The way social media and websites perform is evolving, and customer journeys are no longer linear. This shift requires businesses to adapt, whether that means reallocating marketing budgets or adjusting their visual approach to better align with customer expectations.

What is the marketing funnel?

The marketing funnel describes the varying levels of commitment an audience has to your product or service. Often described as a funnel, as the top lets in lots of people, whilst the process naturally eliminates uninterested or ill-fitting prospects, eventually with a smaller output of people who convert.

How does the marketing funnel inform marketing strategies?

A solid marketing strategy will account for the customers at the various stages of the funnel, producing content and campaigns that cater to each stage of the funnel. Understanding the different stages of engagement better allows the messaging and imagery to be tailored, with the aim of converting them.

The type of content produced for the top of the funnel, for instance, would differ significantly from that created for the bottom of the funnel. Depending on the stage of the funnel the customers are at, the goal will change, and therefore the strategy to achieve the conversion will need to be differentiated.

Measuring engagement for each stage of the marketing funnel

At the top of the funnel, the kind of metrics you’ll need to pay attention to are the reach and click-through rate. These metrics alone will help give you a sense of the interest generated, with the reach being the overall figure, and the click-through rate indicating interest.

As customers advance to the middle of the funnel, metrics that will begin to play a key role in your strategising, these include:

• Average duration
• Drop-off points
• Data captured information (the volume compared to reach)
• Cost per lead
• Engagement rate

The middle of the funnel is where the “make it or break it” moment happens; it shows the clear strengths and challenges. It’s perhaps the most insightful because it allows businesses to distinguish exactly what customers do and do not respond to.

At the bottom of the funnel is where all the work you have done in terms of strategy is either validated or highlights greater pain points. Metrics you’ll need to track for this stage of the funnel range from conversion rates and retention to the customer’s lifetime value.

To calculate your customer lifetime value, you’ll need to multiply the average purchase value by the purchase frequency and the predicted customer lifespan.

Retention is just as crucial as acquisition, as it indicates just how much of the audience wants to engage, an indicator of strong growth. Personalisation is a non-negotiable; in fact, it’s a determining feature in why some customers stay. A better understanding of the interplay of these will allow brands to connect with customers on a profound level.

Is advertising during a sports game an effective way to spend ad budget?

You may be wondering whether investing in advertising during the World Cup is the right move for your business. The answer depends on several factors. Are your business and product offering suitable for this type of exposure? Do you have the budget and resources to secure ad space, whether pitch-side, online, or during broadcast ad breaks?

These are the key questions businesses must consider when evaluating the practicality of World Cup advertising. For established brands, the risks are relatively low compared to those faced by SMEs.

Take major brands such as PepsiCo. They can launch high-impact campaigns with less risk because their brand is already widely recognised, and they typically have larger budgets to produce memorable, visually impressive advertising. Smaller brands, however, face a greater challenge. If their campaigns fail to stand out, they can easily fade into the background amongst the noise of global competition.

What are the regulations around advertising for FIFA games?

Advertising during FIFA events is subject to several regulations and broadcasting standards, including:

·         Gambling and alcohol advertisements cannot appear in areas affiliated with under-18 audiences, such as junior club sections or youth kits.

·         Campaigns must not imply official endorsement or representation of clubs without authorisation.

·         Foods and beverages high in fat, sugar, or salt cannot be promoted before the 9 pm watershed.

·         Ofcom regulates television advertising time, with commercial breaks generally limited to around 12 minutes per hour.

Does the placement of ads matter during the World Cup?

Placement is critical, regardless of the advertising format. Whether ads appear on websites, pitch-side banners, social media feeds, or during half-time breaks, placement directly impacts visibility and audience engagement.

Effective placement increases the likelihood of capturing viewers’ attention, improving brand recall, and ultimately generating a stronger return on investment (ROI).

Securing ad campaigns during sporting events

The strategy brands choose during the World Cup can significantly influence campaign performance.

For smaller brands, lower-risk strategies such as paid social and browser advertising are often more practical. These channels allow businesses to target audiences affordably without directly competing for premium placements against globally recognised brands.

Brands looking to expand their paid advertising strategy may invest in options such as newspaper takeovers, allowing them to dominate a publication’s homepage or digital front page for a set period.

Larger brands, meanwhile, often pursue premium placements such as pitch-side advertising, sponsorship deals, or impression-based broadcast packages. Sponsorships, in particular, are highly effective during major sporting events, helping to create strong associations between a brand, its products, and global competitions such as the FIFA World Cup.

Ultimately, successful World Cup advertising comes down to strategy, placement, and audience relevance. While global brands may dominate the biggest spaces, smaller businesses can still achieve strong results through targeted, well-positioned campaigns that align with both their budget and objectives.

WordPress 7.0 launched 20 May 2026. Named after jazz musician Louis Armstrong, it is the most significant structural update the platform has shipped since the block editor arrived in 2018. For businesses running WordPress sites – which accounts for the vast majority of websites we build and manage – it is worth understanding what has actually changed, what it means in practice, and why the AI integration in particular is more consequential than it might initially appear.

The headline feature that was widely anticipated, real-time collaborative editing, was quietly removed from the release on 8 May after race conditions and server memory failures made it unsafe to ship at scale. That is the bad news. The good news is that what did ship is arguably more important for most businesses: a native AI infrastructure layer built directly into WordPress core, a rebuilt admin interface, and meaningful improvements to editorial workflow.

What WordPress 7.0 actually shipped

WordPress 7.0 formally marks the beginning of Phase 3 of the Gutenberg roadmap, which the core team has described as the Collaboration phase. The real-time editing delay means that the most visible collaboration feature will not arrive until a future release, but the underlying infrastructure work is substantial.

The key changes that shipped are:

• The WP AI Client and Abilities API. A native, provider-agnostic AI layer built into WordPress core. It connects directly to OpenAI, Google Gemini and Anthropic Claude without requiring separate plugin integrations for each.
• A rebuilt admin interface. The first major visual overhaul of the WordPress dashboard since 2013, driven by a new React-based system called DataViews. It brings the backend closer in feel to modern tools like Notion and Airtable.
• Client-side media processing. Image resizing and compression now happens in the browser using WebAssembly, reducing server load and speeding up media handling.
• Improved revision history and editorial tools. The revision system has been significantly updated, making it easier to track, compare and restore previous versions of content.
• PHP 7.4 minimum requirement. Any site running PHP 7.2 or 7.3 that upgrades to WordPress 7.0 will be on an unsupported configuration. If you are unsure which PHP version your site runs on, check with your hosting provider before updating.

Why the AI layer is the most important thing in this release

The WP AI Client and Abilities API deserve more attention than they have received in most of the coverage so far. Until now, AI integration in WordPress has been fragmented: different plugins connecting to different AI providers in different ways, with no standardised approach to authentication, rate limiting or content handling. Every developer building an AI-powered WordPress feature had to solve the same infrastructure problems independently.

WordPress 7.0 changes that. The Abilities API provides a standardised layer that handles authentication, rate limiting, content sanitisation and context management centrally. Plugin developers can now register their plugin’s capabilities so that AI assistants can recognise and use them. Rather than each plugin managing its own AI connection, everything routes through the same core infrastructure with admin approval required before any plugin can use stored AI credentials.

In practical terms, this means AI features in WordPress are about to become significantly more coherent and trustworthy. Instead of a patchwork of third-party solutions with varying quality, reliability and security, the platform now has a single, well-architected layer that plugins can build on. The immediate use cases include content generation assistance, automated alt text for images, SEO optimisation suggestions and workflow automation. The longer-term possibilities, as more plugins adopt the Abilities API, are considerably broader.

Why this matters for your website specifically

The timing of this release is worth noting in the context of the wider changes happening in search. We have written recently about why websites now need to work for AI agents as well as human readers, and the tools available to help businesses monitor and improve their AI search visibility. WordPress 7.0’s AI layer is the platform-level infrastructure that makes it possible to act on those recommendations directly within your CMS, rather than through external tools bolted on afterwards.

For businesses in content-heavy sectors, the improvement to editorial workflows is also meaningful. The revised revision system and better content management tools reduce the friction in maintaining large libraries of treatment pages, service descriptions or course content – exactly the kind of content that AI search systems are trying to parse and cite accurately. Cleaner workflows produce better-maintained content, which produces better AI visibility outcomes.

The admin redesign, while it will take some getting used to, is long overdue. For any client or team member who manages their own WordPress backend, the move toward a more modern interface reduces the learning curve and the number of support requests that agencies like ours receive about basic navigation.

What to be cautious about

WordPress 7.0 is a major release, and major releases carry risks that point updates do not. There are a few things worth being careful about before updating.

• Check your PHP version. PHP 7.4 is now the minimum. If you are on an older version, contact your hosting provider before touching the WordPress update.
• Test plugins and themes before updating. The admin rebuild and the new DataViews system may cause compatibility issues with plugins that rely on the old admin interface. Test on a staging environment first, not on your live site.
• Do not rush the AI features. The Abilities API requires admin approval before any plugin can use stored AI credentials. Take time to understand which plugins you are granting AI access to and why. The framework is sound, but the decisions around which tools to enable are yours to make.
• Real-time collaboration is not here yet. If you were planning to restructure your editorial workflow around simultaneous editing in WordPress, that feature has been deferred and is unlikely to arrive before 2027.

The bigger picture

WordPress powers around 43% of all websites on the internet. The decision to build a native, standardised AI layer into core is not a minor product update. It is a signal that the platform intends to be a serious player in the AI-assisted web, rather than ceding that ground to newer tools. For the tens of millions of businesses running WordPress, that is a meaningful commitment. For agencies building and managing those sites, it represents a significant expansion of what is possible within the platform most clients are already on. We will be looking closely at how the AI tooling ecosystem evolves to take advantage of the Abilities API over the coming months, and will keep you updated as the picture becomes clearer.

In the meantime, if your site runs on WordPress and you have not already done so, now is a good time to check your PHP version, review your plugin stack, and make sure your staging environment is up to date. The update itself is worth making, but it is worth making carefully.

Brand collaborations don’t always deliver the cultural impact brands hope for. When partnerships feel forced, disconnected or poorly judged, campaigns can quickly alienate audiences instead of attracting them.

Why do brands pursue collaborations?

Brand collaborations have become one of the most widely used marketing strategies because they allow brands to access audiences that are already highly engaged and culturally established. Rather than building attention from scratch, collaborations enable brands to tap into existing communities that are more likely to interact with, trust and purchase from a campaign.

Collaborations also allow brands and creators to borrow credibility from one another. When audiences already trust one side of the partnership, that trust can transfer onto the campaign itself, helping brands appear more culturally relevant and authentic.

What causes brand collaborations to fail?

The key issue that causes brand collaborations to fail is when the audience can’t understand how the two belong together. A collaboration is only effective when brands share  one of the following things in common:

• Personality (whether that be portrayed as a funny, honest or professional type of brand)
• Audience perception
• Cultural positioning
• Emotional alignment
• Product relevance
• A shared audience                                                                                                                                                                                                                                                                                                                       

If brands fail to align on at least one area, it can result in collaborations that feel random, inauthentic or forced.

The latest brand collaboration fails

Peppa Pig x Tottenham Hotspur Football Club

One of the more recent brand collaboration fails we’ve seen to date was the Peppa Pig x Tottenham Hotspur F.C  merchandise collaboration. For many supporters and spectators, the collaboration felt disconnected from the club’s current reality. At a time when fans were frustrated with on-pitch performance and concerns around relegation were growing, the campaign appeared unserious and commercially tone-deaf.

The lack of overlap between fanbases makes campaigns like this irrelevant. A great campaign should solve a problem or feel deliberate and understandable.

Sydney Sweeney x American Eagle

with messaging that many audiences interpreted as echoing ideas associated with eugenics and exclusionary beauty standards. We discussed the negative impact of the campaign on both American Eagle and Sydney Sweeney.

By contrast, this campaign lacked the right tone or messaging, rather than being poorly aligned with the collaborative partner.

Successful collaborations feel inevitable once consumers see them. Failed collaborations do the opposite; they force audiences to question why the partnership exists at all. In a market where consumers are increasingly sensitive to authenticity and cultural awareness, collaboration alone is no longer enough to guarantee relevance.

Google confirmed last week that it will no longer support FAQ rich results in search. The expandable question-and-answer panels that appeared directly beneath certain search listings are being removed, along with the Search Console features that allowed webmasters to monitor their performance. For any business that invested time in implementing the FAQ schema, this is worth understanding clearly: what is changing, what it means in practice, and whether any of that investment needs to be redirected.

The short answer is that this change is less damaging than it might initially sound. But there are some useful lessons in it about how to think about structured data more broadly as Google continues to adjust what it surfaces and how.

What FAQ rich results actually were

FAQ rich results were the expandable accordions that appeared below a search listing, showing individual question-and-answer pairs pulled directly from a page’s structured data. When implemented correctly using FAQ schema markup, they could significantly expand a search listing’s visual footprint on the page, making it more prominent without requiring a higher ranking.

Google started restricting FAQ rich results in 2023, limiting them to government and health websites. The full removal confirmed last week completes that process. The associated Search Console report, which showed impressions and clicks from FAQ rich results, will be deprecated alongside the feature itself.

How much does this actually matter?

For most businesses, the honest answer is: less than it might appear. By 2023, Google had already restricted FAQ rich results to a narrow category of sites, which means the vast majority of businesses had not been benefiting from them in search results for some time. The visual expansion of a listing was a genuine competitive advantage when the feature was widely available, but that window closed a few years ago.

What is changing now is the formal retirement of a feature that was already largely inactive for commercial websites. The Search Console report being removed is a minor practical inconvenience if you were still tracking FAQ impressions, but the disappearance of the report does not reflect a loss of current traffic or visibility for most sites.

Should you remove your FAQ schema?

Not necessarily, and in many cases the answer is no. This is an important distinction. FAQ schema no longer produces rich result panels in standard Google Search, but structured data serves multiple purposes beyond generating visual enhancements in the search results page.

As we covered recently when looking at the tools worth using for AEO, structured data is one of the cleaner signals available for AI retrieval. FAQ schema specifically provides AI systems with a machine-readable layer of question-and-answer content that can inform how those systems cite and use your content in AI-generated answers, entirely separate from whether Google renders it as a rich result in traditional search.

The argument for keeping well-implemented FAQ schema in place is straightforward. It costs nothing to maintain, it provides clarity to search engines and AI systems about the purpose and structure of your content, and removing it does not guarantee any benefit. Unless your FAQ schema is technically broken or generating errors in Search Console, the case for removing it is weak.

What to redirect your structured data efforts towards

If this news prompts a review of how structured data is implemented on your site, that is a worthwhile exercise. The specific types of schema that continue to produce rich results in Google Search and that are increasingly relevant for AI retrieval are worth prioritising. The most consistently valuable include:

• Review schema. Star ratings in search results remain one of the highest-impact visual enhancements available and are directly relevant to businesses in sectors such as healthcare, dental, aesthetics and professional services where social proof influences decisions.
• Local business schema. For businesses with physical locations, accurate and complete local business schema reinforces the information shown in Google Business Profiles and supports consistent citation across AI search systems. This is particularly important for multi-location businesses and sectors where local search intent is high.
• Product schema. For e-commerce businesses, product schema supporting price, availability and review information continues to produce rich results in both standard search and Shopping. This remains one of the most directly commercial schema types available.
• Article and breadcrumb schema. These support how content pages are understood and indexed, contributing to cleaner crawling and more accurate representation in search results, and remain relevant for content-heavy sites.
• How-to and event schema. Both continue to produce rich results for relevant content types and are worth implementing where the content justifies it.

The broader pattern is worth noting

The removal of FAQ rich results is part of a longer pattern. Google has been progressively reducing the variety of rich result types it surfaces in standard search as AI Overviews and AI Mode take up more of the results page. The shift towards AI-generated answers changes what it means to be visible in search. The visual real estate previously occupied by FAQ panels, knowledge panels and similar features is increasingly being consumed by AI-generated content instead.

This does not mean structured data is becoming less important. If anything, the opposite is true. As AI systems take a more active role in assembling answers from multiple sources, the clarity and accuracy of the signals you provide about your content become more valuable, not less. The mechanism by which those signals produce a visible result in search is changing. The underlying importance of giving search engines and AI systems well-structured, accurate, machine-readable information is not.

What to do now

A few practical steps are worth taking in light of this change.

• Check your Search Console for any FAQ rich result errors or warnings. These will stop being reported when the feature is deprecated, but addressing any existing errors is good practice before the report disappears.
• Audit your current structured data implementation more broadly. If FAQ schema was the only schema type in use on your site, now is a good time to review whether review, local business or product schema should be added where applicable.
• Do not remove FAQ schema solely because of this change. If your FAQ schema is well-implemented and error-free, leave it in place. Its value in an AI retrieval context is not affected by Google’s decision to stop rendering it as a rich result.
• Focus new structured data investment on the types that continue to produce visible results: review, local business, product and event schema, depending on what is relevant to your business.

The disappearance of FAQ rich results is worth knowing about, but it is not a reason to panic or make sweeping changes. It is a reminder that search is a changing environment and that the value of any single technical feature is always temporary. The underlying principle, making your content clear, accurate and well-structured, remains constant regardless of which specific features Google chooses to support at any given time.

Agentic Engine Optimisation, or AEO, has become one of the more discussed topics in digital marketing in 2026. The coverage has generated a fair amount of heat but not always much light, partly because the tooling landscape is still developing and partly because a lot of what is being written treats AEO as something entirely new when, in practice, it shares most of its foundations with work that good SEO practitioners have been doing for years.

This article covers the tools that are actually useful right now, split into those with a clear proven use case and those worth testing as the category matures. But before getting into the tools, it is worth addressing the terminology question directly, because the shift in how AI systems retrieve and surface content has caused some confusion about what has actually changed and what has not.

AEO and SEO: different names, same foundation

Despite what some of the more excitable coverage suggests, AEO is not a replacement for SEO, and it does not require a completely different strategic approach. The two disciplines share the same core premise: make your content easy to find, easy to understand, and clearly relevant to what someone is trying to know or do.

The difference is in the audience being optimised for. Traditional SEO focuses on helping human searchers find and engage with your content. AEO extends that to cover AI systems that fetch, parse and use your content to formulate answers, often without a human ever clicking through to your site. The signals that matter are largely the same: well-structured pages, clear headings, specific and accurate information, strong authority and credible backlinks. What changes is the layer of intent you apply when thinking about how that content is read and used.

Research consistently shows that AI Overviews and similar systems draw heavily from pages that already rank well organically. Google has been clear for some time that content quality and audience relevance are the primary factors that determine whether a site performs. AEO does not change that message. It adds a layer of consideration: once your content is authoritative and well-structured, is it also legible and extractable for AI systems working within processing constraints?

In practical terms, we treat AEO and SEO as the same discipline. The same improvements that help AI systems cite your pages accurately also make those pages clearer and more useful for human readers. They are not in tension. The tools below reflect that: some are well-established SEO tools that remain highly relevant in an AEO context, and some are newer platforms built specifically to measure AI search visibility.

The tools with a clear, proven use case

1. LLM assistants used with a defined methodology

ChatGPT, Claude and Gemini are themselves useful AEO research tools when used intentionally rather than ad hoc. The most practical applications are competitive landscape research, content gap analysis, prompt testing to understand how AI platforms respond to queries in your category, and entity and topical coverage audits.

Asking an LLM what it knows about your brand, your competitors and your sector, and then interrogating where the gaps and inaccuracies are, is a fast and accessible way to understand your current AI search position. Most businesses have not done this basic audit, and a meaningful first pass takes less than an hour. It is also one of the few AEO-relevant activities that costs nothing beyond the time invested.

2. Google Search Console

Search Console remains one of the most important tools in any AEO workflow, primarily because it provides direct performance data from Google: the platform that produces the AI Overviews appearing above organic results for a significant proportion of searches. Understanding which of your pages are currently being surfaced in AI Overviews, and which are not, gives you a baseline from which to measure the impact of content changes.

It also helps identify the queries where AI Overviews are appearing for keywords you rank for, which is increasingly important as AI-generated answers above the fold reduce click-through rates on the organic listings below them. Knowing where you are losing clicks to AI answers on your own target keywords is the starting point for deciding where to focus content improvement efforts.

3. Google Trends

Google Trends serves a different purpose than Search Console, but it is equally valuable for AEO strategy. Where Search Console tells you how you are performing, Google Trends tells you where demand is heading. It does not give absolute search volume, but it gives relative momentum across topics and queries, which is often more strategically useful when trying to get ahead of emerging patterns rather than simply responding to existing ones.

For AEO specifically, rising query trends can signal emerging answer opportunities you can address before your competitors do. AI systems tend to favour content that is well-established and authoritative on a topic, which means the window for getting in early is narrow. Identifying rising demand trends through Google Trends and creating strong content quickly is one of the more practical ways to build AI citation presence in a new area before it becomes competitive.

4. SE Ranking and SE Visible

SE Ranking is the platform we use day-to-day for client SEO work, and its relevance to AEO has grown considerably over the past 12 months. The AI Overviews Tracker monitors how your keywords are performing within Google’s AI-generated results, including citation frequency, source analysis, and estimated traffic impact from AI Overviews. It also identifies which competitor domains are being cited in AI answers for keywords you are targeting, which is actionable competitive intelligence.

The AI Search Toolkit extends this further by tracking brand mentions and linked citations across AI Overviews, AI Mode, ChatGPT, Gemini and Perplexity. You can monitor how often your domain is cited, whether citations are linked or unlinked, and how this compares to named competitors over time.

SE Visible is a companion product that sits alongside SE Ranking and focuses specifically on brand AI visibility at a strategic level: how your brand is presented, ranked and perceived across AI systems. It provides a Brand Visibility Index that measures performance over time and competitive benchmarking across AI platforms. For agencies managing multiple client accounts, the combination of SE Ranking for tactical execution and SE Visible for strategic oversight is a coherent and cost-effective approach.

5. Semrush

Semrush has expanded its feature set to include AI Overviews tracking and visibility data, making it one of the more complete tools for monitoring how content performs across both traditional search and AI-generated results within a single platform. For teams already using Semrush for keyword research, position tracking and site auditing, the AI visibility layer adds meaningful value without requiring a separate tool or workflow.

The topic clustering and content gap analysis features are particularly relevant for AEO, helping identify where topical coverage is thin relative to what AI systems are pulling from competitors. Thin or fragmented coverage in a topic area is one of the more common reasons a site gets passed over in AI-generated answers in favour of a competitor with more comprehensive, well-organised content on the same subject.

6. Profound

Profound is purpose-built for AI search monitoring. It tracks how platforms, including ChatGPT, Perplexity, Google AI Overviews, and Claude discover, surface and cite your brand and content. It monitors brand mention frequency and sentiment, competitor share of voice, and the specific prompts that trigger your content to appear in AI-generated answers.

The most useful shift Profound enables is in the metric itself. Rather than asking where you rank in a search result, you can ask: when AI answers a question in your category, are you in the answer? The cross-platform view, covering multiple AI engines simultaneously rather than one in isolation, is its most distinctive feature and makes competitive benchmarking significantly more meaningful than single-platform tracking.

It is not a cheap tool and is better suited to businesses with an existing content and SEO foundation. For agencies managing multiple clients in competitive sectors, the monitoring and benchmarking functionality is particularly valuable.

7. Screaming Frog

Screaming Frog has been a technical SEO staple for years, and its relevance extends directly into AEO. Many of the technical issues that prevent AI agents from correctly parsing and using your content are exactly the issues Screaming Frog identifies: missing or misconfigured structured data, poorly structured heading hierarchies, thin or duplicated page content, and slow server response times.

Running a Screaming Frog audit with a focus on schema markup completeness, heading structure, and page-level content depth is one of the most practical first steps in any AEO improvement programme. The tool now integrates with Google Search Console and PageSpeed Insights, making it straightforward to cross-reference technical findings with actual performance data.

8. Google Rich Results Test and Schema Markup Validator

Structured data is one of the cleaner signals available for AI retrieval. Schema markup for FAQs, services, reviews, products and local business information gives AI systems a reliable, machine-readable layer of data to draw from, independent of how the surrounding content is written or formatted. Getting this right is a relatively contained piece of work that can have a disproportionate impact on how accurately your content is cited.

Both tools are free. The Rich Results Test checks whether your structured data is correctly implemented and eligible for enhanced display in search results. The Schema Markup Validator checks for errors and warnings at a more granular level. For businesses in sectors where FAQ, review or service schema are applicable, a structured data audit is one of the most immediately actionable AEO improvements available.

How to approach this practically

The AEO tools market has grown faster than the evidence base for what actually works. Many platforms are repackaging existing SEO or content analytics functionality under AEO branding without meaningfully changing what they measure. The most reliable signal for whether a tool is genuinely useful is whether it changes a specific decision you make about your content or your site.

A practical starting sequence looks like this. Use an LLM to audit your current brand position across AI platforms in your category. Use Google Search Console to understand which of your pages are appearing in AI Overviews and where the gaps are. Use Google Trends to identify rising demand patterns worth targeting early. Use Screaming Frog and the schema validation tools to fix any technical issues preventing your content from being correctly parsed. Then use SE Ranking, Semrush or Profound, depending on the depth of monitoring your situation requires, to track how your visibility is changing over time.

Starting with the fundamentals, well-structured content, strong authority signals, accurate structured data, and a clear technical foundation will deliver more impact sooner than any monitoring platform can on its own. The monitoring tools tell you whether the work is making a difference. They are not a substitute for doing the work.

A report released by Emplifi on Q1 for social platforms has revealed that UGC is driving 6.7x higher conversions than in Q4 2025, increasing from 4.27x, totalling a 57% jump in just one quarter. Crossing a threshold from being a supporting type of content to a primary revenue driver for marketers.

User-generated content is part of a broader performance shift. The conversion uplift significantly surpasses traffic uplift. Resulting in UGC bringing in often higher-intent users.

Platform and content dynamics

Short-form content is particularly compatible with UGC, with Reels, TikTok and Shorts all fitting into their native platforms’ user behaviour. This type of content consumption feeds into the ease of algorithmic discovery. Users want to engage with lo-fi, fast-paced, natural and observer-style content, often in vertical format.

Video format often outperforms static content because it increases dwell time, finds ways to prompt interaction, all while making it feel less staged or manufactured. It feels less interruptive and therefore tends to hold attention for much longer. It also blends in with other feed content, which takes on a naturalistic, in-situ style.

What does this mean for Q2 in marketing

Q2 for marketers can be expected to shift in a couple of ways, with UGC being looked at from an entirely different standpoint.

1. User-generated content will dominate marketing strategies

We expect to see a shift with brands adopting more UGC into their overall marketing strategy. Utilising the value of naturalistic, in-situ content to position, promote and sell products/services, rather than depending on heavily branded and often overly-produced content.

2. Video-first is non-negotiable

Short-form content, whether that be Reels, Shorts or TikTok videos, is rewarded with high engagement and a greater opportunity to reach new people.

Algorithms are shifting, displaying content that’s relevant to your most-watched content themes, rather than displaying users because you follow them. This has contributed to the ease of discovering new short-form content.

3. Shares and saves matter more than likes

Q2 KPI’s will likely begin to move further toward deeper engagement signals. Think shares, saves, watch time, and whether DM’s have been sent as algorithms prioritise content people actively interact with and distribute.

4. TikTok will absorb more budget for brand awareness

Brands will continue reallocating top-of-funnel spend toward TikTok as it outperforms other platforms on engagement and discovery. This could result in a surplus of budget being spent just to cut through the noise and heavy competition.

5. Revenue accountability intensification

Marketing teams will likely face growing pressure to account for all marketing spend in a bid to prove the commercial impact. Forging stronger connections between content, creators, attribution and e-commerce.

6. Agile brands may outperform larger competitors

Smaller and mid-sized brands could gain an advantage in Q2 because platform algorithms increasingly reward speed, relatability, and creator-style execution over heavily polished campaigns.

It’s less about who a creator is and more about the type of content they create, as well as the format it is in.

In conclusion, Emplifi’s Q1 report highlights a clear evolution in digital marketing, with user-generated content emerging as a key driver of both engagement and revenue. As platforms continue to prioritise short-form, creator-style video content, brands that embrace authenticity, agility, and performance-led strategies will be best positioned to succeed in Q2.

The shift away from polished brand messaging toward relatable, community-driven content signals a new era where trust, discoverability, and measurable impact are becoming central to social media marketing success.

In April, the British Government voted against a social media ban for under-16s, which we would have initially assumed would end the discussion. But now, ministers are discussing implementing alternative protections with restrictions. Reports suggest restrictions could be implemented before summer.

 What sort of restrictions can be expected?

Whilst the details are yet to be ironed out, groups like the Mental Health Foundation

Have made recommendations to parliament about certain changes that could help protect young people on social platforms.

Revoking platforms

One of the recommendations that has been made is to remove access to these platforms until it can be evidenced by said company that the right safety measures are implemented. 

Age-rated content 

As in the film and television industry, a proposed idea is to age-rate content to ensure that content shown in users’ feeds appropriately corresponds to their age. This could look like a 13, 16 and 18 age rating. This approach would essentially ensure that all content is moderated and checked for any potential harm.

Better offline support

That means increasing funding for mental health support and budgeting for technological education. This approach looks to set up various supports both in the community and during school hours.

Social media curfews

A social media curfew is being proposed as a potential form of protection. This would limit the amount of time young people are able to utilise social media for, which could, in practice, reduce the harms which children are exposed to online.

Feature and algorithmic adjustments

Consultation has extended to potentially adjusting certain app features or algorithms to make social media less addictive. This could include stripping auto-play, axing infinite scroll or replacing algorithms with chronological feeds, rather than curating content to the individual user’s preferences.

That’s not necessarily bad, but it does make growth slower, less predictable, and more effort-intensive.

How could social media restrictions for under-16’s impact marketers?

Each type of restriction that is theorised to be implemented could have different repercussions for marketers, effectively eliminating algorithm-based tactics and forcing marketers towards a less addictive, moderated model.

Revoking platforms (temporary bans until safety compliance) could create a level of uncertainty. Platform stability is vital for building and maintaining audiences and ad campaigns. This would likely result in brands having to plan in the short-term, increasing the risks around campaigns not working.

Brands may depend on owned channels like websites and email lists instead of rented platforms for better security.
Age-rated content (13 / 16 / 18 categories) could mean that businesses create campaigns with compliance at the forefront of creation. Some high-performing content (e.g. edgy humour, influencer-style trends) may be limited to older age groups

Social media curfews would directly limit the usage of younger users. Less screen time can result in fewer impressions. Brands with a specifically younger audience are likely to be affected the most.
Feature & algorithm changes (no infinite scroll, chronological feeds, no autoplay)
This is arguably the biggest shift:

• Engagement drops because platforms become less addictive
• Algorithmic targeting becomes weaker and less personalised
• Organic reach becomes more dependent on posting time and follower base (not algorithm boosts)
• Viral growth becomes harder to achieve
  For marketers, this means:
• Greater emphasis on content quality over algorithm gaming
• More importance on brand loyalty and direct followers
• Paid ads may become less efficient if targeting precision declines

In short, while a full under-16 social media ban appears off the table for now, the UK Government is clearly still exploring ways to tighten online protections for young users. For marketers, this signals a likely shift towards safer, less algorithm-dependent strategies, making adaptability and stronger owned-channel marketing more important than ever.

World Intellectual Property Day has rolled around for 2026, and it’s got us thinking about just how much can change within a relatively short period. IP laws are in constant limbo, trying to establish what is and isn’t “fair game”.

One of the latest regulatory points of contention centres around AI. We’re not that shocked. When the discussion around the Studio Ghibli AI generative trend was at its peak, the key argument was about the bastardisation and theft of intellectual property, and the dilution of skill.

IP regulation currently

AI and copyright

AI copyrighting is still a grey area legally, with no clear ruling yet on whether training AI with copyright content is evidence of infringement. We see this in cases like Getty vs Stability, where there’s yet to be a definitive ruling for or against such approaches. That leaves a lot of room for questions for marketers, like, is it ok to use AI in my content?

The only clear answer we can give so far is that it can’t be assumed that AI content is legally safe. AI can and may utilise protected IP of other brands to generate visual elements, copy or ads. The impacts aren’t fully understood yet, which means brands using AI could trigger legal disputes later down the line. Some of the other risks it potentially brings on are:

• Loss of ownership
• Data leaks
• Damaging trust and authenticity
• Loss of IP
• An unknowing use of protected assets and ideas.

AI clauses in contracts

The rules around business use of AI are becoming more stringent, requiring closer attention to be paid to the contracts being signed and the terms of use you agree to. The kinds of stipulations that can be found in some of these contracts include:

1. Who owns the AI-generated content
2. Liability for IP infringement
3. Whether your data will be reused

Copycat branding to be penalised

Brand assets are better protected now than ever before in some cases. Brands can no longer copy along just because it worked for another brand. Specifically, when brands don’t adapt their content or assets to reflect their own branding, this dupe approach is now much riskier.

We see this happen time and time again in the UK courts with cases like Aldi vs M&S and the Thatchers vs Aldi case, which again ruled in the appellants’ favour.

Increased costs for IP and Trademarking

For the first time since 1998, on April 1^st, the UKIPO has increased the cost to trademark and claim intellectual property by an average of 25%. With a stronger push for brands to select and prioritise what it is they want to protect.

This means you can’t just trademark anything; instead, there needs to be a stronger focus on core brand assets, protecting your name, logo and key campaigns created. High-value content, now more than ever, is protected when distinguishable with the unique elements of a brand’s IP.

What is slop?

Slop, or AI slop, is a term coined for low-quality and value, often repetitive or very generic content produced at scale with the assistance of AI.

It’s becoming increasingly common for short-form video content like reels and shorts to feature marketing slop.

Is Slop hurting marketing?

Slop definitely has an impact on the quality and output of some marketers. AI should be utilised to enhance and improve upon what already exists, rather than diluting or replacing quality marketing content. Some of the main harms slop has for marketing are:

• Reducing engagement rates, audiences won’t engage in low-quality disengaging content
• Oversaturating the content market, because its low quality makes it easier to produce, thus the churn is greater and can dominate algorithms
• Runs the risk of diluting branding, slop tends to fall in the generic, overdone category, risking the brand’s unique tone of voice being watered down.
• Audiences can become fatigued, and slop in particular can be churned out, risking boring the audience and creating a disconnect

But slop isn’t just risking negative audience response and platform performance; it can result in marketers overly relying on automation, which won’t help them stand out.  This lack of human touch takes away the depth and meaning often created in content; AI is not able to capture the same emotion or soul that a human can.

Actionable Fixes for using AI to enhance quality

The key to fixing slop is to use AI with responsibility and consideration. AI is an invaluable tool, especially when looking to polish and perfect something you’ve already created.

Editorial standards

One of the key ways this can be corrected is by setting an editorial standard. Acting as a framework for creators to work within. Think of it as a quality check before it’s released, ask yourself:

1. Is this on brand?
2. Does this make sense?
3. Is this content relevant?
4. Is the AI component noticeable? Is that the intention?

Enforcing your brand voice

Branding is a crucial aspect of content marketing, so portraying your brand authentically is especially important. Referring to brand guidelines for tone, style and messaging ensures that AI isn’t filling in the blanks with generic, non-tailored types of content.

Use AI in assistance, not as the final version

AI can be mistakenly used to recreate what was a perfectly great human-designed piece of content, when really the AI should be part of the ideation and development process. AI should not replace the thinking or creativity of a person or brand; doing so is disingenuous.

A simple workflow you could follow is to use AI to brainstorm, research and help influence structure. Your role is to then use your opinion, voice, and editorial capabilities to flesh out and produce content. AI should help to accelerate thinking, not replace it.