I’m thrilled to share that Profound Agents can now seamlessly create presentations, documents, and webpages within Gamma as part of my automated workflows. No more hassle of exporting data and rebuilding it elsewhere. My Agent takes the outputs from upstream nodes and crafts them into ready-to-share assets in Gamma, streamlining the entire process.
Inspired by this post on Try Profound Blog.
Your organic clicks increased. Before you call that an SEO win, find out who was searching. If the increase came almost entirely from queries containing your brand, organic search may be capturing demand created by advertising, public relations, product activity, or existing customer awareness. If non-branded queries grew instead, you may be reaching people who were searching for a problem or category rather than for you.
Contextual SEO keeps those situations separate. The goal is not to find one universal definition of good performance. It is to identify what changed, for which queries and pages, under which conditions, and what you should do next.
A click has no strategic meaning by itself. A branded click to a login page, a non-branded click to a comparison page, and an image-search click to a product page all appear in organic performance data, but they represent different needs and different opportunities.
This is why a responsible SEO answer so often begins with "it depends". Dependence is not an excuse to avoid a recommendation. It tells you which conditions must be defined before the recommendation becomes useful.
For branded search measurement, define these layers before interpreting a trend:
Without those boundaries, a sitewide average can combine unrelated behavior. Branded queries commonly carry stronger navigational intent than broad category queries, so comparing their CTRs directly does not reveal which segment is better optimized. Each segment should be compared with its own history and with similar query-page cohorts.
Average position needs the same care. It is an average across the queries included in the view. A change can reflect different queries entering the mix, not just an existing set of pages moving up or down. Use it to locate a question, then inspect the contributing queries and pages before making a decision.
Google Search Console provides a native branded-queries filter in the Search results Performance report. It separates queries into branded and non-branded groups and applies the selected group to impressions, clicks, CTR, and average position. The filter works with Web, Image, Video, and News search types.
Use it to create a reproducible baseline rather than taking a single screenshot:
The four Search Console metrics answer different questions. Impressions indicate how often the included results were shown. Clicks show how much traffic those appearances produced. CTR describes clicks relative to impressions. Average position provides a directional view of visibility across the selected query set. None of them establishes why demand existed or whether the visit produced a business result.
Google uses an AI-driven system to classify branded queries. It can recognize brand variations, misspellings, multiple languages, and distinctive products or services associated with a brand. Contextual classification also creates the possibility of mistakes, especially where a term is ambiguous.
Audit the classification before presenting it as a clean split. Review the highest-impression and highest-click queries in both groups. Mark apparent false positives, false negatives, and terms whose meaning is genuinely ambiguous. You cannot rewrite Google’s classifier, but you can maintain an external exception list and disclose material ambiguity in your report. If questionable terms meaningfully affect the conclusion, create a separate ambiguous group in your exported analysis rather than forcing certainty.
The option is limited to eligible sites, and query or impression volume can affect eligibility. If the filter is unavailable, use a documented query list or regular-expression rule as a temporary substitute. Include the company name, known variations, misspellings, and distinctive product or service names. Version the rule whenever you change it so historical comparisons do not silently change definition.
The branded filter changes reporting, not rankings. Turning it on does not alter how a query or page performs in search.
A branded query is a query-level signal. It does not identify the searcher as a loyal customer, prove that the person has visited before, or show which channel created the awareness. Someone can encounter a company elsewhere and then search its name for the first time. An existing customer can also use a generic query. Treat branded versus non-branded as a useful proxy for the wording and likely relationship of the query, not as an audience identity system.
With that limitation understood, the split gives you three useful views:
You can also calculate branded click share by dividing branded clicks by the combined branded and non-branded clicks in the same filtered scope. Use that percentage as a dependency indicator: it tells you how much reported organic traffic came through branded queries. It is not market share, brand awareness, or an SEO score.
Always place the share next to its raw numerator and denominator. Branded click share can fall because branded clicks declined, because non-branded clicks grew, or because both changed at different rates. Those scenarios lead to very different decisions.
| Observed movement | Plausible reading | What to inspect next |
|---|---|---|
| Branded impressions rise while branded CTR is stable | More searches are being classified as brand-related, while organic capture remains proportionally similar. | Check which branded terms grew and compare the timing with campaigns, launches, publicity, seasonality, and other demand-generating activity. |
| Branded impressions are stable while branded clicks or CTR fall | Existing brand demand may be captured less effectively, although a changed query mix or search-results environment could also be involved. | Inspect the affected queries, ranking URLs, average position, result titles, page availability, indexation, and any migration or template changes. |
| Non-branded impressions rise while clicks lag | The site may be appearing for more queries without yet earning proportionate traffic. Weaker positions, poor intent alignment, or an expanded query mix are possible explanations. | Group the new visibility by query intent and landing page. Examine query-page fit, average position, and how accurately the result communicates the page’s value. |
| Non-branded clicks rise while branded activity is flat | Organic discovery improved, but the data does not yet show an accompanying increase in observed brand-query demand. | Identify the pages and topics driving discovery, then use analytics or customer data to evaluate engagement, conversion, and later brand interaction. |
| Branded activity rises while non-branded activity falls | Stronger observed brand demand may be masking weaker category discovery in the sitewide total. | Report the two movements separately. Diagnose non-branded losses by page group, intent, market, device, and search type before celebrating aggregate growth. |
| Both branded and non-branded clicks rise | Demand capture and discovery may both be improving, but common causes such as seasonality or broader market demand remain possible. | Find the query and page cohorts responsible for each increase, then compare them with known marketing activity and conversion outcomes. |
These are diagnostic hypotheses, not automatic verdicts. Search Console shows patterns of visibility and traffic. It cannot by itself tell you that public relations caused branded demand, that a content change caused non-branded growth, or that an SEO campaign created awareness. The next check is part of the analysis, not an optional footnote.
A useful report does more than label two lines on a chart. It connects a tightly defined observation to a decision. For every material change, write the analysis in this order:
Suppose non-branded clicks increase on comparison pages while branded clicks remain flat. The defensible conclusion is that organic discovery improved within that page cohort. It is not yet evidence that brand awareness increased. Your next step is to inspect the gaining queries, confirm that the pages serve the intended comparison need, and evaluate downstream engagement or conversion in your analytics and customer systems.
The action should follow the diagnosed segment:
On your next reporting cycle, export the branded and non-branded views before discussing total organic growth. Pick the segment that changed, inspect its query-page cohort, write one falsifiable explanation, and attach one action to it. That small discipline turns "it depends" from a vague qualification into a measurement method your team can use.
You check the AI answers for your priority queries. Your brand appears in one tool, disappears in another, and a colleague sees a different mix of links. That doesn’t automatically mean one test is wrong. It means “AI visibility” is too broad to be useful unless you preserve the conditions that produced each answer.
If you are deciding where to invest, don’t chase a universal top source or compress every result into one score. Measure visibility by platform, intent, category, user context and data access. That will show you whether you have a content problem, a channel problem, an access problem or simply a misleading average.
A conventional ranking report usually starts with a query and a position. That model is incomplete for AI search. An answer can vary with the platform, the product surface, the user’s intent, the category, the information available to the system and the context attached to the user. The cited page is therefore an outcome of a particular test condition, not a universal position your page owns.
Start by separating four outcomes that teams often collapse into “visibility”:
The distinctions matter because citation behavior is highly conditional. Across high-commercial-intent prompts in nine verticals, citation patterns varied by platform, industry and intent during four months ending in January 2026. That is enough to reject the idea that one domain is the best citation target for every brand.
Reddit shows how quickly a headline can become a bad strategy. Its citations grew 73% in the tracked set from October 2025 to January 2026. Yet its January citation share was above 5% on ChatGPT and as low as 0.1% on Google Gemini. The category split was also substantial: Reddit accounted for 10% of citations in apparel and 2% in transportation. Growth, platform share and category share are different measurements. None of them, on its own, tells you to make Reddit the center of your plan.
The type of page matters too. ChatGPT’s Reddit citations in that period pointed to individual discussion threads rather than generic subreddit pages or branded community content. If those threads appear in your own category tests, the opportunity is useful participation in the exact conversations people and AI systems find valuable. Merely creating a branded Reddit presence does not reproduce that value.
Keep the scope attached to the figures: high-commercial-intent prompts, nine verticals, four months and an end date of January 2026. Use the numbers as evidence that averages can mislead, not as a benchmark your industry must match.
Personalization doesn’t just reorder a set of public links. It can change the surface on which discovery happens and place public information beside private account data, live feeds and followed interests.
Yahoo’s MyScout illustrates the shift. In its U.S. beta, logged-in users can build a personalized homepage from tiles connected to Yahoo Mail, News, Sports, Finance and Games, as well as topics or queries they choose. Users can add, remove and reorder tiles. Some information, such as stock prices, can update in real time; email, sports and breaking-news tiles can refresh during the day. Yahoo says the experience will become more personalized as it learns from activity.
That creates several data lanes in one interface. A public publisher page can compete for attention beside an inbox preview, a watchlist, a favorite team’s score or a followed topic. You cannot optimize a public article into becoming someone’s private email or finance data. You can, however, make the public part of the journey clear, attributable and worth following.
Yahoo’s publisher features make that distinction concrete. Brand pages can collect a publisher’s articles, videos and social feeds, while a follow function can turn an initial discovery into a subscription and curated email exposure. A query citation and a publisher follow are both valuable, but they are not the same result and should not share one KPI.
Use separate scorecards:
Your testing also needs explicit account states. Label whether a result came from a logged-out session, a dedicated test account or an established account with follows, watchlists or activity. Record the exact account used. Calling a result “personalized” without documenting the relevant context makes it impossible to interpret or reproduce.
The smallest meaningful unit in an AI visibility audit is a test cell: platform and product surface x exact prompt and intent x category x account context x source-access state. You can summarize cells later, but collect the raw conditions first.
| Field | What to capture | Why it matters |
|---|---|---|
| Test condition | Platform, product surface, app or web, market, account and login state | Prevents unlike environments from being treated as the same result |
| Prompt | Exact wording, intent, category and journey stage | Shows whether citation behavior changes with the decision the user is making |
| Response | Brand mention, link presence, cited URLs, domains and page types | Separates brand awareness from actual citation capture |
| Source relationship | Owned site, publisher profile, community thread, third-party editorial page or competitor | Points to the channel and owner capable of making a change |
| Access state | Known crawler policy, restriction or platform relationship affecting the source | Identifies cases where availability, rather than page quality, may be the bottleneck |
| Timing | Date, time and any visible product or model label | Preserves context when feeds refresh or platform behavior changes |
| User action | Click, compare, follow, subscribe or another next step offered by the answer | Connects visibility to what the user could actually do |
Be precise about denominators. Citation growth is a change in count over time. Citation share is a source’s portion of all captured citations. Brand citation rate is the portion of eligible test runs that link to your brand or its owned pages, depending on the definition you set. Reporting one as if it were another is how an impressive number becomes an unhelpful decision.
Do not hide missing citations either. A no-citation answer, a citation to a third party that mentions you and a citation to your own page represent different source pathways. Each should have its own value in the log rather than being collapsed into a generic success column.
Once the matrix is segmented, the pattern usually tells you where to investigate. The useful question is not “How do we rank in AI?” It is “Why does this source win for this decision on this surface under these conditions?”
Compare the cited page with yours at the decision level. Identify the question it resolves, the claims it supports, the details it makes explicit and the next action it enables. Build the missing value into the most relevant page on your site rather than publishing a generic AI-search article or copying the competitor’s structure.
Keep important facts in accessible page content. Use appropriate JSON-LD to identify the entity and content type and to connect information already visible on the page. Schema can reduce ambiguity for machines, but it is not a citation switch and should not be reported as one.
Work at the thread level. Find the recurring questions in the cited discussions, answer them with category knowledge and disclose your relationship to the brand. The documented Reddit pattern favored unique discussions, so a generic corporate profile or empty branded community is not an equivalent intervention.
Track community citations separately from owned citations. A useful third-party discussion can increase brand representation without giving you control of the page, its future edits or its availability. That is a different asset and a different risk profile.
Make the publisher identity coherent across the material collected by that surface. Treat the brand page, follow action and newsletter as a retention path after discovery. Measure whether users can reach and follow the publisher; do not count the existence of the feature as a citation.
Data availability is not uniform. Commercial deals, restrictions and lawsuits have been fragmenting what AI systems can access. Your content can remain unchanged while its eligibility differs from one platform to another.
Amazon demonstrates the competitive consequence. Its more aggressive blocking of AI crawlers coincided with lower Amazon citation visibility on ChatGPT and more room for Walmart in the tracked results. That does not prove that every publisher should open every crawler. Amazon’s choice also reflects a preference for controlling direct customer interactions.
Before changing access, document which crawler or pathway is affected, which content is in scope, which AI surfaces matter to the business and what control or content-rights concerns prompted the restriction. Bring the content owner, technical team and appropriate legal or commercial stakeholders into the decision. A blanket unblock made only to chase citations can create a larger governance problem; a blanket block can surrender visibility to an accessible competitor.
Platform-specific source preferences can create another kind of gap. Even Google’s AI surfaces showed different citation mixes for social sources such as Reddit, Medium, YouTube and LinkedIn. If one format performs on one surface, verify the pattern elsewhere before expanding the entire channel program.
Use the next test to isolate one decision. Select one high-value category, preserve its exact prompts and account states, and map every citation to its source pathway. Then make the narrowest change that addresses the observed gap. Your first useful deliverable is not a universal visibility score. It is a map showing which source wins under which condition, who can influence it and what you will test next.
You may have handed Google more control than your operating process can currently supervise. Performance Max can place catalog images on television screens, Merchant Center data can shape what is eligible to advertise, and automated recommendations can alter campaign behavior faster than a monthly report will reveal.
The answer isn’t to reject automation. It is to build a control system around it: define the business outcome, verify the inputs, expose where the budget goes, assign owners to platform alerts, and reserve consequential decisions for a person. Here is the operating model we would put in place.
An automated campaign is not a set-and-forget campaign. It is a feedback loop. You supply goals, conversion signals, budgets, product data, creative assets, audience information, and landing pages. Google makes allocation and delivery decisions from those inputs. Performance data comes back, but not always at the level of detail you would prefer.
Your job is therefore broader than adjusting settings. You need to govern the loop. Start by documenting four things for every automated decision surface:
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If you market a hotel, restaurant, tour, or attraction, a weak Tripadvisor listing can shape the decision before a traveler reaches your website. The platform can occupy valuable search-result space for your business name, appear during category discovery, and expose reviews, photos, and business details while the customer is deciding where to book.
Your goal is not to make Tripadvisor the center of your local SEO strategy. It is to manage the listing as one coordinated part of your search presence: accurate business facts, a clearly described experience, fresh evidence, useful customer language, and a credible path from discovery to action.
Tripadvisor performs three jobs at once. It is a search result, a comparison marketplace, and a reputation page. That combination matters because travelers visiting it are often beyond general inspiration and actively comparing places, experiences, or meals.
The scale is difficult to dismiss: Tripadvisor receives about 490 million monthly visits. Its large, programmatically structured collection of indexable destination, category, and business pages also gives it substantial visibility in conventional search results. In some tourism and hospitality searches, a Tripadvisor listing can even appear above the business’s own website.
That does not mean optimizing Tripadvisor will directly raise your website or Google Business Profile rankings. There is no defensible reason to report it as a guaranteed ranking shortcut. Its local SEO contribution is broader and more practical:
Tripadvisor can also contribute to AI discovery, but the mechanism should be described carefully. Detailed profile text and factual owner responses create more explicit language about your amenities, audience, setting, and experiences. That gives AI-driven search systems more context to interpret; it does not guarantee that an AI answer will mention or recommend you. For AEO and GEO, prioritize clear passages and verifiable details, not inserted keyword strings.
A beautifully written description cannot repair a fragmented business identity. Begin with the fields that determine which entity the listing represents and where it can be discovered.
Do not add categories merely because they attract desirable searches. If the listing claims a romantic dining experience, family-oriented amenity, or particular type of cuisine, the photos, menu, description, and customer feedback should support that claim. A misleading classification may win an impression but lose the booking when the visitor inspects the page.
Use this priority order when resources are limited: correct identity, remove duplication, choose the right categories, update the offer, refresh the visual evidence, and then refine promotional wording. The early steps determine whether the right listing can be found; the later steps help it convert.
A review response is not only reputation management. It is public content attached to a specific customer experience. A thoughtful reply can turn a vague mention into a clearer explanation of what the business offers.
If a guest says only that the pool was enjoyable, for example, a useful response can acknowledge the comment and mention a relevant family feature or activity, provided that feature genuinely exists. This creates additional semantic context around the property’s amenities. The response should still sound like a reply to a person, not a paragraph built to carry search terms.
A reliable response structure is:
You can also encourage more informative reviews without scripting praise. After the visit, invite the customer to describe which experience they booked, what stood out, who the experience suited, or what they would tell another traveler. That produces more decision-useful language than asking only for a star rating.
Review velocity matters as an operational signal, but do not confuse velocity with sudden volume. The sustainable objective is a continuing stream of feedback from real customers, followed by regular owner attention. A burst of requests followed by months of silence leaves the listing looking less current and gives you fewer recent customer questions to learn from.
Travel and hospitality decisions are visual. The strongest images quickly show what the guest will receive: the room, dish, view, activity, atmosphere, or defining feature. Replace photos that show an old menu, previous decor, unavailable amenities, or an experience that no longer represents the business.
You do not need to guess which creative deserves the lead position. If you already publish comparable photos on Instagram, use the engagement data as a directional signal for which subjects and compositions attract attention, then confirm that the selected image accurately represents the bookable experience. Popularity is useful only after accuracy.
Captions should describe the image in natural language. A practical formula is: what is shown, where or how it is experienced, and who or when it may be relevant. For example, a dish caption can identify the meal, the terrace or dining setting, and the season in which it is offered. Include audience claims such as “popular with solo travelers” only when you have a real basis for them. A string of location and service keywords does not help a traveler understand the image.
Profile optimization becomes difficult to defend when the only metric is average rating. Rating matters to customers, but it does not tell you whether the listing is accurate, discoverable, engaging, or sending qualified demand.
Track the channel in layers:
Capture a baseline before making a substantial change. Compare equivalent reporting periods and annotate major profile updates, promotions, closures, and seasonal offer changes. This will not prove that a single caption or response caused a result, but it will prevent you from attributing every movement to the most recent edit.
Website traffic is only one part of the journey. Tripadvisor also functions as a comparison environment where a customer may make a decision without visiting your domain. Read referral traffic alongside profile engagement and actual bookings rather than declaring the channel successful or unsuccessful from sessions alone.
A manageable recurring workflow is to inspect identity fields and duplicates, clear the review-response backlog, replace outdated images or offer information, record emerging customer themes, and review referral outcomes. Assign ownership to a person or role. A listing that belongs vaguely to “marketing” is likely to remain untouched until a negative review or incorrect detail creates urgency.
Start with a duplicate and identity audit of the listing that already exists. Once the correct entity is established, improve one decision layer at a time: classification, offer clarity, reviews, images, and measurement. That sequence turns Tripadvisor from an unmanaged reputation page into a useful part of your local search system.
Short-form video, Thought Leader Ads, personalized creative, and Qualified Lead Optimization are showing promise. Here’s how I plan to test them.
LinkedIn made some noteworthy moves last year with significant payoffs for our B2B clients. As we embrace 2026 and zero in on our yearly marketing goals, I’ve gathered some exciting insights from 2025 to help you maximize your strategies. Let’s dive into the top tests to run, including:
Let’s explore each of these tests and the potential benefits they offer.
Even though Meta and TikTok are more suited for videos, LinkedIn hasn’t shied away from the wave — especially with short-form videos (7-15 seconds). Crafting the right content is crucial for your marketing strategy. Here’s how you can leverage video effectively:
Consider new placements like First Impression Ads. Compare the performance of video ads in the feed against other ads to gauge impact and engagement.
The usual tips apply:
Dig deeper: LinkedIn study reveals how B2B video ads can gain +129% engagement lift
The SEO toolkit you know, plus the AI visibility data you need.
Engaging potential B2B clients can often be challenging, especially through a corporate lens. Thought Leader Ads (TLAs), which allow companies to boost employee content, have been around. Since I tested them rigorously in 2025, I’ve noticed they garner significantly higher engagement compared to typical business profile ads.
TLAs also afford creativity. Humorous posts, for instance, feel more authentic when shared from a personal profile.
As with all boosted content, selective investment is key. If a post organically gains traction and aligns with your business goals, it’s a prime TLA candidate.
Caveats to consider:
Dig deeper: LinkedIn Ads retargeting: How to reach prospects at every funnel stage
Get the newsletter search marketers rely on.
In late 2025, I experimented with personalized LinkedIn ads across various regions and campaigns. Globally, I witnessed a >20% improvement in cost per lead, paired with better CTR and lower CPC. U.S. campaigns were remarkable, showing a 33% drop in CPLs.
According to my LinkedIn contacts, European users value privacy more than their U.S. counterparts, explaining why personalization resonated better stateside. Yet, even U.S. campaigns showed fatigue with personalized ads after a month.
Combining personalized and non-personalized ads in one campaign decreased the frequency of personalized ads and facilitated side-by-side performance comparisons.
Dig deeper: LinkedIn’s new playbook taps creators as the future of B2B marketing
Having experience with Conversions API (CAPI) and enhanced conversions in Meta and Google, the concept of Qualified Lead Optimization is familiar. LinkedIn’s take lets you merge your first-party data with its algorithm to target high-quality users more effectively.
Though not as adept as Meta and Google yet, I’ve noted an increase in qualified leads through LinkedIn.
Here’s how to test it:
This tactical feature has saved me time across accounts, making it an essential tool. In March 2025, LinkedIn improved Campaign Manager with a feature for duplicating ads across campaigns and accounts, expediting our campaign launches — a win with no downsides.
I’m still evaluating LinkedIn’s new CTV capability. It offers potential for testing brand messages and positioning through targeted niche audiences before committing to broader campaigns.
LinkedIn introduced substantial updates last year, prompting us to boost client budgets there. Setting clear platform expectations and having a robust evaluation framework will maximize LinkedIn’s value.
Armed with these strategies and a deep understanding of your ideal customer profile (ICP), LinkedIn could serve as a surprising source of growth in the coming months.
Inspired by this post on Search Engine Land.
Your Meta campaign can hit its media-spend target and still exceed the amount finance expected to pay. From July 1, ads aimed at several European markets carry an additional charge of 2%, 3% or 5%, before any VAT.
If you advertise across borders, your company’s address won’t protect the budget. The rate follows the location targeted by the ad, so you need to revise forecasts, performance metrics and client billing at the market level.
Under Meta’s announced digital-services-tax policy, the advertiser pays a location-specific surcharge beginning July 1. France, Italy and Spain carry a 3% rate; Austria and Turkey carry 5%; and the UK carries 2%.
The practical rule is simple: look at where the campaign targets people, not where the ad account, agency or company is based. A US business targeting France is exposed to France’s 3% rate. A UK business targeting Austria is exposed to Austria’s 5% rate.
| Target location | Surcharge | Cost of $100 in media, before VAT |
|---|---|---|
| France | 3% | $103 |
| Italy | 3% | $103 |
| Spain | 3% | $103 |
| Austria | 5% | $105 |
| Turkey | 5% | $105 |
| UK | 2% | $102 |
The table shows why a media budget and a payable budget can no longer be treated as the same number. Meta’s own example is a $100 ad targeting Italy: the advertiser pays $103, excluding VAT. VAT remains separate, so $103 should not automatically be treated as the final invoice total.
For campaigns covering several countries, don’t apply one country’s rate to the whole plan. Allocate spend by target market, multiply each amount by the applicable rate, and add the results. If delivery shifts toward a 5% market, the total charge rises even when aggregate media spend stays unchanged.
For locations outside the listed schedule, don’t invent a planning rate. Check the billing notice for that market before approving the budget. The absence of a country from this table is not evidence about every other tax or platform fee that might apply.
You can’t preserve the same media delivery, the same total cash outlay and the same return ratio simultaneously when a new cost is added. Decide which constraint matters before changing campaign budgets.
Use two formulas in your planning sheet:
Do not respond by cutting every European campaign 5%. That would overcorrect UK campaigns, which carry a 2% rate, and the 3% markets. It would also confuse a finance constraint with a performance decision. Apply the actual target-location rate first; then decide whether the resulting economics still meet your threshold.
The same distinction matters in annual and quarterly plans. If your existing budget authorization covers media only, add a separate surcharge line. If it is an all-in cash ceiling, calculate how much media remains available after the charge. Write that assumption into the plan so the campaign manager and finance team don’t each interpret the same number differently.
A billing surcharge can create a reporting split. The advertising view may focus on media spend and auction performance, while the ledger records the higher amount actually paid. Unless your reporting layer imports the surcharge, both views can be internally correct and still lead to different decisions.
Keep the media metrics for campaign diagnosis. They tell you whether targeting, creative, bids or conversion volume changed. Add all-in metrics for budget and profitability decisions:
Suppose an Italy campaign produces the same impressions, conversions and revenue after July 1 as it did before. Its media performance has not deteriorated. Its economic performance has: every $100 of media now creates $103 of pre-VAT cost. If you compare the old media-only ROAS with the new all-in ROAS without labeling the methodology, the apparent decline can be mistaken for an auction or creative problem.
Preserve both columns rather than rewriting history. Label one set as media metrics and the other as all-in metrics, then mark July 1 as a change in cost methodology. This gives operators a stable campaign diagnostic while giving finance and leadership the number that reflects actual cost.
VAT needs its own treatment. Whether VAT belongs in a profitability model can depend on the business, jurisdiction and recoverability. Have the finance or tax owner decide that treatment; don’t make a universal VAT assumption inside the advertising dashboard.
A single blended percentage is acceptable for a rough scenario, but it is weak operational control. The country mix can change, and the difference between 2% and 5% is large enough to distort forecasts when spend is concentrated in the higher-rate markets.
Your control sheet should contain one row per target market and these fields:
Then work through the change in this order:
You don’t necessarily need to split every multi-country campaign. Separate markets when country-level budget control, margin differences, client ownership or invoice reconciliation justify the added structure. Keep them consolidated when a unified campaign is operationally preferable, but calculate the expected surcharge as a spend-weighted amount rather than using the highest or lowest rate.
Agencies also need a contract check. Don’t add a generic 5% client fee to all European activity: the listed rates differ, and the charge follows the target location. Confirm whether taxes and platform surcharges are included in the existing fee arrangement or passed through separately. If the contract is unclear, get legal or finance review before changing a client’s invoice.
Before the next Europe-focused budget is approved, add the country, rate and all-in cost fields to the planning sheet and make one person responsible for the first invoice reconciliation. The surcharge itself isn’t optional for covered delivery; the decision you control is whether it becomes a planned cost or an unexplained miss.
Your video can finish exactly as edited and still deliver a different final impression from the one your team approved. On an eligible Google video ad, an automated conversion card can appear after playback and replace the YouTube end screen you expected viewers to see.
If you run mobile app install campaigns, review the served experience rather than approving only the video file. The ending now depends on the creative, the campaign data used to build Google’s card, and whether an existing YouTube end screen is displaced.
The most important distinction is between an embedded outro and a YouTube end screen. An embedded outro is part of the video file: the logo, message, animation, or call to action is encoded into the final frames. A YouTube end screen is a platform-level element added around the video. Google’s automatic card is another platform-level element, shown after playback.
That means you are managing three layers, not one. Approving the edited file verifies only the first layer. It does not verify which platform-level screen will follow it or whether the information on that screen is correct.
| Layer | What to verify | Main risk |
|---|---|---|
| Embedded video ending | Brand, message, visual hierarchy, and spoken call to action | The outro assumes a different action from the automated card |
| Manual YouTube end screen | Whether the campaign depends on it for an essential message or destination | It can be overwritten when automatic end screens are active |
| Google automatic end screen | App name, icon, price, install link, and overall presentation | Campaign data becomes part of the creative without appearing in the source video |
| Billing and view reporting | Normal campaign accounting | No change is expected, so these metrics are not a QA signal |
The replacement behavior matters most when a manual end screen carries information that appears nowhere else. If your offer, product distinction, or required next step exists only in that layer, the automated card can remove it from the experience. Treat any message essential to comprehension as part of the video itself.
You do not need to rebuild every eligible video around the automatic card. You do need an ending that remains coherent when the card follows it. The safest pattern is to let the video complete the argument and let the automated screen provide the conversion path.
This approach also prepares non-eligible campaigns for a wider rollout. There is no announced timetable, so a wholesale redesign would be premature. Making new endings self-contained is a low-regret change: it improves message continuity without depending on an unconfirmed expansion date.
The current priority is easy to define: find in-stream video ads used in mobile app install campaigns. Those are the ads within the stated scope. Other campaign types can go on a watchlist, but they do not need to be treated as eligible without confirmation.
Repeat this check when the video changes, relevant campaign details change, the app destination changes, or Google expands eligibility. You do not need a daily inspection. You need a defined trigger that puts the end screen back into the normal creative approval process.
Automatic end screens are intended to guide viewers toward conversion, but intent is not proof of incremental performance. Treat creative QA and performance evaluation as separate questions. First establish that the card is accurate and brand-safe. Then assess whether campaign outcomes changed.
Do not look for evidence in billing or view totals. Google states that automatic end screens do not affect billing or view counts. An unchanged view count therefore says nothing about whether the card rendered, whether viewers interacted with it, or whether it improved conversion behavior.
Start with the campaigns inside the known eligibility boundary. Add the automatic card to your creative sign-off, move indispensable messaging into the video, and keep non-eligible formats on a monitored list until Google confirms a broader rollout. That gives you control over the part you can verify now without pretending the future scope is settled.
If your AI commerce plan assumes an assistant can find a product, sign in and complete the purchase, the Perplexity-Amazon dispute exposes a flaw in that model: discovery, account access and transaction authority are separate permissions.
A preliminary injunction now prevents Perplexity’s Comet agent from entering Amazon’s password-protected areas and requires Perplexity to delete the Amazon data it collected. That does not end AI shopping, but it gives SEO, ecommerce and agent teams a practical warning: being visible to an AI system does not give that system permission to act inside a platform.
The scope matters. U.S. District Judge Maxine Chesney issued a preliminary injunction concerning Comet’s access to password-protected parts of Amazon, including areas used by Prime members. It is not a final judgment declaring every AI shopping agent unlawful, nor does it establish that public product pages cannot be found, interpreted or recommended by AI systems.
The central distinction is between two kinds of authorization. A customer may authorize an assistant to use the customer’s account, but the platform may still withhold authorization from the assistant itself. The judge cited strong evidence that users granted Comet access while Amazon did not. For anyone building an agent, user consent is therefore necessary but may not be sufficient.
Amazon has accused Perplexity of computer fraud and unauthorized access, including allegedly allowing Comet to make purchases without identifying itself properly as a bot. Those are Amazon’s allegations, not settled findings on every claim. At issuance, the injunction was suspended for one week so Perplexity could appeal.
The deletion requirement deserves as much attention as the access restriction. An agent team may need to identify and remove data by platform, account, user and collection method. If you cannot isolate data at that level, a dispute over one integration can turn into a much larger data-governance problem.
AI commerce is often discussed as one continuous journey, but three layers determine whether it works. Each has a different owner, failure mode and remedy.
| Layer | Question it answers | Typical responsibility | Common failure |
|---|---|---|---|
| Visibility | Can an AI system find and understand the product? | SEO, content, structured data and public-site engineering | The product is absent, misunderstood or cited inaccurately |
| Recommendation | Does the product fit the user’s request well enough to be selected? | Product information, positioning, availability and the agent’s decision logic | The product is understood but not chosen |
| Execution | Can the agent enter an account, modify a cart or complete a purchase? | Authentication, platform policy, security, legal review and approved integrations | The journey stops at sign-in, checkout or another protected action |
Schema markup can improve machine understanding at the visibility layer. Clear product details can strengthen the recommendation layer. Neither one grants an agent access to an authenticated account. Treating them as substitutes for platform permission creates a false sense of readiness.
The same distinction applies to robots.txt and other crawl controls. A public crawling directive is not a purchasing authorization system. It does not answer whether an agent may use a signed-in session, accept terms, place an order or retain account data. Those questions need explicit product, security and legal decisions.
The wrong reaction would be to stop optimizing products for AI discovery. The injunction concerns authenticated access, while much of the discovery and evaluation journey happens through public information. Your content can still help an assistant understand what a product is, who it suits and where the customer can continue safely.
Measure these layers separately as well. AI referrals and product-page visibility tell you about discovery. Product selection or cart initiation tells you about consideration. Completed orders tell you about execution. Combining all three into a single “AI traffic” measure hides the exact permission gate where the journey fails.
You do not need to wait for another court dispute to find the weak point in your own workflow. Trace one high-value purchasing journey from the first public result through order confirmation, then record the identity, permission and data rules at every transition.
If your agent enters authenticated services or makes purchases, do not attempt to evade a platform block or disguise automated traffic. That can increase contractual, security and legal exposure. Have qualified counsel review the relevant terms, authorization model and data practices before launch; this dispute is too narrow and preliminary to serve as a universal legal rule for another platform or implementation.
Your next move should be concrete: diagram one purchasing journey, circle every point where the agent crosses from public information into protected action, and assign an owner to each permission. Keep optimizing the public layer for discovery, but do not describe the journey as agent-ready until the authenticated steps have an approved path or a tested human handoff.
You have a credible announcement, useful expertise, or a strong point of view, but journalists aren’t replying. The problem may not be the writing. A polished email still fails when it asks a journalist to turn company news into a story for the audience.
Useful media coverage can increase exposure, support authority and trust, and sometimes produce valuable backlinks. You improve your chances by treating pitching as a disciplined sequence: find the audience consequence, select the right journalist, make the idea easy to evaluate, follow up with restraint, and remain useful after the immediate pitch is over.
Being first, calling yourself the best, or promising to change an industry does not automatically create a story. Those are claims about the company. A journalist needs a change, tension, consequence, or useful insight that matters to the people reading or watching.
Before you draft an email, complete this story test:
A useful angle can often be expressed in one sentence: Because this changed, this audience now faces this consequence, and we can help demonstrate or explain it. If you cannot complete that sentence without returning to promotional language, the idea needs more work before outreach begins.
Compare the underlying shapes of these two approaches:
Brand claim: Our company has launched a groundbreaking platform that will transform the market.
Audience angle: A change in the market is forcing a defined group to reconsider a familiar decision; we can show what is changing, explain the tradeoff, and provide access to a qualified source.
The second version does not hide the company. It gives the company a legitimate role inside a larger story. Your mission can help explain why you are involved, but the mission is usually context, not the headline.
Prepare the supporting material before you pitch. Confirm who can speak, what that person is qualified to address, which claims can be verified, which assets are ready, and whether any information has restrictions. If the strongest sentence in the email depends on evidence you cannot share, remove it.
Do not try to solve a weak angle by paying an individual contributor for undisclosed editorial inclusion. That practice conflicts with many outlet guidelines and can lead to removal or blacklisting when discovered. A publisher’s clearly labeled sponsorship product is advertising; it should not be represented internally or externally as earned coverage.
Media outreach is a matching problem, not a volume contest. The right contact has covered the subject, serves an audience affected by your angle, and works in a format that can use what you are offering.
Start with published work. Search relevant outlets, search engines, and journalists’ professional social profiles for coverage of the underlying issue. Do not stop when a job title appears related. Read enough recent work to understand the journalist’s beat, the questions they pursue, the geography or sector they cover, and the kinds of sources they use.
Qualify each contact with four checks:
Your working media list should contain more than names and email addresses. Record the outlet, beat, relevant coverage, audience, reason for fit, preferred contact route, date of outreach, angle sent, follow-up status, response, and any stated preferences. This prevents duplicate emails and makes future outreach more informed.
Separate contacts by strength of fit. Your primary group should have a clear connection to both the issue and the affected audience. A secondary group may cover an adjacent consequence or a different format. Remove anyone you included only because the outlet is prominent. Prestige does not repair a relevance gap.
Send in controlled waves rather than releasing the same email to the entire list at once. Early replies can expose an unclear premise, a missing fact, or a better framing. You can then improve the pitch for contacts who have not received it. That is useful iteration, provided you do not change facts or imply exclusivity that you have not offered.
A journalist may be sorting through hundreds of pitches in a day. Your email does not need to explain everything. It needs to make the editorial decision clear: what the story is, why it fits, why it matters now, and what you can contribute.
Start with the subject line. It should carry the same angle as the body. Useful structures include:
Avoid empty labels such as press release, exciting announcement, game-changing news, or quick question. They describe your email, not the story. Do not use urgent, exclusive, or breaking unless those terms are accurate.
Then build the body in a simple order:
A reusable draft might look like this:
Subject: [Change] is creating [consequence] for [audience]
Hi [name],
Your coverage of [specific theme] made this worth sending to you.
[State the change.] It matters to [defined audience] because [consequence]. The timely question is [the question an audience needs answered], rather than [the promotional claim your company wants to make].
We can provide [specific evidence or access] and [source name and relevant qualification].
Would this angle be useful for your coverage?
Thanks,
[name]
[role and direct contact information]
Personalization should prove fit, not prove that you can copy a headline. If the opening reference could be pasted into an email to every reporter at the outlet, it is not doing useful work.
Keep the company biography, product detail, and executive history subordinate to the angle. Offer deeper materials rather than forcing every fact into the first email. The pitch earns the next conversation; it does not need to contain the finished coverage.
Before sending, perform a final editorial check:
Silence is common and is not a verdict on your company. It may mean the journalist missed the message, the timing was wrong, the angle did not fit, or other work took priority. Your follow-up should make the idea easier to assess, not create pressure.
Unless the pitch concerns genuinely time-sensitive news, wait about a week between contacts and move on after two or three total attempts. That gives you a clean sequence: the initial pitch, a useful follow-up, and, when warranted, a final note that closes the loop.
A useful first follow-up is short:
Hi [name] – following up on the angle below about [specific consequence]. Since my note, [new relevant fact, available source, or useful clarification]. If it is not a fit for your coverage, no response is needed.
A final note can be even shorter:
Hi [name] – closing the loop on this idea. We will not send another follow-up, but I am happy to help if the issue becomes relevant later.
Do not disguise a repeated pitch as a fresh email, switch channels to evade silence, or add urgency that the underlying story does not have. When the sequence ends, archive the pitch and preserve the contact for a more relevant idea.
Handle each type of response differently:
A no closes the current angle; it does not necessarily close the relationship. Durable media relations come from predictable usefulness. Send future ideas only when they match the journalist’s work. Respect stated preferences. Make qualified people available. Correct errors in your own materials quickly. Never demand favorable wording, advance approval, a backlink, or a preferred anchor phrase in exchange for access.
When coverage is published, keep a record of the URL, outlet, journalist, publication date, brand naming, claims used, expert quoted, destination link, and any follow-up request. For SEO, AEO, and GEO planning, this becomes an auditable public evidence trail rather than a vague claim that PR improved visibility. It shows your team which explanations were credible enough to use, which supporting assets helped, and where brand facts need to become more consistent.
If coverage contains a material factual error, request a precise correction and supply the supporting fact. Do not use a correction request to negotiate more promotional language. Editorial independence is part of the relationship you are trying to preserve.
Before your next outreach, choose your strongest audience-centered angle, remove contacts without demonstrated fit, write the subject line before the body, and schedule the stopping point for follow-ups. That gives you a process you can improve without turning journalists into entries in a mass-email campaign.