, outdated documents, market-specific naming, and unsupported claims will be resolved.
How one page will earn a distinct purpose instead of repeating a slightly altered template across the catalog.
A weak answer relies on a generalist writer researching the product independently and sending a polished draft for your team to repair. That transfers the hardest part of the work back to you. A stronger model captures expert knowledge deliberately, records the supporting evidence, and makes technical review a defined stage rather than a last-minute rescue.
Test technical execution and account ownership
Ask the agency to separate diagnosis from implementation. A technical audit has limited value if no one converts findings into approved development work, verifies the release, and confirms that the intended behavior reached production.
Request a sample issue or development ticket with sensitive information removed. It should show the problem, affected templates or URLs, business consequence, recommended change, owner, dependencies, acceptance criteria, and quality-assurance step. Then ask who writes that ticket, who answers developer questions, and who checks the completed change.
Complex manufacturing sites may combine product pages, application pages, filterable catalogs, distributor locations, technical PDFs, support material, multiple languages, and several conversion paths. Your finalist should be able to explain how it will decide what belongs in the search index, which page owns each intent, how internal links support that ownership, and where a visitor should go next. It should also state what requires your developer, CMS vendor, analytics team, or legal and compliance review.
Get the account map in writing. Identify the strategist, technical lead, writer or editor, project manager, analyst, and executive sponsor where those roles exist. Confirm which people will attend recurring meetings and which person has authority when priorities conflict. A senior salesperson who disappears after signature is not part of the delivery team.
Test reporting with a real lead path
Give every finalist the same scenario: a buyer discovers an application page through non-branded search, returns through a branded search, downloads a specification, and later submits an RFQ that sales accepts. Ask how that journey would appear in reporting and which limitations would remain.
A credible reporting plan distinguishes what is directly observed, what is assisted, what is inferred, and what cannot be known with the available systems. It also includes sales feedback about lead quality. Be cautious when rankings are presented as revenue, all organic conversions are treated as equally valuable, or attribution is described without reference to your CRM and sales process.
Require one operating plan for SEO, AEO, GEO, and handoff
SEO, answer engine optimization, and generative engine optimization should not become three disconnected content programs. For procurement purposes, use simple operational definitions. SEO makes relevant pages discoverable and competitive in conventional search. AEO makes important questions easy to answer directly from clear, supported content. GEO organizes the brand, entities, expertise, and evidence so generative systems can more reliably understand and potentially surface them.
The labels overlap because the same technical truth may serve all three. Your agency should show how one validated knowledge base becomes useful pages, concise answers, consistent entity information, structured data, internal links, and commercial pathways.
For one priority product family or capability, ask for an integrated deliverable map containing:
An intent map that separates product, capability, application, problem, comparison, support, and purchase-oriented needs where they genuinely exist.
A canonical commercial destination with the information a qualified buyer needs to evaluate fit and take the next step.
Supporting pages that answer distinct technical or commercial questions instead of competing with the canonical page.
An evidence inventory showing which statements are supported by approved specifications, certifications, testing, case material, or named expertise.
A terminology and entity map covering the company, brands, product families, processes, locations, industries, and alternate names that must remain consistent.
An internal-link plan connecting educational discovery to evaluation and action.
An AEO plan that answers real presales and support questions without manufacturing an FAQ section merely to occupy search space.
A GEO plan that defines target query sets, systems observed, checks performed, changes made, and the difference between a brand mention and an attributable commercial result.
A JSON-LD plan that describes accurate, visible page content and assigns responsibility for generation, validation, deployment, and maintenance.
A measurement map connecting each asset to its intended search behavior, user action, and commercial signal.
Structured data deserves particular scrutiny because it can look impressive in a deliverables list while doing little to correct weak information. JSON-LD is machine-readable labeling, not evidence. It should match the visible page, use the right entity relationships, and be maintained when templates, products, locations, or claims change. Ask who validates it after deployment and how errors or stale values enter the work queue.
Put the operating model into the contract. Define deliverables, exclusions, dependencies, approval responsibilities, acceptance criteria, reporting cadence, account access, and ownership of content and data. State what happens to analytics configurations, keyword sets, briefs, drafts, dashboards, schema, and other working assets when the engagement ends.
Vague ownership and termination language can leave you paying for unusable work or losing access to accounts and materials. Have your procurement or legal team review confidentiality, intellectual-property, liability, data-access, and termination clauses before signature; an SEO evaluation cannot resolve those legal terms for you.
Use acceptance gates instead of authorizing an undifferentiated stream of activity. The first gate should confirm the baseline, priorities, measurement design, and dependencies. Later gates can cover technical implementation, content production, publication, and performance review. If the agency cannot define what complete means at each handoff, the scope is not ready to sign.
Manufacturing SEO agency FAQ
Must the agency have experience in your exact manufacturing niche?
Exact-niche experience can shorten the learning curve, but it should not replace process evidence. A team with an excellent technical-review workflow, a comparable sales model, and experience handling complex product information may be stronger than a niche specialist that relies on generic pages and weak measurement. Ask both candidates to demonstrate how they learn terminology, verify claims, protect confidential information, and distinguish qualified demand. Also check whether a direct competitor relationship creates practical conflicts.
Should the engagement include a website redesign?
Only when the current site prevents the agreed strategy from being implemented effectively. Require three options where practical: retain the present site, make targeted structural or template changes, or replace it. Each option should identify the SEO consequence, implementation dependency, content work, measurement impact, and ownership. An agency whose main strength is web design may naturally see a rebuild as central; one focused on content may prefer to work around the platform. Your diagnosis and business case should decide, not the agency’s preferred service line.
How can you compare proposals with different scopes?
Normalize them into the same worksheet. Create rows for discovery, technical SEO, implementation, content strategy, expert interviews, writing, editing, design, publication, authority development, AEO, GEO, structured data, analytics, CRM connection, reporting, and project management. Mark every row as included, dependent on your team, handled by a third party, optional, or excluded. Then record the responsible role, deliverable, acceptance condition, and ownership after termination. This exposes a low proposal that depends heavily on your staff and a broad proposal that includes work you do not need.
Write the one-page brief before your next agency call. Give every finalist the same sanitized product-family scenario, commercial action, and reporting question, and ask the people who will perform the work to join the discussion. Choose the team that can trace a validated technical fact into a discoverable page, a useful buyer answer, and a measurable sales action – then put that chain of responsibility in writing.
If Semrush sits at the center of your search program, Adobe’s move raises an immediate operational question: should you renew, integrate, wait, or start evaluating alternatives?
Do not make that decision from an acquisition headline. Use the deal to strengthen your measurement, data portability, and contract position now. Treat the promised combination as strategic direction until specific integrations are available, documented, and commercially defined.
Separate the acquisition agreement from the product reality
That target date is not proof that the transaction has closed. Confirm the current status before making a renewal, migration, staffing, or integration decision. A signed acquisition agreement establishes intent; it does not establish the final product roadmap, pricing model, account structure, or migration path.
Area
What is established
What you still need to verify
Transaction
Adobe agreed to acquire Semrush for approximately $1.9 billion in cash, and both boards approved the deal.
Current closing status and whether every required approval has been obtained.
Strategic direction
Adobe and Semrush intend to combine customer-experience and content-supply-chain capabilities with SEO, GEO, and brand-visibility capabilities.
Which workflows will actually be integrated, in what order, and on what release schedule.
Product impact
The intended destination is a more unified platform for visibility, engagement, and conversion.
Feature availability, supported systems, methodology, account changes, migration requirements, and service continuity.
Commercial impact
No acquisition price or strategic statement determines what an individual customer will pay.
Packaging, renewal terms, price protection, bundles, usage limits, support levels, and API access.
This distinction prevents two expensive mistakes. The first is buying a future integration that exists only as positioning. The second is dismissing the deal and discovering too late that your reporting, procurement, or data architecture is tied to a changing platform.
Key takeaways
Do not migrate or replatform solely because ownership is changing.
Capture a dated baseline of your SEO and GEO data before products, methodologies, or retention policies change.
Evaluate promised integrations against shipped capabilities, documentation, contract terms, and reproducible outputs.
Keep your content inventory, entity facts, prompt sets, keyword sets, and historical measurements portable.
Measure discovery, engagement, and business outcomes separately, even if a future dashboard presents them as one journey.
The important possibility is a closed visibility-to-content loop
Adobe brings customer-experience orchestration, an AI-oriented content supply chain, and AI-driven engagement capabilities. Semrush brings search intelligence and brand-visibility capabilities spanning traditional SEO and GEO. The companies’ strategic thesis is that those functions can become an end-to-end marketing system.
For an SEO or GEO team, the meaningful possibility is not another dashboard. It is a feedback loop in which visibility evidence can directly influence content planning, production, distribution, and revision:
Detect a search question, topic gap, competitor advantage, or weak brand representation.
Prioritize the gap using audience relevance and business value rather than search volume alone.
Create or update a canonical answer, supporting evidence, structured data, and related assets.
Distribute that material through the appropriate web and customer-experience channels.
Measure whether the brand becomes more discoverable, accurately represented, engaged with, and selected.
That loop is an operating model, not evidence that the products already perform every step together. Integration creates value only when the underlying signals remain understandable. A seamless interface can still produce weak decisions if your team cannot see what was measured, where it was measured, or why a recommendation changed.
GEO also should not become a vague label for every AI-related activity. In practical terms, it concerns whether AI-driven search and answer experiences can discover, understand, mention, cite, and accurately represent your brand and content. It overlaps with SEO, but it introduces different observation conditions, including prompts, generated answers, citations, mentions, platform behavior, and repeated sampling.
Keep three measurement layers distinct:
Discovery: rankings, visibility, mentions, citations, answer inclusion, and representation of important entities or claims.
Engagement: qualified visits, assisted journeys, content use, and other observable actions after discovery.
Outcome: leads, revenue, retention, applications, purchases, or another result tied to the organization’s objective.
A platform may connect those layers, but connection is not causation. Your reporting should show which relationship is directly observed, which is attributed by a model, and which is only a working hypothesis.
The intended combination is clearly relevant to complex organizations: Adobe identifies companies including Coca-Cola and IBM among the large businesses using its experience capabilities. That enterprise context makes governance, permissions, regional coverage, data retention, and methodological consistency as important as feature breadth.
Build a 90-day readiness plan without betting on the roadmap
You do not need inside knowledge of the integration roadmap to prepare well. The useful work is the same whether the combined platform becomes essential, optional, delayed, or unsuitable for your stack.
Create a dated baseline. Record your active projects, tracked markets, devices, languages, locations, competitors, keyword groups, prompt sets, reporting cadence, and attribution settings. A trend line is difficult to interpret when nobody can reconstruct how the measurement was configured.
Preserve the history you would need after a platform change. Export the reports and underlying records your team depends on, including rankings, visibility trends, site-audit findings, competitor sets, content inventories, and GEO observations where available. Store the export date, configuration, and field definitions beside the files. Do this before a contract ends; access after cancellation should never be assumed.
Map decisions, not just integrations. For each recurring report, identify who reads it, what decision it triggers, what action follows, and which system records the outcome. A technically elegant connector has little value if the report does not change a decision.
Document your content and entity layer outside any vendor. Maintain a canonical inventory containing the audience question, target entity or topic, approved facts, evidence owner, canonical URL, schema status, last verification date, and responsible editor. This becomes the stable layer beneath changing tools.
Create a vendor-neutral evaluation scorecard. Include geographic and language coverage, SEO depth, GEO methodology, reproducibility, explainability, export options, API access, permissions, integration effort, security review, support, and total contract cost. Weight the criteria before a product demonstration so a polished new feature does not redefine the decision.
Run a fixed measurement sample. Choose a stable set of commercially and reputationally important queries and prompts. Record the platform, market, language, date, result, citation or mention status, linked destination, and whether the brand was represented accurately. Repeat on a defined cadence. The purpose is not to eliminate variability; it is to make your observations comparable.
Set event-based review points. Reassess when the transaction’s current status is formally confirmed, when concrete product integrations are released, when packaging is announced, and before your next renewal deadline. Ownership news alone is not a reason for an emergency migration.
The baseline and exports protect you from data loss. The scorecard protects you from buying on narrative. The fixed sample protects you from mistaking a changing measurement method for a real improvement in visibility.
Put specific questions into renewal and procurement reviews
If your renewal or platform review arrives before the integration picture is clear, do not ask whether Adobe and Semrush will create an end-to-end solution. That phrasing invites an aspirational answer. Ask questions that force a distinction between current capability, committed development, and general direction.
Product and workflow questions
Which integrations are generally available now, and which remain on the roadmap?
What exact data passes between products, in which direction, and how frequently?
Will Semrush workflows continue to support non-Adobe content-management, analytics, and experience systems?
Will customers need separate accounts, permissions, identities, or usage entitlements?
Which SEO and GEO reports share a methodology, and which remain independent measurements?
What changes would require customer migration, reconfiguration, retraining, or implementation services?
Data and measurement questions
Can you export raw observations as well as aggregated scores?
What do visibility scores represent, and can your team reproduce the calculation from documented inputs?
How are market, language, location, personalization, prompt wording, citations, mentions, and answer variability handled?
Will historical data be preserved if a metric, crawler, data source, or model changes?
What retention periods apply, and what can be exported when the contract ends?
Is API access included, limited by usage, or sold separately?
How may customer data, prompts, content, and performance records be used in AI systems?
Commercial and continuity questions
Will current products remain separately renewable, or is a bundle planned?
Which pricing, usage, support, or service-level terms can be committed in the contract?
What notice will customers receive before a material product, metric, API, or packaging change?
Can you run old and new workflows in parallel long enough to validate continuity?
What is the rollback or exit path if an integration disrupts reporting or production?
Will new data flows require another security, privacy, compliance, or regional-hosting review?
Write material answers into the contract, order form, or implementation plan where possible. A roadmap presentation can clarify direction, but it does not protect your access, price, data, or migration timeline.
Keep your SEO and GEO strategy portable
The strongest response to platform consolidation is not reflexive resistance. It is portability. Your organization should be able to change measurement or orchestration tools without losing its understanding of customers, entities, content, evidence, or past decisions.
Keep these assets under your own governance:
A canonical inventory of content, topics, entities, authors, evidence, and responsible owners.
Your approved brand facts, terminology, claims, and correction procedures.
Structured-data specifications and validation records rather than only a vendor’s score.
Dated historical exports with configuration notes and metric definitions.
A decision log showing why important pages, campaigns, schemas, and measurement rules changed.
A mapping from discovery metrics to engagement and business outcomes.
Portability does not prevent you from benefiting from a deeper Adobe-Semrush integration. It gives you a control group. When a new workflow promises better prioritization or attribution, you can compare it with a stable record instead of accepting the platform’s new baseline as the truth.
Source diversity deserves the same attention. Semrush acquired Search Engine Land, MarTech, and their parent Third Door Media in October 2024. That ownership does not by itself invalidate a dataset, product, or publication. It does mean your governance map should recognize when software, market intelligence, and industry media sit within the same corporate group. Avoid relying on one group for measurement, interpretation, and independent validation of the result.
Your next move can be small and concrete: schedule the baseline export, assign an owner to the evaluation scorecard, and add the procurement questions before the next renewal conversation. Watch for confirmed transaction status, shipped integrations, documented methodologies, and binding commercial terms. Act when those details change the decision – not when the strategic promise merely sounds complete.
Affiliate marketing is a major driver of revenue, but it also hides significant losses. I’ve seen firsthand how brand bidding, ad hijacking, coupon abuse, and subtler forms of affiliate fraud can erode ROI and distort attribution figures.
The critical issue isn’t whether these challenges exist, but rather understanding how much they’re impacting our business. In this article, I delve into the most prevalent types of affiliate marketing fraud. I’ll also share insights on how modern tools like Bluepear offer advanced affiliate fraud detection strategies that protect our growth, reputation, and budget.
Not all affiliate programs offer the same benefits, nor do they come with the same risks. Particularly in SaaS, where affiliate commissions can be between 20% to 70%, these programs become highly enticing targets for fraudsters.
Fraudsters exploit trust gaps, often bidding on brand terms or using shady tactics like ad hijacking and coupon code misuse to siphon off profits. A staggering 63% of affiliate marketers identify these threats as their primary concern.
Unfortunately, much of this fraud operates under the radar. Affiliates execute campaigns and manage landing pages without real-time monitoring, which means you may end up paying commissions on existing traffic or, worse, funding brand impostors.
Let’s dig deeper into common fraud tactics and how to recognize and counteract them early on. Equipped with strategies, you can shield your program from such threats.
I focus on four primary fraud tactics: brand bidding, ad hijacking, coupon abuse, and non-compliant content. Each poses unique challenges but can be counteracted with the right preventative measures.
Brand bidding occurs when someone purchases ads using your brand name. This diverts potential customers who are actively searching for your product, resulting in needless commission payments. It’s crucial to maintain a detailed list of brand-related keywords in your affiliate terms and monitor for sudden spikes in performance metrics.
Ad hijacking mimics your paid search ads, lowering your campaign visibility. Regular checks and test searches can expose these fraudulent activities.
Coupon abuse is trickier; it manipulates traffic from affiliates who rank high for brand-related coupon searches. Ensuring coupon activity is pre-approved and regularly monitoring search results helps mitigate this fraud.
Non-compliant content can easily escape detection. Cloaking tactics mean users see different content than compliance teams. Establish strong creative guidelines and treat content audits as an ongoing activity.
Defending against affiliate fraud requires continuous vigilance, clear program rules, and leveraging technology. Platforms like Bluepear use automated systems to highlight and eliminate fraud, giving you back control.
For 2026, my focus is on building stronger relationships with affiliates, ensuring transparency, and promoting a culture that prioritizes honesty and clear communications.
Ultimately, affiliate fraud is a continually evolving threat. By understanding these tactics, setting clear expectations, and utilizing advanced tools, we can protect our interests and secure sustainable growth.
Research from Forrester and insights from Blain’s Farm & Fleet have shown me that the real obstacle in AI adoption isn’t the technology itself; it’s how we approach marketing tasks.
Imagine a chocolate company with a cherished, decades-old recipe. They ask an AI tool to identify cost-cutting measures. After several ingredient eliminations and promising margins, sales plummet. Finally, someone tastes the product: “This isn’t even chocolate anymore.”
Aly Blawat from Blain’s Farm & Fleet shared this during a MarTech webinar to highlight why 82% of marketing teams struggle with AI: automation devoid of human insight often exacerbates failure.
According to a Forrester study for Optimove, just 18% of marketers feel at the vanguard of AI adoption, despite 80% anticipating enhanced targeting through AI. Only a quarter have active AI use cases in production.
As Forrester’s Rusty Warner explains, many await software with built-in safeguards before fully embracing AI. Currently, marketing runs like an assembly line, ill-suited for AI’s potential to overhaul workflows.
Positionless Marketing could be the answer. Here, marketers manage everything from data to campaign launches independently, allowing swift action and reserved teamwork for larger initiatives.
Blain’s Farm & Fleet trialed AI for their brand’s cohesive tone across platforms, utilizing Jasper, a protected system. Warner suggests starting small to build confidence, ensuring data integrity for effective AI outcomes.
Successful marketing teams centralize critical data definitions, providing essential signals directly to marketers. Adoption lags not due to the technology, but because organizations aren’t structured to exploit it effectively.
Balancing automation with authentic customer engagement means deploying AI where it can be most beneficial while maintaining a genuine brand experience. At Blain’s Farm & Fleet, human oversight ensures alignment with customer expectations.
The future points toward AI in execution, allowing unique, personalized customer journeys. This shift demands organizations to enhance customer experience expertise across all channels.
For effective AI integration, restructuring marketing workflows and focusing on measurable outcomes are key. The vision includes less manual effort, fewer illustrative meetings, and more tangible customer impact.
By 2026, AI adoption is expected to soar with more vendors providing embedded, coherent AI solutions. Brands like Blain’s Farm & Fleet illustrate the transformation—the right AI application fosters growth, far beyond superficial changes.
Ultimately, AI can’t repair broken systems but amplifies existing conditions. Successful teams must adapt modern workflows and mindset shifts to harness AI’s full potential.
I’ve recently come across an exciting development from Google that could change the way we approach Google Ads. It’s called Journey Aware Bidding, and it’s designed to optimize Search campaigns by utilizing signals from every step of the customer journey. This aims to provide a smarter and more efficient way of managing campaigns.
Google has rolled out this new Search bidding model to enhance prediction accuracy and improve campaign performance. The idea is to consider the entire customer journey, not just the final conversion point.
How it works: Journey Aware Bidding learns not only from your primary conversion goal but also from non-biddable journey stages. If you’re someone who tracks and defines each step of your purchase funnel meticulously, this model could be particularly beneficial.
Google advises mapping out the entire process—from lead submission to final purchase—and labeling all critical touchpoints as conversions within standard goals. This method promises to integrate more of the conversion funnel into Google’s prediction models, potentially streamlining lengthy, complex journeys such as lead generation.
Why it matters: As someone who’s worked extensively with fragmented signals in conversion funnels, I’m intrigued by how Journey Aware Bidding could bring greater efficiency to our campaigns. It emphasizes learning from all key touchpoints, leading to smarter bidding strategies.
What you should know: To get the most out of this feature, align your optimizations to a single KPI-driven stage, such as purchases or qualified leads. While other journey stages should be marked as primary conversions, they should be excluded from campaign-level or account-default bidding optimization.
Ensure that all tracking and categorization are accurate to achieve the best results.
Pilot phase: Google is launching a closed pilot this year for select advertisers, with plans to expand after refining the model. This could be a game-changer in how we approach Search optimization.
The bottom line: If you’re ready to rethink how you optimize your campaigns, Journey Aware Bidding might be the innovative approach you’ve been waiting for. By understanding not just what converts, but how users get there, we could see significant improvements.
First seen: Senior Consultant Georgi Zayakov shared insights about this new bidding model on LinkedIn during Think Week 2025, alongside other intriguing products.
You are probably comparing GEO tools because your brand is difficult to find in ChatGPT, Gemini, Perplexity, or another generative answer engine. The hard part is not finding a dashboard. It is working out whether a quote buys useful measurement, practical recommendations, or the work required to change the answers.
That distinction matters more than the advertised monthly price. A low-cost tracker can be exactly right for a team that can execute. The same subscription can become shelfware when nobody owns content, SEO, reviews, or digital PR. Use this guide to define the job, compare unlike pricing plans on the same basis, and buy only the scope you can turn into action.
Decide whether you need a GEO tool, a service, or both
GEO software and managed GEO services solve different parts of the problem. Treating them as substitutes is the fastest way to misread a proposal.
A service acts. It may improve pages on your website, create comparison content, pursue inclusion in third-party lists, develop review visibility, or conduct public relations. Some agencies include software access in the engagement, but the dashboard is still only the measurement layer.
Start by naming your actual bottleneck:
You cannot see what is happening. You do not know which prompts matter, whether your brand appears, which pages are cited, or how competitors enter the answer. Begin with measurement software.
You can see the problem but cannot diagnose it. You have reports, but no reliable way to connect an answer change to content, authority, citations, or reputation. Look for a platform or advisory engagement that produces evidence-backed recommendations.
You know what should change but lack execution capacity. The backlog repeatedly loses to other work. A managed service may be more economical than another dashboard because implementation is the scarce resource.
Your website is not the main constraint. Competitors are recommended because they appear in respected comparisons, reviews, and press coverage. A tool can expose this gap, but fixing it requires off-site work.
Do not pay for full-service execution merely because the reporting looks sophisticated. Conversely, do not buy a tracker and assume visibility will improve by itself. Write one sentence before any sales call: We need this purchase to help us decide or do ______. If a vendor cannot connect its deliverables to that sentence, the package is oversized, underspecified, or both.
Require evidence for every capability on the feature list
Feature matrices make GEO platforms look more interchangeable than they are. Two vendors can both advertise prompt tracking while using different engines, collection schedules, sampling methods, and definitions of visibility. Compare the records behind the dashboard, not the labels on the pricing page.
Capability
What to ask
Acceptable proof
Engine coverage
Which engines, answer modes, markets, and account states are included in our quoted plan?
A current coverage list and a raw result from every engine you intend to monitor.
Prompt tracking
Does one tracked prompt cover one engine, or is each prompt-engine-market combination counted separately?
The precise billing definition of a tracked prompt, including reruns and overages.
Answer collection
How often are answers collected, and how does the system handle variation between responses?
Timestamped answer text with collection metadata and a documented sampling method.
Brand detection
Can we define product names, parent brands, abbreviations, misspellings, and excluded terms?
A configurable entity record and examples showing how ambiguous matches are handled.
Citation capture
Does the platform preserve the cited page, domain, answer passage, and engine where the citation appeared?
A citation-level export, not merely a domain total.
Competitor analysis
Can the same prompt set compare our brand with named alternatives without changing the collection method?
A prompt-level view showing every detected entity and citation in the underlying answer.
Recommendations
Does each recommendation identify the evidence, affected prompt group, responsible team, and proposed change?
A sample recommendation that can be accepted, rejected, assigned, and later evaluated.
History and export
What data can we retain or export if we downgrade or leave?
A machine-readable export containing prompts, answers, dates, mentions, citations, and relevant metadata.
Raw answer evidence is essential because a brand mention, a recommendation, and a citation are not the same result. Your company can be named without being endorsed. It can be recommended without receiving a clickable citation. A page can be cited while the answer recommends a competitor. A single visibility score can hide all three situations.
Define the scorecard before you watch the demo
Ask every shortlisted vendor to calculate the same small set of metrics. The names are less important than stable definitions:
Answer inclusion rate: the share of eligible collected answers in which the defined brand or product appears.
Recommendation rate: the share in which the brand is presented as a suitable choice, not merely mentioned in passing.
Cited-source rate: the share that cites a page on a domain you own or another domain you have deliberately classified.
Competitor gap: the prompt groups where a named competitor appears or is recommended and your brand does not.
Evidence gap: the cited domains and page types supporting competitors but absent from your own authority footprint.
Action completion: the recommendations accepted, assigned, implemented, and annotated in the measurement history.
Keep engine-level results separate until you have a reason to combine them. A blended score can rise because performance improved on a low-priority engine while declining where your buyers actually search. If you do create an overall index, document the business weighting so a future team member can reproduce it.
Your prompt inventory needs the same discipline. Group prompts by the decision they represent: category discovery, direct comparison, problem diagnosis, vendor validation, or implementation. Tag branded and unbranded prompts separately. A report dominated by easy branded questions can look healthy while category-level discovery remains weak.
Normalize GEO pricing before comparing quotes
There is no useful universal price without a common unit of scope. GEO packages can vary greatly in cost and included work, with entry-level options offering narrower functionality and premium engagements covering a broader program. A monthly total tells you little until you know what consumes the allowance and what still requires your team.
Build a quote-normalization sheet with these rows:
Pricing variable
Record for every quote
Why it changes the real cost
Prompts or queries
Included quantity, billing definition, and overage rule
A prompt may be counted once, once per engine, or once for every market and configuration.
Engines
Included engines and any plan restrictions
Broad headline coverage is irrelevant if the engines you need sit behind an upgrade.
Markets and languages
Included locations, languages, and regional configurations
Local or international monitoring can multiply the number of configurations being tracked.
Collection cadence
Refresh schedule, reruns, and sampling method
A frequently refreshed series is not equivalent to an occasional snapshot.
Brands and competitors
Included entities and the price of additional ones
A plan can become expensive when each product line or competitor consumes another allowance.
Users and workspaces
Included seats, clients, projects, and permission controls
Agency and enterprise use may require separation that an individual account cannot provide.
History
Retention period and access after downgrade or cancellation
Trend reporting loses value if the underlying evidence expires or cannot be exported.
Exports and integrations
File exports, API access, dashboards, and usage limits
Manual transfer adds labor even when the platform subscription appears inexpensive.
Onboarding
Setup fee, prompt research, entity configuration, and training
A low recurring fee may exclude the work needed to make the account usable.
Analysis and execution
Included analyst time, content work, SEO changes, outreach, reviews, and PR
Software access should not be priced as though implementation is included when it is not.
Commitment
Billing frequency, minimum term, renewal process, and cancellation conditions
An annual commitment carries a different risk from a cancellable pilot, even at the same monthly equivalent.
Then calculate the cost you will actually approve:
Total operating cost = platform or service fee + required add-ons + internal analysis time + implementation labor + external execution spend.
This is the figure that belongs in your decision memo. A subscription can look cheap while requiring hours of prompt cleanup, report interpretation, content production, and outreach. A managed engagement can look expensive while replacing work you would otherwise need to staff. Neither is automatically better; the relevant question is which quote buys the missing capability at the lower total cost.
Use a common monitoring unit, but do not mistake it for value
For quote comparison, define one monitoring configuration as a prompt paired with an engine, market, language, and refresh schedule. Ask vendors to price your exact inventory. This prevents a plan with broad but shallow coverage from appearing equivalent to one collecting the configurations you need.
You can divide total software cost by comparable monitoring configurations to expose pricing differences. Do not use that result as your final value metric. A large inventory of irrelevant prompts is still waste. Value comes from resolving decisions: which content to improve, which evidence to publish, which citation gap to pursue, and which work to stop.
Also separate included capacity from usable capacity. If your team can review only a small portion of the collected results, buying more prompts adds noise. If the allowance is too small to cover meaningful prompt groups, apparent volatility may send the team after isolated answer changes. Scope the inventory around decisions and ownership, then buy the capacity required to support it.
Match the service tier to the work that must change
Service tiers are useful as a procurement model, but their names are not standardized. Define each tier by responsibility rather than by labels such as starter, growth, or enterprise.
Measurement tier: establishes the prompt set, captures answers, reports mentions and citations, and identifies gaps. Choose it when your internal team can interpret the findings and implement changes.
Diagnosis and guidance tier: adds prioritized recommendations, content or authority analysis, and working sessions. Choose it when you have execution capacity but need help deciding what to change.
Managed execution tier: owns agreed work across measurement, website SEO, comparison content, reputation, third-party visibility, and PR. Choose it when the visibility gap extends beyond your site or when internal ownership is the constraint.
A comprehensive GEO program may span several distinct workstreams. Ranking strong comparative or superlative pages can influence the information available to answer engines. Inclusion in third-party lists can create corroborating evidence. Reviews contribute reputation signals on platforms relevant to the category. Press coverage can strengthen the body of independent material associated with the brand. SEO, list visibility, reviews, and traditional PR can all form part of the broader GEO scope.
Review work must be category-specific. Technology services may care about G2 and Clutch, software companies may encounter Capterra, travel brands may depend on TripAdvisor or Yelp, and B2B organizations may need to notice employer-review properties such as Glassdoor and Indeed. The point is not to create profiles everywhere. It is to identify which independent properties appear in the citations and recommendations for your commercial prompt set, then prioritize legitimate review generation and accurate profile management there.
Ask a managed provider to separate owned, earned, and paid activity in its scope. A page published on your website is not equivalent to independent editorial coverage. A paid list placement is not equivalent to an earned recommendation. A review profile is not the same as a program that helps real customers leave candid feedback. If all of these appear under a vague authority-building line item, you cannot judge the method, risk, or expected deliverable.
A lower tier is sensible when you already have strong brand recognition, search performance, editorial resources, or PR support. It is also sensible when you are still validating the prompt set. Premium execution earns its fee only when the provider is responsible for work you genuinely need and can show how that work connects to observed answer and citation gaps.
Run the same buying test with every finalist
Write the decision brief. Specify the products, market, engines, prompt groups, competitors, and business decisions the system must support.
Send an identical inventory. Require every vendor to quote the same prompt-engine-market configurations, refresh expectations, users, history, and export needs.
Inspect a raw record. Ask to see the prompt, collected answer, timestamp, detected entities, cited pages, and relevant collection metadata behind a dashboard result.
Test a difficult distinction. Use a result where your brand is mentioned but not recommended, or where your page is cited while a competitor is favored. Ask how the platform classifies it.
Request an action sample. A recommendation should identify the evidence, affected prompt group, proposed change, owner, and method for evaluating the result later.
Price the full workflow. Add platform fees, overages, setup, analyst time, content or technical implementation, outreach, and any separate PR or review work.
Confirm data control. Obtain the retention, export, cancellation, and post-termination access terms in writing before committing.
If a pilot is available, judge it on traceability rather than a dramatic score change. You should be able to move from an executive chart to a collected answer, from that answer to its citations, and from the gap to an assigned action. A platform that cannot preserve that chain will make it difficult to defend spending or learn from changes.
Key takeaways
Buy measurement software when you need visibility into prompts, mentions, recommendations, citations, and competitors. Buy services when you need someone to change the conditions producing those results.
Compare quotes using the same prompt, engine, market, language, refresh, history, entity, and user requirements. Headline monthly prices are not comparable without those units.
Demand raw, timestamped answer and citation evidence. A single visibility score cannot tell you whether the brand was merely mentioned, actively recommended, or cited.
Calculate total operating cost, including internal analysis and execution. The subscription fee is only one part of the budget.
Choose a lower service tier when your team already has authority and implementation capacity. Choose managed execution when content, third-party lists, reviews, PR, or ownership are the real constraints.
Do not reward data volume for its own sake. The best plan is the smallest one that reliably supports decisions your team is prepared to execute.
Take your real prompt inventory and the normalization table into the next vendor call. Reject any proposal that cannot define its billing unit, expose the evidence behind its metrics, and name who owns the work after a gap is found. That will narrow the field faster than another feature comparison and leave you with a GEO budget tied to action rather than dashboard access.
