AI SEARCH TOPICS VS. REAL AD VERTICALS — BUILDING A CROSS-CHANNEL PLAYBOOK WITH BING AND ANSTREX

AI search is changing how marketers understand online demand. Instead of looking only at individual keywords, marketers increasingly need to understand the broader topics, questions, and related intents that shape how people research products and services.

Microsoft's Topics Portfolio inside Bing Webmaster Tools offers one view into that shift. It groups AI search activity into broader themes, helping website owners understand where their content appears in AI-generated answers and where other sources are cited instead.

But search visibility is only one part of the opportunity.

A topic report can show that people are exploring subjects such as personal finance, health, technology, or consumer products. It does not necessarily reveal how advertisers are approaching those audiences through native ads, push notifications, pop traffic, or instream video.

That is where competitive ad intelligence becomes useful.

By combining AI search topic research with Anstrex, marketers can move from understanding what people are asking to investigating how advertisers are presenting related offers, building funnels, and adapting creatives across channels.

The two data sources serve different purposes:

• AI search topic reports help identify themes, questions, and potential content visibility gaps.
• Ad intelligence helps investigate observable advertising activity, creative approaches, landing pages, and funnel patterns across paid channels.

Neither source proves that a particular campaign is profitable. But together, they can provide a more complete research foundation for deciding what to investigate, what to test, and where to focus campaign development.

This guide explains how to connect Bing's Topics Portfolio with Anstrex data and turn those insights into a practical cross-channel advertising playbook.

AI search has moved beyond the idea of a search box containing isolated keywords. Search systems can interpret a broad question through related topics, subtopics, and follow-up questions.

For marketers, this means demand is easier to understand when it is examined as a collection of connected interests rather than a list of unrelated search terms.

Microsoft's Topics Portfolio inside Bing Webmaster Tools provides a way to examine this broader structure. Instead of presenting only individual grounding queries, it groups AI search activity into themes such as football, taxes, and AI chatbots. This allows website owners to examine visibility across topic clusters rather than looking at every query separately, as described in the feature coverage from Search Engine Roundtable.

The report includes several useful signals:

• Topic Size: An indication of the amount of AI Search demand associated with a topic.
• Sites Cited: A view of the sites appearing in answers for that topic.
• Queries: The underlying questions associated with the topic.

These signals help marketers understand the broader environment in which their content is appearing.

Why topic clusters matter

A person researching a broad subject rarely asks just one question. Someone exploring mortgage refinancing, for example, might move from understanding interest rates to comparing lenders, checking eligibility, and evaluating repayment options.

These questions are related, but they represent different stages of research.

AI search systems may explore related questions and sources when assembling an answer. This behavior is often discussed as query fan-out. Semrush's explanation of query fan-out describes how a system can expand an initial question into related subqueries to gather information from different parts of a subject.

This creates three useful layers for marketers to consider:

1. Topic clusters: The broader themes that organize related questions.
2. Intent layers: The informational, comparative, and transactional purposes behind those questions.
3. Related queries: The specific subquestions that help explain what people want to know.

A topic cluster can therefore reveal more than a single keyword opportunity. It can help marketers identify where a brand has established visibility, where its coverage is incomplete, and which related questions deserve further research.

Finding opportunities beyond existing visibility

Bing's Top Opportunity Queries feature adds another dimension to the report. It highlights queries where other sites are cited in AI answers but your site is not represented.

As Search Engine Journal's coverage of Bing Topics Portfolio explains, these opportunities can help marketers identify areas where competing sources appear in AI answers.

Microsoft's topic-level figures should be treated as directional planning signals rather than exact demand or traffic measurements. They are useful for prioritizing research, but they should not be treated as a precise record of every search or a guarantee of future visibility.

For example, a website may discover that it appears in AI answers for general questions about personal finance but is missing from related questions about debt consolidation or credit card comparisons. Those gaps can inform new content, stronger topic coverage, and further commercial research.

The limitations of AI visibility measurement also matter. Search Engine Journal's SEO Pulse coverage discusses how AI-driven search surfaces can make visibility and referral measurement more complicated. Reporting methods and citation behavior can vary between platforms and change over time.

The practical takeaway is to treat AI topic reports as a demand-research tool. They can help identify themes and questions worth exploring, but they do not replace paid media research or campaign measurement.

AI topic reports are useful for understanding search visibility, but they provide only part of the information media buyers need to plan campaigns.

Bing's Topics Portfolio can help reveal where AI answers associate a website with a subject. It does not show the full paid advertising environment surrounding that subject.

For example, a marketer might discover that mortgage refinancing is a significant topic with several competing sources. That information does not reveal whether advertisers are using native advertorials, short-form video, push notifications, affiliate pages, or lead-generation funnels to reach potential customers.

There are several important gaps to consider.

1. Topic reports are channel-blind

Topics Portfolio focuses on AI search visibility and citations. It does not provide a complete view of paid impressions, ad placements, creative variations, click-through rates, or conversion paths across advertising networks.

A topic may be important in AI search without being equally attractive on every paid channel.

The commercial opportunity may differ depending on the audience, offer, traffic source, geography, and cost of acquiring a customer.

Media buyers therefore need additional research to understand how a topic is being approached through advertising.

2. Broad topics can hide different buying intents

A topic such as hair loss can contain many different questions:

• Why is my hair shedding?
• What causes postpartum hair loss?
• Which hair-care products are worth considering?
• What treatment options are available?
• Where can I find a particular product?

These questions should not automatically be treated as one advertising opportunity.

Some users are looking for information. Others are comparing options. Some may be ready to evaluate a specific product or service.

The appropriate advertising approach can vary significantly across those stages. An educational article, a product comparison, a lead-generation page, and a direct-response offer each serve a different purpose.

Topic-level demand figures alone cannot reliably distinguish those commercial opportunities.

3. AI visibility does not identify every paid competitor

AI search citations often include publishers, educational websites, industry resources, and established brands.

Paid acquisition competitors may be different.

An affiliate advertiser, direct-response brand, or media buyer running native campaigns may not be a prominent source in AI search answers. Yet that advertiser could still be active in the paid market.

The concept of Topical Gravity from Semrush provides a useful perspective on how topical associations influence brand visibility. However, topical authority and paid acquisition activity are separate competitive dimensions.

If you rely only on AI topic reports to identify competitors, you may overlook advertisers that compete for the same commercial intent through paid traffic.

4. Topic reports do not reveal creative strategy

A topic report can show that people are asking about back pain relief. It cannot tell you which advertising messages are being used to promote products in that market.

Are advertisers using product demonstrations, customer stories, expert-led explanations, comparison angles, or short curiosity-driven headlines?

These creative decisions matter because each advertising channel has different formats and audience expectations.

For example, marketers researching TikTok creative approaches may use creative libraries to examine hooks, opening frames, and storytelling patterns. Social Media Examiner's discussion of AI and TikTok advertising highlights the importance of the opening frame in short-form video.

AI topic reports do not provide that creative-level view.

5. Emerging advertising activity may not appear in mature topic reports

AI visibility tools depend on the data available to their reporting systems. A topic may not appear as a distinct cluster until there is sufficient activity or coverage.

That creates a potential delay between emerging commercial interest and what appears in a topic report.

A new product trend, short-lived affiliate offer, or rapidly changing advertising angle may attract paid media activity before it becomes a clearly established AI search topic.

Topic visibility is also platform-specific. The sources and brands appearing in one AI search environment may differ from those appearing in another.

For that reason, AI topic reports should not be treated as a complete or real-time picture of the advertising market.

6. Topics do not map directly to media budgets

Media buyers usually organize campaigns around practical business objectives and verticals.

Examples include:

• Native campaigns for consumer products.
• Lead generation for financial services.
• SaaS trial acquisition.
• Local service inquiries.
• Video campaigns for demonstrable products.
• Affiliate campaigns built around specific offers.

A broad AI topic such as small business marketing could include software, consulting, educational products, agencies, and enterprise services.

Each category may have different conversion paths, economics, and suitable traffic sources.

Without additional research, it is difficult to determine which parts of a broad topic deserve paid testing.

The conclusion: AI topic reports are useful diagnostics for understanding search visibility and content gaps. They are not complete media plans. Media buyers need to add commercial intent, advertising activity, creative research, and funnel analysis before making campaign decisions.

The next step is to connect broad search topics with commercial categories that advertisers actively explore.

Some topics naturally overlap with established performance marketing verticals. Examples include cryptocurrency, dating, sweepstakes, consumer gadgets, and financial lead generation.

However, a topic's presence in Bing's Topics Portfolio does not prove that it is profitable, that it has a high EPC, or that advertisers are achieving a particular return. Those conclusions require separate campaign and financial data.

The useful exercise is to treat topic clusters as starting points for commercial research, then investigate the related advertising activity in Anstrex.

Cryptocurrency and trading

AI search topics around cryptocurrency may include:

• Cryptocurrency trading.
• Bitcoin prices.
• Altcoin research.
• Crypto wallets.
• Digital asset security.
• Trading platform comparisons.

These themes can connect to several advertising categories, including exchange registrations, wallet products, trading education, and financial technology services.

Anstrex research can help marketers investigate the observable creative and landing-page approaches used by advertisers in these categories.

For example, research might reveal different approaches such as educational explainers, platform comparisons, registration offers, or trading-related lead-generation funnels.

Do not assume that a frequently observed campaign is profitable or that a particular headline reflects verified investment performance. Financial promotions also require careful review of applicable regulations, platform policies, and claims.

Dating and relationship-related topics

Dating demand may appear across several related themes rather than one broad category.

Examples include:

• Online dating advice.
• Dating apps for specific audiences.
• Meeting people online.
• Relationship communication.
• Social discovery applications.

These topics can connect to advertising for dating platforms, social apps, messaging services, and subscription products.

A useful research approach is to compare the informational questions appearing in AI search with the messages and landing pages used by advertisers.

For example, informational content about meeting people online may differ considerably from an advertisement promoting a paid dating subscription.

The distinction can help marketers identify different audience intents and decide whether an educational, comparison-led, or direct-response approach is appropriate.

Sweepstakes, giveaways, and consumer promotions

Sweepstakes-related searches may include:

• Gift card giveaways.
• Online contests.
• Product giveaways.
• Survey reward programs.
• Promotional competitions.

These topics can connect to lead-generation campaigns, survey funnels, co-registration experiences, and promotional landing pages.

However, marketers should not assume that every giveaway-related search represents a qualified lead or a valuable acquisition opportunity.

When researching these offers, pay close attention to eligibility requirements, entry conditions, privacy disclosures, and the actual terms of the promotion.

Bing's topic opportunity data can help identify questions that deserve content research, while Anstrex can help investigate the advertising formats and landing-page experiences associated with similar offers.

Viral gadgets and impulse-buy e-commerce

Consumer product topics can emerge from social trends, product demonstrations, and reviews.

Examples include:

• Viral kitchen gadgets.
• Beauty products featured on TikTok.
• Portable fans and accessories.
• Smart home products.
• Product comparisons and reviews.

These topics can connect to direct-to-consumer advertising, affiliate product pages, comparison content, and short-form video campaigns.

Marketers can study how advertisers demonstrate a product, communicate its benefits, handle objections, and guide visitors toward a purchase.

Creative research should focus on the structure of the message rather than copying another advertiser's work. A product demonstration, customer-use scenario, or comparison format may provide a useful starting point for original creative development.

Financial lead generation

Financial topics may include:

• Mortgage refinancing.
• Credit cards.
• Credit repair.
• Personal loans.
• Debt consolidation.
• Financial planning.

These subjects often contain several distinct customer situations. A person comparing credit cards is not necessarily in the same decision stage as someone researching debt consolidation or mortgage refinancing.

Use topic research to identify the specific questions and modifiers that matter. Then investigate the corresponding advertising categories and funnel structures.

For financial offers, avoid assuming that a particular demographic or credit-related qualifier guarantees eligibility or conversion. Review the actual offer terms and ensure that all advertising claims are accurate and compliant.

The connection is intent, not guaranteed revenue

Across these categories, the useful relationship is the overlap between topic clusters and commercial intent.

AI search can help reveal how questions are grouped. Anstrex can help marketers investigate how advertisers approach related problems and offers through paid channels.

Ahrefs' guide to topical authority provides additional context for organizing related subjects into coherent topic clusters.

The objective is to bridge the informational and commercial sides of a subject without assuming that search demand automatically translates into profitable paid traffic.

Once you have identified a topic and its related commercial category, the next question is how advertisers are approaching that category across paid channels.

Anstrex can help with this research by showing observable advertising creatives, landing pages, and campaign patterns across supported traffic types.

The objective is not to assume that every long-running advertisement is profitable. Instead, look for recurring approaches that may reveal how advertisers structure their messages and funnels.

Native advertising — Advertorials, editorial framing, and soft landers

Native advertising often gives marketers more room to introduce a problem, explain an offer, and build context before asking visitors to take action.

Common creative approaches include:

• Image-led advertisements with curiosity-focused headlines.
• Educational or editorial-style framing.
• Product demonstrations and comparison angles.
• Customer stories and explanatory content.
• Advertorials that introduce an offer gradually.

A typical funnel may look like:

Native ad → advertorial or guide → quiz or lead form → offer page.

The pre-sell content can help explain the problem and introduce the product before the visitor reaches the conversion stage.

Different landing pages may be used to explore different messaging approaches. For example, an advertiser might test a detailed product review against a shorter comparison page or an educational guide.

Anstrex can help researchers identify these observable variations and examine how the landing-page experience changes.

For finance and other higher-consideration offers, funnels may include additional steps such as eligibility questions, educational content, registration forms, or consultation scheduling.

The important point is to study how the funnel is structured—not to assume that a particular sequence has achieved a specific conversion rate.

Push advertising — Short messages and immediate intent

Push notifications have limited space, so advertisers generally need to communicate one central idea quickly.

Common formats include:

• A short headline and supporting message.
• A compact image or icon.
• A direct call to action.
• A landing page designed for a quick next step.

Advertisers may experiment with curiosity, convenience, urgency, or product benefits.

However, tactics that imitate system alerts, fabricate messages, or imply that a user has received a personal notification when they have not can mislead audiences and violate advertising policies.

A more sustainable approach is to make the message direct and relevant to the actual offer.

A typical funnel may look like:

Push notification → focused landing page → offer details or lead form.

Because push messages are short, the landing page needs to deliver on the promise made in the notification.

Pop and redirect traffic — Fast transitions and focused landing pages

Pop and redirect formats can create an immediate transition from an advertising placement to a destination page.

In these environments, the landing page plays a particularly important role because there may be little or no traditional creative preceding it.

Common approaches include:

• Interactive product or offer pages.
• Short quizzes.
• Promotional landing pages.
• App-install destinations.
• Lead forms.

A typical flow may look like:

Pop or redirect → landing page or interactive experience → offer or conversion step.

Some campaigns use a quiz or interactive element before presenting the final offer. This can help explain the product or collect information, but it should not create false urgency, conceal material terms, or make participation appear mandatory when it is not.

When reviewing pop campaigns in Anstrex, pay attention to the landing-page structure, the clarity of the offer, and the steps required before a visitor can complete the intended action.

Instream and vertical video — Hooks, demonstrations, and storytelling

Instream and vertical video advertising compete for attention through motion, sound, and visual storytelling.

Common creative approaches include:

• Product demonstrations.
• Creator-style explanations.
• Before-and-after presentations where claims can be substantiated.
• Customer experiences and testimonials.
• Short problem-and-solution narratives.
• Comparisons that demonstrate meaningful differences.

A typical funnel may look like:

Video ad → mobile-friendly landing page → product details or lead form → checkout or next action.

Consistency between the advertisement and landing page is important. If the video introduces a product demonstration, the destination should continue that explanation rather than presenting an unrelated offer.

The opening frame also deserves attention. Social Media Examiner's discussion of TikTok advertising and AI describes why the opening visual can strongly influence whether viewers continue watching.

For researchers, Anstrex can provide examples of how advertisers package their messages and structure visible funnel experiences. Those examples can inspire original concepts, but creative assets, scripts, and brand elements should not be copied.

Five cross-channel patterns worth investigating

Across native, push, pop, and instream advertising, several recurring principles are useful to study:

1. Channel-native packaging: Native ads use editorial-style content, push uses concise messaging, pop relies heavily on the landing experience, and video uses visual storytelling.
2. One primary message: A focused creative is easier to understand than one trying to communicate several unrelated benefits.
3. Consistent ad-to-page messaging: The landing page should deliver on the promise made by the advertisement.
4. Relevant proof: Demonstrations, documentation, and genuine customer evidence can make claims easier to evaluate.
5. A clear next step: Visitors should understand what action is being requested and what happens after they take it.

These are research principles, not guarantees of campaign performance. Use observed advertising patterns to develop hypotheses, then validate those hypotheses through your own controlled testing.

AI search topic reports and advertising intelligence become more useful when they are examined together.

Bing's Topics Portfolio can help marketers identify themes and questions associated with AI search visibility. Anstrex can help investigate how advertisers approach related commercial interests through paid campaigns.

The connection is not a direct conversion from one data source into the other. It is a structured research process.

Use the following steps to move from a topic cluster to a potential advertising opportunity.

Step 1 — Translate a topic cluster into a commercial intent

Start by reviewing the topics that matter to your business in Bing Webmaster Tools.

Look at the Topic Size, Sites Cited, and related Queries. Identify themes that connect to a product, service, audience, or problem your business can credibly address.

Then move beyond the broad topic and examine the underlying need.

For example:

• “Back pain at night” may connect to pain-management information and relevant health-product categories.
• “Debt payoff calculator” may connect to personal finance education and financial lead generation.
• “AI resume builder” may connect to career tools and SaaS trial funnels.

These are research mappings, not proof that every query has commercial value.

The goal is to identify the audience's underlying problem and determine whether there is a legitimate offer that addresses it.

The Topical Gravity framework from Semrush offers a useful way to think about the relationship between audience interests, subject relevance, and business objectives.

Step 2 — Pivot from topic to vertical in Anstrex

Once you have identified a commercial intent, use the core problem or product category as the starting point for ad research.

Inside Anstrex:

• Select the traffic type relevant to your research.
• Search for the main problem, product category, or commercial phrase.
• Narrow the research by available networks, countries, and other relevant filters.
• Review the creatives and landing pages associated with the results.

For example, a topic around resume creation might lead to research into career tools, resume builders, employment services, or SaaS products.

A topic around consumer gadgets might lead to product demonstrations, comparison pages, or affiliate landing pages.

The objective is to identify the types of offers and funnel experiences advertisers are using—not to assume that every advertiser appearing in the results is a direct competitor.

Step 3 — Reverse-engineer creative patterns by channel

Do not limit research to the offer itself.

Examine how advertisers communicate the offer across different channels.

For each topic-to-vertical combination, document:

• Native: Headlines, images, advertorial formats, and pre-sell structures.
• Push: Short messages, visual styles, calls to action, and offer clarity.
• Pop: Landing-page layouts, interactive elements, forms, and conversion steps.
• Instream: Opening frames, demonstrations, story structure, and calls to action.

Look for recurring creative approaches across multiple advertisers.

For example, several advertisers promoting a consumer gadget may use demonstrations that show the product solving a recognizable household problem. That pattern may suggest a useful creative hypothesis for your own campaign.

It does not prove that the approach is profitable. Validate the concept with your own audience, offer, and traffic source.

Step 4 — Prioritize topics using commercial and execution signals

Not every topic with significant AI search demand deserves immediate advertising investment.

Before prioritizing a topic, examine several factors:

1. Commercial relevance: Does the topic connect to an offer your business can legitimately promote?
2. Advertising activity: Are there observable campaigns and landing-page examples worth studying?
3. Funnel complexity: Can the offer be explained with a simple page, or does it require education, qualification, or a multi-step process?
4. Available assets: Do you already have relevant content, creative resources, customer proof, or an existing product?
5. Measurement readiness: Can you track the outcomes that matter, such as qualified leads, purchases, or incremental conversions?

A topic with high search visibility may still be unsuitable for paid acquisition if the offer is weak, the economics do not work, or the audience is not commercially relevant.

Likewise, a competitive vertical may be worth researching even when your own AI search visibility is limited.

Step 5 — Build a topic-to-vertical research map

Bring the information together in one working document.

Use this as a starting research map, not a forecast of performance.

The most useful outcome is a shortlist of topics where audience interest, legitimate commercial intent, observable advertising activity, and your ability to execute overlap.

The missing link is not simply more AI data or more competitor research. It is a repeatable method for connecting the two.

The final step is turning research into a practical plan.

Topics Portfolio can help identify where your website has AI search visibility and where other sources are being cited. Anstrex can help investigate the advertising approaches associated with related commercial intents.

The following workflow brings those insights together.

Step 1 — Pull your AI topic landscape and opportunity queries

In Bing Webmaster Tools, review the AI Performance report and open the Topics Portfolio section.

Identify topics relevant to your business and examine their available signals, including Topic Size, Sites Cited, and Queries.

Next, review the Top Opportunity Queries list. These queries can reveal questions where other sources are cited but your site is not represented.

Use Microsoft's guidance and the Search Engine Journal report breakdown to interpret the report appropriately.

Treat the available figures as directional signals. Export or document the relevant opportunities for further research.

Step 2 — Filter for commercial intent

Not every AI search opportunity is an advertising opportunity.

Review the underlying queries and identify commercial modifiers such as:

• Buy.
• Compare.
• Best.
• Versus.
• Pricing.
• Review.
• Alternatives.
• Near me.
• Free trial.

These modifiers can help identify questions that may indicate product research or commercial evaluation.

However, commercial language alone does not establish purchase intent. Review the context of each query and remove irrelevant branded searches, unrelated questions, and opportunities that do not fit your business.

The result should be a smaller list of relevant topics and queries worth investigating.

Step 3 — Translate topics into ad verticals with Anstrex

Take the filtered topics and commercial queries into Anstrex.

For each priority topic:

• Search the core product category or customer problem.
• Identify relevant verticals, such as e-commerce, finance, SaaS, information products, or local services.
• Examine the visible advertising creatives.
• Review the associated landing pages and funnel steps.
• Record the channels and formats represented in the research.

Look for patterns across multiple advertisers rather than relying on one isolated example.

This helps distinguish a recurring market approach from a creative that simply caught your attention.

Step 4 — Build a cross-channel creative blueprint

Once you have a better understanding of the advertising landscape, translate the findings into original creative concepts.

For each priority topic, define:

Primary hook families

Identify the problems, questions, interests, or product benefits that appear repeatedly in the market.

Proof types

Decide what evidence your own campaign can genuinely provide. This may include product demonstrations, verified customer feedback, transparent comparisons, documented results, or relevant third-party information.

Format by channel

• Native: Educational articles, product comparisons, and advertorial-style explanations.
• Push: Concise messages with a clear and accurate offer.
• Pop: Focused landing pages and straightforward interactive experiences.
• Instream: Short-form demonstrations, explainers, and customer stories.

Use competitor research as inspiration for understanding market patterns. Develop original assets and ensure that all claims, testimonials, and product representations are accurate.

Step 5 — Turn the blueprint into a controlled test plan

Choose a small number of topics that meet your commercial and operational requirements.

For each topic:

1. Select one priority vertical and offer.
2. Choose the channel that best fits the audience and funnel.
3. Develop two or three distinct creative concepts.
4. Create appropriate format variations for the selected channel.
5. Define the landing-page experience and conversion event.
6. Set a measurement period and performance criteria before launch.
7. Review results and decide whether to iterate, expand, or stop.

Where possible, test one major variable at a time so you can understand what changed.

Track meaningful business outcomes rather than relying only on clicks or impressions. Depending on the campaign, these may include qualified leads, completed purchases, customer acquisition cost, revenue, or incremental conversions.

A competitor's visible advertising activity can inform your hypotheses, but your own campaign data must determine whether a strategy is working.

Step 6 — Feed campaign findings back into content research

The process should not end when the campaign launches.

Your paid campaign results may reveal questions, objections, or product comparisons that deserve better content coverage.

For example, if visitors repeatedly ask about product compatibility, eligibility, pricing, or specific use cases, those questions may inform new articles, comparison pages, or FAQ content.

Likewise, changes in AI search visibility may highlight subjects where your content needs clearer explanations or stronger supporting evidence.

This creates a feedback loop:

AI topic research → commercial intent analysis → Anstrex ad research → creative and funnel testing → campaign measurement → stronger content and topic coverage.

Over time, this approach can help marketers connect what people research, what advertisers promote, and what their own campaigns can credibly deliver.

AI search topic reports are changing how marketers understand online demand. They make it easier to examine related questions, topic clusters, and potential visibility gaps instead of relying only on isolated keywords.

But AI search visibility does not tell the whole story.

It does not reveal every paid competitor, explain which creative approaches advertisers are testing, or show how commercial offers are structured across native, push, pop, and instream traffic.

That is why combining topic research with competitive ad intelligence can be valuable.

Use Bing's Topics Portfolio to identify themes and questions worth investigating. Use Anstrex to explore the observable advertising activity, creative patterns, landing pages, and funnel structures associated with related commercial intents.

Then turn those findings into original campaigns, test them with clear measurement criteria, and use the results to improve both your advertising and content strategy.

The goal is not to assume that every popular AI topic is profitable or that every long-running advertisement is a winner. It is to make better-informed decisions by connecting multiple sources of market evidence.

Bing helps you understand the topics and questions shaping AI search. Anstrex helps you investigate how advertisers approach related demand across paid channels. Your cross-channel playbook connects the two—and turns research into testable campaign ideas.