In today’s SEO landscape, it’s about creating content that captivates, builds trust, and converts. I’ve discovered storytelling plays a crucial role in this process.
By incorporating storytelling effectively, I can enhance engagement, improve relevance, and transform traffic into actionable results. Here are seven storytelling techniques I’ve found invaluable for my business blogs.
7 Storytelling Techniques for Boosting Engagement and Conversions
I use these strategies to craft my content’s flow, from the initial hook to the compelling call to action at the end.
1. Hook the Reader
T.S. Eliot wisely said, “If you start with a bang, you won’t end with a whimper.” In my blogging, beginning with an engaging entry point keeps readers invested. For B2B or B2C blogs, it’s crucial to hook the reader effectively.
Here are techniques I use to captivate my audience right away:
Challenge a belief: Start by questioning established norms.
Weave a narrative: A story doesn’t need to start with “Once upon a time.”
Cite a statistic: Numbers, like “Google owns 89.9% of the search market,” can be compelling.
Make a promise: Offer enticing outcomes, such as blogs that drive traffic and conversions.
Empathize: Understand and relate to the reader’s struggles to draw them in.
Quote: Use a powerful quote that aligns with your message.
Combining these methods has helped me set the stage effectively. A reader’s issue paired with a success story often lends itself well to both B2B and B2C blogging.
2. Make Promises and Deliver on Them
I love stories with foreshadowing that hint at what’s to come. In my blogs, I use phrases like “You will learn…” to tantalize and keep interest alive.
This strategy also strengthens SEO. When I introduce keywords with promises about the content, it often boosts my click-through rate, as Google sometimes uses these excerpts.
Getting potential customers to visualize using my products is key. Instead of heavy-handed sales pitches, I rely on vivid storytelling to illustrate problems and solutions, guiding them through their buying journey.
6. Consider a Three-Act Structure
Jessica Brody says Act 2 contrasts Act 1. I introduce an approach, reveal its flaws, and provide a viable solution, crafting a compelling narrative that leads to success stories.
In the drafting process, I’m all about getting the ideas down. Editing refines that initial mess into a narrative that resonates deeply with my audience, choosing the perfect hooks and calls to action.
These techniques have not only polished my storytelling but also significantly boosted reader engagement and business conversions.
Content Quality Shows Its Worth in Performance
I’ve observed that quality content makes a difference in performance metrics. As I experiment with storytelling, I closely track these key performance indicators:
Organic traffic
Keyword rankings
Click-through rate (CTR)
Time on page
Conversions
Google Search Console and Google Analytics are invaluable tools that provide data to evaluate my efforts. With continuous improvement, I not only craft better stories but also drive tangible business results.
I’m excited to share that I can now effortlessly integrate Google Search Console data directly into any of my Profound Agents. This powerful combination, uniting Search Console insights with Profound’s answer engine data, is transforming how I handle reporting, content creation, monitoring, and optimization.
Staying on the Profound platform makes the entire process seamless, allowing me to focus on what truly matters—building and optimizing my digital strategies without the hassle of platform switching.
When I first heard about Walmart’s experiment with ChatGPT’s Instant Checkout, I was intrigued. But after testing 200,000 items, Walmart discovered that conversions through this method were three times lower compared to their website.
Why This Matters: This experiment highlights an important point: traditional shopping environments still hold the crown when it comes to conversions. Even in a world dominated by AI, guiding users to owned environments proves more effective.
The Experiment Details: Starting last November, Walmart introduced around 200,000 products available for purchase directly inside ChatGPT through OpenAI’s Instant Checkout. The goal was to let users buy items without ever leaving ChatGPT.
Daniel Danker, Walmart’s EVP of Product and Design, revealed that these purchases had a conversion rate one-third lower than similar transactions on their website. He described the experience as “unsatisfying,” which prompted Walmart to reconsider their approach.
Farewell to Instant Checkout: Originally, Instant Checkout aimed to complete transactions within ChatGPT. However, OpenAI recently confirmed plans to phase it out, leaning towards merchant-handled app checkouts.
Changes on the Horizon: Walmart plans to integrate its own chatbot, Sparky, within ChatGPT. This will allow users to log into Walmart’s system, sync their carts across platforms, and finalize purchases seamlessly.
A similar integration with Google Gemini is expected next month, broadening Walmart’s technological reach.
The WIRED Report: For those interested in the comprehensive story, WIRED provides further insights into how Walmart and OpenAI are revolutionizing agentic shopping (subscription required).
If you run ecommerce SEO, product feeds, or shopping infrastructure, your next visibility problem may not begin on a search results page. It may begin when an AI shopping agent tries to identify the right variant, confirm that it is available, calculate the correct price, and place it in a working basket.
Google’s Universal Commerce Protocol, or UCP, is intended to connect those steps. Your practical task is to make product and customer data usable across discovery, selection, and checkout without assuming that protocol adoption will automatically produce rankings, recommendations, or sales.
UCP moves product visibility closer to the transaction
That does not make product pages irrelevant. It changes where accuracy has to survive. A persuasive description cannot compensate for an unavailable variant. Valid page markup cannot repair a cart that calculates the wrong price. A feed can expose a product, but the transaction can still fail if customer benefits disappear after identity linking.
This gives you four connected layers to manage:
Page content and structured data explain the product in a crawlable, understandable form.
Catalog data supplies current commercial facts such as price, inventory, and available variants.
Cart logic turns selected items into a valid basket.
Identity and account logic determine whether the shopper receives eligible benefits.
Keep these layers aligned, but do not treat them as interchangeable. UCP is not merely another name for JSON-LD, a product feed, or an ad format. It reaches into live commerce functions that page-level optimization alone cannot perform.
Google has said it plans to use UCP capabilities in AI-enhanced experiences across Search and the Gemini app. That establishes a direction, not a promise that every retailer, market, capability, or product will receive the same access or exposure. Build readiness around documented availability and your own eligibility rather than an assumed rollout.
Map each UCP capability to a real retail responsibility
The useful way to evaluate UCP is capability by capability. Each one touches a different system, failure mode, and internal owner.
Capability
What it enables
What you should verify
Likely owner
Catalog
Access to current product information, including pricing, inventory, and variants
Stable identifiers, variant mapping, update freshness, and agreement between catalog, product page, and checkout
Merchandising, feed operations, or commerce platform team
Cart
Multiple products from one retailer can be assembled into one basket
Add, update, remove, reprice, and out-of-stock behavior across a multi-item order
Ecommerce engineering
Identity linking
Eligible benefits such as member pricing and free shipping can continue across connected experiences
Authentication, consent, entitlement rules, session handling, and safe failure behavior
Identity, security, loyalty, and legal or privacy teams
Modular adoption
A retailer or platform can adopt selected capabilities instead of implementing everything at once
A rollout sequence tied to system readiness and a clear dependency map
Commerce product owner or program lead
The capability names do not answer every implementation question. For example, knowing that an agent can create a cart does not by itself define how your taxes, promotions, substitutions, shipping restrictions, or returns work. Treat those as test cases that need authoritative documentation and validation in your own stack. Do not invent behavior from the protocol’s high-level description.
Modularity is especially important for planning. You do not need to frame UCP as an all-or-nothing rebuild. If your identity system is not ready, that does not erase the value of repairing catalog inconsistencies. If your catalog cannot reliably distinguish variants, however, adding an agent-facing cart simply moves bad data closer to checkout.
Audit product data as if it were the storefront
An agent cannot walk a virtual aisle and infer that a stale price is probably wrong. It receives representations of your inventory and has to make decisions from them. Because the catalog capability is designed to expose real-time pricing, inventory, and variant information, conflicting product facts become a commercial problem, not merely a feed-cleanup task.
Start with one product family that has meaningful variation. A product with size, color, configuration, or member pricing will reveal more than a simple item with one price and one stock state. Trace it through every system an agent-assisted purchase could touch.
Resolve the identity chain. Confirm that the parent product, each purchasable variant, the catalog record, the product page, and the cart line resolve to the intended item. A parent identifier should not silently stand in for a specific variant at purchase time.
Name the source of truth for each commercial fact. Decide which system owns price, sale price, inventory, variant attributes, and account benefits. If two systems can overwrite the same fact, document precedence and failure handling.
Compare anonymous and authenticated states. Check whether public pricing, member pricing, shipping benefits, and eligibility rules remain distinguishable. The agent should not present a conditional benefit as universal.
Test change propagation. Change a price or inventory state in the owning system and observe every downstream representation. Record your actual delay and failure points rather than relying on the intended architecture.
Inspect contradictions. Compare the catalog, rendered product page, structured data, basket, and logged-in experience. Any disagreement can lead to a poor recommendation, a rejected add-to-cart action, or an unpleasant price change at checkout.
Log failed and stale updates. A synchronization process that usually works is not enough. Your team needs a way to identify which products failed, when the last successful update occurred, and which downstream surfaces may still carry old information.
This is also where SEO, GEO, and feed teams should coordinate. Keep descriptive content and structured data consistent with commercial systems, but do not add unsupported claims to markup merely to make the product look more complete to an AI system. The safest machine-readable answer is the same answer the shopper will receive in the cart.
Do not call the audit complete because a sample record validates syntactically. A valid record can still identify the wrong variant, carry an old price, or point to inventory that cannot be purchased. Validation checks form; transaction tests check truth.
Roll out the smallest capability you can verify end to end
Catalog readiness is usually the sensible first workstream because cart and identity experiences depend on accurate merchandise data. That is a sequencing recommendation, not a protocol requirement. Your architecture may justify a different order, but every pilot should have one defined capability, one accountable owner, and an observable pass or fail condition.
Choose a bounded product set. Select products that expose the problems you need to solve, including variants or conditional benefits, while keeping the pilot small enough to inspect manually.
Capture a baseline. Record current catalog mismatches, failed add-to-cart actions, unavailable variants presented as purchasable, and benefit-entitlement failures. Without a baseline, protocol activity can look like progress while customer-facing accuracy remains unchanged.
Define acceptance tests before integration. Write expected results for price changes, inventory changes, variant selection, multi-item baskets, account linking, and entitlement loss. Include negative cases, not just a successful purchase.
Test the cart as a changing object. The new cart capability is intended to let agents place multiple products from one retailer into a single basket. Verify what happens when quantity changes, one line becomes unavailable, a promotion expires, or the shopper switches variants.
Isolate identity testing. Identity linking can preserve member pricing and free shipping, but it also touches account access and personal data. Use controlled test accounts and obtain security, privacy, and legal approval before exposing real customer identities. The specific downside of rushing this step is not just a broken discount; it can be unauthorized account access or inappropriate data sharing.
Monitor outcomes by failure stage. Separate catalog retrieval, variant resolution, cart creation, cart mutation, authentication, entitlement, and checkout failures. A single conversion total will not tell you which capability needs repair.
Your ownership model matters as much as the integration. Feed operations can correct a variant mapping but should not define authentication policy. SEO can identify contradictions visible to search systems but should not own checkout integrity. Ecommerce engineering can make a cart function without knowing whether member benefits are represented correctly. Put these teams behind one shared test plan rather than handing UCP to whichever team first notices it.
Google has also indicated that it plans to simplify UCP onboarding through Merchant Center. Use that as a reason to prepare your data and test cases, not as a reason to assume that implementation is already automatic. When onboarding becomes available to you, confirm supported capabilities, required fields, market coverage, permissions, and reporting from the documentation presented in your account.
Most importantly, do not report UCP adoption as an SEO win by itself. There is no basis here for calling it a guaranteed ranking factor or recommendation boost. Measure what you can actually observe: eligibility, accurate product representation, successful basket creation, preserved benefits, completed purchases, and the failure rate at each handoff.
Key takeaways
UCP connects product discovery with live commerce functions; it is broader than page markup, feeds, or advertising alone.
Catalog accuracy is foundational because price, inventory, and variant errors can follow an agent directly into the cart.
Cart, catalog, and identity linking should be treated as separate capabilities with separate owners and tests.
Modular adoption lets you start with a bounded capability instead of waiting for a complete commerce-stack rebuild.
Identity linking requires controlled testing and security, privacy, and legal review before real customer accounts are involved.
Protocol adoption does not establish a ranking or recommendation benefit. Evaluate transactional accuracy and measurable outcomes.
Your best next step is concrete: take one high-value product family with variants, compare its catalog record, product page, structured data, cart, and logged-in benefits, then document every contradiction. That exercise will tell you whether your first UCP project is an integration project or, more likely, a product-data repair project that needs to happen before integration can deliver anything useful.
When Microsoft Advertising presents Maximize Conversions or Maximize Conversion Value instead of a standalone Target CPA or Target ROAS strategy, you have not lost those performance controls. Microsoft has moved them inside two broader automated bidding choices.
Your real decision is now clearer: decide whether the campaign should produce more completed actions or more reported conversion value, then add a CPA or ROAS target only if you can defend it with reliable tracking and business economics.
Microsoft changed the setup path, not the performance target
The simplified setup organizes automated bidding around two main strategy families with optional targets. Maximize Conversions can include a target CPA. Maximize Conversion Value can include a target ROAS.
Your campaign objective
Main bidding strategy
Optional performance target
Signal that must be trustworthy
Generate more completed conversion actions
Maximize Conversions
Target CPA
Which actions count as conversions
Generate more reported conversion value
Maximize Conversion Value
Target ROAS
The value assigned or passed with each conversion
Microsoft says this restructuring does not change the fundamental bidding behavior. Treat that as a description of the product change, not as a promise that every campaign will produce identical results. Auction conditions, tracking quality, budgets, and the business value of the conversions still matter.
You also do not need to rebuild existing campaigns that use Target CPA or Target ROAS. They can continue as configured. Portfolio bid strategies are outside this change, so keep them separate when you document or audit the transition.
Choose between conversion count and conversion value first
Do not begin with the target field. Begin with the outcome the business wants the bidding system to prioritize.
Choose Maximize Conversions when the counted actions are reasonably comparable. That can fit a campaign built around one qualified lead action, one appointment type, or one product category with similar economics. The important condition is not the name of the conversion. It is whether an additional counted action has roughly the same business meaning as the next one.
Choose Maximize Conversion Value when one conversion can be materially more valuable than another and Microsoft receives values that represent that difference. A campaign cannot optimize sensibly for value if every conversion receives the same placeholder number or if the values measure revenue while the business actually manages toward margin.
Use Maximize Conversions when your primary question is: How many valid actions can this budget produce?
Use Maximize Conversion Value when your primary question is: How much meaningful value can this budget produce?
Fix measurement before choosing either one when duplicate conversions, low-intent actions, missing values, or inconsistent value rules distort the signal.
ROAS may sound like the more financially sophisticated choice, but it is only as useful as the conversion values behind it. If those values do not reflect business priorities, Maximize Conversion Value can optimize a clean-looking metric that leads you in the wrong direction.
Add a CPA or ROAS target only when the number is defensible
The optional target is a control layered onto the main strategy. Target CPA expresses the average cost per conversion you want the campaign to pursue. Target ROAS expresses the relationship you want between reported conversion value and advertising spend. Neither target repairs weak tracking, and neither should be treated as a guaranteed result.
Connect the target to unit economics. A CPA target should reflect what the business can afford for the specific conversion being counted. A ROAS target should reflect how reported conversion value relates to the economic result the business actually needs.
Check that the target matches the strategy. Do not manage a value-based campaign against CPA simply because CPA is familiar. Do not impose ROAS on a campaign whose conversions lack meaningful value differences.
Inspect the measurement inputs. Confirm that the campaign counts the intended actions, excludes accidental or irrelevant actions, and uses consistent value rules.
Separate a real constraint from a preferred outcome. If exceeding a certain acquisition cost makes the campaign uneconomic, record that explicitly. If the number is merely an aspiration, do not present it internally as a hard financial limit.
Leave the target unset until you can justify it. The target is optional. An invented number creates the appearance of control without a sound business instruction behind it.
This is where many setup mistakes begin. An advertiser copies a target from another campaign, another market, or an old reporting period without checking whether the conversion definition and economics are comparable. The setting is precise, but the reasoning is not.
Audit the inputs before changing campaign settings
The interface change is a good reason to standardize how your team approves automated bidding. Use the same short audit for a new campaign and for any existing campaign you are considering changing.
Write the primary objective in one sentence. State whether the campaign should maximize the number of valid actions or their reported value.
Name the conversion actions included in bidding. If a low-intent event and a completed sale both count, decide whether maximizing their combined count represents the outcome you want.
Test the meaning of conversion values. Ask what each value represents, where it originates, and whether two different values genuinely indicate different business importance.
Map the objective to the strategy. Count maps to Maximize Conversions; value maps to Maximize Conversion Value.
Add the matching target only if approved. CPA belongs with Maximize Conversions. ROAS belongs with Maximize Conversion Value.
Label existing and portfolio strategies correctly. Existing Target CPA and Target ROAS campaigns do not require migration, while portfolio strategies are unaffected.
Evaluate the metric the strategy is designed to optimize. Review conversion quality alongside CPA, or the integrity of reported value alongside ROAS. A favorable platform metric is not enough if the underlying business outcome deteriorates.
Avoid changing strategy, target, conversion definitions, and value rules at the same time unless a measurement error makes an immediate correction necessary. Multiple simultaneous changes make it harder to identify which decision altered the result and can expose more budget to a poorly understood setup.
Key takeaways
Microsoft Advertising now centers setup on Maximize Conversions and Maximize Conversion Value.
Target CPA remains available as an optional control within Maximize Conversions.
Target ROAS remains available as an optional control within Maximize Conversion Value.
Existing Target CPA and Target ROAS campaigns can continue without required changes.
Portfolio bid strategies are unaffected.
Your most important choice is whether reliable conversion counts or reliable conversion values better represent the business objective.
Before your next setup, add four fields to the campaign brief: primary outcome, bidding strategy, optional target, and measurement owner. If the team cannot complete all four with a clear rationale, resolve the tracking or economics question before handing more control to automation.
You can no longer judge a page only by whether it earns a traditional search listing. The same page may need to attract that listing, supply a direct answer, support a broader synthesis, and give a browser assistant enough clarity to help someone finish a task.
If you are deciding what to fix first, do not start with AI-only copy tactics. Map the user’s task to the search experience likely to handle it, then make the underlying facts crawlable, consistent, extractable, and usable.
The browser now routes tasks, not just queries
The familiar model of search assumes a short sequence: someone enters a query, chooses a result, and visits a page. An assistant-led browser can keep that route, replace part of it with an answer, or continue beyond the page into research and task completion.
Classify each important page by the outcome its visitor needs:
Reach a destination: The user wants a site, location, product page, service page, or other known endpoint. Traditional search visibility and accurate navigational information remain central.
Resolve a focused question: The user needs a concise fact, definition, requirement, or procedure. Build a direct-answer module for AEO.
Understand a complicated decision: The user needs relationships, conditions, alternatives, or consequences explained together. Build enough connected material for GEO.
Complete an action: The user needs to submit, book, contact, select, or prepare something. The page and its interface must remain understandable to both the person and an assisting system.
Do not assign a page to a category based only on keyword length. A short query can conceal a complicated decision, while a long query can still point to a specific destination. Write down the intended outcome, the facts required to reach it, and the step that should follow. Those three notes will tell you more than a generic label such as informational or transactional.
Key takeaways
Plan for a hybrid search environment. Traditional results, direct answers, synthesized responses, and assistant-led actions can all matter within one journey.
Technical SEO, stable entity information, and verifiable facts are shared infrastructure. They are not optional work that begins only after an AI strategy is complete.
AEO and GEO solve different retrieval problems: AEO makes a focused answer easy to extract, while GEO makes relationships and context easy to synthesize.
Browser readiness extends beyond prose. Navigation, instructions, forms, labels, and completion states must be unambiguous.
Fix inaccessible pages, conflicting facts, and unclear task paths before expanding content. More copy cannot repair an unreliable foundation.
Build the fact layer before optimizing the answer
AI search did not appear without a technical lineage. Many mechanisms associated with modern search can be traced to patent blueprints filed between 2007 and 2016, including work concerned with entities and verification. The practical lesson is not that you need to read every patent. It is that durable search work still depends on machine-accessible information, recognizable entities, consistent relationships, and evidence.
Create a single operational fact set
Before rewriting pages, establish the facts every surface should agree on. For a business, product, service, or named expert, that set may include the canonical name, description, role, location, availability conditions, defining attributes, and relationships to other entities. Include only facts you can maintain.
Then compare that set with the visible page, title and headings, internal links, structured data, profile pages, and any local or commercial landing pages you control. A disagreement is more important than a missing adjective. If one template calls an offering a product, another calls it a service, and the schema describes something else, a machine has to reconcile a conflict you created.
Check the four controls every page depends on
Discovery: Confirm that the page can be reached through ordinary links and that its important content is available to the systems you expect to retrieve it. An orphaned or inaccessible answer is not an AI optimization opportunity.
Identity: Name the main entity consistently. Use clear relationships between the organization, people, products, services, locations, and topics represented on the page.
Information structure: Give each section a descriptive heading, place the answer near the question it resolves, and keep qualifications beside the claim they modify.
Evidence: Connect important claims to specific, trustworthy support. A link should help verify the claim beside it, not merely point to a generic homepage.
Apply the same controls whether the site uses a traditional CMS or a headless architecture. A headless frontend can still hide essential content from retrieval, and a conventional CMS can still generate contradictory templates. Architecture changes where you inspect the problem; it does not remove the problem.
JSON-LD belongs in this fact layer. Use it to express the same entities and relationships that a visitor can verify on the page. Do not use structured data as a second, invisible version of the business. Schema cannot make conflicting visible content trustworthy, and it should not introduce claims the page itself does not support.
Your SEO program can look healthy right up until a key specialist takes leave, a regional team publishes outside the normal process, or a platform release bypasses SEO review. If approvals, standards, and quality checks live in one person’s memory, the program’s apparent maturity is borrowed from that person.
The practical goal of SEO governance is to make good decisions repeatable. You need clear decision rights, standards that appear where work happens, evidence that controls are being used, and enough shared capability for the system to keep working through ordinary organizational change.
Maturity begins where the expert stops
A technical SEO audit asks what is wrong with a website. A governance maturity assessment asks why the organization produced that condition, whether it can prevent a recurrence, and who is accountable for doing so.
That distinction matters because execution and maturity are not the same thing. A team can run sophisticated crawls, write detailed recommendations, and resolve difficult indexing problems while remaining organizationally fragile. The stronger test is whether the capability survives when the usual expert is away, promoted, or gone.
You can expose that fragility without launching a large transformation project. Choose one recently completed change that could affect search visibility. Trace it from request to release:
Who decided that the change should happen?
Who had authority to approve or reject it?
What documented standard governed the decision?
Where was SEO quality checked?
What evidence shows that the check occurred?
Who would have performed each step if the usual specialist had been unavailable?
Who owned the response if the release produced an unexpected result?
If the path breaks when one named person is removed, you have found a single point of failure. That person may be highly capable and generous with their time. The problem is still structural. Access to their memory is not an organizational control.
Watch for softer versions of the same problem. A manager may know that an SEO process exists but not who owns it. A standard may live in a slide deck that delivery teams never open. Quality assurance may happen, but leave no record. A specialist may repeatedly correct the same defect because the publishing or release workflow never changed. Each condition tells you that expertise has not yet become shared capability.
Maturity does not mean eliminating experts. It means using their expertise to design standards, controls, training, and escalation paths that other people can follow. The expert should handle genuinely difficult judgment calls, not serve as the organization’s only memory of how routine work gets done.
Define governance domains around your failure paths
There is no useful universal list of SEO governance domains. Your domains should match the ways your organization makes changes and the places where visibility can be damaged. A business with one editorial site has a different governance surface from a marketplace, an international company, or a brand with hundreds of locations.
Start by mapping the operating areas that can independently create, alter, consolidate, or remove search-facing assets. Common domains include:
Content governance: topic ownership, briefing, approval, duplication, updating, consolidation, retirement, and the relationship between editorial and commercial pages.
Structured data governance: eligible page types, required properties, factual approval, implementation ownership, validation, and maintenance when templates change.
Local visibility governance: location-page ownership, business information, local contributions, shared templates, and the boundary between central and regional publishing.
Measurement governance: metric definitions, reporting ownership, annotations, access, data-quality checks, and escalation when tracking changes.
AI visibility and answer governance: ownership of entity facts, answer-oriented content, citations, structured information, and claims that require specialist approval.
Do not include a domain merely because it appears on someone else’s checklist. Include it when a team in your organization can make decisions in that area, when the area has distinct owners or workflows, or when failure there needs a specific control.
Multi-location SEO shows why the boundary matters. If central marketing, regional teams, and individual locations can all publish for the same demand without agreed page ownership, the organization can create internal competition between its own pages. An optimization tool can identify overlap, but it cannot decide which organizational layer owns a topic or which team has final publishing authority.
For a multi-location domain, settle those governance questions before debating individual keywords:
Which needs belong on national, regional, or location-specific pages?
Who decides the intended page when multiple teams want to target the same need?
Which facts must remain consistent across every location?
Which sections require genuinely local input?
Who can create a new location page or change its purpose?
What review is required before a shared template is changed?
Who resolves an overlap between pages owned by different teams?
Create a short governance card for each domain. Record its purpose, decisions in scope, accountable role, participating teams, controlling standards, quality checks, exception path, backup owner, and evidence location. A domain that cannot be described this way is not ready to be scored.
Give every material SEO decision an owner and a control
The person completing a task is not automatically the person who owns the decision. A developer may implement a directive, an editor may change a page, and a regional marketer may submit local information. Governance identifies who has the authority and accountability to decide what should happen.
Name roles rather than individuals wherever possible. “Content operations lead” remains meaningful when employees change; a person’s name does not. Then name a backup role with the access and training needed to act. Listing a backup who cannot reach the system, interpret the standard, or approve an exception creates the appearance of resilience without the capability.
Governance element
Question it must settle
Acceptable evidence
Scope
Which changes and assets are governed?
A domain definition linked from the relevant workflow
Authority
Who can approve, reject, or escalate a decision?
A named accountable role and an enabled backup role
Standard
What does acceptable work require?
A versioned, testable rule available at the point of work
Quality assurance
How is compliance verified before or after release?
A completed check, test result, or review record
Exception
Who can permit a departure, and for how long?
An approval with rationale, owner, review condition, and expiry or closure
Continuity
Can the capability operate without its usual owner?
Access, training, documentation, and a completed handoff or coverage test
A policy that says “follow SEO best practices” does not provide a usable standard. A working standard states what triggers it, what must happen, who verifies the result, what evidence must be retained, and how an exception is handled. It should be specific enough that two qualified people can reach a consistent decision without reconstructing the original author’s intent.
Put the control where the risk enters the system. If a content requirement matters during briefing, add it to the brief rather than relying on a final audit. If a template change requires SEO review, make that review part of the release workflow. If local teams need approval before creating a new page, put the approval in the request path. A document stored elsewhere may support the control, but it does not replace the trigger.
Use the lightest control that fits the possible impact. A small edit to one page may need only the page owner’s review. A template change that affects every location needs clearer approval, recorded quality assurance, an accountable release owner, and a response path if the outcome is wrong. Governance becomes bureaucracy when every change receives the same treatment; it becomes useful when scrutiny rises with the reach and reversibility of the decision.
Score evidence, not confidence
A maturity assessment is not a survey of how professional the SEO team feels. It tests whether governance is understood, documented, used, and resilient. Ask managers and senior leaders questions they should be able to answer about ownership and accountability. Ask practitioners for the standards, workflow records, and quality evidence that show what happens in practice.
Collect initial answers separately. If everyone aligns in a workshop before answering, the specialist can unknowingly supply the missing knowledge for the group. The gap you need to see is whether responsible leaders already know the operating model.
Use the same core questions for every domain:
Which role is accountable for this domain?
Which events trigger its review or approval process?
Where is the current standard, and who maintains it?
How is an exception approved and revisited?
What is the most recent evidence that the control was used?
Who covers the accountable role when its usual owner is unavailable?
How are affected teams trained when the standard changes?
How does a repeated defect become a workflow or control improvement?
An answer such as “the SEO lead handles that” identifies a dependency, not ownership. “I would need to ask our specialist” is also a result. It shows that the knowledge has not been institutionalized at the level where accountability is supposed to sit.
You can use this simple internal scale to make the findings comparable over time. It is a working rubric, not a universal industry standard.
Score
Maturity state
What must be true
0
Person-dependent
Ownership or standards are unclear, and correct execution relies mainly on individual memory.
1
Documented
An owner and standard exist, but adoption is inconsistent or evidence of use is missing.
2
Operational
The workflow triggers the control, quality evidence is retained, and exceptions follow a defined path.
3
Resilient
Enabled backup ownership, maintained training, and demonstrated continuity allow the capability to operate through absence or role change.
Require evidence before assigning a score. A confident verbal answer is weaker than a current standard. A current standard is weaker than a completed workflow record. A completed record still does not prove continuity unless another enabled person can operate the process.
Keep the domain scores and the underlying findings visible. A single enterprise average can hide a critical zero in migration governance, local publishing, or another high-impact domain. Record single points of failure separately so that a reasonable average does not make them disappear.
A maturity score has little value if it ends as a presentation. Convert each important gap into an operating change with an owner and observable completion criteria.
Prioritize the remediation in this order:
Remove dangerous single points of failure. Start where one unavailable person can block a release, permit an uncontrolled change, or leave a widespread problem without an owner.
Control changes with the widest reach. Shared templates, platform rules, migrations, and multi-location publishing deserve attention before isolated low-impact edits.
Fix recurring failure paths. When the same defect returns, stop treating each instance as a new task. Change the brief, ticket, CMS workflow, release check, or training that keeps allowing it.
Move standards to the point of work. Link requirements from the systems where people request, create, approve, and release changes.
Enable and test backup ownership. Give the backup role access, context, and decision authority, then use a planned handoff or coverage period to expose missing knowledge.
Reassess with the same evidence rules. Raise a score only when the control is being used and continuity is demonstrated, not merely because a document was created.
Write remediation items as capability outcomes. “Create SEO documentation” is an activity with no clear finish line. “A trained backup can approve a location-page request using the current standard, and the workflow retains the approval record” describes a capability you can verify.
Every completed governance improvement should leave behind six things: an accountable role, an enabled backup, a usable standard, a workflow trigger, quality evidence, and an exception path. If one is missing, record the remaining dependency instead of declaring the domain mature.
Key takeaways
SEO maturity is the organization’s ability to preserve good decisions through routine change, not the sophistication of one expert’s work.
Score ownership, standards, adoption, evidence, and continuity separately from technical execution.
Define governance domains around your business model and actual failure paths rather than copying a universal checklist.
Treat dependence on a named person as a single point of failure, even when that person is highly capable.
Place controls inside briefs, tickets, publishing workflows, and release processes so that standards appear when decisions are made.
Use maturity scores as an internal baseline over time, not as a competitive benchmark.
Start with one failure-prone domain and trace one recent change from request to release. Name the first point where the process depends on memory, then replace that dependency with an owner, a standard, a control, and a working backup. That is the smallest useful unit of SEO maturity.
As I explore the ever-evolving landscape of Google’s AI Mode, it’s fascinating to witness how ad formats, reporting, and control are taking shape. Google seems to have a master plan in place that competitors just can’t keep up with.
I find myself intrigued by Google’s entry into this next phase of conversational search. It’s not just about user numbers but who can effectively monetize them. Google’s mature ad systems and extensive advertiser base offer a significant edge.
The initial panic surrounding Google’s position is over. Google’s long-standing advantages and huge investments have leveled the playing field with ChatGPT in LLM search.
Back in December 2025, when Google declared code red, it became clear that they were serious. Apple’s decision to partner with Google for its AI needs is indeed telling.
Initially, it seemed plausible that Google would struggle against ChatGPT, but the market has since adjusted its views. The company’s valuation reflects renewed confidence, rivaling even Apple at a substantial $3.6 trillion.
As I dive deeper into how monetization will shape this race, I’m struck by how Google’s recent advances have significantly boosted its valuation.
It’s clear that the visibility of financial projections plays a massive role in how the company is perceived financially. Google’s approach to shifts in user behavior is crucial in maintaining its robust business model.
From my perspective, much of your digital advertising budget likely goes to Google. Its prominence demands attention, not just in search but also in emerging AI platforms like ChatGPT and Claude.
The competition in LLM conversations is intriguing. Google and ChatGPT are vying for different monetization models, a fascinating case study of differing strategies.
For those of us in advertising, it’s essential to monitor developments like ad formats, rollout pace, and public reception to ads within these platforms.
OpenAI’s current monetization model is intriguing but still nascent, reliant on a small group of major advertisers. We’ll see how they expand and fine-tune this model over time.
Outsourcing inventory to programmatic partners is a smart move for OpenAI but highlights their early stage in building an ads business.
For Google advertisers, the shift to AI Mode need not be alarming. I’m watching for the ways these LLM sessions are shaping user experiences and ad placements.
One thing is for sure; the enhancements in AI Mode continue, promising more seamless and user-friendly interactions. The potential for ads remains, though their form is still evolving.
Monitoring key areas like the extent of monetization, advertiser control, and campaign types becomes more important as we navigate this new landscape.
Ultimately, the future of advertising in AI-driven search is one of adaptability and strategic planning, aligning closely with user and advertiser behaviors in this exciting yet challenging era.
As I look back on 2025, it’s astonishing to see the AI search traffic growth leap by an impressive 180% year-over-year. I’m diving into the data to better understand how this impacts our visibility strategies. We’ll explore insights on ChatGPT, Gemini, Perplexity, and Claude usage trends in this review.
With AI technologies rapidly advancing, I’ve noticed how they continue to reshape how we think about search and brand visibility. The increased use of AI-powered tools signifies a pivotal shift in the way we approach digital marketing strategies.
In 2025, ChatGPT saw a remarkable surge in use, closely followed by interest in platforms like Gemini and Claude. This data is crucial as we plan for future visibility tactics, ensuring that our brand remains competitive in an ever-evolving digital landscape.
How does this data affect your brand’s approach? I believe understanding and leveraging these trends will be key to optimizing AI-driven search capabilities and visibility while crafting more personalized and effective content strategies.
You are not simply hiring a senior marketer. You are choosing the person who may set your agency’s growth strategy, protect its creative culture, retain important clients, and decide how the business adapts when its current model stops working.
That makes the search partner consequential. The right executive search firm will sharpen an unclear mandate, reach leaders who are not actively applying, and test candidates against the realities of agency leadership. The wrong one can produce an impressive slate that solves a different problem from the one you actually have.
Define the leadership mandate before comparing firms
It is tempting to begin with firm names, presentations, and fee proposals. Begin with the business decision instead. Until you can explain why the agency needs this executive, you cannot tell whether a search firm understands the assignment.
A marketing agency leader usually has a dual mandate. The person must improve commercial performance without damaging the creative, technical, or client-service capabilities that make the agency valuable. A candidate who knows growth but treats culture as decoration can lose the people clients came to work with. A respected creative leader who cannot manage delivery or profitability may preserve the work while weakening the business.
Turn the job description into a one-page search brief
Your brief should answer five questions:
What triggered the search? Name the actual event: succession, stalled growth, new ownership, a changing service mix, international expansion, operational strain, or a broader transformation.
What must be different after the hire? Write three to five observable outcomes. Examples include a clearer growth model, stronger new-business leadership, better integration between creative and performance teams, more disciplined operations, or a credible succession bench.
What authority will the executive have? State the reporting line, decision rights, budget control, ownership expectations, and relationship with founders, investors, or a parent company.
Which agency context matters? Specify whether you operate primarily in creative, digital, performance marketing, public relations, consumer communications, CRM, or marketing technology. Include the ownership model and geographic scope.
What cannot be compromised? Separate genuine requirements from preferences. Client credibility, commercial judgment, transformation experience, technical depth, and creative leadership are not interchangeable.
Do not disguise a conflicted mandate with a broad title. If the founders want a CEO to professionalize the business but do not intend to transfer meaningful authority, the search problem is governance, not candidate supply. Resolve that before paying a firm to approach the market.
Give the firm enough economic context to assess fit
An agency-savvy recruiter should want to understand how the business earns money, where growth comes from, how work is delivered, what clients expect from senior leaders, and which capabilities are difficult to scale. That context changes the candidate profile.
For example, a growth mandate based on winning large accounts is different from one based on expanding CRM services inside existing relationships. A creative agency protecting a founder-led reputation needs a different successor from a performance agency integrating data, technology, and delivery operations.
Share sensitive financial or client information carefully. Use sanitized figures, ranges, and anonymized examples during initial discussions, then provide deeper access after confidentiality terms and the working team are clear. An executive search does not require you to expose every commercial detail to every firm that submits a proposal.
Match the search partner to the change you need
No firm is the universal choice for every agency role. Your first shortlist should reflect the ownership model, function, seniority, geography, and kind of change the new executive must lead.
Your situation
What the search partner must understand
Firms to investigate
Agency CEO, president, or VP search with a broad growth mandate
The tension between commercial growth, creative culture, client relationships, and agency operations
Talentfoot has an agency-focused C-suite and VP practice covering traditional and digital businesses.
Private equity-backed agency
Growth expectations, operational discipline, financial leadership, and the relationship between management and ownership
JM Search is particularly aligned with private equity-backed agencies and growth-oriented leadership mandates.
Marketing technology, CRM, or technically complex digital leadership
How technical operations connect with creative services, client delivery, and commercial strategy
Complex stakeholder environments and leadership across consumer-facing and communications businesses
Caldwell Partners has established consumer, media, and communications coverage.
Multinational agency or cross-border communications role
Geographic reach, local market credibility, and assessment across multiple regions
Odgers Berndtson is suited to global agency and communications searches.
Director-level creative or digital role where speed is central
Specialist talent networks and fast access to creative and digital candidates
Mondo is more naturally aligned with rapid creative and digital hiring at the director level than with a strategy-heavy C-suite search.
C-suite transformation
Leadership assessment, cultural alignment, and the executive’s ability to change the organization
N2Growth combines executive search with leadership consulting for transformation mandates.
Treat those alignments as routing signals, not automatic endorsements. A firm’s market reputation does not tell you which partner will lead your assignment, how much agency experience the researcher has, or whether recent placements resemble your mandate.
Push one level deeper when you make the shortlist. For a private equity-backed agency, ask for searches involving comparable ownership pressure and operating expectations. For a chief creative officer, ask how the firm distinguishes creative reputation from the ability to lead people, retain clients, and participate in commercial decisions. For a martech role, test whether the recruiter can discuss technical operations and agency delivery in the same conversation.
Global reach deserves the same scrutiny. A multinational logo and a long office list do not prove that the proposed team has access to the markets you need. Ask which offices will participate, who owns candidate communication, and how assessments will remain consistent across regions.
Use a 100-point scorecard to test the evidence
Presentations make most search firms sound experienced, connected, and consultative. A weighted scorecard forces you to compare evidence instead of adjectives. One practical 100-point model gives the greatest weight to agency leadership specialization and documented executive placements.
Criterion
Weight
Evidence to request
Marketing agency leadership specialization
25 points
Comparable CEO, president, chief creative officer, and other C-suite or VP mandates; relevant backgrounds of the proposed partner and researcher
Documented agency executive placements
20 points
Recent placements with the role, agency model, ownership context, location, and scope clearly identified; anonymized examples can be acceptable when confidentiality prevents naming the client
Agency function expertise
15 points
Evidence that the team understands growth, creative leadership, operations, client relationships, and agency profitability rather than marketing as a generic corporate function
Industry coverage and specialization
15 points
Relevant work across the agency types that matter to you, such as creative, digital, performance, public relations, CRM, martech, media, or communications
Review quality and volume
15 points
Recent review patterns, referenceable clients, and direct references for comparable assignments; distinguish client evidence from employee commentary
Visibility and relevant thinking
10 points
Useful material showing that the proposed team understands agency leadership issues; treat visibility as supporting evidence, not proof of placement performance
Have each decision-maker score the firms independently before the selection meeting. Give no points when the proposal merely repeats your brief. Give partial credit for plausible but unverified experience, and full credit only when the firm supplies specific, relevant evidence. Discuss the scoring differences before calculating a final total; disagreement often exposes an unresolved assumption about what the agency really needs.
Does success mean an accepted offer, a candidate who started, or a placement still in the role after a defined period?
Does the timeline begin when the contract is signed, when the brief is approved, or when outreach starts?
Does it end with the first slate, the accepted offer, or the executive’s start date?
Which roles, seniority levels, locations, and client types are included in the average?
How are cancelled searches, changed mandates, and replacement searches treated?
The same rule applies to methodology. AI-enabled sourcing and a HOGAN assessment may support a disciplined process, but neither tells you whether the firm has defined the right competencies or interpreted the assessment in the context of your agency. Ask what decision each tool informs, who interprets the result, and how it changes the candidate recommendation.
References should validate the team as well as the brand. Ask former clients whether the senior partner stayed involved, whether the initial slate matched the brief, how the firm handled difficult feedback, and whether it disclosed problems early. A polished launch followed by junior execution is a different service from a genuinely partner-led search.
Interview the firm and run the search with the same discipline
The finalist meeting should resemble a working session, not a credentials presentation. Give every firm the same one-page brief and ask it to show how it would execute the assignment.
Ask for a read-back of the mandate. The team should explain the business problem, the tradeoffs in the profile, and which requirement will be hardest to satisfy. If it simply repeats the job description, it has not added much value.
Request a sample market map. You do not need a free candidate list. You do need to see which kinds of organizations and leadership backgrounds the firm considers relevant, including adjacent talent pools you may have overlooked.
Examine two or more analogous searches. Ask what made each mandate comparable, where the search became difficult, what changed during the process, and who on the proposed team did the work.
Meet the operating team. Identify the partner, researcher, project lead, and candidate contact. Clarify their workload, responsibilities, and access to you after kickoff.
Inspect the assessment plan. Require a direct connection between every interview, assessment, and reference question and the competencies in your candidate scorecard.
Put commercial and process terms in writing. Confirm fees, expenses, payment events, off-limits restrictions, confidentiality, data handling, replacement provisions, anticipated timing, deliverables, and update cadence before authorizing outreach.
A vague off-limits answer deserves particular attention. Search firms may be unable to approach people at certain clients because of existing relationships. That constraint can materially change the available market. Ask for a clear explanation of how it affects your search before you sign, especially when your candidate universe is small.
Build the candidate scorecard before the first name arrives
The firm-selection scorecard tells you who should run the search. A separate candidate scorecard tells everyone what a successful executive looks like. Do not let an impressive biography become the standard after the process starts.
Choose competencies that follow directly from the mandate. A CEO or president scorecard may cover growth judgment, client leadership, operating command, culture, and the ability to build a leadership team. A chief creative officer scorecard should distinguish creative quality from talent leadership and commercial contribution. An operations or finance search should test the candidate’s command of delivery and profitability. A martech leader should be assessed across technical depth, service integration, and client-facing leadership.
Assign weights that total 100 and define what strong, acceptable, and weak evidence looks like for each competency. Interviewers should score candidates independently before discussing them. This keeps charisma, pedigree, or enthusiasm from quietly replacing the agreed mandate.
Require an evidence trail throughout the search
At kickoff, approve the final role narrative, candidate scorecard, market boundaries, and confidentiality rules. Before outreach, approve how the opportunity will be described. During the search, require a written update on outreach, responses, candidate status, recurring decline reasons, compensation or location friction, and any assumption the market is challenging.
Every candidate memo should map evidence to the scorecard, identify gaps, and explain why the firm recommends an interview. A biography is not an assessment. Claims such as “growth leader” or “strong cultural fit” should be supported by the situations the candidate handled, the decisions made, and the relevance to your mandate.
Use references to investigate the same competencies, including any concern that emerged in interviews. Generic questions tend to produce generic praise. Ask for a concrete example of how the candidate handled a comparable growth, client, creative, operational, or transformation problem.
If the slate remains weak, diagnose the cause before lowering standards. The obstacle may be compensation, location, authority, ownership dynamics, an unrealistic combination of requirements, or an unconvincing business story. Changing the specification without identifying the constraint merely makes the search less coherent.
Key takeaways
Define the business change, decision rights, agency context, and measurable outcomes before comparing executive search firms.
Match the partner to the mandate: private equity, martech, global communications, creative leadership, director-level hiring, and C-suite transformation require different strengths.
Use a 100-point firm scorecard weighted toward agency specialization and documented placements, then score finalists independently.
Do not accept success rates, timelines, technology, or assessment tools at face value. Ask what they measure, which searches they cover, and how they affect decisions.
Run the search against a separate candidate scorecard and require evidence at every stage, from the market map through references.
Your next move is simple: write the one-page mandate, invite two or three appropriately specialized firms to the same working session, and score the evidence. The safer choice is usually the team that makes your mandate more precise and proves it has solved a comparable leadership problem, not the one with the most polished credentials deck.
